Articles | Volume 21, issue 14
https://doi.org/10.5194/bg-21-3251-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/bg-21-3251-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The influence of plant water stress on vegetation–atmosphere exchanges: implications for ozone modelling
Tamara Emmerichs
CORRESPONDING AUTHOR
Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany
Center for Advanced Simulation and Analytics (CASA), Forschungszentrum Jülich GmbH, Jülich, Germany
Yen-Sen Lu
Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, Jülich, Germany
Center for Advanced Simulation and Analytics (CASA), Forschungszentrum Jülich GmbH, Jülich, Germany
Domenico Taraborrelli
Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany
Center for Advanced Simulation and Analytics (CASA), Forschungszentrum Jülich GmbH, Jülich, Germany
Related authors
Tamara Emmerichs, Abdulla Al Mamun, Lisa Emberson, Huiting Mao, Leiming Zhang, Limei Ran, Clara Betancourt, Anthony Wong, Gerbrand Koren, Giacomo Gerosa, Min Huang, and Pierluigi Guaita
EGUsphere, https://doi.org/10.5194/egusphere-2025-429, https://doi.org/10.5194/egusphere-2025-429, 2025
Short summary
Short summary
The risk of ozone pollution to plants is estimated based on the flux through the plant pores which still has uncertainties. In this study, we estimate this quantity with 9 models at different land types worldwide. The input data stems from a database. The models estimated mostly reasonable summertime ozone deposition. The different results of the models varied by land cover which were mostly related to the moisture deficit. This is an important step for assessing the ozone impact on vegetation.
Yasin Elshorbany, Jerald R. Ziemke, Sarah Strode, Hervé Petetin, Kazuyuki Miyazaki, Isabelle De Smedt, Kenneth Pickering, Rodrigo J. Seguel, Helen Worden, Tamara Emmerichs, Domenico Taraborrelli, Maria Cazorla, Suvarna Fadnavis, Rebecca R. Buchholz, Benjamin Gaubert, Néstor Y. Rojas, Thiago Nogueira, Thérèse Salameh, and Min Huang
Atmos. Chem. Phys., 24, 12225–12257, https://doi.org/10.5194/acp-24-12225-2024, https://doi.org/10.5194/acp-24-12225-2024, 2024
Short summary
Short summary
We investigated tropospheric ozone spatial variability and trends from 2005 to 2019 and related those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone and its precursors, nitrogen dioxide, formaldehyde, and total column CO, as well as ozonesonde data and model simulations.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
Short summary
Short summary
A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Tamara Emmerichs, Bruno Franco, Catherine Wespes, Vinod Kumar, Andrea Pozzer, Simon Rosanka, and Domenico Taraborrelli
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-584, https://doi.org/10.5194/acp-2021-584, 2021
Revised manuscript not accepted
Short summary
Short summary
Near-surface ozone is a harmful air pollutant and it is strongly affected by radical reactions and surface-atmosphere exchanges which in turn are modulated, directly and indirectly, by weather. Understanding the impact of weather on ozone, and air quality, is thus important also in view of weather extremes. The inclusion of additional ozone-weather links in the global model yields a 2-fold reduction of the ozone bias towards satellite observations.
Tamara Emmerichs, Astrid Kerkweg, Huug Ouwersloot, Silvano Fares, Ivan Mammarella, and Domenico Taraborrelli
Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, https://doi.org/10.5194/gmd-14-495-2021, 2021
Short summary
Short summary
Dry deposition to vegetation is a major sink of ground-level ozone. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for global tropospheric ozone. We extended the current model parameterization with a relevant pathway and important meteorological adjustment factors. The comparison with measurements shows that this enables a more realistic model representation of ozone dry deposition velocity. Globally, annual dry deposition loss increases.
Suvarna Fadnavis, Yasin Elshorbany, Jerald Ziemke, Brice Barret, Alexandru Rap, P. R. Satheesh Chandran, Richard J. Pope, Vijay Sagar, Domenico Taraborrelli, Eric Le Flochmoen, Juan Cuesta, Catherine Wespes, Folkert Boersma, Isolde Glissenaar, Isabelle De Smedt, Michel Van Roozendael, Hervé Petetin, and Isidora Anglou
Atmos. Chem. Phys., 25, 8229–8254, https://doi.org/10.5194/acp-25-8229-2025, https://doi.org/10.5194/acp-25-8229-2025, 2025
Short summary
Short summary
Satellites and model simulations show enhancement in tropospheric ozone, which is highly impacted by human-produced nitrous oxides compared to volatile organic compounds. The increased amount of ozone enhances ozone radiative forcing. The ozone enhancement and associated radiative forcing are the highest over South and East Asia. The emissions of nitrous oxides show a higher influence on shifting ozone photochemical regimes than volatile organic compounds.
Raphael Dreger, Timo Kirfel, Andrea Pozzer, Simon Rosanka, Rolf Sander, and Domenico Taraborrelli
Geosci. Model Dev., 18, 4273–4291, https://doi.org/10.5194/gmd-18-4273-2025, https://doi.org/10.5194/gmd-18-4273-2025, 2025
Short summary
Short summary
Model simulations are essential for understanding the interactions between atmospheric composition and weather. However, models including chemistry are very slow. Hence, any computation speedup of such models is important for understanding the role of atmospheric chemistry within the Earth system. In this study we analyzed and optimized the time step for chemistry calculations. Our results show that atmospheric models could be run notably faster without any loss in accuracy.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Tamara Emmerichs, Abdulla Al Mamun, Lisa Emberson, Huiting Mao, Leiming Zhang, Limei Ran, Clara Betancourt, Anthony Wong, Gerbrand Koren, Giacomo Gerosa, Min Huang, and Pierluigi Guaita
EGUsphere, https://doi.org/10.5194/egusphere-2025-429, https://doi.org/10.5194/egusphere-2025-429, 2025
Short summary
Short summary
The risk of ozone pollution to plants is estimated based on the flux through the plant pores which still has uncertainties. In this study, we estimate this quantity with 9 models at different land types worldwide. The input data stems from a database. The models estimated mostly reasonable summertime ozone deposition. The different results of the models varied by land cover which were mostly related to the moisture deficit. This is an important step for assessing the ozone impact on vegetation.
Yasin Elshorbany, Jerald R. Ziemke, Sarah Strode, Hervé Petetin, Kazuyuki Miyazaki, Isabelle De Smedt, Kenneth Pickering, Rodrigo J. Seguel, Helen Worden, Tamara Emmerichs, Domenico Taraborrelli, Maria Cazorla, Suvarna Fadnavis, Rebecca R. Buchholz, Benjamin Gaubert, Néstor Y. Rojas, Thiago Nogueira, Thérèse Salameh, and Min Huang
Atmos. Chem. Phys., 24, 12225–12257, https://doi.org/10.5194/acp-24-12225-2024, https://doi.org/10.5194/acp-24-12225-2024, 2024
Short summary
Short summary
We investigated tropospheric ozone spatial variability and trends from 2005 to 2019 and related those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone and its precursors, nitrogen dioxide, formaldehyde, and total column CO, as well as ozonesonde data and model simulations.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Meghna Soni, Rolf Sander, Lokesh K. Sahu, Domenico Taraborrelli, Pengfei Liu, Ankit Patel, Imran A. Girach, Andrea Pozzer, Sachin S. Gunthe, and Narendra Ojha
Atmos. Chem. Phys., 23, 15165–15180, https://doi.org/10.5194/acp-23-15165-2023, https://doi.org/10.5194/acp-23-15165-2023, 2023
Short summary
Short summary
The study presents the implementation of comprehensive multiphase chlorine chemistry in the box model CAABA/MECCA. Simulations for contrasting urban environments of Asia and Europe highlight the significant impacts of chlorine on atmospheric oxidation capacity and composition. Chemical processes governing the production and loss of chlorine-containing species has been discussed. The updated chemical mechanism will be useful to interpret field measurements and for future air quality studies.
Marc von Hobe, Domenico Taraborrelli, Sascha Alber, Birger Bohn, Hans-Peter Dorn, Hendrik Fuchs, Yun Li, Chenxi Qiu, Franz Rohrer, Roberto Sommariva, Fred Stroh, Zhaofeng Tan, Sergej Wedel, and Anna Novelli
Atmos. Chem. Phys., 23, 10609–10623, https://doi.org/10.5194/acp-23-10609-2023, https://doi.org/10.5194/acp-23-10609-2023, 2023
Short summary
Short summary
The trace gas carbonyl sulfide (OCS) transports sulfur from the troposphere to the stratosphere, where sulfate aerosols are formed that influence climate and stratospheric chemistry. An uncertain OCS source in the troposphere is chemical production form dimethyl sulfide (DMS), a gas released in large quantities from the oceans. We carried out experiments in a large atmospheric simulation chamber to further elucidate the chemical mechanism of OCS production from DMS.
Yen-Sen Lu, Garrett H. Good, and Hendrik Elbern
Geosci. Model Dev., 16, 1083–1104, https://doi.org/10.5194/gmd-16-1083-2023, https://doi.org/10.5194/gmd-16-1083-2023, 2023
Short summary
Short summary
The Weather Forecasting and Research (WRF) model consists of many parameters and options that can be adapted to different conditions. This expansive sensitivity study uses a large-scale simulation system to determine the most suitable options for predicting cloud cover in Europe for deterministic and probabilistic weather predictions for day-ahead forecasting simulations.
Flora Kluge, Tilman Hüneke, Christophe Lerot, Simon Rosanka, Meike K. Rotermund, Domenico Taraborrelli, Benjamin Weyland, and Klaus Pfeilsticker
Atmos. Chem. Phys., 23, 1369–1401, https://doi.org/10.5194/acp-23-1369-2023, https://doi.org/10.5194/acp-23-1369-2023, 2023
Short summary
Short summary
Using airborne glyoxal concentration and vertical column density measurements, vertical profiles are inferred for eight global regions in aged biomass burning plumes and the tropical marine boundary layer. Using TROPOMI observations, an analysis of space- and airborne measurements is performed. A comparison to EMAC simulations shows a general glyoxal underprediction, which points to various missing sources and precursors from anthropogenic activities, biomass burning, and the sea surface.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
Short summary
Short summary
A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Simon Rosanka, Bruno Franco, Lieven Clarisse, Pierre-François Coheur, Andrea Pozzer, Andreas Wahner, and Domenico Taraborrelli
Atmos. Chem. Phys., 21, 11257–11288, https://doi.org/10.5194/acp-21-11257-2021, https://doi.org/10.5194/acp-21-11257-2021, 2021
Short summary
Short summary
The strong El Niño in 2015 led to a particular dry season in Indonesia and favoured severe peatland fires. The smouldering conditions of these fires and the high carbon content of peat resulted in high volatile organic compound (VOC) emissions. By using a comprehensive atmospheric model, we show that these emissions have a significant impact on the tropospheric composition and oxidation capacity. These emissions are transported into to the lower stratosphere, resulting in a depletion of ozone.
Tamara Emmerichs, Bruno Franco, Catherine Wespes, Vinod Kumar, Andrea Pozzer, Simon Rosanka, and Domenico Taraborrelli
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-584, https://doi.org/10.5194/acp-2021-584, 2021
Revised manuscript not accepted
Short summary
Short summary
Near-surface ozone is a harmful air pollutant and it is strongly affected by radical reactions and surface-atmosphere exchanges which in turn are modulated, directly and indirectly, by weather. Understanding the impact of weather on ozone, and air quality, is thus important also in view of weather extremes. The inclusion of additional ozone-weather links in the global model yields a 2-fold reduction of the ozone bias towards satellite observations.
Simon Rosanka, Rolf Sander, Andreas Wahner, and Domenico Taraborrelli
Geosci. Model Dev., 14, 4103–4115, https://doi.org/10.5194/gmd-14-4103-2021, https://doi.org/10.5194/gmd-14-4103-2021, 2021
Short summary
Short summary
The Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) is developed and implemented into the Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA). JAMOC is an explicit in-cloud oxidation scheme for oxygenated volatile organic compounds (OVOCs), which is suitable for global model applications. Within a box-model study, we show that JAMOC yields reduced gas-phase concentrations of most OVOCs and oxidants, except for nitrogen oxides.
Simon Rosanka, Rolf Sander, Bruno Franco, Catherine Wespes, Andreas Wahner, and Domenico Taraborrelli
Atmos. Chem. Phys., 21, 9909–9930, https://doi.org/10.5194/acp-21-9909-2021, https://doi.org/10.5194/acp-21-9909-2021, 2021
Short summary
Short summary
In-cloud destruction of ozone depends on hydroperoxyl radicals in cloud droplets, where they are produced by oxygenated volatile organic compound (OVOC) oxygenation. Only rudimentary representations of these processes, if any, are currently available in global atmospheric models. By using a comprehensive atmospheric model that includes a complex in-cloud OVOC oxidation scheme, we show that atmospheric oxidants are reduced and models ignoring this process will underpredict clouds as ozone sinks.
Domenico Taraborrelli, David Cabrera-Perez, Sara Bacer, Sergey Gromov, Jos Lelieveld, Rolf Sander, and Andrea Pozzer
Atmos. Chem. Phys., 21, 2615–2636, https://doi.org/10.5194/acp-21-2615-2021, https://doi.org/10.5194/acp-21-2615-2021, 2021
Short summary
Short summary
Atmospheric pollutants from anthropogenic activities and biomass burning are usually regarded as ozone precursors. Monocyclic aromatics are no exception. Calculations with a comprehensive atmospheric model are consistent with this view but only for air masses close to pollution source regions. However, the same model predicts that aromatics, when transported to remote areas, may effectively destroy ozone. This loss of tropospheric ozone rivals the one attributed to bromine.
Tamara Emmerichs, Astrid Kerkweg, Huug Ouwersloot, Silvano Fares, Ivan Mammarella, and Domenico Taraborrelli
Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, https://doi.org/10.5194/gmd-14-495-2021, 2021
Short summary
Short summary
Dry deposition to vegetation is a major sink of ground-level ozone. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for global tropospheric ozone. We extended the current model parameterization with a relevant pathway and important meteorological adjustment factors. The comparison with measurements shows that this enables a more realistic model representation of ozone dry deposition velocity. Globally, annual dry deposition loss increases.
Cited articles
Badgley, G., Fisher, J. B., Jiménez, C., Tu, K. P., and Vinukollu, R.: On Uncertainty in Global Terrestrial Evapotranspiration Estimates from Choice of Input Forcing Datasets, J. Hydrometeorol., 16, 1449–1455, https://doi.org/10.1175/JHM-D-14-0040.1, 2015. a
Barriopedro, D., García-Herrera, R., Ordonez, C., Miralles, D. G., and Salcedo-Sanz, S.: Heat Waves: Physical Understanding and Scientific Challenges, Rev. Geophys., 61, e2022RG000780, https://doi.org/10.1029/2022RG000780, 2023. a
Boone, A., Habets, F., Noilhan, J., Clark, D., Dirmeyer, P., Fox, S., Gusev, Y., Haddeland, I., Koster, R., Lohmann, D., Mahanama, S., Mitchell, K., Nasonova, O., Niu, G.-Y., Pitman, A., Polcher, J., Shmakin, A. B., Tanaka, K., van den Hurk, B., Vérant, S., Verseghy, D., Viterbo, P., and Yang, Z.-L.: The Rhône-Aggregation Land Surface Scheme Intercomparison Project: An Overview, J. Climate, 17, 187–208, https://doi.org/10.1175/1520-0442(2004)017<0187:trlssi>2.0.co;2, 2004. a, b
Calvet, J.-C.: Investigating soil and atmospheric plant water stress using physiological and micrometeorological data, Agr. Forest Meteorol., 103, 229–247, https://doi.org/10.1016/S0168-1923(00)00130-1, 2000. a
Calvet, J.-C., Noilhan, J., Roujean, J.-L., Bessemoulin, P., Cabelguenne, M., Olioso, A., and Wigneron, J.-P.: An interactive vegetation SVAT model tested against data from six contrasting sites, Agr. Forest Meteorol., 92, 73–95, https://doi.org/10.1016/S0168-1923(98)00091-4, 1998. a
Calvet, J.-C., Rivalland, V., Picon-Cochard, C., and Guehl, J.-M.: Modelling forest transpiration and CO2 fluxes–response to soil moisture stress, Agr. Forest Meteorol., 124, 143–156, https://doi.org/10.1016/j.agrformet.2004.01.007, 2004. a
Cao, R., Huang, H., Wu, G., Han, D., Jiang, Z., Di, K., and Hu, Z.: Spatiotemporal variations in the ratio of transpiration to evapotranspiration and its controlling factors across terrestrial biomes, Agr. Forest Meteorol., 321, 108984, https://doi.org/10.1016/j.agrformet.2022.108984, 2022. a
De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C., Hickler, T., Jain, A. K., Luo, Y., Parton, W. J., Prentice, I. C., Smith, B., Thornton, P. E., Wang, S., Wang, Y.-P., Wårlind, D., Weng, E., Crous, K. Y., Ellsworth, D. S., Hanson, P. J., Seok Kim, H., Warren, J. M., Oren, R., and Norby, R. J.: Forest water use and water use efficiency at elevated CO2: a model-data intercomparison at two contrasting temperate forest FACE sites, Global Change Biol., 19, 1759–1779, https://doi.org/10.1111/gcb.12164, 2013. a
Domeisen, D. I. V., Eltahir, E. A. B., Fischer, E. M., Knutti, R., Perkins-Kirkpatrick, S. E., Schär, C., Seneviratne, S. I., Weisheimer, A., and Wernli, H.: Prediction and projection of heatwaves, Nat. Rev. Earth Environ., 4, 36–50, https://doi.org/10.1038/s43017-022-00371-z, 2022. a, b
Dong, J., Lei, F., and Crow, W. T.: Land transpiration-evaporation partitioning errors responsible for modeled summertime warm bias in the central United States, Nat. Commun., 13, 336, https://doi.org/10.1038/s41467-021-27938-6, 2022. a, b
Drake, J. E., Tjoelker, M. G., Vårhammar, A., Medlyn, B. E., Reich, P. B., Leigh, A., Pfautsch, S., Blackman, C. J., López, R., Aspinwall, M. J., Crous, K. Y., Duursma, R. A., Kumarathunge, D., De Kauwe, M. G., Jiang, M., Nicotra, A. B., Tissue, D. T., Choat, B., Atkin, O. K., and Barton, C. V. M.: Trees tolerate an extreme heatwave via sustained transpirational cooling and increased leaf thermal tolerance, Global Change Biol., 24, 2390–2402, https://doi.org/10.1111/gcb.14037, 2018. a
ECMWF: IFS Documentation CY47R3, IFS Documentation, ECMWF, https://doi.org/10.21957/eyrpir4vj, 2021. a, b
Egea, G., Verhoef, A., and Vidale, P. L.: Towards an improved and more flexible representation of water stress in coupled photosynthesis–stomatal conductance models, Agr. Forest Meteorol., 151, 1370–1384, https://doi.org/10.1016/j.agrformet.2011.05.019, 2011. a, b, c
Elnashar, A., Wang, L., Wu, B., Zhu, W., and Zeng, H.: Synthesis of global actual evapotranspiration from 1982 to 2019, Earth Syst. Sci. Data, 13, 447–480, https://doi.org/10.5194/essd-13-447-2021, 2021. a
Emmerichs, T., Kerkweg, A., Ouwersloot, H., Fares, S., Mammarella, I., and Taraborrelli, D.: A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54, Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, 2021. a, b, c
Forzieri, G., Miralles, D. G., Ciais, P., Alkama, R., Ryu, Y., Duveiller, G., Zhang, K., Robertson, E., Kautz, M., Martens, B., Jiang, C., Arneth, A., Georgievski, G., Li, W., Ceccherini, G., Anthoni, P., Lawrence, P., Wiltshire, A., Pongratz, J., Piao, S., Sitch, S., Goll, D. S., Arora, V. K., Lienert, S., Lombardozzi, D., Kato, E., Nabel, J. E. M. S., Tian, H., Friedlingstein, P., and Cescatti, A.: Increased control of vegetation on global terrestrial energy fluxes, Nat. Clim. Change, 10, 356–362, https://doi.org/10.1038/s41558-020-0717-0, 2020. a
Fu, T.-M. and Tian, H.: Climate Change Penalty to Ozone Air Quality: Review of Current Understandings and Knowledge Gaps, Current Pollution Reports, 5, 159–171, https://doi.org/10.1007/s40726-019-00115-6, 2019. a
Giorgetta, M. A., Roeckner, E., Mauritsen, T., Bader, J., Crueger, T., Esch, M., Rast, S., Kornblueh, L., Schmidt, H., Kinne, S., Hohenegger, C., Möbis, B., Krismer, T., Wieners, H., and Stevens, B.: The atmospheric general circulation model ECHAM6: Model description, Reports on Earth System Science, 177, https://doi.org/10.17617/2.1810480, 2013. a
Guanter, L., Bacour, C., Schneider, A., Aben, I., van Kempen, T. A., Maignan, F., Retscher, C., Köhler, P., Frankenberg, C., Joiner, J., and Zhang, Y.: The TROPOSIF global sun-induced fluorescence dataset from the Sentinel-5P TROPOMI mission, Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, 2021. a, b, c, d
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006. a, b, c
Hagemann, S.: An Improved Land Surface Parameter Dataset for Global and Regional Climate Models, Tech. Rep., 336, https://doi.org/10.17617/2.2344576, 2002. a, b
Hagemann, S. and Stacke, T.: Impact of the soil hydrology scheme on simulated soil moisture memory, Clim. Dynam., 44, 1731–1750, https://doi.org/10.1007/s00382-014-2221-6, 2015. a, b, c, d
Harper, A. B., Williams, K. E., McGuire, P. C., Duran Rojas, M. C., Hemming, D., Verhoef, A., Huntingford, C., Rowland, L., Marthews, T., Breder Eller, C., Mathison, C., Nobrega, R. L. B., Gedney, N., Vidale, P. L., Otu-Larbi, F., Pandey, D., Garrigues, S., Wright, A., Slevin, D., De Kauwe, M. G., Blyth, E., Ardö, J., Black, A., Bonal, D., Buchmann, N., Burban, B., Fuchs, K., de Grandcourt, A., Mammarella, I., Merbold, L., Montagnani, L., Nouvellon, Y., Restrepo-Coupe, N., and Wohlfahrt, G.: Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements, Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, 2021. a
Iturbide, M., Gutiérrez, J. M., Alves, L. M., Bedia, J., Cerezo-Mota, R., Cimadevilla, E., Cofiño, A. S., Di Luca, A., Faria, S. H., Gorodetskaya, I. V., Hauser, M., Herrera, S., Hennessy, K., Hewitt, H. T., Jones, R. G., Krakovska, S., Manzanas, R., Martínez-Castro, D., Narisma, G. T., Nurhati, I. S., Pinto, I., Seneviratne, S. I., van den Hurk, B., and Vera, C. S.: An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets, Earth Syst. Sci. Data, 12, 2959–2970, https://doi.org/10.5194/essd-12-2959-2020, 2020. a
Jacobs, C. M. J., van den Hurk, B. M. M., and de Bruin, H. A. R.: Stomata1 behaviour and photosynthetic rate of unstressed grapevines in semi-arid conditions, Agr. Forest Meteorol., 24, https://doi.org/10.1016/0168-1923(95)02295-3, 1994. a
Jiang, X., Niu, G.-Y., and Yang, Z.-L.: Impacts of vegetation and groundwater dynamics on warm season precipitation over the Central United States, J. Geophys. Res.-Atmos., 114, D06109, https://doi.org/10.1029/2008JD010756, 2009. a
Jöckel, P., Kerkweg, A., Pozzer, A., Sander, R., Tost, H., Riede, H., Baumgaertner, A., Gromov, S., and Kern, B.: Development cycle 2 of the Modular Earth Submodel System (MESSy2), Geosci. Model Dev., 3, 717–752, https://doi.org/10.5194/gmd-3-717-2010, 2010. a, b
Jöckel, P., Tost, H., Pozzer, A., Kunze, M., Kirner, O., Brenninkmeijer, C. A. M., Brinkop, S., Cai, D. S., Dyroff, C., Eckstein, J., Frank, F., Garny, H., Gottschaldt, K.-D., Graf, P., Grewe, V., Kerkweg, A., Kern, B., Matthes, S., Mertens, M., Meul, S., Neumaier, M., Nützel, M., Oberländer-Hayn, S., Ruhnke, R., Runde, T., Sander, R., Scharffe, D., and Zahn, A.: Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51, Geosci. Model Dev., 9, 1153–1200, https://doi.org/10.5194/gmd-9-1153-2016, 2016. a, b, c, d, e
Jülich Supercomputing Centre: JUWELS: Modular Tier-0/1 Supercomputer at the Jülich Supercomputing Centre, Journal of Large-Scale Research Facilities, 5, A135, https://doi.org/10.17815/jlsrf-5-171, 2019. a
Jülich Supercomputing Centre: JURECA: Data Centric and Booster Modules implementing the Modular Supercomputing Architecture at Jülich Supercomputing Centre, Journal of Large-Scale Research Facilities, 7, A182, https://doi.org/10.17815/jlsrf-7-182, 2021. a
Kala, J., De Kauwe, M. G., Pitman, A. J., Medlyn, B. E., Wang, Y.-P., Lorenz, R., and Perkins-Kirkpatrick, S. E.: Impact of the representation of stomatal conductance on model projections of heatwave intensity, Sci. Rep.-UK, 6, 23418, https://doi.org/10.1038/srep23418, 2016. a, b
Katul, G. G., Palmroth, S., and Oren, R.: Leaf stomatal responses to vapour pressure deficit under current and CO2-enriched atmosphere explained by the economics of gas exchange, Plant Cell Environ., 32, 968–979, https://doi.org/10.1111/j.1365-3040.2009.01977.x, 2009. a
Katul, G. G., Oren, R., Manzoni, S., Higgins, C., and Parlange, M. B.: Evapotranspiration: A process driving mass transport and energy exchange in the soil-plant-atmosphere-climate system, Rev. Geophys., 50, RG3002, https://doi.org/10.1029/2011RG000366, 2012. a
Keenan, T., Sabate, S., and Gracia, C.: Soil water stress and coupled photosynthesis–conductance models: Bridging the gap between conflicting reports on the relative roles of stomatal, mesophyll conductance and biochemical limitations to photosynthesis, Agr. Forest Meteorol., 150, 443–453, https://doi.org/10.1016/j.agrformet.2010.01.008, 2010. a, b
Kennedy, D., Swenson, S., Oleson, K. W., Lawrence, D. M., Fisher, R., Lola da Costa, A. C., and Gentine, P.: Implementing Plant Hydraulics in the Community Land Model, Version 5, J. Adv. Model. Earth Sy., 11, 485–513, https://doi.org/10.1029/2018MS001500, 2019. a, b, c
Kerkweg, A., Buchholz, J., Ganzeveld, L., Pozzer, A., Tost, H., and Jöckel, P.: Technical Note: An implementation of the dry removal processes DRY DEPosition and SEDImentation in the Modular Earth Submodel System (MESSy), Atmos. Chem. Phys., 6, 4617–4632, https://doi.org/10.5194/acp-6-4617-2006, 2006. a, b
Klein, T.: The variability of stomatal sensitivity to leaf water potential across tree species indicates a continuum between isohydric and anisohydric behaviours, Funct. Ecol., 28, 1313–1320, https://doi.org/10.1111/1365-2435.12289, 2014. a
Knohl, A. and Baldocchi, D. D.: Effects of diffuse radiation on canopy gas exchange processes in a forest ecosystem, J. Geophys. Res.-Biogeo., 113, G02023, https://doi.org/10.1029/2007JG000663, 2008. a
Kollet, S. J. and Maxwell, R. M.: Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model, Water Resour. Res., 44, W02402, https://doi.org/10.1029/2007WR006004, 2008. a
Kozlowski, T. T., Kramer, P. J., and Pallardy, S. G.: The Physiological Ecology of Woody Plants, Tree Physiol., 8, 213, https://doi.org/10.1093/treephys/8.2.213, 1991. a, b
Lam, A., Karssenberg, D., van den Hurk, B. J. J. M., and Bierkens, M. F. P.: Spatial and temporal connections in groundwater contribution to evaporation, Hydrol. Earth Syst. Sci., 15, 2621–2630, https://doi.org/10.5194/hess-15-2621-2011, 2011. a
Larsen, M. A. D., Refsgaard, J. C., Drews, M., Butts, M. B., Jensen, K. H., Christensen, J. H., and Christensen, O. B.: Results from a full coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model for a Danish catchment, Hydrol. Earth Syst. Sci., 18, 4733–4749, https://doi.org/10.5194/hess-18-4733-2014, 2014. a
Lian, X., Piao, S., Huntingford, C., Li, Y., Zeng, Z., Wang, X., Ciais, P., McVicar, T. R., Peng, S., Ottlé, C., Yang, H., Yang, Y., Zhang, Y., and Wang, T.: Partitioning global land evapotranspiration using CMIP5 models constrained by observations, Nat. Clim. Change, 8, 640–646, https://doi.org/10.1038/s41558-018-0207-9, 2018. a, b, c, d, e
Maes, W. H., Pagán, B. R., Martens, B., Gentine, P., Guanter, L., Steppe, K., Verhoest, N. E. C., Dorigo, W., Li, X., Xiao, J., and Miralles, D. G.: Sun-induced fluorescence closely linked to ecosystem transpiration as evidenced by satellite data and radiative transfer models, Remote Sens. Environ., 249, 112030, https://doi.org/10.1016/j.rse.2020.112030, 2020. a, b, c
Martini, D., Sakowska, K., Wohlfahrt, G., Pacheco-Labrador, J., van der Tol, C., Porcar-Castell, A., Magney, T. S., Carrara, A., Colombo, R., El-Madany, T. S., Gonzalez-Cascon, R., Martín, M. P., Julitta, T., Moreno, G., Rascher, U., Reichstein, M., Rossini, M., and Migliavacca, M.: Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production, New Phytol., 233, 2415–2428, https://doi.org/10.1111/nph.17920, 2022. a
Millar, A. A., Jensen, R. E., Bauer, A., and Norum, E. B.: Influence of atmospheric and soil environmental parameters on the diurnal fluctuations of leaf water status of barley, Agr. Meteorol., 8, 93–105, https://doi.org/10.1016/0002-1571(71)90099-9, 1971. a
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011. a
Miralles, D. G., Gentine, P., Seneviratne, S. I., and Teuling, A. J.: Land-atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges, Ann. NY Acad. Sci., 1436, 19–35, https://doi.org/10.1111/nyas.13912, 2019. a
Nairn, J. R. and Fawcett, R. J. B.: The excess heat factor: a metric for heatwave intensity and its use in classifying heatwave severity, Int. J. Env. Res. Pub. He., 12, 227–253, https://doi.org/10.3390/ijerph120100227, 2014. a, b
NOVELTI, UPV, SRON, LSCE, and ESA: The TROPOSIF global sun-induced fluorescence dataset from the TROPOMI mission, https://doi.org/10.5270/esa-s5p_innovation-sif-20180501_20210320-v2.1-202104, 2021. a, b, c, d
Paço, T. A. d., Ferreira, M. I., and Pacheco, C. A.: Scheduling peach orchard irrigation in water stress conditions: use of relative transpiration and predawn leaf water potential, Fruits, 68, 147–158, https://doi.org/10.1051/fruits/2013061, 2013. a
Palmer, P. I., Jacob, D. J., Fiore, A. M., Martin, R. V., Chance, K., and Kurosu, T. P.: Mapping isoprene emissions over North America using formaldehyde column observations from space, J. Geophys. Res.-Atmos., 108, 4180, https://doi.org/10.1029/2002JD002153, 2003. a
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Ottlé, C., Poulter, B., Zaehle, S., and Running, S. W.: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling, Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, 2020. a, b, c, d, e, f
Pitman, A. J.: The evolution of, and revolution in, land surface schemes designed for climate models, Int. J. Climatol., 23, 479–510, 2003. a
Pollard, D. and Thompson, S. L.: Use of a land-surface-transfer scheme (LSX) in a global climate model: the response to doubling stomatal resistance, Results from the Model Evaluation Consortium for Climate Assessment, 10, 129–161, http://www.sciencedirect.com/science/article/pii/0921818194000237 (last access: 13 February 2024), 1995. a
Pusede, S. E., Steiner, A. L., and Cohen, R. C.: Temperature and Recent Trends in the Chemistry of Continental Surface Ozone, Chem. Rev., 115, 3898–3918, https://doi.org/10.1021/cr5006815, 2015. a
Rahman, M., Sulis, M., and Kollet, S. J.: The concept of dual-boundary forcing in land surface-subsurface interactions of the terrestrial hydrologic and energy cycles, Water Resour. Res., 50, 8531–8548, https://doi.org/10.1002/2014WR015738, 2014. a
Rasmussen, D. J., Hu, J., Mahmud, A., and Kleeman, M. J.: The Ozone–Climate Penalty: Past, Present, and Future, Environ. Sci. Technol., 47, 14258–14266, https://doi.org/10.1021/es403446m, 2013. a
Robock, A., Schlosser, C. A., Vinnikov, K. Y., Speranskaya, N. A., Entin, J. K., and Qiu, S.: Evaluation of the AMIP soil moisture simulations, Global Planet. Change, 19, 181–208, https://doi.org/10.1016/S0921-8181(98)00047-2, 1998. a, b
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general circulation model ECHAM 5. PART I: Model description, MPI report, Max-Planck-Institut für Meteorologie, 2003. a, b
Rogers, A., Medlyn, B. E., Dukes, J. S., Bonan, G., von Caemmerer, S., Dietze, M. C., Kattge, J., Leakey, A. D. B., Mercado, L. M., Niinemets, U., Prentice, I. C., Serbin, S. P., Sitch, S., Way, D. A., and Zaehle, S.: A roadmap for improving the representation of photosynthesis in Earth system models, New Phytol., 213, 22–42, https://doi.org/10.1111/nph.14283, 2017. a, b, c
Sabot, M. E. B., De Kauwe, M. G., Pitman, A. J., Medlyn, B. E., Ellsworth, D. S., Martin-StPaul, N. K., Wu, J., Choat, B., Limousin, J.-M., Mitchell, P. J., Rogers, A., and Serbin, S. P.: One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models, J. Adv. Model. Earth Sy., 14, e2021MS002761, https://doi.org/10.1029/2021MS002761, 2022. a, b
Sadiq, M., Tai, A. P. K., Lombardozzi, D., and Val Martin, M.: Effects of ozone–vegetation coupling on surface ozone air quality via biogeochemical and meteorological feedbacks, Atmos. Chem. Phys., 17, 3055–3066, https://doi.org/10.5194/acp-17-3055-2017, 2017. a
Schulz, J.-P., Dümenil, L., and Polcher, J.: On the land surface–atmosphere coupling and its impact in a single-column atmospheric model, J. Appl. Meteorol., 40, 642–663, https://doi.org/10.1175/1520-0450(2001)040<0642:OTLSAC>2.0.CO;2, 2001. a, b, c, d
Sellers, P., Dickinson, R. E., Randall, D., Betts, A., Hall, F., Berry, J., Collatz, G., Denning, A., Mooney, H., Nobre, C., Sato, N., Field, C. B., and Henderson-Sellers, A.: Modeling the exchanges of energy, water, and carbon between continents and the atmosphere, Science, 275, 502–509, https://doi.org/10.1126/science.275.5299.502, 1997. a, b, c, d
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010. a, b, c, d, e, f
Shao, Y. and Henderson-Sellers, A.: Modeling soil moisture: A Project for Intercomparison of Land Surface Parameterization Schemes Phase 2(b), J. Geophys. Res., 101, 7227–7250, https://doi.org/10.1029/95JD03275, 1996. a
Shepherd, T. G. , Boyd E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West, I. M., Fowler, H. J., James, R., Maraun D., Martius, O., Senior, C. A., Sobel A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., van den Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., and Zenghelis, D. A.: Storylines: an alternative approach to representing uncertainty in physical aspects of climate change, Climatic Change, 151, 555–571, https://doi.org/10.1007/s10584-018-2317-9, 2018. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Sy., 5, 146–172, https://doi.org/10.1002/jame.20015, 2013. a
Thépaut, J.-N., Dee, D., Engelen, R., and Pinty, B.: The Copernicus programme and its climate change service, in: IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, 1591–1593, IEEE, https://doi.org/10.1109/IGARSS.2018.8518067, 2018. a
Tost, H., Jöckel, P., Kerkweg, A., Sander, R., and Lelieveld, J.: Technical note: A new comprehensive SCAVenging submodel for global atmospheric chemistry modelling, Atmos. Chem. Phys., 6, 565–574, https://doi.org/10.5194/acp-6-565-2006, 2006. a
Trigo, I. F., Dacamara, C. C., Viterbo, P., Roujean, J.-L., Olesen, F., Barroso, C., Camacho-de Coca, F., Carrer, D., Freitas, S. C., Garcia-Haro, J., Geiger, B., Gellens-Meulenberghs, F., Ghilain, N., Melia, J., Pessanha, L., Siljamo, N., and Arboleda, A.: The Satellite Application Facility for Land Surface Analysis, Int. J. Remote Sens., 32, 2725–2744, https://doi.org/10.1080/01431161003743199, 2011. a
Tuzet, A., Perrier, A., and Leuning, R.: A coupled model of stomatal conductance, photosynthesis and transpiration, Plant Cell Environ., 26, 1097–1116, https://doi.org/10.1046/j.1365-3040.2003.01035.x, 2003. a
Utset, A., Farre, I., Martinez-Cob, A., and Cavero, J.: Comparing Penman–Monteith and Priestley–Taylor approaches as reference-evapotranspiration inputs for modeling maize water-use under Mediterranean conditions, Agr. Water Manage., 66, 205–219, https://doi.org/10.1016/j.agwat.2003.12.003, 2004. a
Verhoef, A. and Egea, G.: Modeling plant transpiration under limited soil water: Comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models, Agr. Forest Meteorol., 191, 22–32, https://doi.org/10.1016/j.agrformet.2014.02.009, 2014. a, b, c, d, e, f, g
Wang, B., Yue, X., Zhou, H., and Zhu, J.: Impact of diffuse radiation on evapotranspiration and its coupling to carbon fluxes at global FLUXNET sites, Agr. Forest Meteorol., 322, 109006, https://doi.org/10.1016/j.agrformet.2022.109006, 2022. a
Wang, K. and Dickinson, R. E.: A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability, Rev. Geophys., 50, RG2005, https://doi.org/10.1029/2011RG000373, 2012. a, b, c
Wang, Z., Zhan, C., Ning, L., and Guo, H.: Evaluation of global terrestrial evapotranspiration in CMIP6 models, Theor. Appl. Climatol., 143, 521–531, https://doi.org/10.1007/s00704-020-03437-4, 2021. a, b
Xiao, J., Fisher, J. B., Hashimoto, H., Ichii, K., and Parazoo, N. C.: Emerging satellite observations for diurnal cycling of ecosystem processes, Nat. Plants, 7, 877–887, https://doi.org/10.1038/s41477-021-00952-8, 2021. a
Xiao, Z., Liang, S., and Jiang, B.: Evaluation of four long time-series global leaf area index products, Agr. Forest Meteorol., 246, 218–230, https://doi.org/10.1016/j.agrformet.2017.06.016, 2017. a
Zanis, P., Akritidis, D., Turnock, S., Naik, V., Szopa, S., Georgoulias, A. K., Bauer, S. E., Deushi, M., Horowitz, L. W., Keeble, J., Sager, P. L., O'Connor, F. M., Oshima, N., Tsigaridis, K., and van Noije, T.: Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models, Environ. Res. Lett., 17, 024014, https://doi.org/10.1088/1748-9326/ac4a34, 2022. a
Zhang, L., Brook, J. R., and Vet, R.: A revised parameterization for gaseous dry deposition in air-quality models, Atmos. Chem. Phys., 3, 2067–2082, https://doi.org/10.5194/acp-3-2067-2003, 2003. a, b, c
Zhang, Y., Chiew, F. H. S., Peña-Arancibia, J., Sun, F., Li, H., and Leuning, R.: Global variation of transpiration and soil evaporation and the role of their major climate drivers, J. Geophys. Res.-Atmos., 122, 6868–6881, https://doi.org/10.1002/2017JD027025, 2017. a
Zhou, S., Duursma, R. A., Medlyn, B. E., Kelly, J. W. G., and Prentice, I. C.: How should we model plant responses to drought? An analysis of stomatal and non-stomatal responses to water stress, Agr. Forest Meteorol., 182–183, 204–214, https://doi.org/10.1016/j.agrformet.2013.05.009, 2013. a
Short summary
We assess the representation of the plant response to surface water in a global atmospheric chemistry model. This sensitivity is crucial for the return of precipitation back into the atmosphere and thus significantly impacts the representation of weather as well as air quality. The newly implemented response function reduces this process and has a better comparison with satellite observations. This yields a higher intensity of unusual warm periods and higher production of air pollutants.
We assess the representation of the plant response to surface water in a global atmospheric...
Special issue
Altmetrics
Final-revised paper
Preprint