Articles | Volume 15, issue 22
https://doi.org/10.5194/gmd-15-8453-2022
© Author(s) 2022. 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/gmd-15-8453-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
21 Nov 2022
Model description paper |
| 21 Nov 2022
| 21 Nov 2022
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
now at: Ecologie des Forêts Méditerranéennes (URFM),
Institut national de recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), Avignon, France
Simon Munier
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Anthony Mucia
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Clément Albergel
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
now at: European Space Agency Climate Office, ECSAT, Harwell Campus, OX11 0FD Didcot, Oxfordshire, United Kingdom
Jean-Christophe Calvet
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS,
Toulouse, France
Related authors
Arsène Druel, Julien Ruffault, Hendrik Davi, André Chanzy, Olivier Marloie, Miquel De Cáceres, Albert Olioso, Florent Mouillot, Christophe François, Kamel Soudani, and Nicolas K. Martin-StPaul
Biogeosciences, 22, 1–18, https://doi.org/10.5194/bg-22-1-2025, https://doi.org/10.5194/bg-22-1-2025, 2025
Short summary
Short summary
Accurate radiation data are essential for understanding ecosystem functions and dynamics. Traditional large-scale data lack the precision needed for complex terrain. This study introduces a new model, which accounts for sub-daily direct and diffuse radiation effects caused by terrain features, to enhance the radiation data resolution using elevation maps. Tested on a mountainous area, this method significantly improved radiation estimates, benefiting predictions of forest functions.
Didier G. Leibovici, Shaun Quegan, Edward Comyn-Platt, Garry Hayman, Maria Val Martin, Mathieu Guimberteau, Arsène Druel, Dan Zhu, and Philippe Ciais
Biogeosciences, 17, 1821–1844, https://doi.org/10.5194/bg-17-1821-2020, https://doi.org/10.5194/bg-17-1821-2020, 2020
Short summary
Short summary
Analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, may require land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from. The paper proposes a multivariate spatio-temporal data science method to understand the inherent uncertainties in four LSMs and the variations between them in Nordic areas for the net primary production.
Arsène Druel, Philippe Peylin, Gerhard Krinner, Philippe Ciais, Nicolas Viovy, Anna Peregon, Vladislav Bastrikov, Natalya Kosykh, and Nina Mironycheva-Tokareva
Geosci. Model Dev., 10, 4693–4722, https://doi.org/10.5194/gmd-10-4693-2017, https://doi.org/10.5194/gmd-10-4693-2017, 2017
Short summary
Short summary
To improve the simulation of vegetation–climate feedbacks at high latitudes, three new circumpolar vegetation types were added in the ORCHIDEE land surface model: bryophytes (mosses) and lichens, Arctic shrubs, and Arctic grasses. This article is an introduction to the modification of vegetation distribution and physical behaviour, implying for example lower productivity, roughness, and higher winter albedo or freshwater discharge in the Arctic Ocean.
D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Geosci. Model Dev., 8, 2263–2283, https://doi.org/10.5194/gmd-8-2263-2015, https://doi.org/10.5194/gmd-8-2263-2015, 2015
Short summary
Short summary
This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.
Alexis Jeantet, Jean-Pierre Vergnes, Simon Munier, and Florence Habets
EGUsphere, https://doi.org/10.5194/egusphere-2025-93, https://doi.org/10.5194/egusphere-2025-93, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
The AquiFR hydrogeological modelling plateform is forced by 36 climate projections in order to simulate future groundwater levels over France. The results show significant scatters between regional climate models and RCPs. Overall, a rise in groundwater levels, affecting most of the study area, is the dominant signal. Four storylines have been selected to to illustrate the impacts of worst-case scenarios and help decision-makers to adopt sustainable groundwater management policies.
Arsène Druel, Julien Ruffault, Hendrik Davi, André Chanzy, Olivier Marloie, Miquel De Cáceres, Albert Olioso, Florent Mouillot, Christophe François, Kamel Soudani, and Nicolas K. Martin-StPaul
Biogeosciences, 22, 1–18, https://doi.org/10.5194/bg-22-1-2025, https://doi.org/10.5194/bg-22-1-2025, 2025
Short summary
Short summary
Accurate radiation data are essential for understanding ecosystem functions and dynamics. Traditional large-scale data lack the precision needed for complex terrain. This study introduces a new model, which accounts for sub-daily direct and diffuse radiation effects caused by terrain features, to enhance the radiation data resolution using elevation maps. Tested on a mountainous area, this method significantly improved radiation estimates, benefiting predictions of forest functions.
Malak Sadki, Gaëtan Noual, Simon Munier, Vanessa Pedinotti, Kaushlendra Verma, Clément Albergel, Sylvain Biancamaria, and Alice Andral
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-328, https://doi.org/10.5194/hess-2024-328, 2024
Revised manuscript under review for HESS
Short summary
Short summary
This study explores how 20 years of remote-sensed discharge data from the ESA CCI improve large-scale hydrological models, CTRIP and MGB, through data assimilation. Using an EnKF framework across the Niger and Congo basins, it shows how assimilating denser temporal discharge data reduces biases and improves flow variability, enhancing accuracy. These findings underscore the role of long-term discharge data in refining models for climate assessments, water management, and forecasting.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-103, https://doi.org/10.5194/essd-2024-103, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three main GHG fluxes at the national level. Compared to the previous study, new satellite-based CO2 inversions were included. Additionally, an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
En Liu, Yonghua Zhu, Jean-Christophe Calvet, Haishen Lü, Bertrand Bonan, Jingyao Zheng, Qiqi Gou, Xiaoyi Wang, Zhenzhou Ding, Haiting Xu, Ying Pan, and Tingxing Chen
Hydrol. Earth Syst. Sci., 28, 2375–2400, https://doi.org/10.5194/hess-28-2375-2024, https://doi.org/10.5194/hess-28-2375-2024, 2024
Short summary
Short summary
Overestimated root zone soil moisture (RZSM) based on land surface models (LSMs) is attributed to overestimated precipitation and an underestimated ratio of transpiration to total evapotranspiration and performs better in the wet season. Underestimated SMOS L3 surface SM triggers the underestimated SMOS L4 RZSM, which performs better in the dry season due to the attenuated radiation in the wet season. LSMs should reduce and increase the frequency of wet and dry soil moisture, respectively.
Sophie Barthelemy, Bertrand Bonan, Miquel Tomas-Burguera, Gilles Grandjean, Séverine Bernardie, Jean-Philippe Naulin, Patrick Le Moigne, Aaron Boone, and Jean-Christophe Calvet
EGUsphere, https://doi.org/10.5194/egusphere-2024-1079, https://doi.org/10.5194/egusphere-2024-1079, 2024
Short summary
Short summary
A drought index is developed that quantifies drought on an annual scale for deciduous broadleaf vegetation, making it applicable to monitoring clay shrinkage damage to buildings, agriculture or forestry. It is found that significant soil moisture drought events occurred in France in 2003, 2018, 2019, 2020 and 2022. Particularly high index values are observed throughout the country in 2022. It is also found that droughts will become more severe in the future.
Sophie Barthelemy, Bertrand Bonan, Jean-Christophe Calvet, Gilles Grandjean, David Moncoulon, Dorothée Kapsambelis, and Séverine Bernardie
Nat. Hazards Earth Syst. Sci., 24, 999–1016, https://doi.org/10.5194/nhess-24-999-2024, https://doi.org/10.5194/nhess-24-999-2024, 2024
Short summary
Short summary
This work presents a drought index specifically adapted to subsidence, a seasonal phenomenon of soil shrinkage that occurs frequently in France and damages buildings. The index is computed from land surface model simulations and evaluated by a rank correlation test with insurance data. With its optimal configuration, the index is able to identify years of both zero and significant loss.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
Short summary
Short summary
We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Julia Pfeffer, Anny Cazenave, Alejandro Blazquez, Bertrand Decharme, Simon Munier, and Anne Barnoud
Hydrol. Earth Syst. Sci., 27, 3743–3768, https://doi.org/10.5194/hess-27-3743-2023, https://doi.org/10.5194/hess-27-3743-2023, 2023
Short summary
Short summary
The GRACE (Gravity Recovery And Climate Experiment) satellite mission enabled the quantification of water mass redistributions from 2002 to 2017. The analysis of GRACE satellite data shows here that slow changes in terrestrial water storage occurring over a few years to a decade are severely underestimated by global hydrological models. Several sources of errors may explain such biases, likely including the inaccurate representation of groundwater storage changes.
Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023, https://doi.org/10.5194/hess-27-3375-2023, 2023
Short summary
Short summary
We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.
Remi Madelon, Nemesio J. Rodríguez-Fernández, Hassan Bazzi, Nicolas Baghdadi, Clement Albergel, Wouter Dorigo, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
Short summary
Short summary
We present an approach to estimate soil moisture (SM) at 1 km resolution using Sentinel-1 and Sentinel-3 satellites. The estimates were compared to other high-resolution (HR) datasets over Europe, northern Africa, Australia, and North America, showing good agreement. However, the discrepancies between the different HR datasets and their lower performances compared with in situ measurements and coarse-resolution datasets show the remaining challenges for large-scale HR SM mapping.
En Liu, Yonghua Zhu, Jean-christophe Calvet, Haishen Lü, Bertrand Bonan, Jingyao Zheng, Qiqi Gou, Xiaoyi Wang, Zhenzhou Ding, Haiting Xu, Ying Pan, and Tingxing Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-33, https://doi.org/10.5194/hess-2023-33, 2023
Manuscript not accepted for further review
Short summary
Short summary
Among the 8 considered products, GLDAS_CLSM product performs best. All RZSM products overestimate the in situ measurements which attributes to a wet bias of air temperature, precipitation amount and frequency except the underestimation of SMOS L4 RZSM related to the underestimation of SMOS L3 SSM. The higher R between SMPA L4 and MERRA-2 was attributed to they both use CLSM and meteorological forcing from GEOS-5 where precipitation was corrected with CPCU precipitation product.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
Short summary
Short summary
Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
Short summary
Short summary
Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581, https://doi.org/10.5194/bg-19-2557-2022, https://doi.org/10.5194/bg-19-2557-2022, 2022
Short summary
Short summary
For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Simon Munier and Bertrand Decharme
Earth Syst. Sci. Data, 14, 2239–2258, https://doi.org/10.5194/essd-14-2239-2022, https://doi.org/10.5194/essd-14-2239-2022, 2022
Short summary
Short summary
This paper presents a new global-scale river network at 1/12°, generated automatically and assessed over the 69 largest basins of the world. A set of hydro-geomorphological parameters are derived at the same spatial resolution, including a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The dataset may be useful for hydrology modelling or climate studies.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
Short summary
Short summary
In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
Short summary
Short summary
The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Judith Eeckman, Hélène Roux, Audrey Douinot, Bertrand Bonan, and Clément Albergel
Hydrol. Earth Syst. Sci., 25, 1425–1446, https://doi.org/10.5194/hess-25-1425-2021, https://doi.org/10.5194/hess-25-1425-2021, 2021
Short summary
Short summary
The risk of flash flood is of growing importance for populations, particularly in the Mediterranean area in the context of a changing climate. The representation of soil processes in models is a key factor for flash flood simulation. The importance of the various methods for soil moisture estimation are highlighted in this work. Local measurements from the field as well as data derived from satellite imagery can be used to assess the performance of model outputs.
Bertrand Cluzet, Matthieu Lafaysse, Emmanuel Cosme, Clément Albergel, Louis-François Meunier, and Marie Dumont
Geosci. Model Dev., 14, 1595–1614, https://doi.org/10.5194/gmd-14-1595-2021, https://doi.org/10.5194/gmd-14-1595-2021, 2021
Short summary
Short summary
In the mountains, the combination of large model error and observation sparseness is a challenge for data assimilation. Here, we develop two variants of the particle filter (PF) in order to propagate the information content of observations into unobserved areas. By adjusting observation errors or exploiting background correlation patterns, we demonstrate the potential for partial observations of snow depth and surface reflectance to improve model accuracy with the PF in an idealised setting.
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, and Delphine J. Leroux
Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021, https://doi.org/10.5194/gmd-14-1309-2021, 2021
Short summary
Short summary
Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services such as freshwater supply. Despite the impact of lakes on the water cycle, they are generally not considered in global hydrological studies. Based on a model called MLake, we assessed both the importance of lakes in simulating river flows at global scale and the value of their level variations for water resource management.
Miguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F. Trigo, Sofia L. Ermida, João P. A. Martins, and Emanuel Dutra
Geosci. Model Dev., 13, 3975–3993, https://doi.org/10.5194/gmd-13-3975-2020, https://doi.org/10.5194/gmd-13-3975-2020, 2020
Short summary
Short summary
We used earth observations to evaluate and improve the representation of land surface temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX land surface models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction in daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
Short summary
Short summary
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) land surface model (LSM). This study demonstrates that LDAS-Monde is able to detect, monitor and forecast the impact of extreme weather on land surface states.
Yongjun Zheng, Clément Albergel, Simon Munier, Bertrand Bonan, and Jean-Christophe Calvet
Geosci. Model Dev., 13, 3607–3625, https://doi.org/10.5194/gmd-13-3607-2020, https://doi.org/10.5194/gmd-13-3607-2020, 2020
Short summary
Short summary
This study proposes a sophisticated dynamically running job scheme as well as an innovative parallel IO algorithm to reduce the time to solution of an offline framework for high-dimensional ensemble Kalman filters. The offline and online modes of ensemble Kalman filters are built to comprehensively assess their time to solution efficiencies. The offline mode is substantially faster than the online mode in terms of time to solution, especially for large-scale assimilation problems.
Victor Pellet, Filipe Aires, Fabrice Papa, Simon Munier, and Bertrand Decharme
Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020, https://doi.org/10.5194/hess-24-3033-2020, 2020
Short summary
Short summary
The water mass variation at and below the land surface is a major component of the water cycle that was first estimated using GRACE observations (2002–2017). Our analysis shows the advantages of the use of satellite observation for precipitation and evapotranspiration along with river discharge measurement to perform an indirect and coherent reconstruction of this water component estimate over longer time periods.
Didier G. Leibovici, Shaun Quegan, Edward Comyn-Platt, Garry Hayman, Maria Val Martin, Mathieu Guimberteau, Arsène Druel, Dan Zhu, and Philippe Ciais
Biogeosciences, 17, 1821–1844, https://doi.org/10.5194/bg-17-1821-2020, https://doi.org/10.5194/bg-17-1821-2020, 2020
Short summary
Short summary
Analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, may require land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from. The paper proposes a multivariate spatio-temporal data science method to understand the inherent uncertainties in four LSMs and the variations between them in Nordic areas for the net primary production.
Jean-Pierre Vergnes, Nicolas Roux, Florence Habets, Philippe Ackerer, Nadia Amraoui, François Besson, Yvan Caballero, Quentin Courtois, Jean-Raynald de Dreuzy, Pierre Etchevers, Nicolas Gallois, Delphine J. Leroux, Laurent Longuevergne, Patrick Le Moigne, Thierry Morel, Simon Munier, Fabienne Regimbeau, Dominique Thiéry, and Pascal Viennot
Hydrol. Earth Syst. Sci., 24, 633–654, https://doi.org/10.5194/hess-24-633-2020, https://doi.org/10.5194/hess-24-633-2020, 2020
Short summary
Short summary
The AquiFR hydrogeological modelling platform aims to provide
short-term-to-seasonal hydrological forecasts over France for daily water management and long-term simulations for climate impact studies. The results described in this study confirm the feasibility of gathering independent groundwater models into the same numerical tool. This new tool encourages the development of groundwater modelling, and it has the potential to be valuable for many operational and research applications.
Bertrand Bonan, Clément Albergel, Yongjun Zheng, Alina Lavinia Barbu, David Fairbairn, Simon Munier, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, https://doi.org/10.5194/hess-24-325-2020, 2020
Short summary
Short summary
This paper introduces an ensemble square root filter (EnSRF), a deterministic ensemble Kalman filter, for jointly assimilating observations of the surface soil moisture and leaf area index in the Land Data Assimilation System LDAS-Monde. LDAS-Monde constrains the Interaction between Soil, Biosphere and Atmosphere (ISBA) land surface model to improve the reanalysis of land surface variables. EnSRF is compared with the simplified extended Kalman filter over the European Mediterranean region.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
Short summary
Short summary
This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
Sibo Zhang, Catherine Meurey, and Jean-Christophe Calvet
Atmos. Chem. Phys., 19, 5005–5020, https://doi.org/10.5194/acp-19-5005-2019, https://doi.org/10.5194/acp-19-5005-2019, 2019
Short summary
Short summary
In situ rain temperature measurements are rare. Soil moisture and soil temperature observations in southern France are used to assess the cooling effects on soils of rainfall events. The rainwater temperature is estimated using observed changes of topsoil volumetric soil moisture and soil temperature in response to the rainfall event. The obtained rain temperature estimates are generally lower than the ambient air temperatures, wet-bulb temperatures, and topsoil temperatures.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
Short summary
Short summary
This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Clement Albergel, Emanuel Dutra, Simon Munier, Jean-Christophe Calvet, Joaquin Munoz-Sabater, Patricia de Rosnay, and Gianpaolo Balsamo
Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, https://doi.org/10.5194/hess-22-3515-2018, 2018
Short summary
Short summary
ECMWF recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 (2010–2016). ERA-5 has important changes relative to ERA-Interim including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis. One of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model.
Emiliano Gelati, Bertrand Decharme, Jean-Christophe Calvet, Marie Minvielle, Jan Polcher, David Fairbairn, and Graham P. Weedon
Hydrol. Earth Syst. Sci., 22, 2091–2115, https://doi.org/10.5194/hess-22-2091-2018, https://doi.org/10.5194/hess-22-2091-2018, 2018
Short summary
Short summary
We compared land surface model simulations forced by several meteorological datasets with observations over the Euro-Mediterranean area, for the 1979–2012 period. Precipitation was the most uncertain forcing variable. The impacts of forcing uncertainty were larger on the mean and standard deviation rather than the timing, shape and inter-annual variability of simulated discharge. Simulated leaf area index and surface soil moisture were relatively insensitive to these uncertainties.
Sibo Zhang, Jean-Christophe Calvet, José Darrozes, Nicolas Roussel, Frédéric Frappart, and Gilles Bouhours
Hydrol. Earth Syst. Sci., 22, 1931–1946, https://doi.org/10.5194/hess-22-1931-2018, https://doi.org/10.5194/hess-22-1931-2018, 2018
Short summary
Short summary
Surface soil moisture was retrieved from a grassland site in southwestern France using the GNSS-IR technique. In order to efficiently limit the impact of perturbing vegetation effects, the grass growth period and the senescence period are treated separately. While the vegetation biomass effect can be corrected for, the litter water interception influences the observations and cannot be easily accounted for.
Arsène Druel, Philippe Peylin, Gerhard Krinner, Philippe Ciais, Nicolas Viovy, Anna Peregon, Vladislav Bastrikov, Natalya Kosykh, and Nina Mironycheva-Tokareva
Geosci. Model Dev., 10, 4693–4722, https://doi.org/10.5194/gmd-10-4693-2017, https://doi.org/10.5194/gmd-10-4693-2017, 2017
Short summary
Short summary
To improve the simulation of vegetation–climate feedbacks at high latitudes, three new circumpolar vegetation types were added in the ORCHIDEE land surface model: bryophytes (mosses) and lichens, Arctic shrubs, and Arctic grasses. This article is an introduction to the modification of vegetation distribution and physical behaviour, implying for example lower productivity, roughness, and higher winter albedo or freshwater discharge in the Arctic Ocean.
Clément Albergel, Simon Munier, Delphine Jennifer Leroux, Hélène Dewaele, David Fairbairn, Alina Lavinia Barbu, Emiliano Gelati, Wouter Dorigo, Stéphanie Faroux, Catherine Meurey, Patrick Le Moigne, Bertrand Decharme, Jean-Francois Mahfouf, and Jean-Christophe Calvet
Geosci. Model Dev., 10, 3889–3912, https://doi.org/10.5194/gmd-10-3889-2017, https://doi.org/10.5194/gmd-10-3889-2017, 2017
Short summary
Short summary
LDAS-Monde, a global land data assimilation system, is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. It is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the ISBA land surface model coupled with the CTRIP continental hydrological system. Assimilation of SSM and LAI leads to a better representation of evapotranspiration and gross primary production.
Nemesio J. Rodríguez-Fernández, Joaquin Muñoz Sabater, Philippe Richaume, Patricia de Rosnay, Yann H. Kerr, Clement Albergel, Matthias Drusch, and Susanne Mecklenburg
Hydrol. Earth Syst. Sci., 21, 5201–5216, https://doi.org/10.5194/hess-21-5201-2017, https://doi.org/10.5194/hess-21-5201-2017, 2017
Short summary
Short summary
The new SMOS satellite near-real-time (NRT) soil moisture (SM) product based on a neural network is presented. The NRT SM product has been evaluated with respect to the SMOS Level 2 product and against a large number of in situ measurements showing performances similar to those of the Level 2 product but it is available in less than 3.5 h after sensing. The new product is distributed by the European Space Agency and the European Organisation for the Exploitation of Meteorological Satellites.
Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4861–4878, https://doi.org/10.5194/hess-21-4861-2017, https://doi.org/10.5194/hess-21-4861-2017, 2017
Short summary
Short summary
Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.
Sibo Zhang, Nicolas Roussel, Karen Boniface, Minh Cuong Ha, Frédéric Frappart, José Darrozes, Frédéric Baup, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4767–4784, https://doi.org/10.5194/hess-21-4767-2017, https://doi.org/10.5194/hess-21-4767-2017, 2017
Short summary
Short summary
GNSS SNR data were obtained from an intensively cultivated wheat field in southwestern France. The data were used to retrieve soil moisture and vegetation characteristics during the growing period of wheat. Vegetation growth broke up the constant height assumption used in soil moisture retrieval algorithms. Soil moisture could not be retrieved after wheat tillering. A new algorithm based on a wavelet analysis was implemented and used to retrieve vegetation height.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
Short summary
Short summary
This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Jean-Christophe Calvet, Noureddine Fritz, Christine Berne, Bruno Piguet, William Maurel, and Catherine Meurey
SOIL, 2, 615–629, https://doi.org/10.5194/soil-2-615-2016, https://doi.org/10.5194/soil-2-615-2016, 2016
Short summary
Short summary
Soil thermal conductivity in wet conditions can be retrieved together with the soil quartz content using a reverse modelling technique based on sub-hourly soil temperature observations at three depths below the soil surface.
A pedotransfer function is proposed for quartz, for the considered region in France.
Gravels have a major impact on soil thermal conductivity, and omitting the soil organic matter information tends to enhance this impact.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
Short summary
Short summary
This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
D. Fairbairn, A. L. Barbu, J.-F. Mahfouf, J.-C. Calvet, and E. Gelati
Hydrol. Earth Syst. Sci., 19, 4811–4830, https://doi.org/10.5194/hess-19-4811-2015, https://doi.org/10.5194/hess-19-4811-2015, 2015
Short summary
Short summary
The ensemble Kalman filter (EnKF) and simplified extended Kalman filter (SEKF) root-zone soil moisture analyses are compared when assimilating in situ surface observations. In the synthetic experiments, the EnKF performs best because it can stochastically capture the errors in the precipitation. The two methods perform similarly in the real experiments. During the summer period, both methods perform poorly as a result of nonlinearities in the land surface model.
S. Garrigues, A. Olioso, D. Carrer, B. Decharme, J.-C. Calvet, E. Martin, S. Moulin, and O. Marloie
Geosci. Model Dev., 8, 3033–3053, https://doi.org/10.5194/gmd-8-3033-2015, https://doi.org/10.5194/gmd-8-3033-2015, 2015
Short summary
Short summary
This paper investigates the impacts of uncertainties in the climate, the vegetation dynamic, the soil properties and the cropland management on the simulation of evapotranspiration from the ISBA-A-gs land surface model over a 12-year Mediterranean crop succession. It mainly shows that errors in the soil parameters and the lack of irrigation in the simulation have the largest influence on evapotranspiration compared to the uncertainties in the climate and the vegetation dynamic.
D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Geosci. Model Dev., 8, 2263–2283, https://doi.org/10.5194/gmd-8-2263-2015, https://doi.org/10.5194/gmd-8-2263-2015, 2015
Short summary
Short summary
This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.
S. Garrigues, A. Olioso, J. C. Calvet, E. Martin, S. Lafont, S. Moulin, A. Chanzy, O. Marloie, S. Buis, V. Desfonds, N. Bertrand, and D. Renard
Hydrol. Earth Syst. Sci., 19, 3109–3131, https://doi.org/10.5194/hess-19-3109-2015, https://doi.org/10.5194/hess-19-3109-2015, 2015
Short summary
Short summary
Land surface model simulations of evapotranspiration are assessed over a 12-year Mediterranean crop succession. Evapotranspiration mainly results from soil evaporation when it is simulated over a Mediterranean crop succession. This leads to a high sensitivity to the soil parameters. Errors on soil hydraulic properties can lead to a large bias in cumulative evapotranspiration over a long period of time. Accounting for uncertainties in soil properties is essential for land surface modelling.
G. Balsamo, C. Albergel, A. Beljaars, S. Boussetta, E. Brun, H. Cloke, D. Dee, E. Dutra, J. Muñoz-Sabater, F. Pappenberger, P. de Rosnay, T. Stockdale, and F. Vitart
Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, https://doi.org/10.5194/hess-19-389-2015, 2015
Short summary
Short summary
ERA-Interim/Land is a global land surface reanalysis covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim and a precipitation bias correction based on GPCP. A selection of verification results show the added value in representing the terrestrial water cycle and its main land surface storages and fluxes.
N. Canal, J.-C. Calvet, B. Decharme, D. Carrer, S. Lafont, and G. Pigeon
Hydrol. Earth Syst. Sci., 18, 4979–4999, https://doi.org/10.5194/hess-18-4979-2014, https://doi.org/10.5194/hess-18-4979-2014, 2014
Short summary
Short summary
Regional French agricultural yield statistics are used to benchmark root water uptake representations in the ISBA-A-gs model. Key model parameters governing the inter-annual variability of the simulated biomass are retrieved. A complex multi-layer soil hydrology model does not outperform a simple bulk root-zone reservoir approach. This could be explained by missing processes/information in the model such as hydraulic redistribution and detailed soil properties.
E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, R. Fisher, B. Christoffersen, J. C. Calvet, A. C. L. da Costa, L. V. Ferreira, and P. Meir
Geosci. Model Dev., 7, 2933–2950, https://doi.org/10.5194/gmd-7-2933-2014, https://doi.org/10.5194/gmd-7-2933-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
C. Szczypta, J.-C. Calvet, F. Maignan, W. Dorigo, F. Baret, and P. Ciais
Geosci. Model Dev., 7, 931–946, https://doi.org/10.5194/gmd-7-931-2014, https://doi.org/10.5194/gmd-7-931-2014, 2014
M. Parrens, J.-F. Mahfouf, A. L. Barbu, and J.-C. Calvet
Hydrol. Earth Syst. Sci., 18, 673–689, https://doi.org/10.5194/hess-18-673-2014, https://doi.org/10.5194/hess-18-673-2014, 2014
A. L. Barbu, J.-C. Calvet, J.-F. Mahfouf, and S. Lafont
Hydrol. Earth Syst. Sci., 18, 173–192, https://doi.org/10.5194/hess-18-173-2014, https://doi.org/10.5194/hess-18-173-2014, 2014
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
R. Amri, M. Zribi, Z. Lili-Chabaane, C. Szczypta, J. C. Calvet, and G. Boulet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-8117-2013, https://doi.org/10.5194/hessd-10-8117-2013, 2013
Revised manuscript not accepted
Related subject area
Biogeosciences
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
Parameterisation toolbox for physical-biogeochemical model compatible with FABM. Case study: the coupled 1D GOTM-ECOSMO E2E for the Sylt-Romo Bight, North Sea
China Wildfire Emission (ChinaWED v1) for the period 2012–2022
H2MV (v1.0): Global Physically-Constrained Deep Learning Water Cycle Model with Vegetation
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Including the Phosphorus cycle into the LPJ-GUESS Dynamic Global Vegetation Model (v4.1, r10994) – Global patterns and temporal trends of N and P primary production limitation
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Alquimia v1.0: A generic interface to biogeochemical codes – A tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Sources of Uncertainty in the Global Fire Model SPITFIRE: Development of LPJmL-SPITFIRE1.9 and Directions for Future Improvements
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
A comprehensive land surface vegetation model for multi-stream data assimilation, D&B v1.0
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Process-based Modeling of Solar-induced Chlorophyll Fluorescence with VISIT-SIF version 1.0
The unicellular NUM v.0.91: A trait-based plankton model evaluated in two contrasting biogeographic provinces
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
Short summary
Short summary
Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
Short summary
Short summary
Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-223, https://doi.org/10.5194/gmd-2024-223, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions have changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
Short summary
Short summary
The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
Short summary
Short summary
The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
Short summary
Short summary
Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
EGUsphere, https://doi.org/10.5194/egusphere-2024-2710, https://doi.org/10.5194/egusphere-2024-2710, 2024
Short summary
Short summary
Parameterisation is key in modeling to reproduce observations well but is often done manually. This study presents a Particle Swarm Optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, thus providing different insights into ecosystem dynamics, (2) optimized model complexity.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-170, https://doi.org/10.5194/gmd-2024-170, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Wildfires release large amounts of greenhouse gases, contributing to global warming. We developed a new model that provides near-real-time estimates of wildfire emissions in China. Our model improves the accuracy of burned area measurements and incorporates advanced data in fuel loads and emission factors. We found that most emissions come from agricultural fires, while emissions from forests and grasslands are decreasing. This model will help reduce the environmental impacts of wildfires.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
EGUsphere, https://doi.org/10.5194/egusphere-2024-2044, https://doi.org/10.5194/egusphere-2024-2044, 2024
Short summary
Short summary
We use an innovative approach to study the Earth's water cycle by blending advanced computer learning techniques with a traditional water cycle model. We developed a model that learns from meteorological data, with a special focus on understanding how vegetation influences water movement. Our model closely aligns with real-world observations, yet there are areas that need improvement. This study opens up new possibilities to better understand the water cycle and its interactions with vegetation.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-2592, https://doi.org/10.5194/egusphere-2024-2592, 2024
Short summary
Short summary
Our study maps global nitrogen (N) and phosphorus (P) availability and how they’ve changed from 1901 to 2018. We found that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation has increased, especially in the tropics, while N limitation has decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Sergi Molins, Benjamin Andre, Jeffrey Johnson, Glenn Hammond, Benjamin Sulman, Konstantin Lipnikov, Marcus Day, James Beisman, Daniil Svyatsky, Hang Deng, Peter Lichtner, Carl Steefel, and David Moulton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-108, https://doi.org/10.5194/gmd-2024-108, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
EGUsphere, https://doi.org/10.5194/egusphere-2024-1914, https://doi.org/10.5194/egusphere-2024-1914, 2024
Short summary
Short summary
Under climate change, the conditions for wildfires to form are becoming more frequent in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a crucial platform for future developments.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
Short summary
Short summary
When it comes to climate change, the land surfaces are where the vast majority of impacts happen. The task of monitoring those across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us see what changes on our lands.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
EGUsphere, https://doi.org/10.5194/egusphere-2024-1542, https://doi.org/10.5194/egusphere-2024-1542, 2024
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical process-based model developed to represent the global SIF observed by GOSAT. Our model simulation reproduced the global distribution and seasonal variations of GOSAT SIF. The model can be utilized to improve photosynthetic process through the combination of biogeochemical modeling and GOSAT SIF.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-53, https://doi.org/10.5194/gmd-2024-53, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We describe and test the size-based NUM model, that define organisms by a single set of parameters, on planktonic unicellular ecosystems in a eutrophic and an oligotrophic site. Results show both sites can be modelled with similar parameters, and a robust performance over a wide range of parameters. The study show that the NUM model is useful for non-experts and applicable for modelling domains with limited ecosystem data. It holds promise for evolutionary scenarios and deep-time climate models.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1360, https://doi.org/10.5194/egusphere-2024-1360, 2024
Short summary
Short summary
Our research uses deep learning to predict organic carbon stocks in ocean sediments, crucial for understanding their role in the global carbon cycle. By analyzing over 22,000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate the top 10 cm of ocean sediments hold about 171 petagrams of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Cited articles
Adegoke, J. O., Pielke, R. A., Eastman, J., Mahmood, R., and Hubbard, K. G.:
Impact of Irrigation on Midsummer Surface Fluxes and Temperature under Dry
Synoptic Conditions: A Regional Atmospheric Model Study of the U.S. High
Plains, Mon. Weather Rev., 131, 556–564,
https://doi.org/10.1175/1520-0493(2003)131<0556:IOIOMS>2.0.CO;2, 2003.
Albergel, C., Dutra, E., Bonan, B., Zheng, Y., Munier, S., Balsamo, G., de Rosnay, P., Munoz-Sabater, J., and Calvet, J.-C.: Monitoring and forecasting the impact of the 2018 summer heatwave on vegetation, Remote Sens., 11, 520, https://doi.org/10.3390/rs11050520, 2019.
Al-Yaari, A., Ducharne, A., Tafasca, S., Mizuochi, H., and Cheruy, F.: Influence
of irrigation on the bias between ORCHIDEE and FLUXCOM evapotranspiration
products, 2021 IEEE International Geoscience and Remote Sensing Symposium
IGARSS, 6552–6555, https://doi.org/10.1109/IGARSS47720.2021.9554734, 2021.
AQUASTAT and FAO: Country Fact Sheet, United States of America, http://www.fao.org/nr/water/aquastat/data/cf/readPdf.html?f=USA-CF_eng.pdf (last access: 15 November 2022), 2019.
Baret, F., Weiss, M., Lacaze, R., Camacho, F., Makhmara, H., Pacholcyzk, P.,
and Smets, B.: GEOV1: LAI and FAPAR essential climate variables and FCOVER
global time series capitalizing over existing products. Part1: Principles of
development and production, Remote Sens. Environ., 137, 299–309,
https://doi.org/10.1016/j.rse.2012.12.027, 2013.
Beck, H. E., Pan, M., Roy, T., Weedon, G. P., Pappenberger, F., van Dijk, A. I. J. M., Huffman, G. J., Adler, R. F., and Wood, E. F.: Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, 2019.
Biemans, H., Haddeland, I., Kabat, P., Ludwig, F., Hutjes, R. W. A., Heinke,
J., von Bloh, W., and Gerten, D.: Impact of reservoirs on river discharge and
irrigation water supply during the 20th century, Water Resour. Res., 47, W03509,
https://doi.org/10.1029/2009WR008929, 2011.
Boedhram, N., Arkebauer, T. J., and Batchelor, W. D.: Season-long
characterization of vertical distribution of leaf area in corn, Agron. J.,
93, 1235–1242, https://doi.org/10.2134/agronj2001.1235, 2001.
Bonan, B., Albergel, C., Zheng, Y., Barbu, A. L., Fairbairn, D., Munier, S., and Calvet, J.-C.: An ensemble square root filter for the joint assimilation of surface soil moisture and leaf area index within the Land Data Assimilation System LDAS-Monde: application over the Euro-Mediterranean region, Hydrol. Earth Syst. Sci., 24, 325–347, https://doi.org/10.5194/hess-24-325-2020, 2020.
Bonnemort, C., Bouthier, A., Deumier, J.-M., and Specty, R.: Conduire
l'irrigation avec Irritel ; intérêts et limites, La
Météorologie, 14, 36–43, https://doi.org/10.4267/2042/51182, 1996.
Boone, A., Bellvert, J., Best, M., Brooke, J., Canut-Rocafort, G., Cuxart, J.,
Hartogensis, O., Le Moigne, P., Miró, J. R., Polcher, J., Price, J., Quintana
Seguí, P., and Wooster, M.: Updates on the international Land Surface
Interactions with the Atmosphere over the Iberian Semi-Arid Environment
(LIAISE) Field Campaign, GEWEX News, 31, 16–21, 2021.
Bruinsma, J.: The resource outlook to 2050: By how much do land, water use and crop yields need to Increase by 2050?, FAO Expert meeting on How to Feed the World in 2050, 24–26 June 2009, Rome, Italy, https://www.fsnnetwork.org/sites/default/files/the_resource_outlook_to_2050by_how_much_do_land_water_and_crop_yields_need_to_increase_by_2050_.pdf (last access: November 2022), 2009.
Calvet, J.-C. and Champeaux J.-L.: L'apport de la télédétection
spatiale à la modélisation des surfaces continentales, La
Météorologie, 108, 52–58,
https://doi.org/10.37053/lameteorologie-2020-0016, 2020.
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, Agric. For. Meteorol.,
92, 73–95, https://doi.org/10.1016/S0168-1923(98)00091-4, 1998.
Calvet, J.-C., Gibelin, A.-L., Roujean, J.-L., Martin, E., Le Moigne, P., Douville, H., and Noilhan, J.: Past and future scenarios of the effect of carbon dioxide on plant growth and transpiration for three vegetation types of southwestern France, Atmos. Chem. Phys., 8, 397–406, https://doi.org/10.5194/acp-8-397-2008, 2008.
Carrillo-Guerrero, Y., Glenn, E. P., and Hinojosa-Huerta, O.: Water budget
for agricultural and aquatic ecosystems in the delta of the Colorado River,
Mexico: Implications for obtaining water for the environment, Ecol. Eng.,
59, 41–51, https://doi.org/10.1016/j.ecoleng.2013.04.047, 2013.
Chen, L.: Impacts of climate change on wind resources over North America
based on NA-CORDEX, Renewable Energy, 153, 1428–1438,
https://doi.org/10.1016/j.renene.2020.02.090, 2020.
Chukalla, A. D., Krol, M. S., and Hoekstra, A. Y.: Green and blue water footprint reduction in irrigated agriculture: effect of irrigation techniques, irrigation strategies and mulching, Hydrol. Earth Syst. Sci., 19, 4877–4891, https://doi.org/10.5194/hess-19-4877-2015, 2015.
Colaizzi, P. D., Gowda, P. H., Marek, T. H., and Porter, D. O.: Irrigation in
the Texas High Plains: a brief history and potential reductions in demand,
Irrig. Drain., 58, 257–274, https://doi.org/10.1002/ird.418, 2009.
Copernicus: CGLS LAI, Copernicus, Copernicus [data set], https://land.copernicus.vgt.vito.be/PDF/portal/Application.html#Browse;Root=512260;Collection=1000083;Time=NORMAL,NORMAL,-1,,,-1,, (last
access: 15 November 2022), 2020.
Copernicus: CGLS hourly LST, Copernicus, Copernicus [data set], https://land.copernicus.vgt.vito.be/PDF/portal/Application.html#Browse;Root=520752;Collection=1000300;Time=NORMAL,NORMAL,-1,,,-1,, (last access: 15 November 2022), 2019.
CNRM: SURFEX code, CNRM, http://www.umr-cnrm.fr/surfex/data/OPEN-SURFEX/open_surfex_v8_1_20210914.tar.gz (last access: 15 November 2022), 2016.
DeAngelis, A., Dominguez, F., Fan, Y., Robock, A., Kustu, M. D., and
Robinson, D.: Evidence of enhanced precipitation due to irrigation over the
Great Plains of the United States, J. Geophys. Res., 115, D15115,
https://doi.org/10.1029/2010JD013892, 2010.
Decharme, B., Delire, C., Minvielle, M., Colin, J., Vergnes, J., Alias, A.,
Saint-Martin, D., Séférian, R., Sénési, S., and Voldoire, A.:
Recent Changes in the ISBA-CTRIP Land Surface System for Use in the CNRM-CM6
Climate Model and in Global Off-Line Hydrological Applications, J. Adv.
Model. Earth Syst., 11, 1207–1252, https://doi.org/10.1029/2018MS001545,
2019.
Delire, C., Séférian R., Decharme B., Alkama R., Calvet J.-C.,
Carrer D., Gibelin A.-L., Joetzjer E., Morel X., Rocher M., and Tzanos, D.:
The global land carbon cycle simulated with ISBA-CTRIP: impro-vements over
the last decade, J. Adv. Model. Earth Sy., 12, e2019MS001886,
https://doi.org/10.1029/2019MS001886, 2020.
de Vrese, P., Hagemann, S., and Claussen, M.: Asian irrigation, African rain:
Remote impacts of irrigation, Geophys. Res. Lett., 43, 3737–3745,
https://doi.org/10.1002/2016GL068146, 2016.
Döll, P., Fiedler, K., and Zhang, J.: Global-scale analysis of river flow alterations due to water withdrawals and reservoirs, Hydrol. Earth Syst. Sci., 13, 2413–2432, https://doi.org/10.5194/hess-13-2413-2009, 2009.
Döll, P., Hoffmann-Dobrev, H., Portmann, F. T., Siebert, S., Eicker, A.,
Rodell, M., Strassberg, G., and Scanlon, B. R.: Impact of water withdrawals
from groundwater and surface water on continental water storage variations,
J. Geodyn., 59–60, 143–156, https://doi.org/10.1016/j.jog.2011.05.001,
2012.
Douglas, E. M., Niyogi, D., Frolking, S., Yeluripati, J. B., Pielke, R. A.,
Niyogi, N., Vörösmarty, C. J., and Mohanty, U. C.: Changes in
moisture and energy fluxes due to agricultural land use and irrigation in
the Indian Monsoon Belt, Geophys. Res. Lett., 33, L14403,
https://doi.org/10.1029/2006GL026550, 2006.
Druel, A.: ArseneD/OPEN_SURFEX_V81_IRR: SURFEX_v8.1_IRR_v1.0 (SURFEX_v8.1_IRR_v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.5718063, 2021.
Druel, A.: IrrigationMapV0, initial files and scripts to reproduce the simulation of Druel et al., 2022, Zenodo [data set], https://doi.org/10.5281/zenodo.7221291, 2022.
Evans, R. G. and Sadler, E. J.: Methods and technologies to improve efficiency of water use, Water Resour. Res., 44, W00E04, https://doi.org/10.1029/2007WR006200, 2008.
FAO: Food and Agriculture Organization of the United Nations: Water
withdrawal and pressure on water resources, http://www.fao.org/nr/water/aquastat/infographics/Withdrawal_eng.pdf (last access: 15 November 2022), 2014.
Felfelani, F., Lawrence, D. M., and Pokhrel, Y.: Representing intercell
lateral groundwater flow and aquifer pumping in the community land model,
Water Resour. Res., 56, e2020WR027531,
https://doi.org/10.1029/2020WR027531, 2020.
Field, C. B., Barros, V. R., Dokken, D. J., Mach, K. J. and Mastrandrea, M.
D. (Eds.): Climate Change 2014 Impacts, Adaptation, and Vulnerability:
Working Group II Contribution to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, Cambridge University Press,
Cambridge, 2014.
Fischer, C., Montmerle, T., Berre, L., Auger, L., and Ştefănescu, S.
E.: An overview of the variational assimilation in the ALADIN/France
numerical weather-prediction system, Q. J. Roy. Meteor. Soc., 131,
3477–3492, https://doi.org/10.1256/qj.05.115, 2005.
FluxCom: Carbon fluxes, FluxCom [data set], https://www.fluxcom.org/, last access: 15 November 2022.
Fraiture, C. de, Wichelns, D., Rockström, J., Kemp-Benedict, E.,
Eriyagama, N., Gordon, L. J., Hanjra, M. A., Hoogeveen, J., Huber-Lee, A.,
and Karlberg, L.: Looking ahead to 2050: scenarios of alternative investment
approaches, in: Water for food, water for life: a
Comprehensive Assessment of Water Management in Agriculture, edited by: Molden, D.,
International Water Management Institute (IWMI), London, UK, Earthscan,
Colombo, Sri Lanka, 91–145,
https://hdl.handle.net/10568/36869 (last access: 15 November 2022.), 2007.
Freitas, S. C., Trigo, I. F., Macedo, J., Barroso, C., Silva, R., and
Perdigão, R.: Land surface temperature from multiple geostationary
satellites, Int. J. Remote Sens., 34, 3051–3068,
https://doi.org/10.1080/01431161.2012.716925, 2013.
Gibelin, A.-L., Calvet, J.-C., Roujean, J.-L., Jarlan, L., and Los, S. O.:
Ability of the land surface model ISBA-A-gs to simulate leaf area index at
the global scale: Comparison with satellites products, J. Geophys. Res.,
111, D18102, https://doi.org/10.1029/2005JD006691, 2006.
Grafton, R. Q., Williams, J., Perry, C. J., Molle, F., Ringler, C., Steduto,
P., Udall, B., Wheeler, S. A., Wang, Y., Garrick, D., and Allen, R. G.: The
paradox of irrigation efficiency, Science, 361, 748–750,
https://doi.org/10.1126/science.aat9314, 2018.
Haddeland, I., Skaugen, T., and Lettenmaier, D. P.: Anthropogenic impacts on
continental surface water fluxes, Geophys. Res. Lett., 33, L08406,
https://doi.org/10.1029/2006GL026047, 2006.
Hanasaki, N., Inuzuka, T., Kanae, S., and Oki, T.: An estimation of global
virtual water flow and sources of water withdrawal for major crops and
livestock products using a global hydrological model, J. Hydrol., 384,
232–244, https://doi.org/10.1016/j.jhydrol.2009.09.028, 2010.
Harding, R. J., Blyth, E. M., Tuinenburg, O. A., and Wiltshire, A.: Land
atmosphere feedbacks and their role in the water resources of the Ganges
basin, Sci. Total Environ., 468–469, S85–S92,
https://doi.org/10.1016/j.scitotenv.2013.03.016, 2013.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
Global Reanalysis, Q. J. Roy. Meteor. Soc., 146, 730, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Hoekstra, A. Y. and Mekonnen, M. M.:
The water footprint of humanity, P. Natl. Acad. Sci. USA, 109, 3232–3237,
https://doi.org/10.1073/pnas.1109936109, 2012.
Jägermeyr, J., Gerten, D., Heinke, J., Schaphoff, S., Kummu, M., and Lucht, W.: Water savings potentials of irrigation systems: global simulation of processes and linkages, Hydrol. Earth Syst. Sci., 19, 3073–3091, https://doi.org/10.5194/hess-19-3073-2015, 2015.
Jiang, L., Ma, E., and Deng, X.: Impacts of Irrigation on the Heat Fluxes and
Near-Surface Temperature in an Inland Irrigation Area of Northern China,
Energies, 7, 1300–1317, https://doi.org/10.3390/en7031300, 2014.
Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S.,
Ahlström, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein,
P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B.,
Raduly, B., Rödenbeck, C., Tramontana, G., Viovy, N., Wang, Y.-P.,
Weber, U., Zaehle, S., and Zeng, N.: Compensatory water effects link yearly
global land CO2 sink changes to temperature, Nature, 541, 516–520,
https://doi.org/10.1038/nature20780, 2017.
Khan, S. and Abbas, A.: Upscaling water savings from farm to irrigation
system level using GIS-based agro-hydrological modelling, Irrig. Drain.,
56, 29–42, https://doi.org/10.1002/ird.284, 2007.
Koech, R. and Langat, P.: Improving Irrigation Water Use Efficiency: A
Review of Advances, Challenges and Opportunities in the Australian Context,
Water, 10, 1771, https://doi.org/10.3390/w10121771, 2018.
Kueppers, L. M., Snyder, M. A., and Sloan, L. C.: Irrigation cooling effect:
Regional climate forcing by land-use change, Geophys. Res. Lett., 34,
L03703, https://doi.org/10.1029/2006GL028679, 2007.
Lawston, P. M., Santanello, J. A., Zaitchik, B. F., and Rodell, M.: Impact of
Irrigation Methods on Land Surface Model Spinup and Initialization of WRF
Forecasts, J. Hydrometeorol., 16, 1135–1154,
https://doi.org/10.1175/JHM-D-14-0203.1, 2015.
Le Moigne, P., Albergel, C., Belamari, S., Boone, A., Brun, E., Calvet, J.-C., Decharme, B.,Dumont, M., Faroux, S., Gibelin, A.-L., Giordani, H., Lafont, S., Lebeaupin, C., Mahfouf, J.-F., Martin, E., Masson, V., Mironov, D., Morin, S., Noilhan, J., Tulet, P., Van Den Hurk, B., and Vionnet, V.: SURFEX scientific documentation – V8.1, Sci. Doc. –
SURFEX, http://www.umr-cnrm.fr/surfex/spip.php?rubrique11 (last access: 15 November 2022), 2018.
Leng, G., Leung, L. R., and Huang, M.: Significant impacts of irrigation water sources and methods on modeling irrigation effects in the ACME Land Model, J. Adv. Model. Earth Sy., 9, 1665–1683, https://doi.org/10.1002/2016MS000885, 2017.
Lobell, D. B., Bonfils, C. J., Kueppers, L. M., and Snyder, M. A.: Irrigation
cooling effect on temperature and heat index extremes, Geophys. Res. Lett.,
35, L09705, https://doi.org/10.1029/2008GL034145, 2008.
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013.
Meier, J., Zabel, F., and Mauser, W.: A global approach to estimate irrigated areas – a comparison between different data and statistics, Hydrol. Earth Syst. Sci., 22, 1119–1133, https://doi.org/10.5194/hess-22-1119-2018, 2018a.
Meier, J., Zabel, F., and Mauser, W.: Global Irrigated Areas, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.884744, 2018b.
Moore, N. and Rojstaczer, S.: Irrigation's influence on precipitation: Texas High Plains, U.S.A., Geophys. Res. Lett., 29, 1755, https://doi.org/10.1029/2002GL014940, 2002.
Mucia, A., Bonan, B., Zheng, Y., Albergel, C., and Calvet, J.-C.: From
monitoring to forecasting land surface conditions using a land data
assimilation system: Application over the contiguous United States, Remote
Sens., 12, 12, https://doi.org/10.3390/rs12122020, 2020.
Munier, S. and Decharme, B.: River network and hydro-geomorphological parameters at
Napoly, A., Boone, A., Samuelsson, P., Gollvik, S., Martin, E., Seferian, R., Carrer, D., Decharme, B., and Jarlan, L.: The interactions between soil–biosphere–atmosphere (ISBA) land surface model multi-energy balance (MEB) option in SURFEXv8 – Part 2: Introduction of a litter formulation and model evaluation for local-scale forest sites, Geosci. Model Dev., 10, 1621–1644, https://doi.org/10.5194/gmd-10-1621-2017, 2017.
Noilhan, J. and Planton, S.: A Simple Parameterization of Land Surface
Processes for Meteorological Models, Mon. Weather Rev., 117, 536–549,
https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989.
Ozdogan, M., Rodell, M., Beaudoing, H. K., and Toll, D. L.: Simulating the
Effects of Irrigation over the United States in a Land Surface Model Based
on Satellite-Derived Agricultural Data, J. Hydrometeorol., 11, 171–184,
https://doi.org/10.1175/2009JHM1116.1, 2010.
Perry, C.: Efficient irrigation; Inefficient communication; Flawed
recommendations, Irrig. Drain., 56, 367–378, 2007.
Perry, C., Steduto, P., Allen, R. G., and Burt, C. M.: Increasing
productivity in irrigated agriculture: Agronomic constraints and
hydrological realities, Agr. Water Manage., 96, 1517–1524, 2009.
Perry, C., Steduto, P., and Karejeh, F.: Does Improved Irrigation Technology
Save Water? A Review of the Evidence, Food and Agriculture Organization,
Cairo, Egypt, ISBN 978-92-5-109774-8, 2017.
Pfeiffer, L. and Lin, C.-Y. C.: Does efficient irrigation technology lead to
reduced groundwater extraction? Empirical evidence, J. Environ. Econ.
Manag., 67, 189–208, https://doi.org/10.1016/j.jeem.2013.12.002, 2014.
Piao, S., Ciais, P., Huang, Y., Shen, Z., Peng, S., Li, J., Zhou, L., Liu,
H., Ma, Y., Ding, Y., Friedlingstein, P., Liu, C., Tan, K., Yu, Y., Zhang,
T., and Fang, J.: The impacts of climate change on water resources and
agriculture in China, Nature, 467, 43–51,
https://doi.org/10.1038/nature09364, 2010.
Puma, M. J. and Cook, B. I.: Effects of irrigation on global climate during
the 20th century, J. Geophys. Res., 115, D16120,
https://doi.org/10.1029/2010JD014122, 2010.
Rodell, M., Velicogna, I., and Famiglietti, J. S.: Satellite-based estimates
of groundwater depletion in India, Nature, 460, 999–1002,
https://doi.org/10.1038/nature08238, 2009.
Rost, S., Gerten, D., Bondeau, A., Lucht, W., Rohwer, J., and Schaphoff, S.: Agricultural green and blue water consumption and its influence on the global water system, Water Resour. Res., 44, W09405, https://doi.org/10.1029/2007WR006331, 2008.
Sacks, W. J., Cook, B. I., Buenning, N., Levis, S., and Helkowski, J. H.:
Effects of global irrigation on the near-surface climate, Clim. Dynam.,
33, 159–175, https://doi.org/10.1007/s00382-008-0445-z, 2009.
Saeed, F., Hagemann, S., and Jacob, D.: Impact of irrigation on the South
Asian summer monsoon, Geophys. Res. Lett., 36, L20711,
https://doi.org/10.1029/2009GL040625, 2009.
Shukla, S. P., Puma, M. J., and Cook, B. I.: The response of the South Asian
Summer Monsoon circulation to intensified irrigation in global climate model
simulations, Clim. Dynam., 42, 21–36,
https://doi.org/10.1007/s00382-013-1786-9, 2014.
Siebert, S. and Döll, P.: Quantifying blue and green virtual water
contents in global crop production as well as potential production losses
without irrigation, J. Hydrol., 384, 198–217,
https://doi.org/10.1016/j.jhydrol.2009.07.031, 2010.
Siebert, S., Kummu, M., Porkka, M., Döll, P., Ramankutty, N., and Scanlon, B. R.: A global data set of the extent of irrigated land from 1900 to 2005, Hydrol. Earth Syst. Sci., 19, 1521–1545, https://doi.org/10.5194/hess-19-1521-2015, 2015.
Sorooshian, S., Li, J., Hsu, K., and Gao, X.: Influence of irrigation schemes used in regional climate models on evapotranspiration estimation: Results and comparative studies from California's Central Valley agricultural regions, J. Geophys. Res.-Atmos., 117, D06107, https://doi.org/10.1029/2011JD016978, 2012.
Suyker, A. E. and Verma, S. B.: Evapotranspiration of irrigated and rainfed
maize–soybean cropping systems, Agric. For. Meteorol., 149, 443–452,
https://doi.org/10.1016/j.agrformet.2008.09.010, 2009.
Szilagyi, J. and Franz, T. E.: Anthropogenic hydrometeorological changes at a
regional scale: observed irrigation–precipitation feedback (1979–2015) in
Nebraska, USA, Sustain. Water Resour. Manag. 6, 1,
https://doi.org/10.1007/s40899-020-00368-w, 2020.
Tang, Q., Oki, T., Kanae, S., and Hu, H.: Hydrological Cycles Change in the
Yellow River Basin during the Last Half of the Twentieth Century, J. Climate,
21, 1790–1806, https://doi.org/10.1175/2007JCLI1854.1, 2008.
Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 4291–4313, https://doi.org/10.5194/bg-13-4291-2016, 2016.
UNDESA: World population prospects 2022: Summary of results, UN DESA/POP/2022/TR/NO. 3, https://www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/wpp2022_summary_of_results.pdf, last access: 15 November 2022.
USDA and NASS: Field Crops, Usual Planting and Harvesting Dates, United
States Department of Agriculture – National Agricultural Statistics Service, https://downloads.usda.library.cornell.edu/usda-esmis/files/vm40xr56k/dv13zw65p/w9505297d/planting-10-29-2010.pdf
(last access: 15 November 2022), 2010.
USGS: Water Use Data for Nebraska, USGS [data set], https://waterdata.usgs.gov/ne/nwis/wu (last access: 15 November 2022), 2018.
Verburg, P. H., Dearing, J. A., Dyke, J. G., van der Leeuw, S., Seitzinger,
S., Steffen, W., and Syvitski, J.: Methods and approaches to modelling the
Anthropocene, Glob. Environ. Change, 39, 328–340,
https://doi.org/10.1016/j.gloenvcha.2015.08.007, 2016.
Voirin-Morel, S.: Modélisation distribuée des flux d'eau et d'énergie et des débits à l'échelle régionale du bassin Adour-Garonne, PhD Thesis, 292 pp., Université de Toulouse, https://www.theses.fr/2003TOU30047 (last access: 15 November 2022), 2003.
Voldoire, A., Decharme, B., Pianezze, J., Lebeaupin Brossier, C., Sevault, F., Seyfried, L., Garnier, V., Bielli, S., Valcke, S., Alias, A., Accensi, M., Ardhuin, F., Bouin, M.-N., Ducrocq, V., Faroux, S., Giordani, H., Léger, F., Marsaleix, P., Rainaud, R., Redelsperger, J.-L., Richard, E., and Riette, S.: SURFEX v8.0 interface with OASIS3-MCT to couple atmosphere with hydrology, ocean, waves and sea-ice models, from coastal to global scales, Geosci. Model Dev., 10, 4207–4227, https://doi.org/10.5194/gmd-10-4207-2017, 2017.
Wortmann, C. S., Klein, R. N., and Shapiro, C. A.: Harvesting crop residues, University of Nebraska-Lincoln, Institute of Agriculture and Natural Resouces, G1846, NebGuide Series, 4 pp., https://extensionpubs.unl.edu/publication/9000016365924/harvesting-crop-residues/ (last access: 15 November 2022), 2012.
Yin, Z., Wang, X. H., Ottlé, C., Zhou, F., Guimberteau, M., Polcher, J.,
Peng, S. S., Piao, S. L., Li, L., Bo, Y., Chen, X. L., Zhou, X. D., Kim, H.,
and Ciais, P.: Improvement of the irrigation scheme in the ORCHIDEE land surface
model and impacts of irrigation on regional water budgets over China, J.
Adv. Model. Earth Syst., 12, 1–20, https://doi.org/10.1029/2019MS001770,
2020.
Zaitchik, B. F., Evans, J., and Smith, R. B.: MODIS-Derived Boundary
Conditions for a Mesoscale Climate Model: Application to Irrigated
Agriculture in the Euphrates Basin, Mon. Weather Rev., 133, 1727–1743,
https://doi.org/10.1175/MWR2947.1, 2005.
Zhang, G., Shen, D., Ming, B., Xie, R., Jin, X., Liu, C., Hou, P., Xue, J.,
Chen, J., Zhang, W., Liu, W., Wang, K., and Li, S.: Using irrigation intervals to
optimize water-use efficiency and maize yield in Xinjiang, northwest China,
The Crop J., 7, 322–334, https://doi.org/10.1016/j.cj.2018.10.008, 2019.
Zhang, Z., Barlage, M., Chen, F., Li, Y., Helgason, W., Xu, X., Liu, X., and
Li, Z.: Joint modeling of crop and irrigation in the central United States using
the Noah-MP land surface model, J. Adv. Model. Earth
Sy., 12, e2020MS002159, https://doi.org/10.1029/2020MS002159, 2020.
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Crop phenology and irrigation is implemented into a land surface model able to work at a global...
Special issue