Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4965-2018
© Author(s) 2018. 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-11-4965-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Dec 2018
Development and technical paper |
| 07 Dec 2018
| 07 Dec 2018
ORCHIDEE-ROUTING: revising the river routing scheme using a high-resolution hydrological database
Trung Nguyen-Quang
Laboratoire de Météorologie Dynamique, IPSL, CNRS, École Polytechnique, 91128 Palaiseau, France
Laboratoire de Météorologie Dynamique, IPSL, CNRS, École Polytechnique, 91128 Palaiseau, France
Agnès Ducharne
Sorbonne Université, CNRS, IPSL, Unité Mixte de Recherche METIS, 75005 Paris, France
Thomas Arsouze
Laboratoire de Météorologie Dynamique, IPSL, CNRS, École Polytechnique, 91128 Palaiseau, France
Xudong Zhou
Laboratoire de Météorologie Dynamique, IPSL, CNRS, École Polytechnique, 91128 Palaiseau, France
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China
Ana Schneider
Sorbonne Université, CNRS, IPSL, Unité Mixte de Recherche METIS, 75005 Paris, France
Lluís Fita
Centro de Investigaciones del Mar y la Atmósfera, CONICET, UBA, CNRS UMI-IFAECI, Buenos Aires, Argentina
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Xudong Zhou, Jan Polcher, Tao Yang, and Ching-Sheng Huang
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Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 12, 3503–3521, https://doi.org/10.5194/gmd-12-3503-2019, https://doi.org/10.5194/gmd-12-3503-2019, 2019
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Few Earth system models represent permafrost soil biogeochemistry, contributing to uncertainty in estimating its response and that of the planet to warming. Because the permafrost contains over double the carbon in the present atmosphere, its fate as it is
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Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Shushi Peng, Gerhard Krinner, Ardalan Tootchi, Agnès Ducharne, and Adam Hastie
Geosci. Model Dev., 12, 2961–2982, https://doi.org/10.5194/gmd-12-2961-2019, https://doi.org/10.5194/gmd-12-2961-2019, 2019
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We present a model that can simulate the dynamics of peatland area extent and the vertical buildup of peat. The model is validated across a range of northern peatland sites and over the Northern Hemisphere (> 30° N). It is able to reproduce the spatial extent of northern peatlands and peat carbon accumulation over the Holocene.
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
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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.
Lluís Fita, Jan Polcher, Theodore M. Giannaros, Torge Lorenz, Josipa Milovac, Giannis Sofiadis, Eleni Katragkou, and Sophie Bastin
Geosci. Model Dev., 12, 1029–1066, https://doi.org/10.5194/gmd-12-1029-2019, https://doi.org/10.5194/gmd-12-1029-2019, 2019
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Regional climate experiments coordinated throughout CORDEX aim to study and provide high-quality climate data over a given region. The data are used in climate change mitigation and adaptation policy studies and by stakeholders. CORDEX requires a list of variables, most of which are not provided by atmospheric models. Aiming to help the community and to maximize the use of CORDEX exercises, we create a new module for WRF models to directly produce them by adding
genericand
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Ardalan Tootchi, Anne Jost, and Agnès Ducharne
Earth Syst. Sci. Data, 11, 189–220, https://doi.org/10.5194/essd-11-189-2019, https://doi.org/10.5194/essd-11-189-2019, 2019
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The role of wetlands at regional and global scales depends on their distribution and extent, which is highly uncertain in the literature. We developed comprehensive wetland maps using satellite imagery products and ground water modeling. These high-resolution maps encompass regularly flooded to non-flooded groundwater wetlands, covering more than 21 % of the land surface area, which is among the highest estimates. Wetlands are particularly concentrated over the tropics and northern cold zones.
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
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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.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Xudong Zhou, Jan Polcher, Tao Yang, Yukiko Hirabayashi, and Trung Nguyen-Quang
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Zun Yin, Catherine Ottlé, Philippe Ciais, Matthieu Guimberteau, Xuhui Wang, Dan Zhu, Fabienne Maignan, Shushi Peng, Shilong Piao, Jan Polcher, Feng Zhou, Hyungjun Kim, and other China-Trend-Stream project members
Hydrol. Earth Syst. Sci., 22, 5463–5484, https://doi.org/10.5194/hess-22-5463-2018, https://doi.org/10.5194/hess-22-5463-2018, 2018
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Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3, PGF, CRU-NCEP, and WFDEI. Simulated soil moisture was compared to several datasets to evaluate the ability of ORCHIDEE in reproducing soil moisture dynamics. Results showed that ORCHIDEE soil moisture coincided well with other datasets in wet areas and in non-irrigated areas. It suggested that the ORCHIDEE-MICT was suitable for further hydrological studies in China.
Fuxing Wang, Jan Polcher, Philippe Peylin, and Vladislav Bastrikov
Hydrol. Earth Syst. Sci., 22, 3863–3882, https://doi.org/10.5194/hess-22-3863-2018, https://doi.org/10.5194/hess-22-3863-2018, 2018
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This work improves river discharge estimation by taking advantages of observation and model simulations. The new estimation takes into account both gauged and un-gauged rivers, and it compensates model systematic errors and missing processes (e.g., human water usage). This improved estimation is important not only for water resources management and ecosystem health over continent but also for ocean dynamics and salinity.
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
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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.
Ardalan Tootchi, Anne Jost, and Agnès Ducharne
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-48, https://doi.org/10.5194/hess-2018-48, 2018
Manuscript not accepted for further review
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There is a massive disagreement between wetland extent estimates in literature (3 to 21 % of the land surface area). Some inundated wetlands could be detected using satellite imagery while non-inundated ones and those below vegetation are not easily detectedable. We mapped all wetlands, using both satellite data and geomorphological information, showing large wetland over boreal and tropical zones plus thousands of small oases in arid areas.
Matthieu Guimberteau, Dan Zhu, Fabienne Maignan, Ye Huang, Chao Yue, Sarah Dantec-Nédélec, Catherine Ottlé, Albert Jornet-Puig, Ana Bastos, Pierre Laurent, Daniel Goll, Simon Bowring, Jinfeng Chang, Bertrand Guenet, Marwa Tifafi, Shushi Peng, Gerhard Krinner, Agnès Ducharne, Fuxing Wang, Tao Wang, Xuhui Wang, Yilong Wang, Zun Yin, Ronny Lauerwald, Emilie Joetzjer, Chunjing Qiu, Hyungjun Kim, and Philippe Ciais
Geosci. Model Dev., 11, 121–163, https://doi.org/10.5194/gmd-11-121-2018, https://doi.org/10.5194/gmd-11-121-2018, 2018
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Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module.
Ronny Lauerwald, Pierre Regnier, Marta Camino-Serrano, Bertrand Guenet, Matthieu Guimberteau, Agnès Ducharne, Jan Polcher, and Philippe Ciais
Geosci. Model Dev., 10, 3821–3859, https://doi.org/10.5194/gmd-10-3821-2017, https://doi.org/10.5194/gmd-10-3821-2017, 2017
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ORCHILEAK is a new branch of the terrestrial ecosystem model ORCHIDEE that represents dissolved organic carbon (DOC) production from canopy and soils, DOC and CO2 leaching from soils to streams, DOC decomposition, and CO2 evasion to the atmosphere during its lateral transport in rivers, as well as exchange with the soil carbon and litter stocks on floodplains and in swamps. We parameterized and validated ORCHILEAK for the Amazon basin.
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
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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.
Matthieu Guimberteau, Philippe Ciais, Agnès Ducharne, Juan Pablo Boisier, Ana Paula Dutra Aguiar, Hester Biemans, Hannes De Deurwaerder, David Galbraith, Bart Kruijt, Fanny Langerwisch, German Poveda, Anja Rammig, Daniel Andres Rodriguez, Graciela Tejada, Kirsten Thonicke, Celso Von Randow, Rita C. S. Von Randow, Ke Zhang, and Hans Verbeeck
Hydrol. Earth Syst. Sci., 21, 1455–1475, https://doi.org/10.5194/hess-21-1455-2017, https://doi.org/10.5194/hess-21-1455-2017, 2017
Anaïs Barella-Ortiz, Jan Polcher, Patricia de Rosnay, Maria Piles, and Emiliano Gelati
Hydrol. Earth Syst. Sci., 21, 357–375, https://doi.org/10.5194/hess-21-357-2017, https://doi.org/10.5194/hess-21-357-2017, 2017
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L-band radiometry is considered to be one of the most suitable techniques for estimating surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM. This paper compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones. It shows that models and remote-sensed values agree well in temporal variability, but not in their spatial structures.
Mohamed Ayache, Jean-Claude Dutay, Thomas Arsouze, Sidonie Révillon, Jonathan Beuvier, and Catherine Jeandel
Biogeosciences, 13, 5259–5276, https://doi.org/10.5194/bg-13-5259-2016, https://doi.org/10.5194/bg-13-5259-2016, 2016
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An extensive compilation of published neodymium (Nd) concentrations and isotopic compositions (Nd IC) was realized in order to establish a new database and a map (using a high-resolution geological map of the area) of the distribution of these parameters for all the Mediterranean margins. The use of a high-resolution regional oceanic model (1/12° of horizontal resolution) allows us to realistically simulate for the first time the Nd IC distribution in the Mediterranean Sea.
Jean-Philippe Vidal, Benoît Hingray, Claire Magand, Eric Sauquet, and Agnès Ducharne
Hydrol. Earth Syst. Sci., 20, 3651–3672, https://doi.org/10.5194/hess-20-3651-2016, https://doi.org/10.5194/hess-20-3651-2016, 2016
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Possible transient futures of winter and summer low flows for two snow-influenced catchments in the southern French Alps show a strong decrease signal. It is however largely masked by the year-to-year variability, which should be the main target for defining adaptation strategies. Responses of different hydrological models strongly diverge in the future, suggesting to carefully check the robustness of evapotranspiration and snowpack components under a changing climate.
Yiying Chen, James Ryder, Vladislav Bastrikov, Matthew J. McGrath, Kim Naudts, Juliane Otto, Catherine Ottlé, Philippe Peylin, Jan Polcher, Aude Valade, Andrew Black, Jan A. Elbers, Eddy Moors, Thomas Foken, Eva van Gorsel, Vanessa Haverd, Bernard Heinesch, Frank Tiedemann, Alexander Knohl, Samuli Launiainen, Denis Loustau, Jérôme Ogée, Timo Vessala, and Sebastiaan Luyssaert
Geosci. Model Dev., 9, 2951–2972, https://doi.org/10.5194/gmd-9-2951-2016, https://doi.org/10.5194/gmd-9-2951-2016, 2016
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In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types. An adequate parametrization approach has been presented for the global-scale land surface model (ORCHIDEE-CAN). Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
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This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Mathieu Hamon, Jonathan Beuvier, Samuel Somot, Jean-Michel Lellouche, Eric Greiner, Gabriel Jordà, Marie-Noëlle Bouin, Thomas Arsouze, Karine Béranger, Florence Sevault, Clotilde Dubois, Marie Drevillon, and Yann Drillet
Ocean Sci., 12, 577–599, https://doi.org/10.5194/os-12-577-2016, https://doi.org/10.5194/os-12-577-2016, 2016
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The paper describes MEDRYS, a MEDiterranean sea ReanalYsiS at high resolution for the period 1992–2013. The NEMOMED12 ocean model is forced at the surface by a new high resolution atmospheric forcing dataset (ALDERA). Altimeter data, satellite SST and temperature and salinity vertical profiles are jointly assimilated. The ability of the reanalysis to represent the sea surface high-frequency variability, water mass characteristics and transports through the Strait of Gibraltar is shown.
J. Ryder, J. Polcher, P. Peylin, C. Ottlé, Y. Chen, E. van Gorsel, V. Haverd, M. J. McGrath, K. Naudts, J. Otto, A. Valade, and S. Luyssaert
Geosci. Model Dev., 9, 223–245, https://doi.org/10.5194/gmd-9-223-2016, https://doi.org/10.5194/gmd-9-223-2016, 2016
P. Roudier, A. Ducharne, and L. Feyen
Hydrol. Earth Syst. Sci., 18, 2789–2801, https://doi.org/10.5194/hess-18-2789-2014, https://doi.org/10.5194/hess-18-2789-2014, 2014
M. Guimberteau, A. Ducharne, P. Ciais, J. P. Boisier, S. Peng, M. De Weirdt, and H. Verbeeck
Geosci. Model Dev., 7, 1115–1136, https://doi.org/10.5194/gmd-7-1115-2014, https://doi.org/10.5194/gmd-7-1115-2014, 2014
A. Barella-Ortiz, J. Polcher, A. Tuzet, and K. Laval
Hydrol. Earth Syst. Sci., 17, 4625–4639, https://doi.org/10.5194/hess-17-4625-2013, https://doi.org/10.5194/hess-17-4625-2013, 2013
Related subject area
Climate and Earth system modeling
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models
Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Process-based modeling framework for sustainable irrigation management at the regional scale: Integrating rice production, water use, and greenhouse gas emissions
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Cited articles
Akhil, V., Durand, F., Lengaigne, M., Vialard, J., Keerthi, M.,
Gopalakrishna,
V., Deltel, C., Papa, F., and de Boyer Montégut, C.: A modeling study of
the processes of surface salinity seasonal cycle in the Bay of Bengal,
J. Geophys. Res.-Oceans, 119, 3926–3947, 2014. a
Andersson, J., Pechlivanidis, I., Gustafsson, D., Donnelly, C., and Arheimer,
B.: Key factors for improving large-scale hydrological model performance,
European Water, 49, 77–88, 2015. a
Arora, V., Seglenieks, F., Kouwen, N., and Soulis, E.: Scaling aspects of
river
flow routing, Hydrol. Process., 15, 461–477, 2001. a
Arora, V. K. and Boer, G. J.: A variable velocity flow routing algorithm for
GCMs, J. Geophys. Res.-Atmos., 104, 30965–30979,
1999. a
Arora, V. K., Chiew, F. H., and Grayson, R. B.: A river flow routing scheme
for
general circulation models, J. Geophys. Res., 104, 314–347,
1999. a
Artinyan, E., Habets, F., Noilhan, J., Ledoux, E., Dimitrov, D., Martin, E.,
and Le Moigne, P.: Modelling the water budget and the riverflows of the
Maritsa basin in Bulgaria, Hydrol. Earth Syst. Sci., 12, 21–37,
https://doi.org/10.5194/hess-12-21-2008, 2008. a
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B.,
Hirschi,
M., and Betts, A. K.: A revised hydrology for the ECMWF model: Verification
from field site to terrestrial water storage and impact in the Integrated
Forecast System, J. Hydrometeorol., 10, 623–643, 2009. a
Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Dutra, E., Fink, G., Orth,
R., and Schellekens, J.: Global evaluation of runoff from 10 state-of-the-art
hydrological models, Hydrol. Earth Syst. Sci., 21, 2881–2903,
https://doi.org/10.5194/hess-21-2881-2017, 2017. a, b, c
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles,
D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global
gridded precipitation (1979–2015) by merging gauge, satellite, and
reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615,
https://doi.org/10.5194/hess-21-589-2017, 2017. a, b
Beven, K. J. and Cloke, H. L.: Comment on “Hyperresolution global land
surface modeling: Meeting a grand challenge for monitoring Earth's
terrestrial water” by Eric F. Wood et al., Water Resour. Res., 48, W01801, https://doi.org/10.1029/2011WR010982,
2012. a
Bierkens, M. F.: Global hydrology 2015: State, trends, and directions, Water
Resour. Res., 51, 4923–4947, 2015. a
Bierkens, M. F., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David, C.
H., Roo, A., Döll, P., Drost, N., Famiglietti, J. S., Flörke, M.,
Gochis D. J., Houser, P., Hut, R., Keune, J., Kollet, S., Maxwell, R.,
Reager, J. T., Samaniego, L., Sudicky, E., Sutanudjaja, E. H., Giesen, N.,
Winsemius, H., and Wood, E. F.: Hyper-resolution global hydrological
modelling: what is next?, Hydrol. Process., 29, 310–320, 2015. a
Bontemps, S., Defourny, P., Radoux, J., Van Bogaert, E., Lamarche, C.,
Achard, F., Mayaux, P., Boettcher, M., Brockmann, C., Kirches, G.,
Zülkhe, M., Kalogirou, V., Seifert, F. M., and Arino, O.: Consistent
global land cover maps for climate modelling communities: current
achievements of the ESA's land cover CCI, in: Proceedings of the ESA Living
Planet Symposium, Edimburgh, 9–13, 2013. a
Criss, R. E. and Winston, W. E.: Do Nash values have value? Discussion and
alternate proposals, Hydrol. Process., 22, 2723–2725 https://doi.org/10.1002/hyp.7072, 2008. a
David, C. H., Maidment, D. R., Niu, G.-Y., Yang, Z.-L., Habets, F., and
Eijkhout, V.: River network routing on the NHDPlus dataset, J.
Hydrometeorol., 12, 913–934, 2011. a
Decharme, B. and Douville, H.: Introduction of a sub-grid hydrology in the
ISBA
land surface model, Clim. Dynam., 26, 65–78, 2006a. a
Decharme, B. and Douville, H.: Uncertainties in the GSWP-2 precipitation
forcing and their impacts on regional and global hydrological simulations,
Clim. Dynam., 27, 695–713, 2006b. a
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, 4118, https://doi.org/10.1029/2001JD000634, 2002. a
De Rosnay, P., Polcher, J., Laval, K., and Sabre, M.: Integrated
parameterization of irrigation in the land surface model ORCHIDEE. Validation
over Indian Peninsula, Geophys. Res. Lett., 30, 1986, https://doi.org/10.1029/2003GL018024, 2003. a, b, c
Döll, P. and Lehner, B.: Validation of a new global 30-min drainage
direction map, J. Hydrol., 258, 214–231, 2002. a
d'Orgeval, T., Polcher, J., and de Rosnay, P.: Sensitivity of the West
African hydrological cycle in ORCHIDEE to infiltration processes, Hydrol.
Earth Syst. Sci., 12, 1387–1401, https://doi.org/10.5194/hess-12-1387-2008,
2008. a, b
Drobinski, P., Ducrocq, V., Alpert, P., Anagnostou, E., Béranger, K.,
Borga, M., Braud, I., Chanzy, A., Davolio, S., Delrieu, G., Estournel, C., Filali
Boubrahmi, N., Font, J., Grubišić, V., Gualdi, S., Homar, V.,
Ivančan-Picek, B., Kottmeier, C., Kotroni, V., Lagouvardos, K., Lionello,
P., Llasat, C., Ludwig, W., Lutoff, C., Mariotti, A., Richard, E., Romero,
R., Rotunno, R., Ruin, I., Roussot, O., Somot, S., Taupier-Letage, I.,
Tintoré, J., Uijlenhoet, R., and Wernli, H.: HyMeX: A
10-year multidisciplinary program on the Mediterranean water cycle, B.
Am. Meteorol. Soc., 95, 1063–1082, 2014. a
Dubos, T., Dubey, S., Tort, M., Mittal, R., Meurdesoif, Y., and Hourdin, F.:
DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for
consistency and versatility, Geosci. Model Dev., 8, 3131–3150,
https://doi.org/10.5194/gmd-8-3131-2015, 2015. a
Fekete, B. M., Vörösmarty, C. J., Roads, J. O., and Willmott, C. J.:
Uncertainties in precipitation and their impacts on runoff estimates, J. Climate, 17, 294–304, 2004. a
Fekete, B. M., Looser, U., Pietroniro, A., and Robarts, R. D.: Rationale for
monitoring discharge on the ground, J. Hydrometeorol., 13,
1977–1986, 2012. 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, 2012a. a, b, c, d, e, f
Gupta, H. V. and Kling, H.: On typical range, sensitivity, and normalization
of
Mean Squared Error and Nash-Sutcliffe Efficiency type metrics, Water
Resour. Res., 47, W10601, https://doi.org/10.1029/2011WR010962, 2011. a
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of
the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91, 2009. a
Hagemann, S. and Dümenil, L.: A parametrization of the lateral waterflow
for the global scale, Clim. Dynam., 14, 17–31, 1997. a
Harris, I., Jones, P., Osborn, T., and Lister, D.: Updated high-resolution
grids of monthly climatic observations – the CRU TS3.10 Dataset,
Int. J. Climatol., 34, 623–642, 2014. a
Jensen, T. G., Wijesekera, H. W., Nyadjro, E. S., Thoppil, P. G., Shriver,
J. F., Sandeep, K., and Pant, V.: Modeling salinity exchanges between the
equatorial Indian Ocean and the Bay of Bengal, Oceanography, 29, 92–101,
2016. a
Koirala, S., Yeh, P. J.-F., Hirabayashi, Y., Kanae, S., and Oki, T.:
Global-scale land surface hydrologic modeling with the representation of
water table dynamics, J. Geophys. Res.-Atmos., 119,
75–89, 2014. a
Krause, P., Boyle, D. P., and Bäse, F.: Comparison of different
efficiency criteria for hydrological model assessment, Adv. Geosci., 5,
89–97, https://doi.org/10.5194/adgeo-5-89-2005, 2005. a
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 Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005. a
Lea, D., Mirouze, I., Martin, M., King, R., Hines, A., Walters, D., and
Thurlow, M.: Assessing a new coupled data assimilation system based on the
Met Office coupled atmosphere–land–ocean–sea ice model, Mon. Weather
Rev., 143, 4678–4694, 2015. a
Lehner, B., Verdin, K., and Jarvis, A.: HydroSHEDS technical documentation,
version 1.0, World Wildlife Fund US, Washington, DC, 1–27, 2006. a
Leopold, L. B. and Maddock, T.: The hydraulic geometry of stream channels and
some physiographic implications, Vol. 252, US Government Printing Office,
1953. a
Mahe, G., Lienou, G., Descroix, L., Bamba, F., Paturel, J.-E., Laraque, A.,
Meddi, M., Habaieb, H., Adeaga, O., Dieulin, C., Chahnez Kotti, F., and Khomsi, K.: The rivers of
Africa: witness of climate change and human impact on the environment,
Hydrol. Process., 27, 2105–2114, 2013. a
Margat, J. and Treyer, S.: L'eau des Méditerranéens: situation et
perspectives. PNUE-PAM, Tech. rep., Plan Bleu, Technical Report Series, 2004. a
Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S., and Gedney, N.:
High-resolution global topographic index values for use in large-scale
hydrological modelling, Hydrol. Earth Syst. Sci., 19, 91–104,
https://doi.org/10.5194/hess-19-91-2015, 2015. a
Meile, T., Boillat, J.-L., and Schleiss, A.: Hydropeaking indicators for
characterization of the Upper-Rhone River in Switzerland, Aquat. Sci.,
73, 171–182, 2011. a
Miller, J. R., Russell, G. L., and Caliri, G.: Continental-scale river flow
in
climate models, J. Climate, 7, 914–928, 1994. a
Montanari, A.: Hydrology of the Po River: looking for changing patterns in
river discharge, Hydrol. Earth Syst. Sci., 16, 3739–3747,
https://doi.org/10.5194/hess-16-3739-2012, 2012. a
Nassopoulos, H., Dumas, P., and Hallegatte, S.: Adaptation to an uncertain
climate change: cost benefit analysis and robust decision making for dam
dimensioning, Climatic Change, 114, 497–508, 2012. a
Ngo-Duc, T., Laval, K., Polcher, J., and Cazenave, A.: Contribution of
continental water to sea level variations during the 1997–1998 El
Niño–Southern Oscillation event: Comparison between Atmospheric Model
Intercomparison Project simulations and TOPEX/Poseidon satellite data,
J. Geophys. Res.-Atmos., 110, D09103, https://doi.org/10.1029/2004JD004940, 2005a. a, b
Ngo-Duc, T., Laval, K., Polcher, J., Lombard, A., and Cazenave, A.: Effects
of
land water storage on global mean sea level over the past half century,
Geophys. Res. Lett., 32, 2005b. a
Ngo-Duc, T., Polcher, J., and Laval, K.: A 53-year forcing data set for land
surface models, J. Geophys. Res.-Atmos., 110, D06116, https://doi.org/10.1029/2004JD005434,
2005c. a, b, c
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, 2007a. a, b, c
Ngo-Duc, T., Oki, T., and Kanae, S.: A variable streamflow velocity method
for global river routing model: model description and preliminary results,
Hydrol. Earth Syst. Sci. Discuss., 4, 4389–4414,
https://doi.org/10.5194/hessd-4-4389-2007, 2007b. a, b, c
Oleson, K. W., Lawrence, D. M., Gordon, B., Flanner, M. G., Kluzek, E.,
Peter,
J., Levis, S., Swenson, S. C., Thornton, E., Feddema, J., Heald, C. L.,
Lamarque, J.-F., Niu, G.-Y., Qian, T., Running, S., Sakaguchi, K., Yang, L.,
Zeng, X., Zeng, X., and Decker, M.: Technical
description of version 4.0 of the Community Land Model (CLM), NCAR Technical
Note NCAR/TN-478+STR, 257, 2010. a
Polcher, J.: Les processus de surface à l'échelle globale et leurs
interactions avec l'atmosphère, Habilitation à diriger des
recherches, Université Paris VI, 2003. a
Satoh, M., Tomita, H., Yashiro, H., Miura, H., Kodama, C., Seiki, T., Noda,
A. T., Yamada, Y., Goto, D., Sawada, M., Miyoshi, T., Niwa, Y., Hara, M.,
Ohno, T., Iga, S., Arakawa, T., Inoue, T., and Kubokawa, H.: The
Non-hydrostatic
Icosahedral Atmospheric Model: description and development, Progress in Earth
and Planetary Science, 1, 1–32, 2014. a
Savitzky, A. and Golay, M. J.: Smoothing and differentiation of data by
simplified least squares procedures, Anal. Chem., 36, 1627–1639,
1964. a
Schaefli, B. and Gupta, H. V.: Do Nash values have value?, Hydrol.
Process., 21, 2075–2080, 2007. a
Schneider, A.: Estimation of the base flow time constant for global scale
applications, PhD thesis, Université Pierre et Marie Curie, Paris, France,
available at:
https://www.metis.upmc.fr/~ducharne/documents/these_SCHNEIDER_2017.pdf
(last access: 3 December 2018), 2017. a
Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., Ziese, M., and
Rudolf, B.: GPCC's new land surface precipitation climatology based on
quality-controlled in situ data and its role in quantifying the global water
cycle, Theor. Appl. Climatol., 115, 15–40, 2014. a
Schulzweida, U.: Climate Data Operators (CDO) User Guide, Max Planck
Institute
for Meteorologie, available at: https://code.mpimet.mpg.de/projects/cdo/embedded/cdo.pdf (last access: 3 December 2018),
2018. a
Sevault, F., Somot, S., Alias, A., Dubois, C., Lebeaupin-Brossier, C., Nabat,
P., Adloff, F., Déqué, M., and Decharme, B.: A fully coupled
Mediterranean regional climate system model: design and evaluation of the
ocean component for the 1980–2012 period, Tellus A, 66, https://doi.org/10.3402/TELLUSA.V66.23967, 2014. a
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. a
Snoussi, M., Haïda, S., and Imassi, S.: Effects of the construction of
dams on the water and sediment fluxes of the Moulouya and the Sebou Rivers,
Morocco, Reg. Environ. Change, 3, 5–12, 2002. a
Souty, F., Brunelle, T., Dumas, P., Dorin, B., Ciais, P., Crassous, R.,
Müller, C., and Bondeau, A.: The Nexus Land-Use model version 1.0, an
approach articulating biophysical potentials and economic dynamics to model
competition for land-use, Geosci. Model Dev., 5, 1297–1322,
https://doi.org/10.5194/gmd-5-1297-2012, 2012. a
Tavakoly, A. A., Snow, A. D., David, C. H., Follum, M. L., Maidment, D. R.,
and
Yang, Z.-L.: Continental-Scale River Flow Modeling of the Mississippi River
Basin Using High-Resolution NHDPlus Dataset, J. Am.
Water Resour. As., 53, 258–279, 2017. a
Turuncoglu, U. U., Giuliani, G., Elguindi, N., and Giorgi, F.: Modelling the
Caspian Sea and its catchment area using a coupled regional atmosphere-ocean
model (RegCM4-ROMS): model design and preliminary results, Geosci. Model
Dev., 6, 283–299, https://doi.org/10.5194/gmd-6-283-2013, 2013. a
Vergnes, J.-P., Decharme, B., and Habets, F.: Introduction of groundwater
capillary rises using subgrid spatial variability of topography into the ISBA
land surface model, J. Geophys. Res.-Atmos., 119, 11065–11086, https://doi.org/10.1002/2014JD021573, 2014. a
Vilibić, I., Mihanović, H., Janeković, I., and Šepić,
J.:
Modelling the formation of dense water in the northern Adriatic: Sensitivity
studies, Ocean Model., 101, 17–29, 2016. a
Voisin, N., Li, H., Ward, D., Huang, M., Wigmosta, M., and Leung, L. R.: On
an improved sub-regional water resources management representation for
integration into earth system models, Hydrol. Earth Syst. Sci., 17,
3605–3622, https://doi.org/10.5194/hess-17-3605-2013, 2013a. a
Voisin, N., Liu, L., Hejazi, M., Tesfa, T., Li, H., Huang, M., Liu, Y., and
Leung, L. R.: One-way coupling of an integrated assessment model and a water
resources model: evaluation and implications of future changes over the US
Midwest, Hydrol. Earth Syst. Sci., 17, 4555–4575,
https://doi.org/10.5194/hess-17-4555-2013, 2013b. a
Von Bloh, W., Rost, S., Gerten, D., and Lucht, W.: Efficient parallelization
of
a dynamic global vegetation model with river routing, Environ. Modell.
Softw., 25, 685–690, 2010. a
Walters, D. N., Williams, K. D., Boutle, I. A., Bushell, A. C., Edwards, J.
M., Field, P. R., Lock, A. P., Morcrette, C. J., Stratton, R. A., Wilkinson,
J. M., Willett, M. R., Bellouin, N., Bodas-Salcedo, A., Brooks, M. E.,
Copsey, D., Earnshaw, P. D., Hardiman, S. C., Harris, C. M., Levine, R. C.,
MacLachlan, C., Manners, J. C., Martin, G. M., Milton, S. F., Palmer, M. D.,
Roberts, M. J., Rodríguez, J. M., Tennant, W. J., and Vidale, P. L.: The
Met Office Unified Model Global Atmosphere 4.0 and JULES Global Land 4.0
configurations, Geosci. Model Dev., 7, 361–386,
https://doi.org/10.5194/gmd-7-361-2014, 2014. 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, 2014. a
Weedon, G. P., Prudhomme, C., Crooks, S., Ellis, R. J., Folwell, S. S., and
Best, M. J.: Evaluating the performance of hydrological models via
cross-spectral analysis: case study of the Thames Basin, UK,
J. Hydrometeorol., 16, 214–231, 2015. a
Wood, E. F., Roundy, J. K., Troy, T. J., Van Beek, L., Bierkens, M. F.,
Blyth,
E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de
Giesen,
N., Houser, P., Jaffe, P. R., Kollet, S., Lehner, B., Lettenmaier, D. P.,
PetersLidard, C., Sivapalan, M., Sheffield, J., Wade, A., and Whitehead, P.:
Hyperresolution global land surface modeling: Meeting a grand challenge for
monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301,
https://doi.org/10.1029/2010WR010090, 2011. a
Wu, H., Kimball, J. S., Li, H., Huang, M., Leung, L. R., and Adler, R. F.: A
new global river network database for macroscale hydrologic modeling, Water
Resour. Res., 48, W09701, https://doi.org/10.1029/2012WR012313, 2012. a, b, c
Yamazaki, D., O'Loughlin, F., Trigg, M. A., Miller, Z. F., Pavelsky, T. M.,
and
Bates, P. D.: Development of the Global Width Database for Large Rivers,
Water Resour. Res., 50, 3467–3480, https://doi.org/10.1002/2013WR014664,
2014. a
Zhao, F., Veldkamp, T. I. E., Frieler, K., Schewe, J., Ostberg, S., Willner,
S., Schauberger, B., Gosling, S. N., Schmied, H. M., Portmann, F. T., Leng,
G., Huang, M., Liu, X., Tang, Q., Hanasaki, N., Biemans, H., Gerten, D.,
Satoh, Y., Pokhrel, Y., Stacke, T., Ciais, P., Chang, J., Ducharne, A.,
Guimberteau, M., Wada, Y., Kim, H., and Yamazaki, D.: The critical role of
the routing scheme in simulating peak river discharge in global hydrological
models, Environ. Res. Lett., 12, 075003, https://doi.org/10.1088/1748-9326/aa7250, 2017. a
Short summary
This study presents a revised river routing scheme for the Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model. The revision is carried out to benefit from the high-resolution topography provided by the Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS). We demonstrate that the finer description of the catchments allows for an improvement of the simulated river discharge of ORCHIDEE in an area with complex topography.
This study presents a revised river routing scheme for the Organising Carbon and Hydrology in...
