Articles | Volume 21, issue 23
https://doi.org/10.5194/bg-21-5517-2024
https://doi.org/10.5194/bg-21-5517-2024
Research article
 | 
12 Dec 2024
Research article |  | 12 Dec 2024

On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results

Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng

Related authors

Towards resolving poor performance of mechanistic soil organic carbon models
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, Philippe Ciais, and Daniel S. Goll
EGUsphere, https://doi.org/10.5194/egusphere-2025-2545,https://doi.org/10.5194/egusphere-2025-2545, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, and Raphael A. Viscarra Rossel
SOIL, 10, 619–636, https://doi.org/10.5194/soil-10-619-2024,https://doi.org/10.5194/soil-10-619-2024, 2024
Short summary
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023,https://doi.org/10.5194/esd-14-549-2023, 2023
Short summary
Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems
Jon Cranko Page, Martin G. De Kauwe, Gab Abramowitz, Jamie Cleverly, Nina Hinko-Najera, Mark J. Hovenden, Yao Liu, Andy J. Pitman, and Kiona Ogle
Biogeosciences, 19, 1913–1932, https://doi.org/10.5194/bg-19-1913-2022,https://doi.org/10.5194/bg-19-1913-2022, 2022
Short summary
A flux tower dataset tailored for land model evaluation
Anna M. Ukkola, Gab Abramowitz, and Martin G. De Kauwe
Earth Syst. Sci. Data, 14, 449–461, https://doi.org/10.5194/essd-14-449-2022,https://doi.org/10.5194/essd-14-449-2022, 2022
Short summary

Related subject area

Biodiversity and Ecosystem Function: Terrestrial
The fungal collaboration gradient drives root trait distribution and ecosystem processes in a tropical montane forest
Mateus Dantas de Paula, Tatiana Reichert, Laynara F. Lugli, Erica McGale, Kerstin Pierick, João Paulo Darela-Filho, Liam Langan, Jürgen Homeier, Anja Rammig, and Thomas Hickler
Biogeosciences, 22, 2707–2732, https://doi.org/10.5194/bg-22-2707-2025,https://doi.org/10.5194/bg-22-2707-2025, 2025
Short summary
Measuring and modeling waterlogging tolerance to predict the future for threatened lowland ash forests
Eric J. Gustafson, Dustin R. Bronson, Marcella A. Windmuller-Campione, Robert A. Slesak, and Deahn M. Donner
Biogeosciences, 22, 2499–2515, https://doi.org/10.5194/bg-22-2499-2025,https://doi.org/10.5194/bg-22-2499-2025, 2025
Short summary
Reviews and syntheses: Current perspectives on biosphere research 2024–2025 – eight findings from ecology, sociology, and economics
Friedrich J. Bohn, Ana Bastos, Romina Martin, Anja Rammig, Niak Sian Koh, Giles B. Sioen, Bram Buscher, Louise Carver, Fabrice DeClerck, Moritz Drupp, Robert Fletcher, Matthew Forrest, Alexandros Gasparatos, Alex Godoy-Faúndez, Gregor Hagedorn, Martin C. Hänsel, Jessica Hetzer, Thomas Hickler, Cornelia B. Krug, Stasja Koot, Xiuzhen Li, Amy Luers, Shelby Matevich, H. Damon Matthews, Ina C. Meier, Mirco Migliavacca, Awaz Mohamed, Sungmin O, David Obura, Ben Orlove, Rene Orth, Laura Pereira, Markus Reichstein, Lerato Thakholi, Peter H. Verburg, and Yuki Yoshida
Biogeosciences, 22, 2425–2460, https://doi.org/10.5194/bg-22-2425-2025,https://doi.org/10.5194/bg-22-2425-2025, 2025
Short summary
Role of air–soil temperature in the leaf area index (LAI) course and role of height–diameter at breast height (DBH) in the maximum LAI during foliation of Platanus orientalis L. in an urban–rural greenway system
Melih Öztürk, Turgay Biricik, and Rıdvan Koruyan
Biogeosciences, 22, 2351–2362, https://doi.org/10.5194/bg-22-2351-2025,https://doi.org/10.5194/bg-22-2351-2025, 2025
Short summary
Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River basin
Mingjie Shi, Nate McDowell, Huilin Huang, Faria Zahura, Lingcheng Li, and Xingyuan Chen
Biogeosciences, 22, 2225–2238, https://doi.org/10.5194/bg-22-2225-2025,https://doi.org/10.5194/bg-22-2225-2025, 2025
Short summary

Cited articles

Abramowitz, G.: Towards a benchmark for land surface models, Geophys. Res. Lett., 32, L22702, https://doi.org/10.1029/2005GL024419, 2005. 
Abramowitz, G.: Towards a public, standardized, diagnostic benchmarking system for land surface models, Geosci. Model Dev., 5, 819–827, https://doi.org/10.5194/gmd-5-819-2012, 2012. 
Abramowitz, G., Pouyanné, L., and Ajami, H.: On the information content of surface meteorology for downward atmospheric long-wave radiation synthesis, Geophys. Res. Lett., 39, L04808, https://doi.org/10.1029/2011GL050726, 2012. 
Abramowitz, G., Herger, N., Gutmann, E., Hammerling, D., Knutti, R., Leduc, M., Lorenz, R., Pincus, R., and Schmidt, G. A.: ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing, Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, 2019. 
Arora, V. K., Seiler, C., Wang, L., and Kou-Giesbrecht, S.: Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations, Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, 2023. 
Download
Short summary
This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Share
Altmetrics
Final-revised paper
Preprint