Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-5755-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5755-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
17 Oct 2023
Model description paper |
| 17 Oct 2023
| 17 Oct 2023
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands
Anthony Schrapffer
CORRESPONDING AUTHOR
Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Centro de Investigaciones del Mar y la Atmósfera (CIMA), CONICET – Universidad de Buenos Aires, Buenos Aires, Argentina
Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (UMI 3351 IFAECI), CNRS – IRD – CONICET – UBA, Buenos Aires, Argentina
EthiFinance, 11 Avenue Delcassé 75008, Paris, France
Jan Polcher
Laboratoire de Météorologie Dynamique (LMD), IPSL, CNRS, École Polytechnique, Palaiseau, France
Anna Sörensson
Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Centro de Investigaciones del Mar y la Atmósfera (CIMA), CONICET – Universidad de Buenos Aires, Buenos Aires, Argentina
Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (UMI 3351 IFAECI), CNRS – IRD – CONICET – UBA, Buenos Aires, Argentina
Lluís Fita
Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Centro de Investigaciones del Mar y la Atmósfera (CIMA), CONICET – Universidad de Buenos Aires, Buenos Aires, Argentina
Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (UMI 3351 IFAECI), CNRS – IRD – CONICET – UBA, Buenos Aires, Argentina
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Cited articles
Adler, B., Kalthoff, N., and Gantner, L.: The impact of soil moisture inhomogeneities on the modification of a mesoscale convective system: An idealised model study, Atmos. Res., 101, 354–372, https://doi.org/10.1016/j.atmosres.2011.03.013, 2011. a
Aires, F., Prigent, C., Fluet-Chouinard, E., Yamazaki, D., Papa, F., and Lehner, B.: Comparison of visible and multi-satellite global inundation datasets at high-spatial resolution, Remote Sens. Environ., 216, 427–441, https://doi.org/10.1016/j.rse.2018.06.015, 2018. a
Alsdorf, D., Han, S. C., Bates, P., and Melack, J.: Seasonal water storage on the Amazon floodplain measured from satellites, Remote Sens. Environ., 114, 2448–2456, https://doi.org/10.1016/j.rse.2010.05.020, 2010. a
ANA: Discharge used for Porto Murtinho, Brazilian National Water Agency (ANA) [data set], https://www.snirh.gov.br/hidroweb/, last access: 21 June 2021. a
Assine, M. L.: River avulsions on the Taquari megafan, Pantanal wetland, Brazil, Geomorphology, 70, 357–371, https://doi.org/10.1016/j.geomorph.2005.02.013, 2005. a
Barbosa da Silva, F. H., Nunes da Cunha, C., and Overbeck, G. E.: Seasonal dynamics of flooded tropical grassland communities in the Pantanal wetland, Wetlands, 40, 1257–1268, 2020. a
Barella-Ortiz, A., Polcher, J., Tuzet, A., and Laval, K.: Potential evaporation estimation through an unstressed surface-energy balance and its sensitivity to climate change, Hydrol. Earth Syst. Sci., 17, 4625–4639, https://doi.org/10.5194/hess-17-4625-2013, 2013. a
Barlage, M., Chen, F., Rasmussen, R., Zhang, Z., and Miguez-Macho, G.: The Importance of Scale-Dependent Groundwater Processes in Land-Atmosphere Interactions Over the Central United States, Geophys. Res. Lett., 48, e2020GL092171, https://doi.org/10.1029/2020GL092171, 2021. a
Bazilian, M., Rogner, H., Howells, M., Hermann, S., Arent, D., Gielen, D., Steduto, P., Mueller, A., Komor, P., Tol, R. S., and Yumkella, K. K.: Considering the energy, water and food nexus: Towards an integrated modelling approach, Energy Policy, https://doi.org/10.1016/j.enpol.2011.09.039, 2011. a
Bergier, I.: Effects of highland land-use over lowlands of the Brazilian Pantanal, Sci. Total Environ., 463-464, 1060–1066, https://doi.org/10.1016/j.scitotenv.2013.06.036, 2013. a, b, c
Campoy, A., Ducharne, A., Cheruy, F., Hourdin, F., Polcher, J., and Dupont, J. C.: Response of land surface fluxes and precipitation to different soil bottom hydrological conditions in a general circulation model, J. Geophys. Res.-Atmos., 118, 10725–10739, https://doi.org/10.1002/jgrd.50627, 2013. a, b
Chaney, N. W., Torres-Rojas, L., Vergopolan, N., and Fisher, C. K.: HydroBlocks v0.2: enabling a field-scale two-way coupling between the land surface and river networks in Earth system models, Geosci. Model Dev., 14, 6813–6832, https://doi.org/10.5194/gmd-14-6813-2021, 2021. a, b, c
Collischonn, W., Allasia, D., da Silva, B. C., and Tucci, C. E.: The MGB-IPH model for large-scale rainfall–runoff modelling, Hydrol. Sci. J., 52, 878–895, https://doi.org/10.1623/HYSJ.52.5.878, 2010. a
Dadson, S. J., Ashpole, I., Harris, P., Davies, H. N., Clark, D. B., Blyth, E., and Taylor, C. M.: Wetland inundation dynamics in a model of land surface climate: Evaluation in the Niger inland delta region, J. Geophys. Res.-Atmos., 115, D23114, https://doi.org/10.1029/2010JD014474, 2010. a, b
Decharme, B., Delire, C., Minvielle, M., Colin, J., Vergnes, J. P., 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 Sy., 11, 1207–1252, https://doi.org/10.1029/2018MS001545, 2019. a, b, c
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
de Rosnay, P., Bruen, M., and Polcher, J.: Sensitivity of surface fluxes to the number of layers in the soil model used in GCMs, Geophys. Res. Lett., 27, 3329–3332, https://doi.org/10.1029/2000GL011574, 2000. a, b
de Rosnay, P., Polcher, J., Bruen, M., and Laval, K.: Impact of a physically based soil water flow and soil-plant interaction representation for modeling large-scale land surface processes, J. Geophys. Res.-Atmos., 107, ACL 3-1–ACL 3-19, https://doi.org/10.1029/2001jd000634, 2002. a, b
Diestel, R.: Graph theory, no. 173 in Graduate Texts in Mathematics, 4th edn., 2. corr. print edn., Springer, Heidelberg, oCLC: 820789409, 2012. a
Dirmeyer, P. A.: The terrestrial segment of soil moisture-climate coupling, Geophys. Res. Lett., 38, L16702, https://doi.org/10.1029/2011GL048268, 2011. a
ESA: ESA CCI land cover time-series v2.0.7 (1992-2015)., Tech. rep., European Space Agency-Climate Change Initiative, 2017. a
Fleischmann, A. S., Brêda, J. P., Passaia, O. A., Wongchuig, S. C., Fan, F. M., Paiva, R. C., Marques, G. F., and Collischonn, W.: Regional scale hydrodynamic modeling of the river-floodplain-reservoir continuum, J. Hydrol., 596, 126114, https://doi.org/10.1016/j.jhydrol.2021.126114, 2021. a
Frappart, F., Papa, F., Güntner, A., Werth, S., Santos da Silva, J., Tomasella, J., Seyler, F., Prigent, C., Rossow, W. B., Calmant, S., and Bonnet, M. P.: Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains, Remote Sens. Environ., 115, 1588–1594, https://doi.org/10.1016/J.RSE.2011.02.003, 2011. a, b
Freitas, J. G., Furquim, S. A., Aravena, R., and Cardoso, E. L.: Interaction between lakes' surface water and groundwater in the Pantanal wetland, Brazil, Environ. Earth Sci., 78, 78, 1–15, https://doi.org/10.1007/S12665-019-8140-4, 2019. a
Getirana, A., Jung, H. C., Van Den Hoek, J., and Ndehedehe, C. E.: Hydropower dam operation strongly controls Lake Victoria's freshwater storage variability, Sci. Total Environ., 726, 138343, https://doi.org/10.1016/j.scitotenv.2020.138343, 2020. a
Getirana, A., Kumar, S. V., Konapala, G., and Ndehedehe, C. E.: Impacts of Fully Coupling Land Surface and Flood Models on the Simulation of Large Wetlands' Water Dynamics: The Case of the Inner Niger Delta, J. Adv. Model. Earth Sy., 13, e2021MS002463, https://doi.org/10.1029/2021ms002463, 2021. a, b
Girard, P., Da Silva, C. J., and Abdo, M.: River–groundwater interactions in the Brazilian Pantanal. The case of the Cuiabá River, J. Hydrol., 283, 57–66, https://doi.org/10.1016/S0022-1694(03)00235-X, 2003. a, b
Guerreiro, R. L., Bergier, I., McGlue, M. M., Warren, L. V., de Abreu, U. G. P., Abrahão, J., and Assine, M. L.: The soda lakes of Nhecolândia: A conservation opportunity for the Pantanal wetlands, Persp. Ecol. Conserv., 17, 9–18, https://doi.org/10.1016/J.PECON.2018.11.002, 2019. a
Guimberteau, M., Drapeau, G., Ronchail, J., Sultan, B., Polcher, J., Martinez, J.-M., Prigent, C., Guyot, J.-L., Cochonneau, G., Espinoza, J. C., Filizola, N., Fraizy, P., Lavado, W., De Oliveira, E., Pombosa, R., Noriega, L., and Vauchel, P.: Discharge simulation in the sub-basins of the Amazon using ORCHIDEE forced by new datasets, Hydrol. Earth Syst. Sci., 16, 911–935, https://doi.org/10.5194/hess-16-911-2012, 2012. a
Guinaldo, T., Munier, S., Le Moigne, P., Boone, A., Decharme, B., Choulga, M., and Leroux, D. J.: Parametrization of a lake water dynamics model MLake in the ISBA-CTRIP land surface system (SURFEX v8.1), Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021, 2021. a, b
Guion, A., Turquety, S., Polcher, J., Pennel, R., Bastin, S., and Arsouze, T.: Droughts and heatwaves in the Western Mediterranean: impact on vegetation and wildfires using the coupled WRF-ORCHIDEE regional model (RegIPSL), Clim. Dynam., 58, 2881–2903, 2022. a
Hallouin, T., Ellis, R. J., Clark, D. B., Dadson, S. J., Hughes, A. G., Lawrence, B. N., Lister, G. M. S., and Polcher, J.: UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python, Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, 2022. a
Hamilton, S. K.: Hydrological controls of ecological structure and function in the Pantanal wetland (Brazil), in: The ecohydrology of South American rivers and wetlands, edited by: McClain, M., IAHS (International Association of Hydrological Sciences, Manaus) Press, Wallingford, UK, IAHS Special Publication, 133–158, ISBN 1901502023, 2002. a, b, c, d, e, f, g
Hamilton, S. K., Sippel, S. J., and Melack, J.: Inundation patterns in the Pantanal Wetland of South America determined from passive microwave remote sensing, Archiv für Hydrobiologie, 137, 1–23, https://doi.org/10.1127/archiv-hydrobiol/137/1996/1, 1996. a
Harris, I., Osborn, T. J., Jones, P., and Lister, D.: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset, Sci. Data, 7, 1–18, 2020. a
Howells, M., Hermann, S., Welsch, M., Bazilian, M., Segerström, R., Alfstad, T., Gielen, D., Rogner, H., Fischer, G., Van Velthuizen, H., Wiberg, D., Young, C., Alexander Roehrl, R., Mueller, A., Steduto, P., and Ramma, I.: Integrated analysis of climate change, land-use, energy and water strategies, 3, 621–626, https://doi.org/10.1038/nclimate1789, 2013. a
Hu, S., Niu, Z., and Chen, Y.: Global wetland datasets: a review, Wetlands, 37, 807–817, 2017. a
Junk, W. J. and Wantzen, K. M.: The flood pulse concept: new aspects, approaches and applications-an update, in: Second international symposium on the management of large rivers for fisheries, 117–149, Food and Agriculture Organization and Mekong River Commission, FAO Regional, 2004. a
Junk, W. J., Da Cunha, C. N., Wantzen, K. M., Petermann, P., Strüssmann, C., Marques, M. I., and Adis, J.: Biodiversity and its conservation in the Pantanal of Mato Grosso, Brazil, in: Aquatic Sciences, https://doi.org/10.1007/s00027-006-0851-4, 2006. a
Karabulut, A., Egoh, B. N., Lanzanova, D., Grizzetti, B., Bidoglio, G., Pagliero, L., Bouraoui, F., Aloe, A., Reynaud, A., Maes, J., Vandecasteele, I., and Mubareka, S.: Mapping water provisioning services to support the ecosystem-water-food-energy nexus in the Danube river basin, Ecosyst. Services, 17, 278–292, https://doi.org/10.1016/j.ecoser.2015.08.002, 2016. a
Krause, S., Bronstert, A., and Zehe, E.: Groundwater–surface water interactions in a North German lowland floodplain – Implications for the river discharge dynamics and riparian water balance, J. Hydrol., 347, 404–417, https://doi.org/10.1016/J.JHYDROL.2007.09.028, 2007. a, b
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system, Global Biochem. Cycles, 19, 1–33, https://doi.org/10.1029/2003GB002199, 2005. a
Lauerwald, R., Regnier, P., Camino-Serrano, M., Guenet, B., Guimberteau, M., Ducharne, A., Polcher, J., and Ciais, P.: ORCHILEAK (revision 3875): a new model branch to simulate carbon transfers along the terrestrial–aquatic continuum of the Amazon basin, Geosci. Model Dev., 10, 3821–3859, https://doi.org/10.5194/gmd-10-3821-2017, 2017. a
Lee, H., Beighley, R. E., Alsdorf, D., Jung, H. C., Shum, C. K., Duan, J., Guo, J., Yamazaki, D., and Andreadis, K.: Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry, Remote Sens. Environ., 115, 3530–3538, https://doi.org/10.1016/j.rse.2011.08.015, 2011. a
Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from spaceborne elevation data, Eos, 89, 93–104, https://doi.org/10.1029/2008EO100001, 2008. a
Louzada, R. O., Bergier, I., and Assine, M. L.: Landscape changes in avulsive river systems: Case study of Taquari River on Brazilian Pantanal wetlands, Sci. Total Environ., 723, 138067, https://doi.org/10.1016/j.scitotenv.2020.138067, 2020. a
Lucas-Picher, P., Argüeso, D., Brisson, E., Tramblay, Y., Berg, P., Lemonsu, A., Kotlarski, S., and Caillaud, C.: Convection-permitting modeling with regional climate models: Latest developments and next steps, WIREs Clim. Change, 12, e731, https://doi.org/10.1002/wcc.731, 2021. a
Makungu, E. and Hughes, D. A.: Understanding and modelling the effects of wetland on the hydrology and water resources of large African river basins, J. Hydrol., 603, 127039, https://doi.org/10.1016/J.JHYDROL.2021.127039, 2021. a
Marthews, T. R., Dadson, S. J., Clark, D. B., Blyth, E. M., Hayman, G. D., Yamazaki, D., Becher, O. R. E., Martínez-de la Torre, A., Prigent, C., and Jiménez, C.: Inundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulations, Hydrol. Earth Syst. Sci., 26, 3151–3175, https://doi.org/10.5194/hess-26-3151-2022, 2022. a, b
Munier, S. and Decharme, B.: River network and hydro-geomorphological parameters at
Ngo-Duc, T., Laval, K., Ramillien, G., Polcher, J., and Cazenave, A.: Validation of the land water storage simulated by Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) with Gravity Recovery and Climate Experiment (GRACE) data, Water Resour. Res., 43, W04427, https://doi.org/10.1029/2006WR004941, 2007. a
Nguyen-Quang, T., Polcher, J., Ducharne, A., Arsouze, T., Zhou, X., Schneider, A., and Fita, L.: ORCHIDEE-ROUTING: revising the river routing scheme using a high-resolution hydrological database, Geosci. Model Dev., 11, 4965–4985, https://doi.org/10.5194/gmd-11-4965-2018, 2018. a, b
Nobre, A. D., Cuartas, L. A., Hodnett, M., Rennó, C. D., Rodrigues, G., Silveira, A., Waterloo, M., and Saleska, S.: Height Above the Nearest Drainage – a hydrologically relevant new terrain model, J. Hydrol., 404, 13–29, https://doi.org/10.1016/j.jhydrol.2011.03.051, 2011. a
Padovani: Dinâmica Espaço-Temporal das Inundações do Pantanal, PhD thesis, Piracicaba: Escola Superior de Agricultura Luiz de Queiroz, Centro de Energia Nuclear na Agricultura, Universidade de São Paulo, http://www.teses.usp.br/teses/disponiveis/91/91131/tde-14022011-170515/pt-br.php (last access: 12 October 2023), 2010. a, b, c, d, e, f, g, h, i, j
Paiva, R. C., Collischonn, W., and Tucci, C. E.: Large scale hydrologic and hydrodynamic modeling using limited data and a GIS based approach, J. Hydrol., 406, 170–181, https://doi.org/10.1016/j.jhydrol.2011.06.007, 2011. a
Penatti, N. C., de Almeida, T. I. R., Ferreira, L. G., Arantes, A. E., and Coe, M. T.: Satellite-based hydrological dynamics of the world's largest continuous wetland, Remote Sens. Environ., 170, 1–13, https://doi.org/10.1016/j.rse.2015.08.031, 2015. a, b
Pinzon, J. E., Pak, E. W., Tucker, C. J., Bhatt, U. S., Frost, G. V., and Macander, M. J.: Global Vegetation Greenness (NDVI) from AVHRR GIMMS-3G+, 1981–2022, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/2187, 2023. a
Polcher, J., Scrapffer, A., and Rinchiuso, L.: The pre-processor for ORCHIDEE's routing scheme (Version used for Polcher et al. 2022, GMD), Zenodo [code], https://doi.org/10.5281/zenodo.7058895, 2022. a
Polcher, J., Schrapffer, A., Dupont, E., Rinchiuso, L., Zhou, X., Boucher, O., Mouche, E., Ottlé, C., and Servonnat, J.: Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water, Geosci. Model Dev., 16, 2583–2606, https://doi.org/10.5194/gmd-16-2583-2023, 2023. a, b, c, d, e, f, g
Pontes, P. R. M., Fan, F. M., Fleischmann, A. S., de Paiva, R. C. D., Buarque, D. C., Siqueira, V. A., Jardim, P. F., Sorribas, M. V., and Collischonn, W.: MGB-IPH model for hydrological and hydraulic simulation of large floodplain river systems coupled with open source GIS, Environ. Model. Softw., 94, 1–20, https://doi.org/10.1016/j.envsoft.2017.03.029, 2017. a, b
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S., Schmidli, J., Van Lipzig, N. P., and Leung, R.: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015. a
Prigent, C., Jimenez, C., and Bousquet, P.: Satellite-Derived Global Surface Water Extent and Dynamics Over the Last 25 Years (GIEMS-2), J. Geophys. Res.-Atmos., 125, e2019JD030711, https://doi.org/10.1029/2019JD030711, 2020. a, b, c, d
Reynolds, C. A., Jackson, T. J., and Rawls, W. J.: Estimating soil water-holding capacities by linking the Food and Agriculture Organization soil map of the world with global pedon databases and continuous pedotransfer functions, Water Resour. Res., 36, 3653–3662, https://doi.org/10.1029/2000WR900130, 2000. a
Schmidt, R., Flechtner, F., Meyer, U., Neumayer, K. H., Dahle, C., König, R., and Kusche, J.: Hydrological signals observed by the GRACE satellites, 29, 319–334, https://doi.org/10.1007/s10712-008-9033-3, 2008. a
Schneider, U., Finger, P., Meyer-Christoffer, A., Rustemeier, E., Ziese, M., and Becker, A.: Evaluating the Hydrological Cycle over Land Using the Newly-Corrected Precipitation Climatology from the Global Precipitation Climatology Centre (GPCC), Atmosphere, 8, 52, https://doi.org/10.3390/atmos8030052, 2017. a
Schrapffer, A., Polcher, J., Sörensson, A., and Fita, L.: Experiment for the validation and evaluation of the floodplains scheme in ORCHIDEE, Zenodo [code and data set], https://doi.org/10.5281/zenodo.7761859, 2023b. a
Seneviratne, S. I. and Stöckli, R.: The Role of Land–Atmosphere Interactions for Climate Variability in Europe, in: Climate Variability and Extremes during the Past 100 years, edited by: Brönnimann, S., Luterbacher, J., Ewen, T., Diaz, H. F., Stolarski, R. S., and Neu, U., Springer Dordrecht, 1st edn., https://doi.org/10.1007/978-1-4020-6766-2, 2008. a
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010. a
Stephens, G., Polcher, J., Zeng, X., van Oevelen, P., Poveda, G., Bosilovich, M., Ahn, M.-H., Balsamo, G., Duan, Q., Hegerl, G., Jakob, C., Lamptey, B., Leung, R., Piles, M., Su, Z., Dirmeyer, P., Findell, K. L., Verhoef, A., Ek, M., L'Ecuyer, T., Roca, R., Nazemi, A., Dominguez, F., Klocke, D., and Bony, S.: The First 30 Years of GEWEX, B. Am. Meteorol. Soc., 104, E126–E157, https://doi.org/10.1175/BAMS-D-22-0061.1, 2023. a, b
Taylor, C. M.: Feedbacks on convection from an African wetland, Geophys. Res. Lett., 37, L05406, https://doi.org/10.1029/2009GL041652, 2010. a
Taylor, C. M., Prigent, C., and Dadson, S. J.: Mesoscale rainfall patterns observed around wetlands in sub-Saharan Africa, Q. J. Roy. Meteor. Soc., 144, 2118–2132, https://doi.org/10.1002/qj.3311, 2018. a
Thielen, D., Schuchmann, K. L., Ramoni-Perazzi, P., Marquez, M., Rojas, W., Quintero, J. I., and Marques, M. I.: Quo vadis Pantanal? Expected precipitation extremes and drought dynamics from changing sea surface temperature, PLoS ONE, 15, e0227437, https://doi.org/10.1371/journal.pone.0227437, 2020. a
Vishwakarma, B. D., Zhang, J., and Sneeuw, N.: Downscaling GRACE total water storage change using partial least squares regression, Sci. Data, 8, 95, https://doi.org/10.1038/s41597-021-00862-6, 2021. a
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo, P.: The WFDEI meteorological forcing data set: WATCH Forcing data methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50, 7505–7514, https://doi.org/10.1002/2014WR015638, 2014. a
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description of floodplain inundation dynamics in a global river routing model, Water Resour. Res., 47, W04501, https://doi.org/10.1029/2010WR009726, 2011. a
Yamazaki, D., De Almeida, G. A., and Bates, P. D.: Improving computational efficiency in global river models by implementing the local inertial flow equation and a vector-based river network map, Water Resour. Res., 49, 7221–7235, https://doi.org/10.1002/wrcr.20552, 2013. a, b
Yamazaki, D., Sato, T., Kanae, S., Hirabayashi, Y., and Bates, P. D.: Regional flood dynamics in a bifurcating mega delta simulated in a global river model, Geophys. Res. Lett., 41, 3127–3135, https://doi.org/10.1002/2014GL059744, 2014. a
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F., Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high-accuracy map of global terrain elevations, Geophys. Res. Lett., 44, 5844–5853, https://doi.org/10.1002/2017GL072874, 2017. a
Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G., and Pavelsky, T.: MERIT Hydro: A high‐resolution global hydrography map based on latest topography datasets, Water Resour. Res., 55, 5053–5073, https://doi.org/10.1029/2019WR024873, 2019. a, b, c
Zhou, X., Prigent, C., and Yamazaki, D.: Toward improved comparisons between land‐surface‐water‐area estimates from a global river model and satellite observations, Water Resour. Res., 57, e2020WR029256, https://doi.org/10.1029/2020WR029256, 2021. a, b, c
Short summary
The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
The present paper introduces a floodplain scheme for a high-resolution land surface model river...
