Articles | Volume 20, issue 14
https://doi.org/10.5194/bg-20-2941-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-2941-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Reviews and syntheses
| 
21 Jul 2023
Reviews and syntheses |
| 21 Jul 2023
| 21 Jul 2023
Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions
Alex Mavrovic
CORRESPONDING AUTHOR
Département des sciences de l'environnement, Université du Québec à Trois-Rivières,
Trois-Rivières, Quebec, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, Canada
Canadian High Arctic Research Station Campus, Polar Knowledge Canada, Cambridge Bay, Nunavut, Canada
Département de géographie, Université de Montréal, Montréal, Quebec, Canada
Oliver Sonnentag
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, Canada
Département de géographie, Université de Montréal, Montréal, Quebec, Canada
Juha Lemmetyinen
Finnish Meteorological Institute, Helsinki, Finland
Jennifer L. Baltzer
Biology Department, Wilfrid Laurier University, Waterloo, Ontario,
Canada
Christophe Kinnard
Département des sciences de l'environnement, Université du Québec à Trois-Rivières,
Trois-Rivières, Quebec, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, Canada
Alexandre Roy
Département des sciences de l'environnement, Université du Québec à Trois-Rivières,
Trois-Rivières, Quebec, Canada
Centre d'Études Nordiques, Université Laval, Québec,
Quebec, Canada
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Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
The Cryosphere, 16, 3531–3573, https://doi.org/10.5194/tc-16-3531-2022, https://doi.org/10.5194/tc-16-3531-2022, 2022
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Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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Bin Cheng, Yubing Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Juha Lemmetyinen, Yubao Qiu, and Jouni Pulliainen
Earth Syst. Sci. Data, 13, 3967–3978, https://doi.org/10.5194/essd-13-3967-2021, https://doi.org/10.5194/essd-13-3967-2021, 2021
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Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Pinja Venäläinen, Kari Luojus, Juha Lemmetyinen, Jouni Pulliainen, Mikko Moisander, and Matias Takala
The Cryosphere, 15, 2969–2981, https://doi.org/10.5194/tc-15-2969-2021, https://doi.org/10.5194/tc-15-2969-2021, 2021
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Information about snow water equivalent (SWE) is needed in many applications, including climate model evaluation and forecasting fresh water availability. Space-borne radiometer observations combined with ground snow depth measurements can be used to make global estimates of SWE. In this study, we investigate the possibility of using sparse snow density measurement in satellite-based SWE retrieval and show that using the snow density information in post-processing improves SWE estimations.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
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This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Alex Mavrovic, Renato Pardo Lara, Aaron Berg, François Demontoux, Alain Royer, and Alexandre Roy
Hydrol. Earth Syst. Sci., 25, 1117–1131, https://doi.org/10.5194/hess-25-1117-2021, https://doi.org/10.5194/hess-25-1117-2021, 2021
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This paper presents a new probe that measures soil microwave permittivity in the frequency range of satellite L-band sensors. The probe capacities will allow for validation and calibration of the models used to estimate landscape physical properties from raw microwave satellite datasets. Our results show important discrepancies between model estimates and instrument measurements that will need to be addressed.
Nataniel M. Holtzman, Leander D. L. Anderegg, Simon Kraatz, Alex Mavrovic, Oliver Sonnentag, Christoforos Pappas, Michael H. Cosh, Alexandre Langlois, Tarendra Lakhankar, Derek Tesser, Nicholas Steiner, Andreas Colliander, Alexandre Roy, and Alexandra G. Konings
Biogeosciences, 18, 739–753, https://doi.org/10.5194/bg-18-739-2021, https://doi.org/10.5194/bg-18-739-2021, 2021
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Microwave radiation coming from Earth's land surface is affected by both soil moisture and the water in plants that cover the soil. We measured such radiation with a sensor elevated above a forest canopy while repeatedly measuring the amount of water stored in trees at the same location. Changes in the microwave signal over time were closely related to tree water storage changes. Satellites with similar sensors could thus be used to monitor how trees in an entire region respond to drought.
Jianwei Yang, Lingmei Jiang, Kari Luojus, Jinmei Pan, Juha Lemmetyinen, Matias Takala, and Shengli Wu
The Cryosphere, 14, 1763–1778, https://doi.org/10.5194/tc-14-1763-2020, https://doi.org/10.5194/tc-14-1763-2020, 2020
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There are many challenges for accurate snow depth estimation using passive microwave data. Machine learning (ML) techniques are deemed to be powerful tools for establishing nonlinear relations between independent variables and a given target variable. In this study, we investigate the potential capability of the random forest (RF) model on snow depth estimation at temporal and spatial scales. The result indicates that the fitted RF algorithms perform better on temporal than spatial scales.
Marion Réveillet, Shelley MacDonell, Simon Gascoin, Christophe Kinnard, Stef Lhermitte, and Nicole Schaffer
The Cryosphere, 14, 147–163, https://doi.org/10.5194/tc-14-147-2020, https://doi.org/10.5194/tc-14-147-2020, 2020
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
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Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan Chojnicki, Ankur R. Desai, Albertus J. Dolman, Eugenie S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara H. Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas Pypker, William Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, and Tuula Aalto
Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, https://doi.org/10.5194/essd-11-1263-2019, 2019
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Here we develop a monthly gridded dataset of northern (> 45 N) wetland methane (CH4) emissions. The data product is derived using a random forest machine-learning technique and eddy covariance CH4 fluxes from 25 wetland sites. Annual CH4 emissions from these wetlands calculated from the derived data product are comparable to prior studies focusing on these areas. This product is an independent estimate of northern wetland CH4 emissions and hence could be used, e.g. for process model evaluation.
Michael Prince, Alexandre Roy, Ludovic Brucker, Alain Royer, Youngwook Kim, and Tianjie Zhao
Earth Syst. Sci. Data, 10, 2055–2067, https://doi.org/10.5194/essd-10-2055-2018, https://doi.org/10.5194/essd-10-2055-2018, 2018
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This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the EASE-Grid 2.0 with a resolution of 36 km. To evaluate the product, we compared it with the resampled 37 GHz FT Earth Science Data Record during the overlapping period between 2011 and 2014. The FT-AP ensures, with the SMAP mission that is still in operation, an L-band passive FT monitoring continuum with NASA’s space-borne radiometers, for a period beginning in August 2011.
Fanny Larue, Alain Royer, Danielle De Sève, Alexandre Roy, and Emmanuel Cosme
Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018, https://doi.org/10.5194/hess-22-5711-2018, 2018
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A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by updating meteorological forcings and snowpack states using passive microwave satellite observations. A chain of models was first calibrated to simulate satellite observations over northeastern Canada. The assimilation was then validated over 12 stations where daily SWE measurements were acquired during 4 winters (2012–2016). The overall SWE bias is reduced by 68 % compared to original SWE simulations.
Michael M. Loranty, Benjamin W. Abbott, Daan Blok, Thomas A. Douglas, Howard E. Epstein, Bruce C. Forbes, Benjamin M. Jones, Alexander L. Kholodov, Heather Kropp, Avni Malhotra, Steven D. Mamet, Isla H. Myers-Smith, Susan M. Natali, Jonathan A. O'Donnell, Gareth K. Phoenix, Adrian V. Rocha, Oliver Sonnentag, Ken D. Tape, and Donald A. Walker
Biogeosciences, 15, 5287–5313, https://doi.org/10.5194/bg-15-5287-2018, https://doi.org/10.5194/bg-15-5287-2018, 2018
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Vegetation and soils strongly influence ground temperature in permafrost ecosystems across the Arctic and sub-Arctic. These effects will cause differences rates of permafrost thaw related to the distribution of tundra and boreal forests. As the distribution of forests and tundra change, the effects of climate change on permafrost will also change. We review the ecosystem processes that will influence permafrost thaw and outline how they will feed back to climate warming.
Gustaf Granath, Håkan Rydin, Jennifer L. Baltzer, Fia Bengtsson, Nicholas Boncek, Luca Bragazza, Zhao-Jun Bu, Simon J. M. Caporn, Ellen Dorrepaal, Olga Galanina, Mariusz Gałka, Anna Ganeva, David P. Gillikin, Irina Goia, Nadezhda Goncharova, Michal Hájek, Akira Haraguchi, Lorna I. Harris, Elyn Humphreys, Martin Jiroušek, Katarzyna Kajukało, Edgar Karofeld, Natalia G. Koronatova, Natalia P. Kosykh, Mariusz Lamentowicz, Elena Lapshina, Juul Limpens, Maiju Linkosalmi, Jin-Ze Ma, Marguerite Mauritz, Tariq M. Munir, Susan M. Natali, Rayna Natcheva, Maria Noskova, Richard J. Payne, Kyle Pilkington, Sean Robinson, Bjorn J. M. Robroek, Line Rochefort, David Singer, Hans K. Stenøien, Eeva-Stiina Tuittila, Kai Vellak, Anouk Verheyden, James Michael Waddington, and Steven K. Rice
Biogeosciences, 15, 5189–5202, https://doi.org/10.5194/bg-15-5189-2018, https://doi.org/10.5194/bg-15-5189-2018, 2018
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Peat constitutes a long-term archive for climate reconstruction by using the isotopic composition of carbon and oxygen. We analysed isotopes in two peat moss species across North America and Eurasia. Peat (moss tissue) isotope composition was predicted by soil moisture and isotopic composition of the rainwater but differed between species. Our results suggest that isotope composition can be used on a large scale for climatic reconstructions but that such models should be species-specific.
Christian M. Zdanowicz, Bernadette C. Proemse, Ross Edwards, Wang Feiteng, Chad M. Hogan, Christophe Kinnard, and David Fisher
Atmos. Chem. Phys., 18, 12345–12361, https://doi.org/10.5194/acp-18-12345-2018, https://doi.org/10.5194/acp-18-12345-2018, 2018
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Black carbon (BC) particles emitted by natural and anthropogenic sources (e.g., wildfires, coal burning) can amplify climate warming by increasing sunlight energy absorption on snow-covered surfaces. This paper presents a new ice-core record of historical (1810–1990) BC deposition in the Canadian Arctic. The Devon ice cap record differs from Greenland ice cores, implying large variations in BC deposition across the Arctic that must be accounted for to better quantity their future climate impact.
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208, https://doi.org/10.5194/gi-7-195-2018, https://doi.org/10.5194/gi-7-195-2018, 2018
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To improve microwave satellite and airborne observation products in forest environments, a precise and reliable estimation of the permittivity of trees is required. We developed a probe suitable to measure the permittivity of tree trunks at L band in the field. The system is easily transportable in the field, low energy consuming, operational at low temperatures and weatherproof. The permittivity of seven tree species in both frozen and thawed states was measured, showing important contrast.
Sébastien Monnier and Christophe Kinnard
Earth Surf. Dynam., 5, 493–509, https://doi.org/10.5194/esurf-5-493-2017, https://doi.org/10.5194/esurf-5-493-2017, 2017
Peter Toose, Alexandre Roy, Frederick Solheim, Chris Derksen, Tom Watts, Alain Royer, and Anne Walker
Geosci. Instrum. Method. Data Syst., 6, 39–51, https://doi.org/10.5194/gi-6-39-2017, https://doi.org/10.5194/gi-6-39-2017, 2017
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Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers used for monitoring essential climate variables. A 385-channel hyperspectral L-band radiometer system was designed with the means to quantify the strength and type of RFI. The compact design makes it ideal for mounting on both surface and airborne platforms to be used for calibrating and validating measurement from spaceborne sensors.
Melody Sandells, Richard Essery, Nick Rutter, Leanne Wake, Leena Leppänen, and Juha Lemmetyinen
The Cryosphere, 11, 229–246, https://doi.org/10.5194/tc-11-229-2017, https://doi.org/10.5194/tc-11-229-2017, 2017
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This study looks at a wide range of options for simulating sensor signals for satellite monitoring of water stored as snow, though an ensemble of 1323 coupled snow evolution and microwave scattering models. The greatest improvements will be made with better computer simulations of how the snow microstructure changes, followed by how the microstructure scatters radiation at microwave frequencies. Snow compaction should also be considered in systems to monitor snow mass from space.
Juha Lemmetyinen, Anna Kontu, Jouni Pulliainen, Juho Vehviläinen, Kimmo Rautiainen, Andreas Wiesmann, Christian Mätzler, Charles Werner, Helmut Rott, Thomas Nagler, Martin Schneebeli, Martin Proksch, Dirk Schüttemeyer, Michael Kern, and Malcolm W. J. Davidson
Geosci. Instrum. Method. Data Syst., 5, 403–415, https://doi.org/10.5194/gi-5-403-2016, https://doi.org/10.5194/gi-5-403-2016, 2016
Silvan Leinss, Henning Löwe, Martin Proksch, Juha Lemmetyinen, Andreas Wiesmann, and Irena Hajnsek
The Cryosphere, 10, 1771–1797, https://doi.org/10.5194/tc-10-1771-2016, https://doi.org/10.5194/tc-10-1771-2016, 2016
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Four years of anisotropy measurements of seasonal snow are presented in the paper. The anisotropy was measured every 4 h with a ground-based polarimetric radar. An electromagnetic model has been developed to measured the anisotropy with radar instruments from ground and from space. The anisotropic permittivity was derived with Maxwell–Garnett-type mixing formulas which are shown to be equivalent to series expansions of the permittivity tensor based on spatial correlation function of snow.
Henna-Reetta Hannula, Juha Lemmetyinen, Anna Kontu, Chris Derksen, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 347–363, https://doi.org/10.5194/gi-5-347-2016, https://doi.org/10.5194/gi-5-347-2016, 2016
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The paper described an extensive in situ data set of bulk snow depth, snow water equivalent, and snow density collected as a support of SnowSAR-2 airborne campaign in northern Finland. The spatial and temporal variability of these snow properties was analyzed in different land cover types. The success of the chosen measurement protocol to provide an accurate reference for the simultaneous SAR data products was analyzed in the context of spatial scale, sample size, and uncertainty.
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, https://doi.org/10.5194/gi-5-219-2016, 2016
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Physically based models that predict the properties of snow on the ground are used in many applications, but meteorological input data required by these models are hard to obtain in cold regions. Monitoring at the Sodankyla research station allows construction of model input and evaluation datasets covering several years for the first time in the Arctic. The data are used to show that a sophisticated snow model developed for warmer and wetter sites can perform well in very different conditions.
Jaakko Ikonen, Juho Vehviläinen, Kimmo Rautiainen, Tuomo Smolander, Juha Lemmetyinen, Simone Bircher, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 95–108, https://doi.org/10.5194/gi-5-95-2016, https://doi.org/10.5194/gi-5-95-2016, 2016
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A comprehensive, distributed network of in situ measurement stations gathering information on soil moisture has been set up in recent years at the Finnish Meteorological Institute's (FMI) Sodankylä Arctic research station. The network is used as a tool to evaluate the validity of satellite retrievals of soil properties. We present the soil moisture observation network and the results of comparisons of top layer soil moisture between 2012 and 2014 against ESA CCI product soil moisture retrievals.
William Maslanka, Leena Leppänen, Anna Kontu, Mel Sandells, Juha Lemmetyinen, Martin Schneebeli, Martin Proksch, Margret Matzl, Henna-Reetta Hannula, and Robert Gurney
Geosci. Instrum. Method. Data Syst., 5, 85–94, https://doi.org/10.5194/gi-5-85-2016, https://doi.org/10.5194/gi-5-85-2016, 2016
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The paper presents the initial findings of the Arctic Snow Microstructure Experiment in Sodankylä, Finland. The experiment observed the microwave emission of extracted snow slabs on absorbing and reflecting bases. Snow parameters were recorded to simulate the emission upon those bases using two different emission models. The smallest simulation errors were associated with the absorbing base at vertical polarization. The observations will be used for the development of snow emission modelling.
Alexandre Roy, Alain Royer, Olivier St-Jean-Rondeau, Benoit Montpetit, Ghislain Picard, Alex Mavrovic, Nicolas Marchand, and Alexandre Langlois
The Cryosphere, 10, 623–638, https://doi.org/10.5194/tc-10-623-2016, https://doi.org/10.5194/tc-10-623-2016, 2016
M. Proksch, C. Mätzler, A. Wiesmann, J. Lemmetyinen, M. Schwank, H. Löwe, and M. Schneebeli
Geosci. Model Dev., 8, 2611–2626, https://doi.org/10.5194/gmd-8-2611-2015, https://doi.org/10.5194/gmd-8-2611-2015, 2015
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The measurement of snow properties on global scale relies on microwave remote sensing data. The interpretation of the data is however challenging. Here we introduce MEMLS3&a, an extension of the snow emission model MEMLS, to include a backscatter model for active microwave remote sensing. In MEMLS3&a, snow input parameters can be derived by objective measurement methods, which avoids fitting the scattering efficiency of snow. The model is validated with combined active and passive measurements.
A. Roy, A. Royer, B. Montpetit, P. A. Bartlett, and A. Langlois
The Cryosphere, 7, 961–975, https://doi.org/10.5194/tc-7-961-2013, https://doi.org/10.5194/tc-7-961-2013, 2013
Related subject area
Biogeochemistry: Greenhouse Gases
Air temperature and precipitation constraining the modelled wetland methane emissions in a boreal region in northern Europe
Ensemble estimates of global wetland methane emissions over 2000–2020
Seasonal carbon fluxes from vegetation and soil in a Mediterranean non-tidal salt marsh
Explainable machine learning for modeling of net ecosystem exchange in boreal forests
Dynamics of CO2 and CH4 fluxes in Red Sea mangrove soils
Nitrous oxide (N2O) in Macquarie Harbour, Tasmania
Technical note: A low-cost, automatic soil–plant–atmosphere enclosure system to investigate CO2 and evapotranspiration flux dynamics
Tidal influence on carbon dioxide and methane fluxes from tree stems and soils in mangrove forests
Drought conditions disrupt atmospheric carbon uptake in a Mediterranean saline lake
Physicochemical perturbation increases nitrous oxide production from denitrification in soils and sediments
Carbon degradation and mobilisation potentials of thawing permafrost peatlands in northern Norway inferred from laboratory incubations
Seasonal dynamics and regional distribution patterns of CO2 and CH4 in the north-eastern Baltic Sea
Interannual and seasonal variability of the air–sea CO2 exchange at Utö in the coastal region of the Baltic Sea
CO2 emissions of drained coastal peatlands in the Netherlands and potential emission reduction by water infiltration systems
Seasonal and inter-annual variability of carbon fluxes in southern Africa seen by GOSAT
Influence of wind strength and direction on diffusive methane fluxes and atmospheric methane concentrations above the North Sea
Eddy covariance fluxes of CO2, CH4 and N2O on a drained peatland forest after clearcutting
Eddy Covariance Evaluation of Ecosystem Fluxes at a Temperate Saltmarsh in Victoria, Australia Shows Large CO2 Uptake
Using eddy covariance observations to determine the carbon sequestration characteristics of subalpine forests in the Qinghai–Tibet Plateau
Isotopomer labeling and oxygen dependence of hybrid nitrous oxide production
The emission of CO from tropical rainforest soils
Interferences caused by the microbial methane cycle during the assessment of abandoned oil and gas wells
Carbon sequestration in different urban vegetation types in Southern Finland
Modelling CO2 and N2O emissions from soils in silvopastoral systems of the West African Sahelian band
A case study on topsoil removal and rewetting for paludiculture: effect on biogeochemistry and greenhouse gas emissions from Typha latifolia, Typha angustifolia, and Azolla filiculoides
Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling
Proglacial methane emissions driven by meltwater and groundwater flushing in a high Arctic glacial catchment
Timescale dependence of airborne fraction and underlying climate–carbon-cycle feedbacks for weak perturbations in CMIP5 models
Technical note: Preventing CO2 overestimation from mercuric or copper(II) chloride preservation of dissolved greenhouse gases in freshwater samples
Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data
Diurnal versus spatial variability of greenhouse gas emissions from an anthropogenically modified lowland river in Germany
Regional assessment and uncertainty analysis of carbon and nitrogen balances at cropland scale using the ecosystem model LandscapeDNDC
Resolving heterogeneous fluxes from tundra halves the growing season carbon budget
Lawns and meadows in urban green space – a comparison from perspectives of greenhouse gases, drought resilience and plant functional types
Large contribution of soil N2O emission to the global warming potential of a large-scale oil palm plantation despite changing from conventional to reduced management practices
Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data
Enhanced Southern Ocean CO2 outgassing as a result of stronger and poleward shifted southern hemispheric westerlies
Spatial and temporal variability of methane emissions and environmental conditions in a hyper-eutrophic fishpond
Optical and radar Earth observation data for upscaling methane emissions linked to permafrost degradation in sub-Arctic peatlands in northern Sweden
Herbivore–shrub interactions influence ecosystem respiration and biogenic volatile organic compound composition in the subarctic
Methane emissions due to reservoir flushing: a significant emission pathway?
Carbon dioxide and methane fluxes from mounds of African fungus-growing termites
Diel and seasonal methane dynamics in the shallow and turbulent Wadden Sea
Technical note: Skirt chamber – an open dynamic method for the rapid and minimally intrusive measurement of greenhouse gas emissions from peatlands
Seasonal variability of nitrous oxide concentrations and emissions in a temperate estuary
Simulated methane emissions from Arctic ponds are highly sensitive to warming
Water-table-driven greenhouse gas emission estimates guide peatland restoration at national scale
Relationships between greenhouse gas production and landscape position during short-term permafrost thaw under anaerobic conditions in the Lena Delta
Carbon emissions and radiative forcings from tundra wildfires in the Yukon–Kuskokwim River Delta, Alaska
Carbon monoxide (CO) cycling in the Fram Strait, Arctic Ocean
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Müller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul A. Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
Biogeosciences, 22, 323–340, https://doi.org/10.5194/bg-22-323-2025, https://doi.org/10.5194/bg-22-323-2025, 2025
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Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in northern Europe using ecosystem models, atmospheric inversions, and upscaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions, and upscaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Lorena Carrasco-Barea, Dolors Verdaguer, Maria Gispert, Xavier D. Quintana, Hélène Bourhis, and Laura Llorens
Biogeosciences, 22, 289–304, https://doi.org/10.5194/bg-22-289-2025, https://doi.org/10.5194/bg-22-289-2025, 2025
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Carbon dioxide fluxes have been measured seasonally in four plant species in a Mediterranean non-tidal salt marsh, highlighting the high carbon removal potential that these species have. Carbon dioxide and methane emissions from soil showed high variability among the habitats studied, and they were generally higher than those observed in tidal salt marshes. Our results are important for making more accurate predictions regarding carbon emissions from these ecosystems.
Ekaterina Ezhova, Topi Laanti, Anna Lintunen, Pasi Kolari, Tuomo Nieminen, Ivan Mammarella, Keijo Heljanko, and Markku Kulmala
Biogeosciences, 22, 257–288, https://doi.org/10.5194/bg-22-257-2025, https://doi.org/10.5194/bg-22-257-2025, 2025
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Machine learning (ML) models are gaining popularity in biogeosciences. They are applied as gap-filling methods and used to upscale carbon fluxes to larger areas. Here we use explainable artificial intelligence (XAI) methods to elucidate the performance of machine learning models for carbon dioxide fluxes in boreal forests. We show that statistically equal models treat input variables differently. XAI methods can help scientists make informed decisions when applying ML models in their research.
Jessica Breavington, Alexandra Steckbauer, Chuancheng Fu, Mongi Ennasri, and Carlos M. Duarte
Biogeosciences, 22, 117–134, https://doi.org/10.5194/bg-22-117-2025, https://doi.org/10.5194/bg-22-117-2025, 2025
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Mangrove carbon storage in the Red Sea is lower than average due to challenging growth conditions. We collected mangrove soil cores over multiple seasons to measure greenhouse gas (GHG) flux of carbon dioxide and methane. GHG emissions are a small offset to mangrove carbon storage overall but punctuated by periods of high emission. This variation is linked to environmental and soil properties, which were also measured. The findings aid understanding of GHG dynamics in arid mangrove ecosystems.
Johnathan Daniel Maxey, Neil D. Hartstein, Hermann W. Bange, and Moritz Müller
Biogeosciences, 21, 5613–5637, https://doi.org/10.5194/bg-21-5613-2024, https://doi.org/10.5194/bg-21-5613-2024, 2024
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The distribution of N2O in fjord-like estuaries is poorly described in the Southern Hemisphere. Our study describes N2O distribution and its drivers in one such system in Macquarie Harbour, Tasmania. Water samples were collected seasonally in 2022 and 2023. Results show the system removes atmospheric N2O when river flow is high, whereas the system emits N2O when the river flow is low. N2O generated in basins is intercepted by the surface water and exported to the ocean during high river flow.
Wael Al Hamwi, Maren Dubbert, Jörg Schaller, Matthias Lück, Marten Schmidt, and Mathias Hoffmann
Biogeosciences, 21, 5639–5651, https://doi.org/10.5194/bg-21-5639-2024, https://doi.org/10.5194/bg-21-5639-2024, 2024
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We present a fully automatic, low-cost soil–plant enclosure system to monitor CO2 and evapotranspiration fluxes within greenhouse experiments. It operates in two modes: independent, using low-cost sensors, and dependent, where multiple chambers connect to a single gas analyzer via a low-cost multiplexer. This system provides precise, accurate measurements and high temporal resolution, enabling comprehensive monitoring of plant–soil responses to various treatments and conditions.
Zhao-Jun Yong, Wei-Jen Lin, Chiao-Wen Lin, and Hsing-Juh Lin
Biogeosciences, 21, 5247–5260, https://doi.org/10.5194/bg-21-5247-2024, https://doi.org/10.5194/bg-21-5247-2024, 2024
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We measured CO2 and CH4 fluxes from mangrove stems and soils of Avicennia marina and Kandelia obovata during tidal cycles. Both stem types served as CO2 and CH4 sources, emitting less CH4 than soils, with no difference in CO2 flux. While A. marina stems showed increased CO2 fluxes from low to high tides, they acted as a CH4 sink before flooding and as a source after ebbing. However, K. obovata stems showed no flux pattern. This study highlights the need to consider tidal influence and species.
Ihab Alfadhel, Ignacio Peralta-Maraver, Isabel Reche, Enrique P. Sánchez-Cañete, Sergio Aranda-Barranco, Eva Rodríguez-Velasco, Andrew S. Kowalski, and Penélope Serrano-Ortiz
Biogeosciences, 21, 5117–5129, https://doi.org/10.5194/bg-21-5117-2024, https://doi.org/10.5194/bg-21-5117-2024, 2024
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Inland saline lakes are crucial in the global carbon cycle, but increased droughts may alter their carbon exchange capacity. We measured CO2 and CH4 fluxes in a Mediterranean saline lake using the eddy covariance method under dry and wet conditions. We found the lake acts as a carbon sink during wet periods but not during droughts. These results highlight the importance of saline lakes in carbon sequestration and their vulnerability to climate-change-induced droughts.
Nathaniel B. Weston, Cynthia Troy, Patrick J. Kearns, Jennifer L. Bowen, William Porubsky, Christelle Hyacinthe, Christof Meile, Philippe Van Cappellen, and Samantha B. Joye
Biogeosciences, 21, 4837–4851, https://doi.org/10.5194/bg-21-4837-2024, https://doi.org/10.5194/bg-21-4837-2024, 2024
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Nitrous oxide (N2O) is a potent greenhouse and ozone-depleting gas produced largely from microbial nitrogen cycling processes, and human activities have resulted in increases in atmospheric N2O. We investigate the role of physical and chemical disturbances to soils and sediments in N2O production. We demonstrate that physicochemical perturbation increases N2O production, microbial community adapts over time, and initial perturbation appears to confer resilience to subsequent disturbance.
Sigrid Trier Kjær, Sebastian Westermann, Nora Nedkvitne, and Peter Dörsch
Biogeosciences, 21, 4723–4737, https://doi.org/10.5194/bg-21-4723-2024, https://doi.org/10.5194/bg-21-4723-2024, 2024
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Permafrost peatlands are thawing due to climate change, releasing large quantities of carbon that degrades upon thawing and is released as CO2, CH4 or dissolved organic carbon (DOC). We incubated thawed Norwegian permafrost peat plateaus and thermokarst pond sediment found next to permafrost for up to 350 d to measure carbon loss. CO2 production was initially the highest, whereas CH4 production increased over time. The largest carbon loss was measured at the top of the peat plateau core as DOC.
Silvie Lainela, Erik Jacobs, Stella-Theresa Luik, Gregor Rehder, and Urmas Lips
Biogeosciences, 21, 4495–4519, https://doi.org/10.5194/bg-21-4495-2024, https://doi.org/10.5194/bg-21-4495-2024, 2024
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We evaluate the variability of carbon dioxide and methane in the surface layer of the north-eastern basins of the Baltic Sea in 2018. We show that the shallower coastal areas have considerably higher spatial variability and seasonal amplitude of surface layer pCO2 and cCH4 than measured in the offshore areas of the Baltic Sea. Despite this high variability, caused mostly by coastal physical processes, the average annual air–sea CO2 fluxes differed only marginally between the sub-basins.
Martti Honkanen, Mika Aurela, Juha Hatakka, Lumi Haraguchi, Sami Kielosto, Timo Mäkelä, Jukka Seppälä, Simo-Matti Siiriä, Ken Stenbäck, Juha-Pekka Tuovinen, Pasi Ylöstalo, and Lauri Laakso
Biogeosciences, 21, 4341–4359, https://doi.org/10.5194/bg-21-4341-2024, https://doi.org/10.5194/bg-21-4341-2024, 2024
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The exchange of CO2 between the sea and the atmosphere was studied in the Archipelago Sea, Baltic Sea, in 2017–2021, using an eddy covariance technique. The sea acted as a net source of CO2 with an average yearly emission of 27.1 gC m-2 yr-1, indicating that the marine ecosystem respired carbon that originated elsewhere. The yearly CO2 emission varied between 18.2–39.2 gC m-2 yr-1, mostly due to the yearly variation of ecosystem carbon uptake.
Ralf C. H. Aben, Daniël van de Craats, Jim Boonman, Stijn H. Peeters, Bart Vriend, Coline C. F. Boonman, Ype van der Velde, Gilles Erkens, and Merit van den Berg
Biogeosciences, 21, 4099–4118, https://doi.org/10.5194/bg-21-4099-2024, https://doi.org/10.5194/bg-21-4099-2024, 2024
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Drained peatlands cause high CO2 emissions. We assessed the effectiveness of subsurface water infiltration systems (WISs) in reducing CO2 emissions related to increases in water table depth (WTD) on 12 sites for up to 4 years. Results show WISs markedly reduced emissions by 2.1 t CO2-C ha-1 yr-1. The relationship between the amount of carbon above the WTD and CO2 emission was stronger than the relationship between WTD and emission. Long-term monitoring is crucial for accurate emission estimates.
Eva-Marie Metz, Sanam Noreen Vardag, Sourish Basu, Martin Jung, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-1955, https://doi.org/10.5194/egusphere-2024-1955, 2024
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We estimate CO2 fluxes in semi-arid southern Africa from 2009 to 2018 based on satellite CO2 measurements and atmospheric inverse modelling. By selecting process-based vegetation models, which agree with the satellite CO2 fluxes, we find that soil respiration mainly drives the seasonality, whereas photosynthesis substantially influences the interannual variability. Our study emphasizes the need of better representing the response of semi-arid ecosystems to soil rewetting in vegetation models.
Ingeborg Bussmann, Eric P. Achterberg, Holger Brix, Nicolas Brüggemann, Götz Flöser, Claudia Schütze, and Philipp Fischer
Biogeosciences, 21, 3819–3838, https://doi.org/10.5194/bg-21-3819-2024, https://doi.org/10.5194/bg-21-3819-2024, 2024
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Methane (CH4) is an important greenhouse gas and contributes to climate warming. However, the input of CH4 from coastal areas to the atmosphere is not well defined. Dissolved and atmospheric CH4 was determined at high spatial resolution in or above the North Sea. The atmospheric CH4 concentration was mainly influenced by wind direction. With our detailed study on the spatial distribution of CH4 fluxes we were able to provide a detailed and more realistic estimation of coastal CH4 fluxes.
Olli-Pekka Tikkasalo, Olli Peltola, Pavel Alekseychik, Juha Heikkinen, Samuli Launiainen, Aleksi Lehtonen, Qian Li, Eduardo Martinez-García, Mikko Peltoniemi, Petri Salovaara, Ville Tuominen, and Raisa Mäkipää
EGUsphere, https://doi.org/10.5194/egusphere-2024-1994, https://doi.org/10.5194/egusphere-2024-1994, 2024
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The emissions of greenhouse gases (GHG) carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) were measured from a clearcut peatland forest site. The measurements covered the whole year of 2022 which was the second growing season after the clearcut. The site was a strong GHG source and the highest emissions came from CO2 followed by N2O and CH4. A statistical model that included information on different surfaces in the site was developed to unravel surface-type specific GHG fluxes.
Ruth Reef, Edoardo Daly, Tivanka Anandappa, Eboni-Jane Vienna-Hallam, Harriet Robertson, Matthew Peck, and Adrien Guyot
EGUsphere, https://doi.org/10.5194/egusphere-2024-2182, https://doi.org/10.5194/egusphere-2024-2182, 2024
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Studies show that saltmarshes excel at capturing carbon from the atmosphere. In this study, we measured CO2 flux in an Australian temperate saltmarsh on French Island. The temperate saltmarsh exhibited strong seasonality. During the warmer growing season, the saltmarsh absorbed on average 10.5 grams of CO2 from the atmosphere per m2 daily. Even in winter, when plants were dormant, it continued to be a CO2 sink, albeit smaller. Cool temperatures and high cloud cover inhibit carbon sequestration.
Niu Zhu, Jinniu Wang, Dongliang Luo, Xufeng Wang, Cheng Shen, and Ning Wu
Biogeosciences, 21, 3509–3522, https://doi.org/10.5194/bg-21-3509-2024, https://doi.org/10.5194/bg-21-3509-2024, 2024
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Our study delves into the vital role of subalpine forests in the Qinghai–Tibet Plateau as carbon sinks in the context of climate change. Utilizing advanced eddy covariance systems, we uncover their significant carbon sequestration potential, observing distinct seasonal patterns influenced by temperature, humidity, and radiation. Notably, these forests exhibit robust carbon absorption, with potential implications for global carbon balance.
Colette L. Kelly, Nicole M. Travis, Pascale Anabelle Baya, Claudia Frey, Xin Sun, Bess B. Ward, and Karen L. Casciotti
Biogeosciences, 21, 3215–3238, https://doi.org/10.5194/bg-21-3215-2024, https://doi.org/10.5194/bg-21-3215-2024, 2024
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Nitrous oxide, a potent greenhouse gas, accumulates in regions of the ocean that are low in dissolved oxygen. We used a novel combination of chemical tracers to determine how nitrous oxide is produced in one of these regions, the eastern tropical North Pacific Ocean. Our experiments showed that the two most important sources of nitrous oxide under low-oxygen conditions are denitrification, an anaerobic process, and a novel “hybrid” process performed by ammonia-oxidizing archaea.
Hella van Asperen, Thorsten Warneke, Alessandro Carioca de Araújo, Bruce Forsberg, Sávio José Filgueiras Ferreira, Thomas Röckmann, Carina van der Veen, Sipko Bulthuis, Leonardo Ramos de Oliveira, Thiago de Lima Xavier, Jailson da Mata, Marta de Oliveira Sá, Paulo Ricardo Teixeira, Julie Andrews de França e Silva, Susan Trumbore, and Justus Notholt
Biogeosciences, 21, 3183–3199, https://doi.org/10.5194/bg-21-3183-2024, https://doi.org/10.5194/bg-21-3183-2024, 2024
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Carbon monoxide (CO) is regarded as an important indirect greenhouse gas. Soils can emit and take up CO, but, until now, uncertainty remains as to which process dominates in tropical rainforests. We present the first soil CO flux measurements from a tropical rainforest. Based on our observations, we report that tropical rainforest soils are a net source of CO. In addition, we show that valley streams and inundated areas are likely additional hot spots of CO in the ecosystem.
Sebastian F. A. Jordan, Stefan Schloemer, Martin Krüger, Tanja Heffner, Marcus A. Horn, and Martin Blumenberg
EGUsphere, https://doi.org/10.5194/egusphere-2024-1461, https://doi.org/10.5194/egusphere-2024-1461, 2024
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In a multilayered approach, we studied eight cut and buried abandoned oil wells in a peat rich area of Northern Germany for methane flux, soil gas composition, and isotopic signatures of soil methane and carbon dioxide. The detected methane emissions were of biogenic, peat origin and were not associated with the abandoned wells. Additional microbial analysis and methane oxidation rate measurements demonstrated a high methane-emission mitigation potential in the studied peat-soils.
Laura Thölix, Leif Backman, Minttu Havu, Esko Karvinen, Jesse Soininen, Justine Trémeau, Olli Nevalainen, Joyson Ahongshangbam, Leena Järvi, and Liisa Kulmala
EGUsphere, https://doi.org/10.5194/egusphere-2024-1453, https://doi.org/10.5194/egusphere-2024-1453, 2024
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Cities seek carbon neutrality and are interested in the sinks of urban vegetation. Measurements are difficult to do which leads to the need for modeling carbon cycle. In this study, we examined the performance of models in estimating carbon sequestration rates in lawns, park trees, and urban forests in Helsinki, Finland. We found that models simulated seasonal and annual variations well. Trees had larger carbon sequestration rates compared with lawns and irrigation often increased carbon sink.
Yélognissè Agbohessou, Claire Delon, Manuela Grippa, Eric Mougin, Daouda Ngom, Espoir Koudjo Gaglo, Ousmane Ndiaye, Paulo Salgado, and Olivier Roupsard
Biogeosciences, 21, 2811–2837, https://doi.org/10.5194/bg-21-2811-2024, https://doi.org/10.5194/bg-21-2811-2024, 2024
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Emissions of greenhouse gases in the Sahel are not well represented because they are considered weak compared to the rest of the world. However, natural areas in the Sahel emit carbon dioxide and nitrous oxides, which need to be assessed because of extended surfaces. We propose an assessment of such emissions in Sahelian silvopastoral systems and of how they are influenced by environmental characteristics. These results are essential to inform climate change strategies in the region.
Merit van den Berg, Thomas M. Gremmen, Renske J. E. Vroom, Jacobus van Huissteden, Jim Boonman, Corine J. A. van Huissteden, Ype van der Velde, Alfons J. P. Smolders, and Bas P. van de Riet
Biogeosciences, 21, 2669–2690, https://doi.org/10.5194/bg-21-2669-2024, https://doi.org/10.5194/bg-21-2669-2024, 2024
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Drained peatlands emit 3 % of the global greenhouse gas emissions. Paludiculture is a way to reduce CO2 emissions while at the same time generating an income for landowners. The side effect is the potentially high methane emissions. We found very high methane emissions for broadleaf cattail compared with narrowleaf cattail and water fern. The rewetting was, however, effective to stop CO2 emissions for all species. The highest potential to reduce greenhouse gas emissions had narrowleaf cattail.
Thea H. Heimdal, Galen A. McKinley, Adrienne J. Sutton, Amanda R. Fay, and Lucas Gloege
Biogeosciences, 21, 2159–2176, https://doi.org/10.5194/bg-21-2159-2024, https://doi.org/10.5194/bg-21-2159-2024, 2024
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Measurements of ocean carbon are limited in time and space. Machine learning algorithms are therefore used to reconstruct ocean carbon where observations do not exist. Improving these reconstructions is important in order to accurately estimate how much carbon the ocean absorbs from the atmosphere. In this study, we find that a small addition of observations from the Southern Ocean, obtained by autonomous sampling platforms, could significantly improve the reconstructions.
Gabrielle Emma Kleber, Leonard Magerl, Alexandra V. Turchyn, Mark Trimmer, Yizhu Zhu, and Andrew Hodson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1273, https://doi.org/10.5194/egusphere-2024-1273, 2024
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Our research on Svalbard has uncovered that melting glaciers can release large amounts of methane, a potent greenhouse gas. By studying a glacier over two summers, we found that its river was highly concentrated in methane. This suggests that as the Arctic warms and glaciers melt, they could be a significant source of methane emissions. This is the first time such emissions have been measured on Svalbard, indicating a wider environmental concern as similar processes may occur across the Arctic.
Guilherme L. Torres Mendonça, Julia Pongratz, and Christian H. Reick
Biogeosciences, 21, 1923–1960, https://doi.org/10.5194/bg-21-1923-2024, https://doi.org/10.5194/bg-21-1923-2024, 2024
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We study the timescale dependence of airborne fraction and underlying feedbacks by a theory of the climate–carbon system. Using simulations we show the predictive power of this theory and find that (1) this fraction generally decreases for increasing timescales and (2) at all timescales the total feedback is negative and the model spread in a single feedback causes the spread in the airborne fraction. Our study indicates that those are properties of the system, independently of the scenario.
François Clayer, Jan Erik Thrane, Kuria Ndungu, Andrew King, Peter Dörsch, and Thomas Rohrlack
Biogeosciences, 21, 1903–1921, https://doi.org/10.5194/bg-21-1903-2024, https://doi.org/10.5194/bg-21-1903-2024, 2024
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Determination of dissolved greenhouse gas (GHG) in freshwater allows us to estimate GHG fluxes. Mercuric chloride (HgCl2) is used to preserve water samples prior to GHG analysis despite its environmental and health impacts and interferences with water chemistry in freshwater. Here, we tested the effects of HgCl2, two substitutes and storage time on GHG in water from two boreal lakes. Preservation with HgCl2 caused overestimation of CO2 concentration with consequences for GHG flux estimation.
Helena Rautakoski, Mika Korkiakoski, Jarmo Mäkelä, Markku Koskinen, Kari Minkkinen, Mika Aurela, Paavo Ojanen, and Annalea Lohila
Biogeosciences, 21, 1867–1886, https://doi.org/10.5194/bg-21-1867-2024, https://doi.org/10.5194/bg-21-1867-2024, 2024
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Current and future nitrous oxide (N2O) emissions are difficult to estimate due to their high variability in space and time. Several years of N2O fluxes from drained boreal peatland forest indicate high importance of summer precipitation, winter temperature, and snow conditions in controlling annual N2O emissions. The results indicate increasing year-to-year variation in N2O emissions in changing climate with more extreme seasonal weather conditions.
Matthias Koschorreck, Norbert Kamjunke, Uta Koedel, Michael Rode, Claudia Schuetze, and Ingeborg Bussmann
Biogeosciences, 21, 1613–1628, https://doi.org/10.5194/bg-21-1613-2024, https://doi.org/10.5194/bg-21-1613-2024, 2024
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We measured the emission of carbon dioxide (CO2) and methane (CH4) from different sites at the river Elbe in Germany over 3 days to find out what is more important for quantification: small-scale spatial variability or diurnal temporal variability. We found that CO2 emissions were very different between day and night, while CH4 emissions were more different between sites. Dried out river sediments contributed to CO2 emissions, while the side areas of the river were important CH4 sources.
Odysseas Sifounakis, Edwin Haas, Klaus Butterbach-Bahl, and Maria P. Papadopoulou
Biogeosciences, 21, 1563–1581, https://doi.org/10.5194/bg-21-1563-2024, https://doi.org/10.5194/bg-21-1563-2024, 2024
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We performed a full assessment of the carbon and nitrogen cycles of a cropland ecosystem. An uncertainty analysis and quantification of all carbon and nitrogen fluxes were deployed. The inventory simulations include greenhouse gas emissions of N2O, NH3 volatilization and NO3 leaching from arable land cultivation in Greece. The inventory also reports changes in soil organic carbon and nitrogen stocks in arable soils.
Sarah M. Ludwig, Luke Schiferl, Jacqueline Hung, Susan M. Natali, and Roisin Commane
Biogeosciences, 21, 1301–1321, https://doi.org/10.5194/bg-21-1301-2024, https://doi.org/10.5194/bg-21-1301-2024, 2024
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Landscapes are often assumed to be homogeneous when using eddy covariance fluxes, which can lead to biases when calculating carbon budgets. In this study we report eddy covariance carbon fluxes from heterogeneous tundra. We used the footprints of each flux observation to unmix the fluxes coming from components of the landscape. We identified and quantified hot spots of carbon emissions in the landscape. Accurately scaling with landscape heterogeneity yielded half as much regional carbon uptake.
Justine Trémeau, Beñat Olascoaga, Leif Backman, Esko Karvinen, Henriikka Vekuri, and Liisa Kulmala
Biogeosciences, 21, 949–972, https://doi.org/10.5194/bg-21-949-2024, https://doi.org/10.5194/bg-21-949-2024, 2024
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We studied urban lawns and meadows in the Helsinki metropolitan area, Finland. We found that meadows are more resistant to drought events but that they do not increase carbon sequestration compared with lawns. Moreover, the transformation from lawns to meadows did not demonstrate any negative climate effects in terms of greenhouse gas emissions. Even though social and economic aspects also steer urban development, these results can guide planning to consider carbon-smart options.
Guantao Chen, Edzo Veldkamp, Muhammad Damris, Bambang Irawan, Aiyen Tjoa, and Marife D. Corre
Biogeosciences, 21, 513–529, https://doi.org/10.5194/bg-21-513-2024, https://doi.org/10.5194/bg-21-513-2024, 2024
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We established an oil palm management experiment in a large-scale oil palm plantation in Jambi, Indonesia. We recorded oil palm fruit yield and measured soil CO2, N2O, and CH4 fluxes. After 4 years of treatment, compared with conventional fertilization with herbicide weeding, reduced fertilization with mechanical weeding did not reduce yield and soil greenhouse gas emissions, which highlights the legacy effects of over a decade of conventional management prior to the start of the experiment.
Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Tobias Houska, David Kraus, Gretchen Maria Gettel, Ralf Kiese, Lutz Breuer, and Klaus Butterbach-Bahl
Biogeosciences, 20, 5029–5067, https://doi.org/10.5194/bg-20-5029-2023, https://doi.org/10.5194/bg-20-5029-2023, 2023
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Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO2, CH4, or N2O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.
Laurie C. Menviel, Paul Spence, Andrew E. Kiss, Matthew A. Chamberlain, Hakase Hayashida, Matthew H. England, and Darryn Waugh
Biogeosciences, 20, 4413–4431, https://doi.org/10.5194/bg-20-4413-2023, https://doi.org/10.5194/bg-20-4413-2023, 2023
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As the ocean absorbs 25% of the anthropogenic emissions of carbon, it is important to understand the impact of climate change on the flux of carbon between the ocean and the atmosphere. Here, we use a very high-resolution ocean, sea-ice, carbon cycle model to show that the capability of the Southern Ocean to uptake CO2 has decreased over the last 40 years due to a strengthening and poleward shift of the southern hemispheric westerlies. This trend is expected to continue over the coming century.
Petr Znachor, Jiří Nedoma, Vojtech Kolar, and Anna Matoušů
Biogeosciences, 20, 4273–4288, https://doi.org/10.5194/bg-20-4273-2023, https://doi.org/10.5194/bg-20-4273-2023, 2023
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We conducted intensive spatial sampling of the hypertrophic fishpond to better understand the spatial dynamics of methane fluxes and environmental heterogeneity in fishponds. The diffusive fluxes of methane accounted for only a minor fraction of the total fluxes and both varied pronouncedly within the pond and over the studied summer season. This could be explained only by the water depth. Wind substantially affected temperature, oxygen and chlorophyll a distribution in the pond.
Sofie Sjögersten, Martha Ledger, Matthias Siewert, Betsabé de la Barreda-Bautista, Andrew Sowter, David Gee, Giles Foody, and Doreen S. Boyd
Biogeosciences, 20, 4221–4239, https://doi.org/10.5194/bg-20-4221-2023, https://doi.org/10.5194/bg-20-4221-2023, 2023
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Permafrost thaw in Arctic regions is increasing methane emissions, but quantification is difficult given the large and remote areas impacted. We show that UAV data together with satellite data can be used to extrapolate emissions across the wider landscape as well as detect areas at risk of higher emissions. A transition of currently degrading areas to fen type vegetation can increase emission by several orders of magnitude, highlighting the importance of quantifying areas at risk.
Cole G. Brachmann, Tage Vowles, Riikka Rinnan, Mats P. Björkman, Anna Ekberg, and Robert G. Björk
Biogeosciences, 20, 4069–4086, https://doi.org/10.5194/bg-20-4069-2023, https://doi.org/10.5194/bg-20-4069-2023, 2023
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Herbivores change plant communities through grazing, altering the amount of CO2 and plant-specific chemicals (termed VOCs) emitted. We tested this effect by excluding herbivores and studying the CO2 and VOC emissions. Herbivores reduced CO2 emissions from a meadow community and altered VOC composition; however, community type had the strongest effect on the amount of CO2 and VOCs released. Herbivores can mediate greenhouse gas emissions, but the effect is marginal and community dependent.
Ole Lessmann, Jorge Encinas Fernández, Karla Martínez-Cruz, and Frank Peeters
Biogeosciences, 20, 4057–4068, https://doi.org/10.5194/bg-20-4057-2023, https://doi.org/10.5194/bg-20-4057-2023, 2023
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Based on a large dataset of seasonally resolved methane (CH4) pore water concentrations in a reservoir's sediment, we assess the significance of CH4 emissions due to reservoir flushing. In the studied reservoir, CH4 emissions caused by one flushing operation can represent 7 %–14 % of the annual CH4 emissions and depend on the timing of the flushing operation. In reservoirs with high sediment loadings, regular flushing may substantially contribute to the overall CH4 emissions.
Matti Räsänen, Risto Vesala, Petri Rönnholm, Laura Arppe, Petra Manninen, Markus Jylhä, Jouko Rikkinen, Petri Pellikka, and Janne Rinne
Biogeosciences, 20, 4029–4042, https://doi.org/10.5194/bg-20-4029-2023, https://doi.org/10.5194/bg-20-4029-2023, 2023
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Fungus-growing termites recycle large parts of dead plant material in African savannas and are significant sources of greenhouse gases. We measured CO2 and CH4 fluxes from their mounds and surrounding soils in open and closed habitats. The fluxes scale with mound volume. The results show that emissions from mounds of fungus-growing termites are more stable than those from other termites. The soil fluxes around the mound are affected by the termite colonies at up to 2 m distance from the mound.
Tim René de Groot, Anne Margriet Mol, Katherine Mesdag, Pierre Ramond, Rachel Ndhlovu, Julia Catherine Engelmann, Thomas Röckmann, and Helge Niemann
Biogeosciences, 20, 3857–3872, https://doi.org/10.5194/bg-20-3857-2023, https://doi.org/10.5194/bg-20-3857-2023, 2023
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This study investigates methane dynamics in the Wadden Sea. Our measurements revealed distinct variations triggered by seasonality and tidal forcing. The methane budget was higher in warmer seasons but surprisingly high in colder seasons. Methane dynamics were amplified during low tides, flushing the majority of methane into the North Sea or releasing it to the atmosphere. Methanotrophic activity was also elevated during low tide but mitigated only a small fraction of the methane efflux.
Frederic Thalasso, Brenda Riquelme, Andrés Gómez, Roy Mackenzie, Francisco Javier Aguirre, Jorge Hoyos-Santillan, Ricardo Rozzi, and Armando Sepulveda-Jauregui
Biogeosciences, 20, 3737–3749, https://doi.org/10.5194/bg-20-3737-2023, https://doi.org/10.5194/bg-20-3737-2023, 2023
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A robust skirt-chamber design to capture and quantify greenhouse gas emissions from peatlands is presented. Compared to standard methods, this design improves the spatial resolution of field studies in remote locations while minimizing intrusion.
Gesa Schulz, Tina Sanders, Yoana G. Voynova, Hermann W. Bange, and Kirstin Dähnke
Biogeosciences, 20, 3229–3247, https://doi.org/10.5194/bg-20-3229-2023, https://doi.org/10.5194/bg-20-3229-2023, 2023
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Nitrous oxide (N2O) is an important greenhouse gas. However, N2O emissions from estuaries underlie significant uncertainties due to limited data availability and high spatiotemporal variability. We found the Elbe Estuary (Germany) to be a year-round source of N2O, with the highest emissions in winter along with high nitrogen loads. However, in spring and summer, N2O emissions did not decrease alongside lower nitrogen loads because organic matter fueled in situ N2O production along the estuary.
Zoé Rehder, Thomas Kleinen, Lars Kutzbach, Victor Stepanenko, Moritz Langer, and Victor Brovkin
Biogeosciences, 20, 2837–2855, https://doi.org/10.5194/bg-20-2837-2023, https://doi.org/10.5194/bg-20-2837-2023, 2023
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We use a new model to investigate how methane emissions from Arctic ponds change with warming. We find that emissions increase substantially. Under annual temperatures 5 °C above present temperatures, pond methane emissions are more than 3 times higher than now. Most of this increase is caused by an increase in plant productivity as plants provide the substrate microbes used to produce methane. We conclude that vegetation changes need to be included in predictions of pond methane emissions.
Julian Koch, Lars Elsgaard, Mogens H. Greve, Steen Gyldenkærne, Cecilie Hermansen, Gregor Levin, Shubiao Wu, and Simon Stisen
Biogeosciences, 20, 2387–2403, https://doi.org/10.5194/bg-20-2387-2023, https://doi.org/10.5194/bg-20-2387-2023, 2023
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Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The emissions are triggered by lowering the water table, which is a necessary step in order to make peatlands arable. Many countries aim at reducing their emissions by restoring peatlands, which can be achieved by stopping agricultural activities and thereby raising the water table. We estimate a total emission of 2.6 Mt CO2-eq for organic-rich peatlands in Denmark and a potential reduction of 77 %.
Mélissa Laurent, Matthias Fuchs, Tanja Herbst, Alexandra Runge, Susanne Liebner, and Claire C. Treat
Biogeosciences, 20, 2049–2064, https://doi.org/10.5194/bg-20-2049-2023, https://doi.org/10.5194/bg-20-2049-2023, 2023
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In this study we investigated the effect of different parameters (temperature, landscape position) on the production of greenhouse gases during a 1-year permafrost thaw experiment. For very similar carbon and nitrogen contents, our results show a strong heterogeneity in CH4 production, as well as in microbial abundance. According to our study, these differences are mainly due to the landscape position and the hydrological conditions established as a result of the topography.
Michael Moubarak, Seeta Sistla, Stefano Potter, Susan M. Natali, and Brendan M. Rogers
Biogeosciences, 20, 1537–1557, https://doi.org/10.5194/bg-20-1537-2023, https://doi.org/10.5194/bg-20-1537-2023, 2023
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Tundra wildfires are increasing in frequency and severity with climate change. We show using a combination of field measurements and computational modeling that tundra wildfires result in a positive feedback to climate change by emitting significant amounts of long-lived greenhouse gasses. With these effects, attention to tundra fires is necessary for mitigating climate change.
Hanna I. Campen, Damian L. Arévalo-Martínez, and Hermann W. Bange
Biogeosciences, 20, 1371–1379, https://doi.org/10.5194/bg-20-1371-2023, https://doi.org/10.5194/bg-20-1371-2023, 2023
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Carbon monoxide (CO) is a climate-relevant trace gas emitted from the ocean. However, oceanic CO cycling is understudied. Results from incubation experiments conducted in the Fram Strait (Arctic Ocean) indicated that (i) pH did not affect CO cycling and (ii) enhanced CO production and consumption were positively correlated with coloured dissolved organic matter and nitrate concentrations. This suggests microbial CO uptake to be the driving factor for CO cycling in the Arctic Ocean.
Cited articles
Adams, J., McNairn, H., Berg, A., and Champagne, C.: Evaluation of
near-surface soil moisture data from an AAFC monitoring network in Manitoba,
Canada: implications for L-band satellite validation, J. Hydrol., 521,
582–592, https://doi.org/10.1016/j.jhydrol.2014.10.024, 2015.
Aires, F., Prigent, C., Rossow, W., and Rothtein, M.: A new neural network
approach including first guess for retrieval of atmospheric water vapor,
cloud liquid water path, surface temperature, and emissivities over land
from satellite microwave observations, J. Geophys. Res.-Atmos., 106,
14887–14907, https://doi.org/10.1029/2001JD900085, 2001.
Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodriguez-Fernandez, N., and Wigneron, J.-P.: The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth Syst. Sci. Data, 9, 293–315, https://doi.org/10.5194/essd-9-293-2017, 2017.
Alshammari, L., Boyd, D., Sowter, A., Marshall, C., Anderson, R., Gilbert,
P., Marsh, S., and Large, D.: Use of Surface Motion Characteristics
Determined by InSAR to Assess Peatland Condition, J. Geophys. Res.-Biogeo.,
125, 293–315, https://doi.org/10.1029/2018JG004953, 2019.
Alvarez-Salazar, O., Hatch, S., Rocca, J., Rosen, P., Shaffer, S., Shen, Y.,
Sweetser, T., and Xaypraseuth, P.: Mission design for NISAR repeat-pass
Interferometric SAR. Sensors, Systems, and Next-Generation Satellites XVIII, 92410C, 11 November 2014,
Amsterdam, the Netherlands, 2014.
Andresen, C. G., Lawrence, D. M., Wilson, C. J., McGuire, A. D., Koven, C., Schaefer, K., Jafarov, E., Peng, S., Chen, X., Gouttevin, I., Burke, E., Chadburn, S., Ji, D., Chen, G., Hayes, D., and Zhang, W.: Soil moisture and hydrology projections of the permafrost region – a model intercomparison, The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, 2020.
Angert, A., Biraud, S., Bonfils, C., Henning, C., Buermann, W., Pinzon, J.,
Tucker, C., and Fung, I.: Drier summers cancel out the CO2 uptake
enhancement induced by warmer springs, P. Natl. Acad. Sci. USA, 102,
10823–10827, https://doi.org/10.1073/pnas.0501647102, 2005.
Arslan, A., Mattila, O.-P., Markkanen, T., Böttcher, K., Susiluoto, J., Törmä, M., Lemmetyinen, J., Metsämäki, S., Aurela, M., Kervinen, M., Takala, M., Härmä, P, Aalto, T., Laurila, T., and Pulliainen, J.: SNOWCARBO: Monitoring and assessment of carbon balance related phenomena in Finland and northern Eurasia, 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada, 3206–3209, https://doi.org/10.1109/IGARSS.2011.6049901, 2011.
Attema, E. and Ulaby, F.: Vegetation modeled as a water cloud, Radio Sci.,
13, 357–364, https://doi.org/10.1029/RS013i002p00357, 1978.
Bachmann, M., Borla Tridon, D., De Zan, F., Krieger, G., and Zink, M.:
Tandem-L observation concept – An acquisition scenario for the global
scientific mapping machine, Proceedings of EUSAR 2016: 11th European
Conference on Synthetic Aperture Radar, 6–9 June 2016, Hamburg, Germany,
1–5, 2016.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein,
A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel,
W., Paw U, K., Pilegaard, K., Schmid, H., Valentini, R., Verma, S., Vesala,
T., Wilson, K., and Wofsy, S.: FLUXNET: A New Tool to Study the Temporal and
Spatial Variability of Ecosystem–Scale Carbon Dioxide, Water Vapor, and
Energy Flux Densities, B. Am. Meteorol. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:fantts>2.3.co;2, 2001.
Bamler, R.: Principles of Synthetic Aperture Radar, Surv. Geophys., 21,
147–157, https://doi.org/10.1023/A:1006790026612, 2000.
Bartsch, A., Kidd, R., Pathe, C., Scipal, K., and Wagner, W.: Satellite
radar imagery for monitoring inland wetlands in boreal and sub-arctic
environments, Aquat. Conserv., 17, 305–317, https://doi.org/10.1002/aqc.836, 2007.
Bartsch, A., Widhalm, B., Kuhry, P., Hugelius, G., Palmtag, J., and Siewert, M. B.: Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?, Biogeosciences, 13, 5453–5470, https://doi.org/10.5194/bg-13-5453-2016, 2016.
Basist, A., Grody, N., Peterson, T., and Williams, C.: Using the special
sensor microwave/imager to monitor land surface temperatures, wetness, and
snow cover, J. Appl. Meteorol. Clim., 37, 888–911, https://doi.org/10.1175/1520-0450(1998)037<0888:UTSSMI>2.0.CO;2, 1998.
Bindlish, R., Jackson, T., Cosh, M., Zhao, T., and O'Neill, P.: Global soil
moisture from the Aquarius/SAC-D satellite: description and initial
assessment, IEEE T. Geosci. Remote Sens., 12, 923–927, https://doi.org/10.1109/LGRS.2014.2364151, 2015.
Bircher, S., Demontoux, F., Razafindratsima, S., Zakharova, E., Drusch, M.,
Wigneron, J.-P., and Kerr, Y.: L-Band Relative Permittivity of Organic Soil
Surface Layers – A New Dataset of Resonant Cavity Measurements and Model
Evaluation, Remote Sens., 8, 1024, https://doi.org/10.3390/rs8121024, 2016.
Björkman, M., Morgner, E., Cooper, E., Elberling, B., Klemedtsson, L.,
and Björk, R.: Winter carbon dioxide effluxes from Arctic ecosystems :
An overview and comparison of methodologies, Gobal Biogeochem. Cy., 24,
GB3010, https://doi.org/10.1029/2009GB003667, 2010.
Bokhorst, S., Pedersen, S., Brucker, L., Anisimov, O., Bjerke, J., Brown,
R., Ehrich, D., Essery, R., Heilig, A., Ingvander, S., Johansson, C.,
Johansson, M., Jónsdóttir, I. S., Inga, N., Luojus, K., Macelloni,
G., Mariash, H., McLennan, D., Rosqvist, G., Sato, A., Savela, H.,
Schneebeli, M., Sokolov, A., Sokratov, S., Terzago, S., Vikhamar-Schuler,
D., Williamson, S., Qiu, Y., and Callaghan, T.: Changing Arctic snow cover:
A review of recent developments and assessment of future needs for
observations, modeling, and impacts, Ambio, 45, 516–537, https://doi.org/10.1007/s13280-016-0770-0, 2016.
Bowling, L., Kane, D., Gieck, R., Hinzman, L., and Lettenmaier, D.: The role
of surface storage in a low-gradient Arctic watershed, Water Resour. Res.,
39, 1087, https://doi.org/10.1029/2002WR001466, 2003.
Box, J., Colgan, W., Christensen, T. R., Schmidt, N. M., Lund, M.,
Parmentier, F.-J., Brown, R., Bhatt, U., Euskirchen, E., and Romanovsky, V.:
Key indicators of Arctic climate change: 1971–2017, Environ. Res. Lett.,
14, 045010, https://doi.org/10.1088/1748-9326/aafc1b, 2019.
Brooks, P. and Williams, M.: Snowpack controls on nitrogen cycling and
export in seasonally snow-covered catchments, Hydrol. Process., 13,
2177–2190, https://doi.org/10.1002/(SICI)1099-1085(199910)13:14/15<2177::AID-HYP850>3.0.CO;2-V, 1999.
Brooks, P., Schmidt, S., and Williams, M.: Winter production of CO2 and N2O
from alpine tundra: Environmental controls and relationship to inter-system
C and N fluxes, Oecologia, 110, 403–413, https://doi.org/10.1007/PL00008814, 1997.
Brown, J., Ferrians, O., Heginbottom, J., and Melnikov, E.: Circum-Arctic
Map of Permafrost and Ground-Ice Conditions, Version 2. Boulder, Colorado
USA, NSIDC, National Snow and Ice Data Center [data set], https://doi.org/10.7265/skbg-kf16, 2002.
Brucker, L., Dinnat, E. P., and Koenig, L. S.: Weekly gridded Aquarius L-band radiometer/scatterometer observations and salinity retrievals over the polar regions – Part 1: Product description, The Cryosphere, 8, 905–913, https://doi.org/10.5194/tc-8-905-2014, 2014.
Buchwitz, M., Schneising, O., Burrows, J. P., Bovensmann, H., Reuter, M., and Notholt, J.: First direct observation of the atmospheric CO2 year-to-year increase from space, Atmos. Chem. Phys., 7, 4249–4256, https://doi.org/10.5194/acp-7-4249-2007, 2007.
Callaghan, T., Johansson, M., Brown, R., Groisman, P., Labba, N., Radionov,
V., Bradley, R., Blangy, S., Bulygina, O., Christensen, T., Colman, J.,
Essery, R., Forbes, B., Forchhammer, M., Golubev, V., Honrath, R., Juday,
G., Meshcherskaya, A., Phoenix, G., Pomeroy, J., Rautio, A., Robinson, D.,
Schmidt, N., Serreze, M., Shevchenko, V., Shiklomanov, A., Shmakin, A.,
Sköld, P., Sturm, M., Woo, M., Woodm E.: Multiple effects of
changes in Arctic snow cover, Ambio, 40, 32–45, https://doi.org/10.1007/s13280-011-0213-x, 2011.
Carreiras, J., Quegan, S., Le Toan, T., Ho Tong Minh, D., Saatchi, S.,
Carvalhais, N., Reichstein, M., and Scipal, K.: Coverage of high biomass
forests by the ESA BIOMASS mission under defense restrictions, Remote Sens.
Environ., 196, 154–162, https://doi.org/10.1016/j.rse.2017.05.003, 2017.
Chan, S., Bindlish, R., O'Neill, P., Njoku, E., Jackson, T., Colliander, A.,
Chen, F., Burgin, M., Dunbar, S., Piepmeier, J., Yueh, S., Entekhabi, D.,
Cosh, M., Caldwell, T., Walker, J., Berg, A., Rowlandson, T., Pacheco, A.,
McNairn, H., Thibeault, M., Martinez-Fernández, J.,
González-Zamora, A., Bosch, D., Starks, P., Goodrich, D., Prueger, J.,
Palecki, M., Small, E., Zreda, M., Calvet, J., Crow, W., and Kerr., Y.:
Assessment of the SMAP passive soil moisture product, IEEE T. Geosci.
Remote, 54, 4994–5007, https://doi.org/10.1109/TGRS.2016.2561938, 2016.
Chan, S., Bindlish,, R., O'Neill, P., Jackson, T., Njoku, E., Dunbar, S.,
Chaubell, J., Piepmeier, J., Yueh, S., Entekhabi, D., Colliander, A., Chen,
F., Cosh, M., Caldwell, T., Walker, J., Berg, A., McNairn, H., Thibeault,
M., Martinez- Fernández, J., Uldall, F., Seyfried, M., Bosch, D.,
Starks, P., Collins, C., Prueger, J., Van der Velde, R., Asanuma, J.,
Palecki, M., Small, E., Zreda, M., Calvet, J., Crow, W., and Kerr, Y.:
Development and assessment of the SMAP enhanced passive soil moisture
product. Remote Sens. Environ., 204, 931–941, https://doi.org/10.1016/j.rse.2017.08.025, 2018.
Chang, A., Foster, J., Hall, D., Rango, A., and Hartline, B.: Snow water
equivalent estimation by microwave radiometry, Cold Reg. Sci. Technol.,
5, 259–267, https://doi.org/10.1016/j.jag.2011.10.014, 1982.
Chapin III, F., Woodwell, G., Randerson, J., Rastetter, E., Lovett, G.,
Baldocchi, D., Clark, D., Harmon, M., Schimel, D., Valentini, R., Wirth, C.,
Aber, J., Cole, J., Goulden, M., Harden, J., Heimann, M., Howarth, R.,
Matson, P., McGuire, A., Melillo, J., Mooney, H., Neff, J., Houghton, R.,
Pace, M., Ryan, M., Running, S., Sala, O., Schlesinger, W., and Schulze,
E.-D.: Reconciling carbon-cycle concepts, terminology, and methods,
Ecosystems, 9, 1041–1050, https://doi.org/10.1007/s10021-005-0105-7, 2006.
Chen, X., Liu, L., and Bartsch, A.: Detecting soil freeze/thaw onsets in
Alaska using SMAP and ASCAT data, Remote Sens. Environ., 220, 59–70, https://doi.org/10.1016/j.rse.2018.10.010, 2019.
Chirici, G., Chiesi, M., Corona, P., Salvati, R., Papale, D., Fibbi, L.,
Sirca, C., Spano, D., Duce, P., Marras, S., Matteucci, G., Cescatti, A., and
Maselli, F.: Estimating daily forest carbon fluxes using a combination of
ground and remotely sensed data, J. Geophys. Res.-Biogeo., 121, 266–279,
https://doi.org/10.1002/2015JG003019, 2016.
Ciais, P., Tan, J., Wang, X., Roedenbeck, C., Chevallier, F., Piao, S.-L.,
Moriarty, R., Broquet, G., Le Quéré, C., Canadell, J., Peng, S.,
Poulter, B., Liu, Z., and Tans, P.: Five decades of northern land carbon
uptake revealed by the interhemispheric CO2 gradient, Nature, 568, 221–225,
https://doi.org/10.1038/s41586-019-1078-6, 2019.
Cohen, J., Rautiainen, K., Ikonen, J., Lemmetyinen, J., Smolander, T.,
Vehvilêinen, J., and Pulliainen, J.: A modeling-based approach for soil
frost detection in the northern boreal forest region with C-Band SAR, IEEE
T. Geosci. Remote, 57, 1069–1083, https://doi.org/10.1109/TGRS.2018.2864635, 2019.
Colliander, A., Jackson, T., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh,
M., Dunbar, R., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A.,
Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D., al
Jassar, H., Lopez-Baeza, E., Martínez Fernández, J.,
González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A.,
Moghaddam, M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T.,
Prueger, J., Pulliainen, J., Rautiainen, K., Ramos, J., Seyfried, M.,
Starks, P., Su, Z., Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W.,
Vreugdenhil, M., Walker, J. P., Wu, X., Monerris, A., O'Neill, P. E.,
Entekhabi, D., Njoku, E. G., Yueha, S.: Validation of SMAP surface soil
moisture products with core validation sites, Remote Sens. Environ., 191,
215–231, https://doi.org/10.1016/j.rse.2017.01.021, 2017.
Colliander, A., Reichle, R., Crow, W., Cosh, M., Chen, F., Chan, S., Das,
N., Bindlish, R., Chaubell, J., Kim, S., Liu, Q., O'Neill, P., Dunbar, R.
S., Dang, L., Kimball, J., Jackson, T., Al-Jassar, H., Asanuma, J.,
Bhattacharya, B., Berg, A., Bosch, D., Bourgeau-Chevez, L., Caldwell, T.,
Calvert, J.-C., Collins, C. H., Jenson, K., Livingston, S., Lopez-Baeza, E.,
Martínez-Fernández, J., McNairn, H., Moghaddam, M., Montzka, C.,
Notarnicola, C., Pellarin, T., Greimeister-Pfeil, I., Pulliainen, J., Gpe,
J., Hernández, R., Seyfried, M., Starks, P., Su, Z., van der Velde, R.,
Zeng, Y., Thibeault, M., Vreugdenhil, M., Walker, J., Zribi, M., Entekhabi,
D., and Yueh, S.: Validation of soil moisture data products from the NASA
SMAP mission, IEEE J. Sel. Top. Appl., 15, 364–392, https://doi.org/10.1109/JSTARS.2021.3124743, 2022.
Cui, Q., Shi, J., Du, J., Zhao, T., and Xiong, C.: An approach for
monitoring global vegetation based on multiangular observations from SMOS,
IEEE J. Sel. Top. Appl., 8, 604–616, https://doi.org/10.1109/JSTARS.2015.2388698,
2015.
Das, B., Bordoloi, R., Deka, S., Paul, A., Pandey, P. K., Singha, L. B.,
Tripathi, O. P., Mishra, B. P., and Mishra, M.: Above ground biomass carbon
assessment using field, satellite data and model based integrated approach
to predict the carbon sequestration potential of major land use sector of
Arunachal Himalaya, India, Carbon Manag., 12, 201–214, https://doi.org/10.1080/17583004.2021.1899753, 2021.
Das, K. and Paul, P.: Present status of soil moisture estimation by
microwave, Remote Sens., Cogent Geoscience, 1, 1084669, https://doi.org/10.1080/23312041.2015.1084669, 2015.
Das, N., Entekhabi, D., Kim, S., Yueh, S. Dunbar, R. S., and Colliander, A.:
SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 km EASE-Grid Soil
Moisture, Version 1. Boulder, Colorado USA, NASA National Snow and Ice Data
Center Distributed Active Archive Center [data set], https://doi.org/10.5067/9UWR1WTHW1WN, 2017.
Derksen, C., Xu, X., Scott Dunbar, R., Colliander, A., Kim, Y., Kimball, J.
S., Black, T. A., Euskirchen, E., Langlois, A., Loranty, M. M., Marsh, P.,
Rautiainen, K., Roy, A., Royer, A., and Stephens, J.: Retrieving landscape
freeze/thaw state from Soil Moisture Active Passive (SMAP) radar and
radiometer measurements, Remote Sens. Environ., 194, 48–62, https://doi.org/10.1016/j.rse.2017.03.007, 2017.
Derksen, C., Burgess, D., Duguay, C., Howell, S., Mudryk, L., Smith, S.,
Thackeray, C., and Kirchmeier-Young, M.: Changes in snow, ice, and
permafrost across Canada. Canada's Changing Climate Report – Chap. 5,
Government of Canada, Ottawa, Ontario, Canada, 194–260, 2019.
Dimitrov, D. D., Lafleur, P., Sonnentag, O., Talbot, J., and Quinton, W. L.:
Hydrology of peat estimated fron near-surface water contents, Hydrolog. Sci.
J., 67, 1702–1721, 2022.
Dobson, M., Ulaby, F., Hallikainen, M., and El-Rayes, M.: Microwave
dielectric behavior of wet soil – Part II: Dielectric mixing models, IEEE T. Geosci. Remote Sens., 23, 35–46, https://doi.org/10.1109/TGRS.1985.289498, 1985.
Dobson, M., Ulaby, F., and Pierce, L.: Land-cover classification and
estimation of terrain attributes using synthetic aperture radar, Remote
Sens. Environ., 51, 199–214, https://doi.org/10.1016/0034-4257(94)00075-X, 1995.
Dolant, C., Langlois, A., Brucker, L., Royer, A., Roy, A., and Montpetit,
B. L.: Meteorological inventory of rain-on-snow events in the Canadian Arctic
Archipelago and satellite detection assessment using passive microwave data,
Phys. Geogr., 39, 428–444, https://doi.org/10.1080/02723646.2017.1400339, 2018.
Dou, Y., Tian, F., Wigneron, J. P., Tagesson, T., Du, J., Brandt, M., Liu,
Y., Zou, L., Kimball, J. S., and Fensholt, R.: Reliability of using vegetation
optical depth for estimating decadal and interannual carbon dynamics, Remote
Sens. Environ., 285, 113390, https://doi.org/10.1016/j.rse.2022.113390, 2023.
Du, J., Kimball, J. S., Jones, L. A., Kim, Y., Glassy, J., and Watts, J. D.: A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations, Earth Syst. Sci. Data, 9, 791–808, https://doi.org/10.5194/essd-9-791-2017, 2017.
Du, J., Watts, J., Jiang, L., Lu, H., Cheng, X., Duguay, C., Farina, M.,
Qiu, Y., Kim, Y., Kimball, J., and Tarolli, P.: Remote sensing of
environmental changes in cold regions: methods, achievements and challenges,
Remote Sens., 11, 1952, https://doi.org/10.3390/rs11161952, 2019.
Du, J., Kimball, J. S., Bindlish, R., Walker, J. P., and Watts, J. D.: Local
Scale (3-m) Soil Moisture Mapping Using SMAP and Planet SuperDove, Remote
Sens., 14, 3812, https://doi.org/10.3390/rs14153812, 2022.
Du, S., Liu, L., Liu, X., Guo, J., Hu, J., Wang, S., and Zhang, Y.: SIFSpec:
Measuring solar-induced chlorophyll fluorescence observations for remote
sensing of photosynthesis, Sensors, 19, 3009, https://doi.org/10.3390/s19133009,
2019.
Dubock, D., Spoto, F., Simpson, J., Spencer, D., Schutte, E., and Sontag,
H.: The Envisat satellite and its integration, ESA Bull., 106, 26–45,
2001.
Duan, S.-B., Han, X.-J., Huang, C., Li, Z.-L., Wu, H., Qian, Y., Gao, M.,
Leng, P.: Land surface temperature retrieval from passive microwave
satellite observations: state-of-the-art and future directions, Remote
Sens., 12, 2573, https://doi.org/10.3390/rs12162573, 2020.
Edokossi, K., Calabia, A., Jin, S., and Molina, I.: GNSS-Reflectometry and
Remote Sensing of Soil Moisture: A Review of Measurement Techniques,
Methods, and Applications, Remote Sens., 12, 614, https://doi.org/10.3390/rs12040614,
2020.
El-Amine, M., Roy, A., Koebsch, F., Baltzer, J., Barr, A., Black, A., Ikawa,
H., Iwata, H., Kobayashi, H., Ueyama, M., and Sonnentag, O.: What explains
the year-to-year variation in thestart and end of the photosynthetic growing
season of boreal black spruceforests?, Agr. Forest Meteorol., 324, 109113,
https://doi.org/10.1016/j.agrformet.2022.109113, 2022.
Elberling, B.: Annual soil CO2 effluxes in the High Arctic: The role of snow
thickness and vegetation type, Soil Biol. Biochem., 39, 646–654, https://doi.org/10.1016/j.soilbio.2006.09.017, 2007.
El Hajj, M., Baghdadi, N., Zribi, M., and Bazzi, H.: Synergic Use of
Sentinel-1 and Sentinel-2 Images for operational soil moisture mapping at
high spatial resolution over agricultural areas, Remote Sens., 9, 1292,
https://doi.org/10.3390/rs9121292, 2017.
El-Rayes, M. and Ulaby, F.: Microwave dielectric spectrum of
vegetation-Part I: Experimental observations, IEEE T. Geosci. Remote, 25,
541–549, https://doi.org/10.1109/TGRS.1987.289832, 1987.
Engman, E.: Applications of microwave remote sensing of soil moisture for
water resources and agriculture, Remote Sens. Environ., 35, 213-2-26,
https://doi.org/10.1016/0034-4257(91)90013-V, 1991.
Entekhabi, D., Njoku, E., O'Neill, P., Kellogg, K., Crow, W., Edelstein, W.,
Entin, J., Goodman, S., Jackson, T., Jackson, J., Kimball, J., Piepmeier,
J., Koster, R., Martin, N., McDonald, K., Moghaddam, M., Moran, S., Reichle,
R., Shi, J., Spencer, M., Thurman, S., Tsang, L., and Van Zyl, J.: The Soil
Moisture Active Passive (SMAP) mission, P. IEEE, 98, 704–716, https://doi.org/10.1109/JPROC.2010.2043918, 2010.
Euskirchen, E., McGuire, A., Kicklighter, D., Zhuang, Q., Clein, J., Dargaville, R., Dye, D., Kimball, J., McDonald, K., Melilli, J., Romanovsky, V., and Smith, N.: Importance of recent shifts in soil thermal dynamics on growing season length, productivity, and carbon sequestration in terrestrial high-latitude ecosystems, Glob. Change Biol., 12, 731–750, https://doi.org/10.1111/j.1365-2486.2006.01113.x, 2006.
Fahnestock, J., Jones, M., Brooks, P., Walker, D., and Welker, J.: Winter
and early spring CO2 efflux from tundra communities of northern Alaska,
J. Geophys. Res., 103, 29023–29027, https://doi.org/10.1029/98JD00805, 1998.
Fahnestock, J., Jones, M., and Welker, J.: Wintertime CO2 efflux from
arctic soils: implications for annual carbon budgets, Gobal Biogeochem. Cy.,
13, 775–779, https://doi.org/10.1029/1999gb900006, 1999.
FAO – Food and Agriculture Organization of the United Nations: Global forest
resources assessment 2000: main report, FAO Forestry Paper 140, United
Nations, Rome, Italy, 479 pp., https://www.fao.org/3/Y1997E/Y1997E00.htm (last access: 16 July 2023), 2001.
Figa-Saldaña, J., Wilson, J., Attema, E., Gelsthorpe, R., Drinkwater,
M., and Stoffelen, A.: The advanced scatterometer (ASCAT) on the
meteorological operational (MetOp) platform: A follow on for European wind
scatterometers, Can. J. Remote Sens., 28, 404–412, https://doi.org/10.5589/m02-035, 2002.
Fily, M., Royer, A., Goïta, K., and Prigent, C.: A simple retrieval
method for land surface temperature and fraction of water surface
determination from satellite microwave brightness temperatures in sub-arctic
areas, Remote Sens. Environ., 85, 328–338, https://doi.org/10.1016/S0034-4257(03)00011-7, 2003.
Fisher, J., Hayes, D., Schwalm, C., Huntzinger, D., Stofferahn, E.,
Schaefer, K., Luo, Y., Wullschleger, S., Goetz, S., Miller, C., Griffith,
P., Chadburn, S., Chatterjee, A., Ciais, P., Douglas, T., Genet, H., Ito,
A., Neigh, C., Poulter, B., Rogers, B., Sonnentag, O., Tian, H., Wang, W.,
Xue, Y., Yang, Z.-L., Zeng, N., and Zhang, Z.: Missing pieces to modeling
the Arctic-Boreal puzzle, Environ. Res. Lett., 13, 020202, https://doi.org/10.1088/1748-9326/aa9d9a, 2018.
Forster, R., Long, D., Jezel, K., Brobot, S., and Anderson, M.: The onset of
Arctic sea-ice snowmelt as detected with passive- and active-microwave, Ann. Glaciol., 33, 85–93, https://doi.org/10.3189/172756401781818428,
2001.
Foster, A. C., Shuman, J. K., Rogers, B. M., Walker, X. J., Mack, M. C.,
Bourgeau-Chavez, L. L., Veraverbeke, S., and Goetz, S. J.: Bottom-up drivers of
future fire regimes in western boreal North America, Environ. Res. Lett.,
17, 025006, https://doi.org/10.1088/1748-9326/ac4c1e, 2022.
Frolking, S., Goulden, M.,Wofsy, S., Fan, S.-M., Sutton, D., Munger, J.,
Bazzaz, A., Daube, B., Crill, P., Aber, J., Band, L., Wang, X., Savage K.,
Moore, T., and Harriss, R.: Modeling temporal variability in the carbon
balance of a spruce/moss boreal forest, Glob. Change Biol., 2, 343–366,
https://doi.org/10.1111/j.1365-2486.1996.tb00086.x, 1996.
Fu, Z., Stoy, P., Luo, Y., Chen, J., Sun, J., Montagnani, L., Wohlfahrt, G.,
Rahman, A., Rambal, S., Bernhofer, C., Wang, J., Shirkey, G., and Niu, S.:
Climate controls over the net carbon uptake period and amplitude of net
ecosystem production in temperate and boreal ecosystems., Agr. Forest
Meteorol., 243, 9–18, https://doi.org/10.1016/j.agrformet.2017.05.009, 2017.
Gaiser, P., St. Germain, K., Twarog, E., Poe, G., Purdy, W., Richardson, D., Grossman, W., Jones, W., L., Spencer, D., Golba, G., Cleveland, J., Choy, L., Bevilacqua, R., and Chang, P.: The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance, IEEE T. Geosci. Remote Sens., 42, 2347–2361, https://doi.org/10.1109/TGRS.2004.836867, 2004.
Gasser, T., Crepin, L., Quilcaille, Y., Houghton, R. A., Ciais, P., and Obersteiner, M.: Historical CO2 emissions from land use and land cover change and their uncertainty, Biogeosciences, 17, 4075–4101, https://doi.org/10.5194/bg-17-4075-2020, 2020.
Gauthier, S., Bernier, P., Kuuluvainen, T., Shvidenko, A., and
Schepaschenko, D.: Boreal forest health and global change, Science,
349, 819–822, https://doi.org/10.1126/science.aaa9092, 2015.
Gloersen, P. and Barath, F.: A scanning multichannel microwave radiometer
for Nimbus-G and SeaSat-A, IEEE J. Ocean. Eng., 2, 172–178, https://doi.org/10.1109/JOE.1977.1145331, 1977.
Gough, C. M.: Terrestrial primary production: Fuel for life, Nat. Educ. Knowl., 3, p. 28, 2011.
Grasso, M., Renga, A., Fasano, G., Graziano, M., Grassi, M., and Moccia, A.:
Design of an end-to-end demonstration mission of a Formation-Flying
Synthetic Aperture Radar (FF-SAR) based on microsatellites, Adv. Space Res., 67, 3909–3923,
https://doi.org/10.1016/j.asr.2020.05.051, 2021.
Grosse, G., Harden, J., Turetsky, M., McGuire, D., Camill, P., Tarnocai, C.,
Frolking, S., Schuur, E., Jorgenson, T., Marchenko, S., Romanovsky, V.,
Wickland, K., French, N., Waldrop, M., Bourgeau-Chavez, L., and Striegl, R.:
Vulnerability of high-latitude soil organic carbonin North America to
disturbance, J. Geophys. Res., 116, G00K06, https://doi.org/10.1029/2010JG001507, 2011.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.: Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, 2019.
Harrison, J., Sanders-DeMott, R., Reinmann, A., Sorensen, P., Phillips, N.,
and Templer, P.: Growing-season warming and winter soil freeze/thaw cycles
increase transpiration in a northern hardwood forest, Ecology, 101,
e03173, https://doi.org/10.1002/ecy.3173, 2020.
Hayes, J., McGuire, A., Kicklighter, D., Gurney, K., Burnside, T., and
Melillo, J.: Is the northern high-latitude land-based CO2 sink weakening?.
Gobal Biogeochem. Cy., 25, GB3018, https://doi.org/10.1029/2010GB003813, 2011.
Hollinger, J., Peirce, J., and Poe, G.: SSM/I instrument evaluation, IEEE T.
Geosci. Remote Sens., 28, 781–790, https://doi.org/10.1109/36.58964, 1990.
Holtzman, N. M., Anderegg, L. D. L., Kraatz, S., Mavrovic, A., Sonnentag, O., Pappas, C., Cosh, M. H., Langlois, A., Lakhankar, T., Tesser, D., Steiner, N., Colliander, A., Roy, A., and Konings, A. G.: L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand, Biogeosciences, 18, 739–753, https://doi.org/10.5194/bg-18-739-2021, 2021.
Hori, M., Sugiura, K., Kobayashi, K., Aoki, T, Tanikawa, T., Kuchiki, K.,
Niwano, M., and Enomoto, H.: A 38-year (1978–2015) Northern Hemisphere
daily snow cover extent product derived using consistent objective criteria
from satellite-borne optical sensors, Remote Sens. Environ., 191, 402–418,
https://doi.org/10.1016/j.rse.2017.01.023, 2017.
Houghton, R.: Aboveground Forest Biomass and the Global Carbon Balance,
Glob. Change Biol., 11, 945–958, https://doi.org/10.1111/j.1365-2486.2005.00955.x,
2005.
Huang, H., Tsang, L., Njoku, E., Colliander, A., Liao, T.-H., and Ding,
K.-H.: Propagation and Scattering by a Layer of Randomly Distributed
Dielectric Cylinders Using Monte Carlo Simulations of 3D Maxwell Equations
With Applications in Microwave Interactions With Vegetation, IEEE Access, 5,
11985–12003, https://doi.org/10.1109/ACCESS.2017.2714620, 2017.
Huber, S., Villano, M., Younis, M., Krieger, G., Moreira, A., Grafmueller,
B., and Wolters, R.: Tandem-L: Design Concepts for a Next-Generation
Spaceborne SAR System, in: Proceedings of the EUSAR 2016: 11th European
Conference on Synthetic Aperture Radar, 6–9 June 2016, Hamburg, Germany,
1–5, 2016.
Huntzinger, D., Schaefer, K., Schwalm, C., Fisher, J., Hayes, D.,
Stofferahn, E., Carey, J., Michalak, A., Wei, Y., Jain, A., Kolus, H., Mao,
J., Poulter, B., Shi, X., Tang, J., and Tian, H.: Evaluation of simulated
soil carbon dynamics in Arctic-Boreal ecosystems, Environ. Res. Lett.,
15, 025005, https://doi.org/10.1088/1748-9326/ab6784, 2020.
IPCC (Intergovernmental Panel on Climate Change): Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O. Roberts, D., Masson Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N., Cambridge University Press, Cambridge, UK and New York, NY, USA, 755 pp., https://doi.org/10.1017/9781009157964, 2019.
Jackson, T. and Schmugge, T.: Vegetation effects on the microwave emission of
soils, Remote Sens. Environ., 36, 203–212, https://doi.org/10.1016/0034-4257(91)90057-D, 1991.
Jarvis, P. and Linder, S.: Constraints to growth of boreal forests, Nature,
405, 904–905, https://doi.org/10.1038/35016154, 2000.
Jenson, J.: Remote sensing of the Environment: An Earth Resource Perspective,
2nd Edn., Pearson Prentice Hall, Upper Saddle River, New Jersey, United
States, 656 pp., ISBN 978-1-29202-170-6, 2006.
Jiménez-Muñoz, G. and Sobrino, J.: Error sources on the land
surface temperature retrieved from thermal infrared single channel remote
sensing data, Int. J. Remote Sens., 27, 999–1014, https://doi.org/10.1080/01431160500075907, 2006.
Jones, L., Kimball, J., McDonald, K., Chan, S., Njoku, E., and Oechel, W.:
Satellite microwave remote sensing of boreal and Arctic soil temperatures
from AMSR-E, IEEE T. Geosci. Remote Sens., 45, 2004–2018, https://doi.org/10.1109/TGRS.2007.898436, 2007.
Jones, L., Kimball, J., Reichle, R., Madani, N., Glassy, J., Ardizzone, J.,
Colliander, A., Cleverly, J., Desai, A., Eamus, D., Euskirchen, E., Hutley,
L., Macfarlane, C., and Scott, R.: The SMAP Level 4 Carbon Product for
Monitoring Ecosystem Land–Atmosphere CO2 Exchange, IEEE T. Geosci.
Remote Sens., 55, 6517–6532, https://doi.org/10.1109/TGRS.2017.2729343, 2017.
Jones, L. A., Ferguson, C. R., Kimball, J. S., Zhang, K., Chan, S. T. K.,
McDonald, K. C., Njoku, E. G., and Wood, E. F.: Satellite Microwave Remote Sensing
of Daily Land Surface Air Temperature Minima and Maxima From AMSR-E, IEEE J.
Sel. Top. Appl., 3, 111–123,
https://doi.org/10.1109/jstars.2010.2041530, 2010.
Jones, M., Jones, L., Kimball, J., and McDonald, K.: Satellite passive
microwave remote sensing for monitoring global land surface phenology,
Remote Sens. Environ., 115, 1102–1114, https://doi.org/10.1016/j.rse.2010.12.015,
2011.
Kawanishi, T., Sezai, T., Ito, Y., Imaoka, K., Takashima, T., Ishido, Y., Shibata, A., Miura, M., Inahata, H., and Spencer, R.: The advanced scanning microwave radiometer for the EarthObserving System (AMSR-E): NASDA’s contribution to the EOS for global energy and water cycle studies, IEEE T. Geosci. Remote Sens., 41, 184–194, https://doi.org/10.1109/TGRS.2002.808331, 2003.
Kerr, Y., Waldteufel, P., Wigneron, J.-P., Delwart, S., Cabot, F., Boutin,
J., Escorihuela, M., Font, J., Reul, N., Gruhier, C., and Juglea, S.: The
SMOS mission: New tool for monitoring key elements of the global water
cycle, IEEE T. Geosci. Remote, 98, 666–687, https://doi.org/10.1109/JPROC.2010.2043032, 2010.
Kerr, Y., Waldteufel, P., Richaume, P., Wigneron, J., Ferrazzoli, P.,
Mahmoodi, A., Al Bitar, A., Cabot, F., Gruhier, C., Juglea, S., Leroux, D.,
Mialon, A., and Delwart, S.: The SMOS soil moisture retrieval algorithm,
IEEE T. Geosci. Remote. Sens., 50, 1384–1403, https://doi.org/10.1109/TGRS.2012.2184548,
2012.
Kilic, L., Prigent, C., Aires, F., Boutin, J., Heygster, G., Tonboe, R.,
Roquet, H., Jimenez, C., and Donlon, C.: Expected Performances of the
Copernicus Imaging Microwave Radiometer (CIMR) for an All-Weather and High
Spatial Resolution Estimation of Ocean and Sea Ice Parameters, J. Geophys.
Res.-Oceans, 123, 7564–7580, https://doi.org/10.1029/2018JC014408, 2018.
Kim, S.-B., van Zyl, J., Johnson, J., Moghaddam, M., Tsang, L., Colliander,
A., Dunbar, R., Jackson, T., Jaruwatanadilok, S., West, R., Berg, A.,
Caldwell, T., Cosh, M., Goodrich, D., Livingston, S., López-Baeza, E.,
Rowlandson, T., Thibeault, M., Walker, J., Entekhabi, D., Njoku, E.,
O'Neill, P., and Yueh, S.: Surface Soil Moisture Retrieval Using the L-Band
Synthetic Aperture Radar Onboard the Soil Moisture Active–Passive Satellite
and Evaluation at Core Validation Sites, IEEE T. Geosci. Remote Sens., 55,
1897–1914, https://doi.org/10.1109/TGRS.2016.2631126, 2017.
Kim, Y., Kimball, J., Zhang, K., and McDonald, K.: Satellite detection of
increasing Northern Hemisphere non-frozen seasons from 1979 to 2008:
Implications for regional vegetation growth, Remote Sens. Environ., 121,
472–487, https://doi.org/10.1016/j.rse.2012.02.014, 2012.
Kim, Y., Kimball, J., Xu, X., Dunbar, S., Colliander, A., and Derksen, C.:
Global Assessment of the SMAP Freeze/Thaw Data Record and Regional
Applications for Detecting Spring Onset and Frost Events, Remote Sens.,
11, 1317, https://doi.org/10.3390/rs11111317, 2019.
Kimball, J., McDonald, K., Keyser, A. R., Frolking, S., and Running, S.:
Application of the NASA Scatterometer (NSCAT) for determining the Daily
Frozen and Nonfrozen Landscape of Alaska, Remote Sens. Environ., 75,
113–126, https://doi.org/10.1016/S0034-4257(00)00160-7, 2001.
Kimball, J., Zhao, M., McDonald, K., Heinsch, F. A., and Running, S.:
Satellite observations of annual variability in terrestrial carbon cycles
and seasonal growing seasons at high northern latitudes, Proc. Spie,
Microwave Remote Sensing of the Atmosphere and Environment IV, 5654, https://doi.org/10.1117/12.578815, 2004a.
Kimball, J., McDonald, K., Running, S., and Frolking, S.: Satellite radar
Remote sensingof seasonal growing seasons for boreal and subalpine evergreen
forests, Remote Sens. Environ., 90, 243–258, https://doi.org/10.1016/j.rse.2004.01.002,
2004b.
Kimball, J., Jones, L., Zhang, K., Heinsch, F. A., McDonald, K., and Oechel,
W.: A Satellite Approach to Estimate Land-Atmosphere CO2 Exchange for Boreal
and Arctic Biomes Using MODIS and AMSR-E, IEEE T. Geosci. Remote Sens., 47,
569–587, https://doi.org/10.1109/TGRS.2008.2003248, 2009.
Kimball, J., Jones, L., Glassy, J., Stavros, N., Madani, N., Reichle, R., Jackson, T., and Colliander, A.: Soil Moisture Active Passive
Mission L4_C Data Product Assessment (Version 2 Validated Release), MAO Office Note No. 13 (Version 1.0), NASA Goddard Space Flight Center, Greenbelt, Maryland, United States, 37 pp., https://gmao.gsfc.nasa.gov/pubs/docs/Kimball852.pdf (last access: 19 July 2023), 2017.
Köcher, P., Horna, V., and Leuschner, C.: Stem water storage in five
coexisting temperate broad-leaved tree species: significance, temporal
dynamics and dependence on tree functional traits, Tree Physiol., 33,
817–832, https://doi.org/10.1093/treephys/tpt055, 2013.
Kohn, J. and Royer, A.: AMSR-E data inversion for soil temperature
estimation under snow cover, Remote Sens. Environ., 114, 2951–2961, https://doi.org/10.1016/j.rse.2010.08.002, 2010.
Konings, A., Piles, M., Das N., and Entekhabi, D.: L-band vegetation visible
depth and effective scattering albedo estimation from SMAP, Remote Sens.
Environ., 198, 460–470, https://doi.org/10.1016/j.rse.2017.06.037, 2017.
Konings, A., Rao, K., and Steele-Dunne, S.: Macro to micro: microwave Remote
sensing of plant water content for physiology and ecology, New Phytol.,
223, 1166–1172, https://doi.org/10.1111/nph.15808, 2019.
Krieger, G., Moreira, A., Zink, M., Hajnsek, I., Huber, S., Villano, M.,
Papathanassiou, K., Younis, M., Lopez Dekker, P., Pardini, M., Schulze, D.,
Bachmann, M., Borla Tridon, D., Reimann, J., Bräutigam, B.,
Steinbrecher, U., Tiendra, C., Sanjuan Ferrer, M., Zonno, M., Eineder, M.,
De Zan, F., Parizzi, A., Fritz, T., Diedrich, E., Maurer, E.,
Münzenmayer, R., Grafmüller, B., Wolters, R., te Hennepe, F., Ernst,
R., and Bewick, C.: Tandem-L: Main results of the phase a feasibility
study,” 2016 IEEE International Geoscience and Remote Sensing Symposium
(IGARSS), 10–15 July 2016, Beijing, China, 2116–2119, https://doi.org/10.1109/IGARSS.2016.7729546, 2016.
Krishnan, P., Meyers, T., Hook, S., Heuer, M., Senn, D., and Dumas, E.:
Intercomparison of In Situ Sensors for Ground-Based Land Surface Temperature
Measurements, Sensors, 20, 5268, https://doi.org/10.3390/s20185268, 2020.
Lai, D.: Methane Dynamics in Northern Peatlands: A Review, Pedosphere,
19, 409–421, https://doi.org/10.1016/S1002-0160(09)00003-4, 2009.
Lakhankar, T., Krakauer, N., and Khanbilvardi, R.: Applications of microwave
Remote sensing of soil moisture for agricultural applications, Int. J.
Terraspace Sci. Eng., 2, 81–91, 2009.
Larue, F., Royer, A., De Sève, D., Langlois, A., Roy, A., and Brucker,
L.: Validation of GlobSnow-2 snow water equivalent over Eastern Canada,
Remote Sens. Environ., 194, 264–277, https://doi.org/10.1016/j.rse.2017.03.027, 2017.
Larue, F., Royer, A., De Sève, D., Roy, A., and Cosme, E.: Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over northeastern Canada, Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018, 2018.
Lawrence, H., Wigneron, J.-P., Richaume, P., Novello, N., Grant, J., Mialon,
A., Al Bitar, A., Merlin, O., Guyon, D., Leroux, D., Bircher, S., and Kerr,
Y.: Comparison between SMOS Vegetation Visible Depth products and MODIS
vegetation indices over crop zones of the USA, Remote Sens. Environ., 140,
396–406, https://doi.org/10.1016/j.rse.2013.07.021, 2014.
Leanza, A., Manzoni, M., Monti-Guarnieri, A., and di Clemente, M.: LEO to
GEO-SAR Interferences: Modelling and performance evaluation, Remote Sens.,
11, 1720, https://doi.org/10.3390/rs11141720, 2019.
Lee, J.-S., Grunes, M., and Pottier, E.: Quantitative comparison of
classification capability: fully polarimetric versus dual and
single-polarization SAR, IEEE T. Geosci. Remote Sens., 39, 2343–2351, https://doi.org/10.1109/36.964970, 2001.
Lees, K., Quaife, T., Artz, R., Khomik, M., and Clarl, J.: Potential for
using remote sensing to estimate carbon fluxes across northern peatlands –
A review. Sci. Total Environ., 615, 857–874, https://doi.org/10.1016/j.scitotenv.2017.09.103, 2018.
Le Toan, T., Quegan, S., Davidson, M., Balzter, H., Paillou, P.,
Papathanassiou, K., Plummer, S., Rocca, F., Saatchi, S., Shugart, H., and
Ilander, L.: The BIOMASS mission: Mapping global forest biomass to better
understand the terrestrial carbon cycle, Remote Sens. Environ., 115,
2850–2860, https://doi.org/10.1016/j.rse.2011.03.020, 2011.
Li, Q., Kelly, R., Leppanen, L., Vehvilainen, J., Kontu, A., Lemmetyinen,
J., and Pulliainen, J.: The influence of thermal properties and
canopy-intercepted snow on passive microwave transmissivity of a scots pine.
IEEE T. Geosci. Remote Sens., 57, 5424–5433, https://doi.org/10.1109/TGRS.2019.2899345,
2019.
Li, W., Cardellach, E., Ribó, S., Oliveras, S., and Rius, A.:
Exploration of Multi-Mission Spaceborne GNSS-R Raw IF Data Sets: Processing,
Data Products and Potential Applications, Remote Sens., 14, 1344, https://doi.org/10.3390/rs14061344, 2022.
Li, X., Wigneron, J. P., Fan, L., Frappart, F., Simon, H., Colliander, A.,
Ebtehaj, A., Gao, L., Fernandez-Moran, R., Liu, X. Z., Wang, M. J., Ma, H. L., Moisy,
C., and Ciais, P.: A new SMAP soil moisture and vegetation optical depth
product (SMAP-IB): Algorithm, assessment and inter-comparison, Remote Sens.
Environ., 271, 112921, https://doi.org/10.1016/j.rse.2022.112921, 2022.
Lieffers, V. and Rothwell, R.: Rooting of peatland black spruce and
tamarack in relation to depth of water table, Can. J. Bot., 65, 817–821,
https://doi.org/10.1139/b87-111, 1987.
Lievens, H., Demuzere, M., Marshall, H.-P., Reichle, R., Brucker, L.,
Brangers, I., de Rosnay, P., Dumont, M., Girotto, M., Immerzeel, W., Jonas,
T., Kim, E., Koch, I., Marty, C., Saloranta, T., Schöber, J., and De
Lannoy, G.: Snow depth variability in the Northern Hemisphere mountains
observed from space, Nat. Commun., 10, 4629, https://doi.org/10.1038/s41467-019-12566-y, 2019.
Liljedahl, A., Boike, J., Daanen, R., Fedorov, A., Frost, G., Grosse, G.,
Hinzman, L., Iijma, Y., Jorgenson, J., Matveyeva, N., Necsoiu, M., Raynolds,
M., Romanovsky, V., Schulla, J., Tape, K., Walker, D., Wilson, C., Yabuki,
H., and Zona, D.: Pan-Arctic ice-wedge degradation in warming permafrost and
its influence on tundra hydrology, Nat. Geosci., 9, 312–318, https://doi.org/10.1038/ngeo2674, 2016.
Liu, X., Wigneron, J.-P., Fan, L., Frappart, F., Ciais, P., Baghdadi, N.,
Zribi, M., Jaghuber, T., Li, X., Wang, M., Bai, X., and Moisy, C.: ASCAT IB:
A radar-based vegetation optical depth retrieved from the ASCAT
scatterometer satellite, Remote Sens. Environ., 264, 112587, https://doi.org/10.1016/j.rse.2021.112587, 2021.
Liu Y., van Dijk, A., de Jeu, R., Canadell, J., McCabe, M., Evans, J., and
Wang, G.: Recent reversal in loss of global terrestrial biomass, Nat. Clim.
Change, 5, 470–474, https://doi.org/10.1038/nclimate2581, 2011a.
Liu, Y. A., de Jeu, R. J., McCabe, M., Evans, J., and van Dijk, A.: Global
long-term passive microwave satellite-based retrievals of vegetation visible
depth, Geophys. Res. Lett., 38, L18402, https://doi.org/10.1029/2011GL048684,
2011b.
Liu, Y., Holtzman, N. M., and Konings, A. G.: Global ecosystem-scale plant hydraulic traits retrieved using model–data fusion, Hydrol. Earth Syst. Sci., 25, 2399–2417, https://doi.org/10.5194/hess-25-2399-2021, 2021.
Loisel, J., Gallego-Sala, A. V., Amesbury, M. J., Magnan, G., Anshari, G.,
Beilman, D. W., Benavides, J. C., Blewett, J., Camill, P., Charman, D. J.,
Chawchai, S., Hedgpeth, A., Kleinen, T., Korhola, A., Large, D., Mansilla,
C. A., Müller, J., van Bellen, S., West, J. B., Yu, Z., Bubier, J. L.,
Garneau, M., Moore, T., Sannel, A. B. K., Page, S., Väliranta, M.,
Bechtold, M., Brovkin, V., Cole, L. E. S., Chanton, J. P., Christensen, T. R.,
Davies, M. A., De Vleeschouwer, F., Finkelstein, S. A., Frolking, S., Galka,
M., Gandois, L., Girkin, N., Harris, L. I., Heinemeyer, A., Hoyt, A. M.,
Jones, M. C., Joos, F., Juutinen, S., Kaiser, K., Lacourse, T., Lamentowicz,
M., Larmola, T., Leifeld, J., Lohila, A., Milner, A. M., Minkkinen, K., Moss,
P., Naafs, B. D. A., Nichols, J., O'Donnel, J., Payne, R., Philben, M., Piilo,
S., Quillet, A., Ratnayake, A. S., Roland, T. P., Sjögersten, S.,
Sonnentag, O., Swindles, G. T., Swinnen, W., Talbot, J., Treat, C., Valach,
A. C., and Wu, J.: Expert assessment of future vulnerability of the global
peatland carbon sink, Nat. Clim. Change, 11, 70–77, 2021.
Lönnqvist, A., Rauste, Y., Molinier, M., and Häme, T.: Polarimetric
SAR Data in Land Cover Mapping in Boreal Zone, IEEE T. Geosci. Remote Sens.,
48, 3652–3662, https://doi.org/10.1109/TGRS.2010.2048115, 2010.
Lorente, A., Borsdorff, T., Butz, A., Hasekamp, O., aan de Brugh, J., Schneider, A., Wu, L., Hase, F., Kivi, R., Wunch, D., Pollard, D. F., Shiomi, K., Deutscher, N. M., Velazco, V. A., Roehl, C. M., Wennberg, P. O., Warneke, T., and Landgraf, J.: Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements, Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, 2021.
Luojus, K., Pulliainen, J., Takala, M., Lemmetyinen, J., Mortimer, C.,
Derksen, C., Mudryk, L., Moisander, M., Hiltunen, M., Smolander, T., Ikonen,
J., Cohen, J., Salminen, M., Norberg, J., Veijola, K., and
Venäläinen, P.: GlobSnow v3.0 Northern Hemisphere snow water
equivalent dataset, Sci. Data, 8, 163, https://doi.org/10.1038/s41597-021-00939-2,
2021.
Maeda, T., Taniguchi, Y., and Imaoka, K.: GCOM-W1 AMSR2 Level 1R Product:
Dataset of brightness temperature modified using the antenna pattern
matching technique, IEEE T. Geosci. Remote Sens., 54, 770–782, https://doi.org/10.1109/TGRS.2015.2465170, 2016.
Magney, T., Bowling, D., Logan, B., Grossmann, K., Stutz, J., Blanken, P.,
Burns, S., Cheng, R., Garcia, M., Köhler, P., Lopez, S., Parazoo, N.,
Raczka, B., Schimel, D., and Frankenberg, C.: Mechanistic evidence for
tracking the seasonality of photosynthesis with solar-induced fluorescence,
P. Natl. Acad. Sci. USA, 116, 11640–11645, https://doi.org/10.1073/pnas.1900278116,
2019.
Mao, J., Ribes, A., Yan, B., Shi, X., Thornton, P., Séférian, R.,
Ciais, P., Myneni, R., Douville, H., Piao, S., Zhu, Z., Dickinson, R., Dai,
Y., Ricciuto, D., Jin, M., Hoffman, F., Wang, B., Huang, M., and Lian, X.:
Human-induced greening of the northern extratropical land surface, Nat.
Clim. Change, 6, 959–963, https://doi.org/10.1038/nclimate3056, 2016.
Mao, K., Zuo, Z., Shen, X., Xu, T., Gao, C., and Liu, G.: Retrieval of
land-surface temperature from AMSR2 data using a deep dynamic learning
neural network, Chinese Geogr. Sci., 28, 1–11, https://doi.org/10.1007/s11769-018-0930-1, 2018.
Marchand, N., Royer, A., Krinner, G., Roy, A., Langlois, A., and Vargel, C.:
Snow-covered soil temperature retrieval in Canadian Arctic permafrost areas,
using a land surface scheme informed with satellite remote sensing data,
Remote Sens., 10, 1703, https://doi.org/10.3390/rs10111703, 2018.
Marghany, M.: Principle theories of synthetic aperture radar. Synthetic
aperture radar imaging mechanism for oil spills, 127–150, Gulf Professional
Publishing, United States, 322 pp., ISBN 9780128181119, 2019.
Matheny, A., Bohrer, G., Garrity, S., Morin, T., Howard, C., and Vogel, C.:
Observations of stem water storage in trees of opposing hydraulic
strategies, Ecosphere, 6, 1–13, https://doi.org/10.1890/ES15-00170.1, 2015.
Matthews, E., Johnson, M. S., Genovese, V., Du, J., and Bastviken, D.:
Methane emission from high latitude lakes: methane-centric lake
classification and satellite-driven annual cycle of emissions, Sci. Rep.,
10, 12465, https://doi.org/10.1038/s41598-020-68246-1, 2020.
McDonald, K., Kimball, J., Njoku, E., Zimmermann, R., and Zhao, M.: Variability in Springtime Thaw in the Terrestrial High Latitudes: Monitoring a Major Control on the Biospheric Assimilation of Atmospheric CO2 with Spaceborne Microwave Remote Sensing, Earth Interact., 8, 1–23, https://doi.org/10.1175/1087-3562(2004)8<1:VISTIT>2.0.CO;2, 2004.
McMahon, S., Parker, G., and Miller, D.: Evidence for a recent increase in
forest growth, P. Natl. Acad. Sci. USA, 107, 3611–3615, https://doi.org/10.1073/pnas.0912376107, 2010.
Meloche, J., Langlois, A., Rutter, N., Royer, A., King, J., Walker, B., Marsh, P., and Wilcox, E. J.: Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals, The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, 2022.
Melton, J. R., Arora, V. K., Wisernig-Cojoc, E., Seiler, C., Fortier, M., Chan, E., and Teckentrup, L.: CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance, Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, 2020.
Merchant, M., Adams, J., Berg, A., Baltzer, J., Quinton, W., and Chasmer,
L.: Contributions of C-Band SAR data and polarimetric decompositions to
subarctic boreal peatland mapping, IEEE J. Sel. Top. Appl., 10,
1467–1482, https://doi.org/10.1109/JSTARS.2016.2621043, 2017.
Merchant, M., Warren, R., Edwards, R., and Kenyon, J.: An object-based
assessment of multi-wavelength SAR, optical imagery and topographical
datasets for operational wetland mapping in boreal Yukon, Canada, Can. J.
Remote Sens., 45, 308–332, https://doi.org/10.1080/07038992.2019.1605500, 2019.
Merchant, M., Obadia, M., Brisco, B., DeVries, B., and Berg, A.: Applying
machine learning and time-series analysis on Sentinel-1A SAR/InSAR for
characterizing arctic tundra hydro-ecological condition, Remote Sens.,
14, 1123, https://doi.org/10.3390/rs14051123, 2022.
Merzouki, A., McNairn, H., and Pacheco, A.: Mapping soil moisture using
RADARSAT-2 data and local autocorrelation statistics, IEEE J. Sel. Top.
Appl., 4, 128–137, https://doi.org/10.1109/JSTARS.2011.2116769, 2011.
Mialon, A., Royer, A., Fily, M., and Picard, G.: Daily microwave-derived
surface temperature over Canada/Alaska, J. Appl. Meteorol. Clim., 46,
591–604, https://doi.org/10.1175/JAM2485.1, 2007.
Mialon, A., Rodríguez-Fernández, N., Santoro, M., Saatchi, S.,
Mermoz, S., Bousquet, E., and Kerr, Y.: Evaluation of the sensitivity of
SMOS L-VOD to forest above-ground biomass at global scale, Remote Sens.,
12, 1450, https://doi.org/10.3390/rs12091450, 2020.
Mikan, C., Schimel, J., and Doyle, A.: Temperature controls of microbial
respiration above and below freezing in Arctic tundra soils, Soil Biol.
Biochem., 34, 1785–1795, https://doi.org/10.3390/rs12091450, 2002.
Miner, K. R., Turesky, M. R., Malina, E., Bartsch, A., Tamminen, J., McGuire,
A. D., Fix, A., Sweeney, C., Elder, C. D., and Miller, C. E.: Permafrost carbon
emissions in a changing Arctic, Nat. Rev. Earth Environ., 3, 55–67, https://doi.org/10.1038/s43017-021-00230-3, 2022.
Mironov, V. and Savin, I.: A temperature-dependent multi-relaxation
spectroscopic dielectric model for thawed and frozen organic soil at
0.05–15 GHz, Phys. Chem. Earth, 83–84, 57–64, https://doi.org/10.1016/j.pce.2015.02.011, 2015.
Misra, T., Jha, A., Putrevu, D., Rao, J., Dave, D., and Rana, S.: Ground
calibration of multifrequency ScanningMicrowave radiometer (MSMR), IEEE T.
Geosci. Remote Sens., 40, 504–508, https://doi.org/10.1109/36.992823, 2002.
Mo, T., Choudhury, B., Schmugge, T., Wang, J., and Jackson, T.: A model for
microwave emission from vegetation-covered fields, J. Geophys. Res., 87,
11229–11237, https://doi.org/10.1029/JC087iC13p11229, 1982.
Moreira, A., Bachmann, M., Balzer, W., Tridon, D., Diedrich, E., Fritz, T.,
Grigorov, C., Kahle, R., Krieger, G., Hajnsek, I., Huber, S., Jörg, H.,
Klenk, P., Lachaise, M., Maier, M., Maurer, E., Papathanassiou, K., Parizzi,
A., Prats, P., Reimann, J., Rodriguez, M., Schättler, B., Schwinger, M.,
Schulze, D., Steinbrecher, U., Villano, M., Younis, M., De Zan, F., Zink,
M., and Zonno, M.: Tandem-L: Project Status and Main Findings of the Phase
Bl Study, IGARSS 2018 – 2018 IEEE International Geoscience and Remote
sensing Symposium, 22–27 July 2018, Valencia, Spain, 8667–8670, https://doi.org/10.1109/IGARSS.2018.8518591, 2018.
Morrissey, L., Durden, S., Livingston, G., Steam, J., and Guild, L.:
Differentiating methane source areas in Arctic environments with
multitemporal ERS-1 SAR data, IEEE T. Geosci. Remote Sens., 34, 667–673, https://doi.org/10.1109/36.499746, 1996.
Mortimer, C., Mudryk, L., Derksen, C., Luojus, K., Brown, R., Kelly, R., and Tedesco, M.: Evaluation of long-term Northern Hemisphere snow water equivalent products, The Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020, 2020.
Mortin, J., Schrøder, T., Walløe Hansen, A., Holt, B., and McDonald,
K.: Mapping of seasonal freeze-thaw transitions across the pan-Arctic land
and sea ice domains with satellite radar, J. Geophys. Res.-Oceans, 117, C08004,
https://doi.org/10.1029/2012JC008001, 2012.
Mu, Q., Zhao, M., Heinsch, F. A., Liu, M., Tian, H., and Running, S.:
Evaluating water stress controls on primary production in biogeochemical and
remote sensing based models, J. Geophys. Res.-Biogeo., 112, G01012, https://doi.org/10.1029/2006JG000179, 2007.
Murfitt, J. and Duguay, C.: 50 years of lake ice research from active
microwave remote sensing: Progress and prospects, Remote Sens. Environ.,
264, 112616, https://doi.org/10.1016/j.rse.2021.112616, 2021.
Myers-Smith, I. H., Forbes, B., Wilmking, M., Hallinger, M., Lantz, T.,
Blok, D., Tape, K., Macias-Fauria, M., Sass-Klaassen, U., Lévesque, E.,
Boudreau, S., Ropars, P., Hermanutz, L., Trant, A., Collier, L., Weijers,
S., Rozema, J., Rayback, S., Schmidt, N., Schaepman-Strub, G., Wipf, S.,
Rixen, C., Ménard, C., Venn, S., Goetz, S., Andreu-Hayles, L.,
Elmondorf, S., Ravolainen, V., Welker, J., Grogan, P., Epstein, H., and Hik,
D.: Shrub expansion in tundra ecosystems: dynamics, impacts and research
priorities, Environ. Res. Lett., 6, 045509, https://doi.org/10.1088/1748-9326/6/4/045509, 2011.
Myers-Smith, I. H., Kerby, J., Phoenix, G., Bjerke, J., Epstein, H.,
Assmann, J., John, C., Andreu-Hayles, L., Angers-Blondin, S., Beck, P.,
Berner, L., Bhatt, U., Bjorkman, A., Blok, C., Bryn, A., Christiansen, C.,
Cornelissen, J. H. C., Cunliffe, A., Elmendorf, S., Forbes, B., Goetz, S.,
Hollister, R., de Jong, R., Loranty, M., Macias-Fauria, M., Maseyk, K.,
Normand, S., Olofsson, J., Parker, T., Parmentier, F.-J., Post. E.,
Schaepman-Strub, G., Stordal, F., Sullivan, P., Thomas, H., Tømmervik,
H., Treharne, R., Tweedie, C., Walker, D., Wilmking, M., and Wipf, S.:
Complexity revealed in the greening of the Arctic, Nat. Clim. Change, 10,
106–117, https://doi.org/10.1038/s41558-019-0688-1, 2020.
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An
Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer
Observations, IEEE T. Geosci. Remote Sens., 47, 1999–2013, https://doi.org/10.1109/TGRS.2008.2011617, 2009.
Naeimi, V., Paulik, C., Bartsch, A., Wagner, W., Kidd, R., Park, S.-E.
Elger, K., and Boike, J.: ASCAT Surface State Flag (SSF): Extracting
Information on Surface Freeze/Thaw Conditions From Backscatter Data Using an
Empirical Threshold-Analysis Algorithm, IEEE T. Geosci. Remote Sens., 50,
2566–2582, https://doi.org/10.1109/TGRS.2011.2177667, 2012.
Nagler, T. and Rott, H.: Retrieval of wet snow by means of multitemporal
SAR data, IEEE T. Geosci. Remote Sens., 38, 754–765, https://doi.org/10.1109/36.842004,
2000.
Natali, S.,Watts, J., Rogers, B., Potter, S., Ludwig, S., Selbmann, A.-K.,
Sullivan, P., Abbott, B., Arndt, K., Birch, L., Björkman, M., Bloom, A.,
Celis, G., Christensen, T., Christiansen, C., Commane, R., Cooper, E.,
Crill, P., Czimczik, C., Davydov, S., Du, J., Egan, J., Elberling, B.,
Euskirchen, E., Friborg, T., Genet, H., Göckede, M., Goodrich, J.,
Grogan, P., Helbig, M., Jafarov, E., Jastrow, J., Kalhori, A., Kim, Y.,
Kimball, J., Kutzbach, L., Lara, M., Larsen, K., Lee, B.-Y., Liu, Z.,
Loranty, M., Lund, M., Lupascu, M., Madani, N., Malhotra, A., Matamala, R.,
McFarland, J., McGuire, A., Michelsen, A., Minions, C., Oechel, W.,
Olefeldt, D., Parmentier, F.-J., Pirk, N., Poulter, B., Quinton, W.,
Rezanezhad, F., Risk, D., Sachs, T., Schaefer, K., Schmidt, N., Schuur, E.,
Semenchuk, P., Shaver, G., Sonnentag, O., Starr, G., Treat, C., Waldrop, M.,
Wang, Y., Welker, J., Wille, C., Xu, X., Zhang, Z., Zhuang, Q., and Zona,
D.: Large loss of CO2 in winter observed across the northern permafrost
region, Nat. Clim. Change, 9, 852–857, https://doi.org/10.1038/s41558-019-0592-8, 2019.
Neumann, M., Saatchi, S., Ulander, L., and Fransson, J.: Assessing
performance of L- and P-Band polarimetric interferometric SAR data in
estimating boreal forest above-ground biomass, IEEE T. Geosci. Remote,
50, 714–726, https://doi.org/10.1109/TGRS.2011.2176133, 2012.
Osińska-Skotak, K.: Studies of soil temperature on the basis of
satellite data, Int. Agrophys., 21, 275–284, 2007.
Pallandt, M. M. T. A., Kumar, J., Mauritz, M., Schuur, E. A. G., Virkkala, A.-M., Celis, G., Hoffman, F. M., and Göckede, M.: Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements, Biogeosciences, 19, 559–583, https://doi.org/10.5194/bg-19-559-2022, 2022.
Pan, Y., Birdsey, R., Fang, J., Houghton, R., Kauppi, P., Kurz, W.,
Phillips, O., Shvidenko, A., Lewis, S., Canadell, J., Ciais, P., Jackson,
R., Pacala, S., McGuire, A., Piao, S., Rautiainen, A., Sitch, S., and Hayes,
D.: A large and persistent carbon sink in the world's forests, Science,
333, 988–993, https://doi.org/10.1126/science.1201609, 2011.
Pan, Y., Birdsey, R., Phillips, O., and Jackson, R.: The structure,
distribution, and biomass of the world's forests, Annu. Rev. Ecol. Syst.,
44, 593–622, https://doi.org/10.1146/annurev-ecolsys-110512-135914, 2013.
Panikov, N., Flanagan, P., Oechel, W., Mastepanov, M., and Christensen, T.:
Microbial activity in soils frozen to below −39 ∘C, Soil Biol.
Biochem., 38, 785–794, https://doi.org/10.1016/j.soilbio.2005.07.004, 2006.
Pappas, C., Maillet, J., Rakowski, S., Baltzer, J., Barr, A., Black, A.,
Fatichi, S., Laroque, C., Matheny, A., Roy, A., Sonnentag, O., and Zha, T.:
Aboveground tree growth is a minor and decoupled fraction of boreal forest
carbon input, Agr. Forest Meteorol., 290, 108030, https://doi.org/10.1016/j.agrformet.2020.108030, 2020.
Parinussa, R., Holmes, T., and de Jeu, R.: Soil moisture retrievals from the
WindSat spaceborne polarimetric microwave radiometer, IEEE T. Geosci.
Remote Sens., 50, 2683–2694, https://doi.org/10.1109/TGRS.2011.2174643, 2012.
Pastorello, G., Trotta, C., Canfora, E., et al.: The FLUXNET2015 dataset and
the ONEFlux processing pipeline for eddy covariance data, Sci. Data, 7, 225,
https://doi.org/10.1038/s41597-020-0534-3, 2020.
Peng, C., Ma, Z., Lei, X., Zhu, Q., Chen, H., Wang, W., Liu, S., Li, W.,
Fang, X., and Zhou, X.: A drought-induced pervasive increase in tree
mortality across Canada's boreal forests, Nat. Clim. Change, 1, 467–471,
https://doi.org/10.1038/nclimate1293, 2011.
Piao, S., Ciais, P., Friedlingstein, P., Peylin, P., Reichstein, M.,
Luyssaert, S., Margolis, H., Fang, J., Barr, A., Chen, A., Grelle, A.,
Hollinger, D., Laurila, T., Lindroth, A., Richardson, A., and Vesala, T.:
Net carbon dioxide losses of northern ecosystems in response to autumn
warming, Nature, 451, 49–52, https://doi.org/10.1038/nature06444, 2008.
Picard, G., Sandells, M., and Löwe, H.: SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0), Geosci. Model Dev., 11, 2763–2788, https://doi.org/10.5194/gmd-11-2763-2018, 2018.
Pierce, L., Ulaby, F., Sarabandi, K., and Dobson, M.: Knowledge-based
classification of polarimetric SAR images, IEEE T. Geosci. Remote Sens., 31,
1081–1086, https://doi.org/10.1109/36.312896, 1994.
Pierdicca, N., Davidson, M., Chini, M., Dierking, W., Djavidnia, S.,
Haarpaintner, J., Hajduch, G., Laurin, G., Lavalle, M.,
López-Martínez, C., Nagler, T., and Su, B.: The Copernicus L-band
SAR mission ROSE-L (Radar Observing System for Europe, Proc. Spie, Microwave
Remote sensing for Environmental Monitoring III, 111540E, https://doi.org/10.1117/12.2534743, 2019.
Pierrat, Z., Nehemy, M. F., Roy, A., Magney, T., Parazoo, N., Laroque, C.,
Pappas, C., Sonnentang, O., Grossman, K., Bowling, D. R., Seibt, U., Ramirez,
A., Johnson, B., Helgason, W., Barr, A., and Stutz, J.: Tower-based Remote
sensing reveals mechanisms behind a two-phased spring transition in a mixed
species boreal forest, J. Geophys. Res.-Biogeo., 126, e2020JG006191,
https://doi.org/10.1029/2020JG006191, 2021.
Potapov, P., Hansen, M., Stehman, S., Loveland, T., and Pittman, K.:
Combining MODIS and Landsat imagery to estimate and map boreal forest cover
loss, Remote Sens. Environ., 112, 3708–3719, https://doi.org/10.1016/j.rse.2008.05.006, 2008.
Prince, M., Roy, A., Brucker, L., Royer, A., Kim, Y., and Zhao, T.: Northern Hemisphere surface freeze–thaw product from Aquarius L-band radiometers, Earth Syst. Sci. Data, 10, 2055–2067, https://doi.org/10.5194/essd-10-2055-2018, 2018.
Prince, M., Roy, A., Royer, A., and Langlois, A.: Timing and spatial
variability of fall soil freezing in boreal forest and its effect on SMAP
L-band radiometer measurements, Remote Sens. Environ., 231, 111230, https://doi.org/10.1016/j.rse.2019.111230, 2019.
Pulliainen, J., Grandell, J., and Hallikainen, M.: Retrieval of surface
temperature in boreal forest zone from SSM/I data, IEEE T. Geosci. Remote Sens.,
35, 1188–1200, https://doi.org/10.1109/36.628786, 1997.
Pulliainen, J.: Mapping of snow water equivalent and snow depth in boreal
and sub-arctic zones by assimilating space-borne microwave radiometer data
and ground-based observations, Remote Sens. Environ., 101, 257–269, https://doi.org/10.1016/j.rse.2006.01.002, 2006.
Pulliainen, J., Aurela, M., Laurila, T., Aalto, T., Takala, M., Salminen,
M., Kulmala, M., Barr, A., Heimann, M., Lindroth, A., Laaksonen, A.,
Derksen, C., Mäkelä, A., Markkanen, T., Lemmetyinen, J., Susiluoto,
J., Dengel, S., Mammarella, I., Tuovinen, J.-P., and Vesala, T.: Early
snowmelt significantly enhances boreal springtime carbon uptake, P. Natl. Acad.
Sci. USA, 114, 11081–11086, https://doi.org/10.1073/pnas.1707889114, 2017.
Pulliainen, J., Luojus, K., Derksen, C., Mudryk, L., Lemmetyinen, J.,
Salminen, M., Ikonen, J., Takala, M., Cohen, J., Smolander, T., and Norberg,
J.: Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018,
Nature, 581, 294–298, https://doi.org/10.1038/s41586-020-2258-0, 2020.
Quegan, S., Le Toan, T., Chave, J., Dall, J., Exbrayat, J.-F., Minh, D.,
Lomas, M., Mariotti D'Alessandro, M. , Paillou, P., Papathanassiou, K.,
Rocca, F., Saatchi, S., Scipal, K., Shugart, H., Smallman, L., Soja, M.,
Tebaldini, S., Ulander, L., Vllard, L., and Williams, M.: The European Space
Agency BIOMASS mission: Measuring forest above-ground biomass from space,
Remote Sens. Environ., 227, 44–60, https://doi.org/10.1016/j.rse.2019.03.032, 2019.
Rafat, A., Rezanezhad, F., Quinton, W. L., Humphreys, E. R., Webster, K., and
Van Cappellen, P.: Non-growing season carbon emissions in a northern
peatland are projected to increase under global warming, Commun. Earth
Environ., 2, 111, https://doi.org/10.1038/s43247-021-00184-w, 2021.
Ranson, K. and Sun, G.: Effects of environmental conditions on boreal
forest classification and biomass estimates with SAR, IEEE T. Geosci.
Remote Sens., 38, 1242–1252, https://doi.org/10.1109/36.843016, 2000.
Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen,
O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic has warmed
nearly four times faster than the globe since 1979, Commun. Earth Environ.,
3, 168, https://doi.org/10.1038/s43247-022-00498-3, 2022.
Rautiainen, K., Lemmetyinen, J., Pulliainen, J., Vehviläinen, J.,
Drusch, M., Kontu, A., Kainulainen, J., and Seppanen, J.: L-band radiometer
observations of soil processes at boreal and sub- Arctic environments, IEEE
T. Geosci. Remote Sens., 50, 1483–1497, https://doi.org/10.1109/TGRS.2011.2167755, 2012.
Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A.,
Ikonen, J., Derksen, C., Davydov, S., Davydova, A., Boike, J., and Langer,
M.: SMOS prototype algorithm for detecting autumn soil freezing, Remote
Sens. Environ., 180, 346–360, https://doi.org/10.1016/j.rse.2016.01.012, 2016.
Rautiainen, K., Comite, D., Cohen, J., Cardellach, E., Unwin, M., and
Pierdicca, N.: Freeze–Thaw Detection Over High-Latitude Regions by Means of
GNSS-R Data, IEEE T. Geosci. Remote Sens., 60, 4302713, https://doi.org/10.1109/TGRS.2021.3125315, 2022.
Ravn, N., Elberling, B., and Michelsen, A.: Arctic soil carbon turnover
controlled by experimental snow addition, summer warming and shrub removal,
Soil Biol. Biochem., 142, 107698, https://doi.org/10.1016/j.soilbio.2019.107698, 2020.
Rodríguez-Fernández, N. J., Mialon, A., Mermoz, S., Bouvet, A., Richaume, P., Al Bitar, A., Al-Yaari, A., Brandt, M., Kaminski, T., Le Toan, T., Kerr, Y. H., and Wigneron, J.-P.: An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: high sensitivity of L-VOD to above-ground biomass in Africa, Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, 2018.
Rodríguez-Fernández, N., Al Bitar, A., Colliander, A., and Zhao,
T.: Soil moisture remote sensing across scales, Remote Sens., 11, 190,
https://doi.org/10.3390/rs11020190, 2019a.
Rodríguez-Fernández, N., Mialon, A., Merlin, O., Suere, C., Cabot,
F., Khazaal, A., Costeraste, J., Palacin, B., Rodriguez-Suquet, R.,
Tournier, T., Decoopman, T., Colom, M., Morel, J.-M., and Kerr, Y.: SMOS-HR:
A high resolution L-Band passive radiometer for earth science and
applications, IGARSS 2019 – 2019 IEEE International Geoscience and Remote
sensing Symposium, 28 July–2 August 2019, Yokohama, Japan, 8392–8395,
https://doi.org/10.1109/IGARSS.2019.8897815, 2019b.
Rogers, M., Sullivan, P., and Welker, J.: Evidence of nonlinearity in the
response of net ecosystem CO2 exchange to increasing levels of winter
snow depth in the high Arctic of Northwest Greenland, Arct. Antarct. Alp.
Res., 43, 95–106, https://doi.org/10.1657/1938-4246-43.1.95, 2010.
Rosen, P., Hensley, S., Shaffer, S., Veilleux, L., Chakraborty, M., Misra,
T., Bhan, R., Sagi, R., and Satish, R.: The NASA-ISRO SAR mission – An
international space partnership for science and societal benefit, 2015 IEEE
Radar Conference (RadarCon), 10–15 May 2015, Arlington, United States,
1610–1613, https://doi.org/10.1109/RADAR.2015.7131255, 2015.
Rosen, P., Hensley, S., Shaffer, S., Edelstein, W., Kim, Y., Kumar, R.,
Misra, T., Bhan, R., Satish, R., and Sagi, R.: An update on the NASA-ISRO
dual-frequency DBF SAR (NISAR) mission, 2016 IEEE International Geoscience
and Remote sensing Symposium (IGARSS), 10–15 July 2016, Beijing, China,
2106–2108, https://doi.org/10.1109/IGARSS.2016.7729543, 2016.
Roy, A., Royer, A., Wigneron, J.-P., Langlois, A., Bergeron, J., and Cliche,
P.: A simple parameterization for a boreal forest radiative transfer model
at microwave frequencies, Remote Sens. Environ., 124, 371–383, https://doi.org/10.1016/j.rse.2012.05.020, 2012.
Roy, A., Royer, A., and Hall, R.: Relationship between forest microwave
transmissivity and structural parameters for the Canadian boreal forest,
IEEE Geosci. Remote Sens., 11, 1802–1806, https://doi.org/10.1109/LGRS.2014.2309941,
2014.
Roy, A., Royer, A., Derksen, C., Brucker, L., Langlois, A., Mialon, A., and
Kerr, Y.: Evaluation of spaceborne L-Band radiometer measurements for
terrestrial freeze/thaw retrievals in Canada, IEEE J. Sel. Top. Appl., 8,
4442–4459, https://doi.org/10.1109/JSTARS.2015.2476358, 2015.
Roy, A., Toose, P., Williamson, M., Rowlandson, T., Derksen, C., Royer, A.,
Berg, A., Lemmetyinen, J., and Arnold, L.: Response of L-Band brightness
temperatures to freeze/thaw and snow dynamics in a prairie environment from
ground-based radiometer measurements, Remote Sens. Environ., 191, 67–80,
https://doi.org/10.1016/j.rse.2017.01.017, 2017a.
Roy, A., Toose, P., Derksen, C., Rowlandson, T., Berg, A., Lemmetyinen, J.,
Royer, A., Tetlock, E., Helgason, W., and Sonnentag, O.: Spatial Variability
of L-Band Brightness Temperature during Freeze/Thaw Events over a Prairie
Environment, Remote Sens., 9, 894, https://doi.org/10.3390/rs9090894, 2017b.
Roy, A., Toose, P., Mavrovic, A., Pappas, C., Royer, C., Derksen, C., Berg,
A., Rowlandson, T., El-Amine, M., Barr, A., Black, A., Langlois, A., and
Sonnentag, O.: L-Band response to freeze/thaw in a boreal forest stand from
ground- and tower-based radiometer observations, Remote Sens. Environ., 237,
111542, https://doi.org/10.1016/j.rse.2019.111542, 2020.
Royer, A. and Poirier, S.: Surface temperature spatial and temporal
variations in North America from homogenized satellite SMMR-SSM/I microwave
measurements and reanalysis for 1979–2008, J. Geophys. Res., 115, D08110,
https://doi.org/10.1029/2009JD012760, 2010.
Royer, A., Roy, A., Jutras, S., and Langlois, A.: Review article:
Performance assessment of radiation-based field sensors for monitoring the
water equivalent of snow cover (SWE), Cryosphere, 15, 5079–5098, https://doi.org/10.5194/tc-15-5079-2021, 2021.
Ruiz-Pérez, G. and Vico, G.: Effects of Temperature and Water
Availability on Northern European Boreal Forests, Front. For. Glob. Change,
3, 34, https://doi.org/10.3389/ffgc.2020.00034, 2020.
Saatchi, S. and Rignot, E.: Classification of boreal forest cover types
using SAR images, Remote Sens. Environ., 60, 270–281, https://doi.org/10.1016/S0034-4257(96)00181-2, 1997.
Saberi, N., Kelly, R., Flemming, M., and Li, Q.: Review of snow water
equivalent retrieval methods using spaceborne passive microwave radiometry,
Int. J. Remote Sens., 41, 996–1018, https://doi.org/10.1080/01431161.2019.1654144,
2020.
Santoro, M. and Cartus, O.: Research pathways of forest above-ground
biomass estimation based on SAR backscatter and interferometric SAR
observations, Remote Sens., 10, 608, https://doi.org/10.3390/rs10040608, 2018.
Santoro, M., Cartus, O., Mermoz, S., Bouvet, A., Le Toan, T., Carvalhais,
N., Rozendaal, D., Herold, M., Avitabile, V., Shaun, Q., Carreiras, J.,
Rauste, Y., Balzter, H., Schmullius, C., and Seifert, F.: A detailed
portrait of the forest aboveground biomass pool for the year 2010 obtained
from multiple Remote sensing observations, Geophys. Res. Abstr.,
EGU2018-18932, EGU General Assembly 2018, Vienna, Austria, 2018.
Schär, C., Fuhrer, O., Arteaga, A., Ban, N., Charpilloz, C., Di
Girolamo, S., Hentgen, L., Hoefler, T., Lapillonne, X., Leutwyler, D.,
Osterried, K., Panosetti, D., Rüdisühli, S., Schlemmer, L.,
Schulthess, T., Sprenger, M., Ubbiali, S., and Wernli, H.: Kilometer-scale
climate models: prospects and challenges, B. Am. Meteorol. Soc., 101,
E567–E587, https://doi.org/10.1175/BAMS-D-18-0167.1, 2020.
Schädel, C., Bader, M., Schuur, E., Biasi, C., Bracho, R., Čapek,
P., De Baets, S., Diáková, K., Ernakovich, J., Estop-Aragones, C.,
Graham, D., Hartley, I., Iversen, C., Kane, E., Knoblauch, C., Lupascu, M.,
Martikainen, P., Natali, S., Norby, R., O'Donnell, J., Chowdhury, T.,
Šantrůčková, H., Shaver, G., Sloan, V., Treat, C., Turetsky,
M., Waldrop, M., and Wickland, K.: Potential carbon emissions dominated by
carbon dioxide from thawed permafrost soils, Nat. Clim. Change, 6, 950–953,
https://doi.org/10.1038/nclimate3054, 2016.
Schlund, M., Scipal, K., and Quegan, S.: Assessment of a power law
relationship between P-band SAR backscatter and aboveground biomass and its
implications for BIOMASS mission performance, IEEE J. Sel. Top. Appl.,
11, 3538–3547, https://doi.org/10.1109/JSTARS.2018.2866868, 2018.
Schuur, E., McGuire, A., Schädel, C., Grosse, G., Harden, J., Hayes, D.,
Hugelius, G., Koven, C., Kuhry, P., Lawrence, D., Natali, S., Olefeldt, D.,
Romanovsky, V., Schaefer, K., Turetsky, M., Treat, C., and Vonk, J.: Climate
change and the permafrost carbon feedback, Nature, 520, 171–179, https://doi.org/10.1038/nature14338, 2015.
Seiler, C., Melton, J., Arora, V., Sitch, S., Friedlingstein, P., Anthoni,
P., Goll, D., Jain, A., Joetzjer, E., Lienert, S., Lombardozzi, D.,
Luyssaert, S., Nabel, J., Tian, H., Vuichard, N., Walker, A., Yuan, W., and
Zaehle, S.: Are terrestrial biosphere models fit for simulating the global
land carbon sink?, J. Adv. Model Earth Sy., 14, e2021MS002946, https://doi.org/10.1029/2021MS002946,
2022.
Shi, J., Xiong, C., and Jiang, L.: Review of snow water equivalent microwave
remote Sensing, Sci. China Earth Sci., 59, 731–745, https://doi.org/10.1007/s11430-015-5225-0, 2016.
Sitch, S., McGuire, D., Kimball, J., Gedney, N., Gamon, J., Engstrom, R.,
Wolf, A., Zhuang, Q., Clein, J., and McDonald, K.: Assessing the carbon
balance of circumpolar Arctic tundra using Remote sensing and process
modelling, Ecol. Appl., 17, 213–234, https://doi.org/10.1890/1051-0761(2007)017[0213:ATCBOC]2.0.CO;2, 2007.
Sniderhan, A., Mamet, S., and Baltzer, J.: Non-uniform growth dynamics of a
dominant boreal tree species (Picea mariana) in the face of rapid climate change, Can. J.
Forest Res., 51, 565–572, https://doi.org/10.1139/cjfr-2020-0188, 2021.
Stefan, V.-G., Indrio, G., Escorihuela, M.-J., Quintana-Sehuì, P., and
Villar, J., M.: High-resolution SMAP-derived root-zone soil moisture using
an exponential filter model calibrated per land cover type, Remote Sens.,
13, 1112, https://doi.org/10.3390/rs13061112, 2021.
Stocker, B., Zscheischler, J., Keenan, T., Prentice, C., Peñuelas, J., and Seneviratne, S.: Quantifying soil moisture impacts on light use efficiency across biomes, New Phytol., 218, 1430–1449, https://doi.org/10.1111/nph.15123, 2018.
Sturm, M., Holmgren, J., König, M., and Morris, K.: The thermal
conductivity of seasonal snow, J. Glaciol., 43, 26–41, https://doi.org/10.3189/s0022143000002781, 1997.
Sturm, M., Schimel, J., Michaelson, G., Welker, J., Oberbauer, S., Liston,
G., Fahnestock, J., and Romanovsky, V.: Winter biological processes could
help convert arctic tundra to shrubland, Bioscience, 55, 17–26, https://doi.org/10.1641/0006-3568(2005)055[0017:WBPCHC]2.0.CO;2, 2005.
Sulla-Menashe, D., Woodcock, C., and Friedl, M.: Canadian boreal forest
greening and browning trends: an analysis of biogeographic patterns and the
relative roles of disturbance versus climate drivers, Environ. Res. Lett.,
13, 014007, https://doi.org/10.1088/1748-9326/aa9b88, 2018.
Takala, M., Luojus, K., Pulliainen, J., Derksen, C., Lemmetyinen, J.,
Kärnä, J.-P., Koskinen, J., and Bojkov, B.: Estimating northern
hemisphere snow water equivalent for climate research through assimilation
of space-borne radiometer data and ground-based measurements, Remote Sens.
Environ., 115, 3517–3529, https://doi.org/10.1016/j.rse.2011.08.014, 2011.
Tanja, S., Berninger, F., Vesala, T., Markkanen, T., Hari, P.,
Mäkelä, A., Ilvesniemi, H., Hänninen, H., Nikinmaa, E., Huttula,
T., Laurila, T., Aurela, M., Grelle, A., Lindroth, A., Arneth, A.,
Shibistova, O., and Lloyd, J.: Air temperature triggers the commencement of
evergreen boreal forest photosynthesis in spring, Glob. Change Biol., 9,
1410–1426, https://doi.org/10.1046/j.1365-2486.2003.00597.x, 2003.
Tarnocai, C., Canadell, J., Schuur, E., Kuhry, P., Mazhitova, G., and Zimov,
S.: Soil organic carbon pools in the northern circumpolar permafrost region,
Gobal Biogeochem. Cy., 23, GB2023, https://doi.org/10.1029/2008GB003327, 2009.
Tebaldini, S., Ho Tong Minh, D., Mariotti d'Alessandro, M., Villard, L., Le
Toan, T., and Chave, J.: The status of technologies to measure forest
biomass and structural properties: state of the art in SAR tomography of
tropical forests, Surv. Geophys., 40, 779–801, https://doi.org/10.1007/s10712-019-09539-7, 2019.
Tedesco, M. and Jeyaratnam, J.: A new operational snow retrieval algorithm
applied to historical AMSR-E brightness temperatures, Remote Sens., 8,
1037, https://doi.org/10.3390/rs8121037, 2016.
Tei, S. and Sugimoto, A.: Excessive positive response of model-simulated
land net primary production to climate changes over circumboreal forests,
Plant-Environment Interactions, 1, 102–121, https://doi.org/10.1002/pei3.10025,
2020.
Tenkanen, M., Tsuruta, A., Rautiainen, K., Kangasaho, V., Ellul, R., and
Aalto, T.: Utilizing earth observations of soil freeze/thaw data and
atmospheric concentrations to estimate cold season methane emissions in the
Northern high latitudes, Remote Sens., 13, 5059, https://doi.org/10.3390/rs13245059, 2021.
Teubner, I., Forkel, M., Jung, M., Liu, Y., Miralles, D., Parinussa, R., van
der Schalie, R., Vreugdenhil, M., Schwalm, C., Tramontana, G., Camps-Valls,
G., and Drigo, W.: Assessing the relationship between microwave vegetation
visible depth and gross primary production, Int. J. Appl. Earth Obs., 65,
79–91, https://doi.org/10.1016/j.jag.2017.10.006, 2018.
Teubner, I., Forkel, M., Camps-Valls, G., Jung, M., Miralles, D.,
Tramontana, G., van der Schalie, R., Vreugdenhil, Mösinger, L., and
Dorigo, W.: A carbon sink-driven approach to estimate gross primary
production from microwave satellite observations, Remote Sens. Environ.,
229, 100–113, https://doi.org/10.1016/j.rse.2019.04.022, 2019.
Tian, F., Brandt, M., Liu, Y., Verger, A., Tagesson, T., Diouf, A.,
Rasmussen, K., Mbow, C., Wang, Y., and Fensholt, R.: Remote sensing of
vegetation dynamics in drylands: Evaluating vegetation visible depth (VOD)
using AVHRR NDVI and in situ green biomass data over West African Sahel,
Remote Sens. Environ., 177, 265–276, https://doi.org/10.1016/j.rse.2016.02.056, 2016.
Tomiyasu, K.: Tutorial Review of Synthetic-Aperture Radar (SAR) with
Applications to Imaging of Ocean Surface, P. IEEE, 66, 563–583, https://doi.org/10.1109/PROC.1978.10961, 1978.
Touati, C., Ratsimbazafy, T., Ludwig, R., and Bernier, M.: New approaches
for removing the effect of water damping on SMAP freeze/thaw mapping, Can.
J. Remote Sens., 45, 405–422, https://doi.org/10.1080/07038992.2019.1638236, 2019.
Töyrä, J., Pietroniro, A., and Martz, L.: Multisensor hydrologic
assessment of a freshwater wetland, Remote Sens. Environ., 75, 162–173,
https://doi.org/10.1016/s0034-4257(00)00164-4, 2001.
Tu, Q., Hase, F., Blumenstock, T., Kivi, R., Heikkinen, P., Sha, M. K., Raffalski, U., Landgraf, J., Lorente, A., Borsdorff, T., Chen, H., Dietrich, F., and Chen, J.: Intercomparison of atmospheric CO2 and CH4 abundances on regional scales in boreal areas using Copernicus Atmosphere Monitoring Service (CAMS) analysis, COllaborative Carbon Column Observing Network (COCCON) spectrometers, and Sentinel-5 Precursor satellite observations, Atmos. Meas. Tech., 13, 4751–4771, https://doi.org/10.5194/amt-13-4751-2020, 2020.
Tucker, C. J.: Red and photographic infrared linear combinations for
monitoring vegetation, Remote Sens. Environ., 8, 127–150, https://doi.org/10.1016/0034-4257(79)90013-0, 1979.
Turner, D., Ollinger, S., and Kimball, J.: Integrating remote sensing and
ecosystem process models for landscape- to regional-scale analysis of the
carbon cycle, Bioscience, 54, 573–584, https://doi.org/10.1641/0006-3568(2004)054[0573:IRSAEP]2.0.CO;2, 2004.
Ulaby, F., Moore, R., and Fung, A.: Microwave Remote Sens.-Basel: Active and
Passive, Vol. II – Radar remote sensing and surface scattering and emission
theory, Addison-Wesley Publishing Company, Advanced Book Program/World
Science Division, Norwood, Massachusetts, United-States, ISBN 9780201107609, 1982.
Ulaby, F., Allen, C., and Fung, A.: Method for Retrieving the True Backscattering Coefficient from Measurements with a Real Antenna, IEEE T. Geosci. Remote Sens., GE-21, 308–313, https://doi.org/10.1109/TGRS.1983.350558, 1983.
Ulaby, F., Moore, R., and Fung, A.: Microwave Remote Sens.: Active and
Passive. Vol. III. From theory to applications, Artech House Publishers,
Norwood, Massachusetts, United-States, https://doi.org/10.1017/S0016756800015831, 1986.
Ulaby, F., Sarabandi, K., McDonald, K., Whitt, M., and Dobson, M. C.:
Michigan microwave canopy scattering model, Int. J. Remote Sens., 11,
1223–1253, https://doi.org/10.1080/01431169008955090, 1990.
Ullmann, T., Schmitt, A., Roth, A., Duffe, J., Dech, S., Hubberten, H.-W.,
and Baumhauer, R.: Land cover characterization and classification of arctic
tundra environments by means of polarized synthetic aperture X- and C-Band
radar (PolSAR) and Landsat 8 multispectral imagery – Richards Island,
Canada, Remote Sens., 6, 8565–8593, https://doi.org/10.3390/rs6098565, 2014.
van Huissteden, J. and Dolman, A.: Soil carbon in the Arctic and the
permafrost carbon feedback, Curr. Opin. Env. Sust., 4, 545–551, https://doi.org/10.1016/j.cosust.2012.09.008, 2012.
Virkkala, A.-M., Aalto, J., Rogers, B., Tagesson, T., Treat, C., Natali, S.,
Watts, J., Potter, S., Lehtonen, A., Mauritz, M., Schuur, E., Kochendorfer,
J., Zona, D., Oechel, W., Kobayashi, H., Humphreys, E., Goeckede, M., Iwata,
H., Lafleur, P., Euskirchen, E., Bokhorst, S., Marushchak, M., Martikainen,
P., Elberling, B., Voigt, C., Biasi, C., Sonnentag, O., Parmentier, F.-J.,
Ueyama, M., Celis, G., St.Louis, V., Emmerton, C., Peichl, M., Chi, J.,
Järveoja, J., Nilsson, M., Oberbauer, S., Torn, M., Park, S.-J., Dolman,
H., Mammarella, I., Chae, N., Poyatos, R., López-Blanco, E.,
Christensen, T., Kwon, M., Sachs, T., Holl, D., and Luoto, M.: Statistical
upscaling of ecosystem CO2 fluxes across the terrestrial tundra and
boreal domain: Regional patterns and uncertainties, Glob. Change Biol.,
27, 4040–4059, https://doi.org/10.1111/gcb.15659, 2021.
Vittucci, C., Vaglio Laurin, G., Tramontana, G., Ferrazzoli, P., Guerriero,
L., and Papale, D.: Vegetation visible depth at L-band and above ground
biomass in the tropical range: Evaluating their relationships at continental
and regional scales, Int. J. Appl. Earth Obs., 77, 151–161, https://doi.org/10.1016/j.jag.2019.01.006, 2019.
Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S.,
Figa-Saldaña, J., de Rosnay, P., Jann, A., Schneider, S., Komma, J.,
Kubu, G., Brugger, K., Aubrecht, C., Züger, J., Gangkofner, U.,
Kienberger, S., Brocca, L., Wang, Y., Blöschl, G., Eitzinger, J., and
Steinnocher, K.: The ASCAT soil moisture product: A review of its
specifications, validation results, and emerging applications, Meteorol. Z.,
22, 5–33, https://doi.org/10.1127/0941-2948/2013/0399, 2013.
Walker, X. and Johnstone, J.: Widespread negative correlations between
black spruce growth and temperature across topographic moisture gradients in
the boreal forest, Environ. Res. Lett., 9, 064016, https://doi.org/10.1088/1748-9326/9/6/064016, 2014.
Walker, X., Rogers, B., Veraverbeke, S., Johnstone, J., Baltzer, J.,
Barrett, K., Bourgeau-Chavez, L., Day, N., de Groot, W., Dieleman, C.,
Goetz, S., Hoy, E., Jenkins, L., Kane, E., Parisien, M.-A., Potter, S.,
Schuur, E., Turetsky, M., Whitman, E., and Mack, M.: Fuel availability not
fire weather controls boreal wildfire severity and carbon emissions, Nat.
Clim. Change, 10, 1130–1136, https://doi.org/10.1038/s41558-020-00920-8, 2020.
Wang, J., Sulla-Menashe, D., Woodcock, C., Sonnentag, O., Keeling, R., and
Friedl, M.: Extensive land cover change across Arctic-Boreal Northwestern
North America from disturbance and climate forcing, Glob. Change Biol.,
26, 807–822, https://doi.org/10.1111/gcb.14804, 2019.
Wang, J., Sulla-Menashe, D., Woodcock, C., Sonnentag, O., Keeling, R., and Friedl, M.: Extensive land cover change across Arctic–Boreal Northwestern North America from disturbance and climate forcing, Glob. Change Biol., 26, 807–822, https://doi.org/10.1111/gcb.14804, 2020.
Washington, W., Buja, L., and Craig, A.: The computational future for
climate and Earth system models: on the path to petaflop and beyond, Philos.
T. R. Soc. A., 367, 833–846, https://doi.org/10.1098/rsta.2008.0219, 2009.
Watts, J., Kimball, J., Bartsch, A., and McDonald, K.: Surface water
inundation in the boreal-Arctic: potential impacts on regional methane
emissions, Environ. Res. Lett., 9, 075001, https://doi.org/10.1088/1748-9326/9/7/075001, 2014.
Webb, E., Schuur, E., Natali, S., Oken, K., Bracho, R., Krapek, J., Risk,
D., and Nickerson, N.: Increased wintertime CO2 loss as a result of
sustained tundra warming, J. Geophys. Res.-Biogeo., 121, 249–265, https://doi.org/10.1002/2014JG002795, 2016.
Welker, J., Fahnestock, J., and Jones, M.: Annual CO2 flux in dry and
moist Arctic tundra: field responses to increases in summer temperatures and
winter snow depth, Climatic Change, 44, 139–150, https://doi.org/10.1023/A:1005555012742, 2000.
Whitcomb, J., Moghaddam, M., McDonald, K., Kellndorfer, J., and Podest, E.:
Mapping vegetated wetlands of Alaska using L-band radar satellite imagery,
Can. J. Remote Sens., 35, 54–72, https://doi.org/10.5589/m08-080, 2009.
Wigneron, J.-P., Kerr, Y., Waldteufel, P., Saleh, K., Escorihuela, M.-J.,
Richaume, P., Ferrazzoli, P., de Rosnay, P., Gurneye, R., Calvet, J.-C.,
Grant, J., Guglielmetti, M., Hornbuckle, B., Mätzler, C., Pellarin, T.,
and Schwank, M.: L-band Microwave Emission of the Biosphere (L-MEB) Model:
Description and calibration against experimental data sets over crop fields,
Remote Sens. Environ., 107, 639–655, https://doi.org/10.1016/j.rse.2006.10.014,
2007.
Wigneron, J.-P., Li, X., Frappart, F., Fan, L., Al-Yaari, A., De Lannoy, G.,
Liu, X., Wang, M., Le Masson, E., and Moisy, C.: Overview of the SMOS-IC
data recordofsoil moisture and L-VOD: Historic development, applications and
perspectives, Remote Sens. Environ., 254, 112238, https://doi.org/10.1016/j.rse.2020.112238, 2021.
Wohlfahrt, G., Gerdel, K., Migliavacca, M., Rotenberg, E., Tatarinov, F.,
Müller, J., Hammerle, A., Julitta, T., Spielmann, F., and Yakir, D.:
Sun-induced fluorescence and gross primary productivity during a heat wave,
Sci. Rep.-UK, 8, 14169, https://doi.org/10.1038/s41598-018-32602-z, 2018.
Wu, M., Scholze, M., Kaminski, T., Voßbeck, M., and Tagesson, T.: Using
SMOS soil moisture data combining CO2 flask samples to constrain carbon
fluxes during 2010–2015 within a Carbon Cycle Data Assimilation System
(CCDAS), Remote Sens. Environ., 240, 111719, https://doi.org/10.1016/j.rse.2020.111719,
2020.
Xian, D., Zhang, P., Gao, L., Sun, R., Zhang, H., and Jia, X.: Fengyun
Meteorological Satellite Products for Earth System Science Applications,
Adv. Atmos. Sci., 38, 1267–1284, https://doi.org/10.1007/s00376-021-0425-3, 2021.
Xiao, J., Chevallier, F., Gomez, C., Guanter, L., Hicke, J., Huete, A.,
Ichii, K., Nih, W., Pang, Y., Rahman, A., Sun, G., Yuan, W., Zhang, L., and
Zhang, X.: Remote sensing of the terrestrial carbon cycle: A review of
advances over 50 years, Remote Sens. Environ., 233, 111383, https://doi.org/10.1016/j.rse.2019.111383, 2019.
Xu, X., Derksen, C., Yueh, S. Dunbar, R., and Colliander, A.: Freeze/thaw
detection and validation using Aquarius' L-Band backscattering data, IEEE J.
Sel. Top. Appl., 9, 1370–1381, https://doi.org/10.1109/JSTARS.2016.2519347, 2016.
Yang, W., Meng, H., Ferraro, R., Moradi, I., and Devaraj, C.: Cross-Scan
asymmetry of AMSU-A window channels: characterization, correction, and
verification, IEEE T. Geosci. Remote, 51, 1514–1530, https://doi.org/10.1109/TGRS.2012.2211884, 2013.
Yi, Y., Kimball, J., Jones, L., Reichle, R., Nemani, R., and Margolis, H.:
Recent climate and fire disturbance impacts on boreal and arctic ecosystem
productivity estimated using a satellite-based terrestrial carbon flux
model, J. Geophys. Res.-Biogeo., 118, 606–622, https://doi.org/10.1002/jgrg.20053,
2013.
Yi, Y., Chen, R., Kimball, J., Moghaddam, M., Xu, X., Euskirchen, E., Das,
N., and Miller, C.: Potential satellite monitoring of surface organic soil
properties in arctic tundra from SMAP, Water Resour. Res., 58,
e2021WR030957, https://doi.org/10.1029/2021WR030957, 2022.
Yu, K., Han, S., Bu, J., An, Y., Zhou, Z., Wang, C., Tabibi, S., and Cheong,
J. W.: Spaceborne GNSS Reflectometry, Remote Sens., 14, 1605, https://doi.org/10.3390/rs14071605, 2022.
Zhang, Q. and Cheng, J.: An empirical algorithm for retrieving land surface
temperature from AMSR-E data considering the comprehensive effects of
environmental variables, Earth Space Sci., 7, e2019EA001006, https://doi.org/10.1029/2019EA001006, 2020.
Zhang, Y. Song, C., Sun, G., Band, L., Noormets, A. and Zhang, Q.:
Understanding moisture stress on light use efficiency across terrestrial
ecosystems based on global flux and remote-sensing data, J. Geophys. Res.-Biogeo.,
120, 2053–2066, https://doi.org/10.1002/2015JG003023, 2015.
Zhou, Z., Li, Z., Waldron, S., and Tanaka, A.: InSAR time series analysis of
L-Band data for understanding tropical peatland degradation and restoration,
Remote Sens., 11, 2592, https://doi.org/10.3390/rs11212592, 2019.
Zona, D., Gioli, B., Commane, R., and Oechel, W. C.: Cold season emissions
dominate the Arctic tundra methane budget, P. Natl. Acad. Sci. USA, 113, 40–45, https://doi.org/10.1073/pnas.1516017113, 2015.
van Zyl, J.: Unsupervised classification of scattering behavior using radar
polarimetry data, IEEE T. Geosci. Remote Sens., 27, 36–45, https://doi.org/10.1109/36.20273, 1989.
Short summary
This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
This review supports the integration of microwave spaceborne information into carbon cycle...
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