Articles | Volume 13, issue 3
https://doi.org/10.5194/gmd-13-1373-2020
© Author(s) 2020. 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-13-1373-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
23 Mar 2020
Model description paper |
| 23 Mar 2020
| 23 Mar 2020
Simulating coupled surface–subsurface flows with ParFlow v3.5.0: capabilities, applications, and ongoing development of an open-source, massively parallel, integrated hydrologic model
Civil and Environmental Engineering, Washington State University,
Pullman, WA, USA
Nicholas B. Engdahl
Civil and Environmental Engineering, Washington State University,
Pullman, WA, USA
Carol S. Woodward
Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA
Laura E. Condon
Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
Stefan Kollet
Institute for Bio- and Geosciences, Agrosphere (IBG-3), Research
Centre Jülich, Geoverbund ABC/J, Jülich, Germany
Centre for High-Performance Scientific Computing in Terrestrial
Systems, Geoverbund ABC/J, Jülich, Germany
Reed M. Maxwell
Integrated GroundWater Modeling Center and Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO, USA
Related authors
No articles found.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
Short summary
Short summary
We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
Short summary
Short summary
Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Max Berkelhammer, Gerald F. M. Page, Frank Zurek, Christopher Still, Mariah S. Carbone, William Talavera, Laura Hildebrand, James Byron, Kyle Inthabandith, Angellica Kucinski, Melissa Carlson, Kelsey Foss, Wendy Brown, Rosemary W. H. Carroll, Austin Simonpietri, Marshall Worsham, Ian Breckheimer, Anna Ryken, Reed Maxwell, David Gochis, Mark S. Raleigh, Eric Small, and Kenneth H. Williams
Hydrol. Earth Syst. Sci., 29, 701–718, https://doi.org/10.5194/hess-29-701-2025, https://doi.org/10.5194/hess-29-701-2025, 2025
Short summary
Short summary
Warming in montane systems is affecting the snowmelt input amount. At the global scale, this will impact subalpine forests that rely on spring snowmelt to support their water demands. We use a network of sensors across a hillslope in the Upper Colorado Basin to show that the changing spring snowpack has a more pronounced impact on dense forest stands, while open stands show a higher reliance on summer rain and are less sensitive to significant changes in snow.
Benjamin D. West, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 29, 245–259, https://doi.org/10.5194/hess-29-245-2025, https://doi.org/10.5194/hess-29-245-2025, 2025
Short summary
Short summary
This article describes the addition of reservoirs to the hydrologic model ParFlow. ParFlow is particularly good at helping us understand some of the broader drivers behind different parts of the water cycle. By having reservoirs in such a model, we hope to be able to better understand both our impacts on the environment and how to adjust our management of reservoirs to changing conditions.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
Short summary
Short summary
Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
Peyman Abbaszadeh, Fadji Zaouna Maina, Chen Yang, Dan Rosen, Sujay Kumar, Matthew Rodell, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-280, https://doi.org/10.5194/hess-2024-280, 2024
Preprint under review for HESS
Short summary
Short summary
To manage Earth's water resources effectively amid climate change, it's crucial to understand both surface and groundwater processes. We developed a new modeling system that combines two advanced tools, ParFlow and LIS/Noah-MP, to better simulate both land surface and groundwater interactions. By testing this integrated model in the Upper Colorado River Basin, we found it improves predictions of hydrologic processes, especially in complex terrains.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
Short summary
Short summary
Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-292, https://doi.org/10.5194/hess-2024-292, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
We developed the first high-resolution, integrated surface water-groundwater hydrologic model of the entire continental China using ParFlow. The model shows good performance of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Liubov Poshyvailo-Strube, Niklas Wagner, Klaus Goergen, Carina Furusho-Percot, Carl Hartick, and Stefan Kollet
Earth Syst. Dynam., 15, 167–189, https://doi.org/10.5194/esd-15-167-2024, https://doi.org/10.5194/esd-15-167-2024, 2024
Short summary
Short summary
Groundwater (GW) representation is simplified in most regional climate models. Here, we introduce a unique Terrestrial Systems Modeling Platform (TSMP) dataset with an explicit representation of GW, in the context of dynamical downscaling of GCMs for climate change studies. We compare the heat events statistics of TSMP and the CORDEX ensemble. Our results show that TSMP systematically simulates fewer heat waves, and they are shorter and less intense.
Jennie C. Steyaert and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 1071–1088, https://doi.org/10.5194/hess-28-1071-2024, https://doi.org/10.5194/hess-28-1071-2024, 2024
Short summary
Short summary
Reservoirs impact all river systems in the United States, yet their operations are difficult to quantify due to limited data. Using historical reservoir operations, we find that storage has declined over the past 40 years, with clear regional differences. We observe that active storage ranges are increasing in arid regions and decreasing in humid regions. By evaluating reservoir model assumptions, we find that they may miss out on seasonal dynamics and can underestimate storage.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
Short summary
Short summary
Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
Short summary
Short summary
Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
Short summary
Short summary
Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Zbigniew P. Piotrowski, Jaro Hokkanen, Daniel Caviedes-Voullieme, Olaf Stein, and Stefan Kollet
EGUsphere, https://doi.org/10.5194/egusphere-2023-1079, https://doi.org/10.5194/egusphere-2023-1079, 2023
Preprint withdrawn
Short summary
Short summary
The computer programs capable of simulation of Earth system components evolve, adapting new fundamental science concepts and more observational data on more and more powerful computer hardware. Adaptation of a large scientific program to a new type of hardware is costly. In this work we propose cheap and simple but effective strategy that enable computation using graphic processing units, based on automated program code modification. This results in better resolution and/or longer predictions.
Amanda Triplett and Laura E. Condon
Hydrol. Earth Syst. Sci., 27, 2763–2785, https://doi.org/10.5194/hess-27-2763-2023, https://doi.org/10.5194/hess-27-2763-2023, 2023
Short summary
Short summary
Accelerated melting in mountains is a global phenomenon. The Heihe River basin depends on upstream mountains for its water supply. We built a hydrologic model to examine how shifts in streamflow and warming will impact ground and surface water interactions. The results indicate that degrading permafrost has a larger effect than melting glaciers. Additionally, warming temperatures tend to have more impact than changes to streamflow. These results can inform other mountain–valley system studies.
Tobias Tesch, Stefan Kollet, and Jochen Garcke
Geosci. Model Dev., 16, 2149–2166, https://doi.org/10.5194/gmd-16-2149-2023, https://doi.org/10.5194/gmd-16-2149-2023, 2023
Short summary
Short summary
A recent statistical approach for studying relations in the Earth system is to train deep learning (DL) models to predict Earth system variables given one or several others and use interpretable DL to analyze the relations learned by the models. Here, we propose to combine the approach with a theorem from causality research to ensure that the deep learning model learns causal rather than spurious relations. As an example, we apply the method to study soil-moisture–precipitation coupling.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura E. Condon
EGUsphere, https://doi.org/10.5194/egusphere-2023-666, https://doi.org/10.5194/egusphere-2023-666, 2023
Preprint archived
Short summary
Short summary
Long Short-Term Memory (LSTM) is a widely-used machine learning (ML) model in hydrology. However, it is difficult to extract knowledge from it. We propose HydroLSTM which represents processes analogous to a hydrological reservoir. Models using HydroLSTM perform similarly to LSTM but require fewer cell states. The learned parameters are informative about the dominant hydroclimatic characteristics of a catchment. Our results demonstrate how hydrological knowledge is encoded in the new structure.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
Short summary
Short summary
It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
Short summary
Short summary
We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
Mohamed Saadi, Carina Furusho-Percot, Alexandre Belleflamme, Ju-Yu Chen, Silke Trömel, and Stefan Kollet
Nat. Hazards Earth Syst. Sci., 23, 159–177, https://doi.org/10.5194/nhess-23-159-2023, https://doi.org/10.5194/nhess-23-159-2023, 2023
Short summary
Short summary
On 14 July 2021, heavy rainfall fell over central Europe, causing considerable damage and human fatalities. We analyzed how accurate our estimates of rainfall and peak flow were for these flooding events in western Germany. We found that the rainfall estimates from radar measurements were improved by including polarimetric variables and their vertical gradients. Peak flow estimates were highly uncertain due to uncertainties in hydrological model parameters and rainfall measurements.
Aniket Gupta, Alix Reverdy, Jean-Martial Cohard, Basile Hector, Marc Descloitres, Jean-Pierre Vandervaere, Catherine Coulaud, Romain Biron, Lucie Liger, Reed Maxwell, Jean-Gabriel Valay, and Didier Voisin
Hydrol. Earth Syst. Sci., 27, 191–212, https://doi.org/10.5194/hess-27-191-2023, https://doi.org/10.5194/hess-27-191-2023, 2023
Short summary
Short summary
Patchy snow cover during spring impacts mountainous ecosystems on a large range of spatio-temporal scales. A hydrological model simulated such snow patchiness at 10 m resolution. Slope and orientation controls precipitation, radiation, and wind generate differences in snowmelt, subsurface storage, streamflow, and evapotranspiration. The snow patchiness increases the duration of the snowmelt to stream and subsurface storage, which sustains the plants and streamflow later in the summer.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-345, https://doi.org/10.5194/hess-2022-345, 2022
Publication in HESS not foreseen
Short summary
Short summary
As the stress on water resources from climate change grows, we need models that represent water processes at the scale of counties, states, and even countries in order to make viable predictions about things will change. While such models are powerful, they can be cumbersome to deal with because they are so large. This research explores a novel way of increasing the efficiency of large-scale hydrologic models using an approach called Simulation-Based Inference.
Jennie C. Steyaert and Laura E. Condon
EGUsphere, https://doi.org/10.5194/egusphere-2022-1051, https://doi.org/10.5194/egusphere-2022-1051, 2022
Preprint archived
Short summary
Short summary
All river systems in the US are impacted by dams, yet analyses are limited by a lack of data. We use the first national dataset of reservoir data to analyze reservoir storage trends from 1980–2019. We show that reservoir storage has decreased over the past 40 years. The range in monthly storage has increased over time in drier regions and decreased in wetter ones. Lastly, we find that most regions have reservoir storage that takes longer to recover from and are therefore more vulnerable.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
Short summary
Short summary
Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Mary M. F. O'Neill, Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell
Geosci. Model Dev., 14, 7223–7254, https://doi.org/10.5194/gmd-14-7223-2021, https://doi.org/10.5194/gmd-14-7223-2021, 2021
Short summary
Short summary
Modeling the hydrologic cycle at high resolution and at large spatial scales is an incredible opportunity and challenge for hydrologists. In this paper, we present the results of a high-resolution hydrologic simulation configured over the contiguous United States. We discuss simulated water fluxes through groundwater, soil, plants, and over land, and we compare model results to in situ observations and satellite products in order to build confidence and guide future model development.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
Short summary
Short summary
In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Jun Zhang, Laura E. Condon, Hoang Tran, and Reed M. Maxwell
Earth Syst. Sci. Data, 13, 3263–3279, https://doi.org/10.5194/essd-13-3263-2021, https://doi.org/10.5194/essd-13-3263-2021, 2021
Short summary
Short summary
Existing national topographic datasets for the US may not be compatible with gridded hydrologic models. A national topographic dataset developed to support physically based hydrologic models at 1 km and 250 m over the contiguous US is provided. We used a Priority Flood algorithm to ensure hydrologically consistent drainage networks and evaluated the performance with an integrated hydrologic model. Datasets and scripts are available for direct data usage or modification of processing as desired.
Yueling Ma, Carsten Montzka, Bagher Bayat, and Stefan Kollet
Hydrol. Earth Syst. Sci., 25, 3555–3575, https://doi.org/10.5194/hess-25-3555-2021, https://doi.org/10.5194/hess-25-3555-2021, 2021
Short summary
Short summary
This study utilized spatiotemporally continuous precipitation anomaly (pra) and water table depth anomaly (wtda) data from integrated hydrologic simulation results over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the time-varying and time-lagged relationship between pra and wtda in order to obtain reliable models to estimate wtda at the individual pixel level.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Stephen R. Maples, Laura Foglia, Graham E. Fogg, and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 24, 2437–2456, https://doi.org/10.5194/hess-24-2437-2020, https://doi.org/10.5194/hess-24-2437-2020, 2020
Short summary
Short summary
In this study, we use a combination of local- and global-sensitivity analyses to evaluate the relative importance of (1) the configuration of subsurface alluvial geology and (2) the hydraulic properties of geologic facies on recharge processes. Results show that there is a large variation of recharge rates possible in a typical alluvial aquifer system and that the configuration proportion of sand and gravel deposits in the subsurface have a large impact on recharge rates.
Annette Hein, Laura Condon, and Reed Maxwell
Hydrol. Earth Syst. Sci., 23, 1931–1950, https://doi.org/10.5194/hess-23-1931-2019, https://doi.org/10.5194/hess-23-1931-2019, 2019
Short summary
Short summary
Drought is a natural disaster that can result from changes to temperature, precipitation and/or vegetation. Here we apply a
high-resolution computer model to explore the relative importance of each factor on the North American High Plains, one of the most important agricultural regions of the USA. Decreased precipitation caused larger changes in hydrologic variables (evapotranspiration, soil moisture, stream flow and water table levels) than increased temperature or disturbed vegetation did.
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277–301, https://doi.org/10.5194/hess-23-277-2019, https://doi.org/10.5194/hess-23-277-2019, 2019
Short summary
Short summary
This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
Wendy Sharples, Ilya Zhukov, Markus Geimer, Klaus Goergen, Sebastian Luehrs, Thomas Breuer, Bibi Naz, Ketan Kulkarni, Slavko Brdar, and Stefan Kollet
Geosci. Model Dev., 11, 2875–2895, https://doi.org/10.5194/gmd-11-2875-2018, https://doi.org/10.5194/gmd-11-2875-2018, 2018
Short summary
Short summary
Next-generation geoscientific models are based on complex model implementations and workflows. Next-generation HPC systems require new programming paradigms and code optimization. In order to meet the challenge of running complex simulations on new massively parallel HPC systems, we developed a run control framework that facilitates code portability, code profiling, and provenance tracking to reduce both the duration and the cost of code migration and development, while ensuring reproducibility.
David J. Gardner, Jorge E. Guerra, François P. Hamon, Daniel R. Reynolds, Paul A. Ullrich, and Carol S. Woodward
Geosci. Model Dev., 11, 1497–1515, https://doi.org/10.5194/gmd-11-1497-2018, https://doi.org/10.5194/gmd-11-1497-2018, 2018
Short summary
Short summary
As the computational power of supercomputing systems increases, and models for simulating the fluid flow of the Earth's atmosphere operate at higher resolutions, new approaches for advancing these models in time will be necessary. In order to produce the best possible result in the least amount of time, we evaluate a number of splittings, methods, and solvers on two test cases. Based on these results, we identify the most accurate and efficient approaches for consideration in production models.
Laura E. Condon and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 21, 1117–1135, https://doi.org/10.5194/hess-21-1117-2017, https://doi.org/10.5194/hess-21-1117-2017, 2017
Short summary
Short summary
We evaluate the impact of groundwater–surface water exchanges on the fraction of precipitation that leaves a watershed as either surface runoff or evapotranspiration. Results show that groundwater storage can systematically influence watershed behavior at the land surface. This is an important finding because most studies of tradeoffs between runoff and evapotranspiration assume that watersheds are in a steady-state condition where there are no net exchanges between the surface and subsurface.
James M. Gilbert and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 21, 923–947, https://doi.org/10.5194/hess-21-923-2017, https://doi.org/10.5194/hess-21-923-2017, 2017
Short summary
Short summary
Understanding how groundwater and streamflow interact over large areas is a challenge. In this study we use a computer simulation that calculates water movement and storage at the land surface and in the subsurface within California's San Joaquin River basin to analyze different parts of the watershed. Results show that the mountains may be an important source of groundwater to the Central Valley while differences in relative speed of groundwater and river flow affect their connection patterns.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
Short summary
Short summary
In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
Stefan J. Kollet
Hydrol. Earth Syst. Sci., 20, 2801–2809, https://doi.org/10.5194/hess-20-2801-2016, https://doi.org/10.5194/hess-20-2801-2016, 2016
Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, https://doi.org/10.5194/gmd-9-1341-2016, 2016
Short summary
Short summary
This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library.
Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP.
Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
P. Shrestha, M. Sulis, C. Simmer, and S. Kollet
Hydrol. Earth Syst. Sci., 19, 4317–4326, https://doi.org/10.5194/hess-19-4317-2015, https://doi.org/10.5194/hess-19-4317-2015, 2015
Short summary
Short summary
This study highlights the grid resolution dependence of energy and water balance of the 3-D physically based integrated surface-groundwater model. The non-local controls of soil moisture were found to be highly grid resolution dependent, but the local vegetation control strongly modulates the scaling behavior of surface energy fluxes. For coupled runs, variability in patterns of surface fluxes due to this scale dependence can affect the simulated atmospheric boundary layer and local circulation.
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-7395-2015, https://doi.org/10.5194/gmdd-8-7395-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
R. M. Maxwell, L. E. Condon, and S. J. Kollet
Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, https://doi.org/10.5194/gmd-8-923-2015, 2015
Short summary
Short summary
A model that simulates groundwater and surface water flow has been developed for the major river basins of the continental United States. Fundamental data sets provide input to the model resulting in a natural organization of stream networks and groundwater flow that is compared to observations of surface water and groundwater. Model results show relationships between flow and area that are moderated by aridity and represent an important step toward integrated hydrological prediction.
L. E. Condon, S. Gangopadhyay, and T. Pruitt
Hydrol. Earth Syst. Sci., 19, 159–175, https://doi.org/10.5194/hess-19-159-2015, https://doi.org/10.5194/hess-19-159-2015, 2015
F. Gasper, K. Goergen, P. Shrestha, M. Sulis, J. Rihani, M. Geimer, and S. Kollet
Geosci. Model Dev., 7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, https://doi.org/10.5194/gmd-7-2531-2014, 2014
Related subject area
Climate and Earth system modeling
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
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
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
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
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Reducing Time and Computing Costs in EC-Earth: An Automatic Load-Balancing Approach for Coupled ESMs
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
Short summary
Short summary
We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. 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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
Short summary
Short summary
This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-155, https://doi.org/10.5194/gmd-2024-155, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This work presents an automatic tool to enhance the performance of climate models by optimizing how computer resources are allocated. Traditional methods are time-consuming and error-prone, often resulting in inefficient simulations. Our tool improves speed and reduces computational costs without needing expert knowledge. The tool has been tested on European climate models, making simulations up to 34 % faster while using fewer resources, helping to make climate simulations more efficient.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
Short summary
Short summary
We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
Cited articles
Abu-El-Sha'r, W. Y. and Rihani, J. F.: Application of the high performance
computing techniques of parflow simulator to model groundwater flow at Azraq
basin, Water Resour. Manage., 21, 409–425, https://doi.org/10.1007/s11269-006-9023-5,
2007.
Ajami, H., McCabe, H. M., Evans, J. P., and Stisen, S.: Assessing the impact of model spin-up on surface water-groundwater interactions using an integrated hydrologic model, Water Resour. Res., 50, 2636–2656, https://doi.org/10.1002/2013WR014258, 2014.
Ajami, H., McCabe, M. F., and Evans, J. P.: Impacts of model initialization
on an integrated surface water-groundwater model, Hydrol. Process., 29, 3790–3801, https://doi.org/10.1002/hyp.10478, 2015.
Allievi, A. and Calisal, S. M.: Application of Bubnov-Galerkin formulation
to orthogonal grid generation, J. Comput. Phys., 98, 163–173,
https://doi.org/10.1016/0021-9991(92)90181-W, 1992.
Amdahl, G. M.: Validity of the single processor approach to achieving large
scale computing capabilities, in spring joint computer conference, Vol. 37,
256–259, 1967.
Anyah, R. O., Weaver, C. P., Miguez-Macho, G., Fan, Y., and Robock, A.:
Incorporating water table dynamics in climate modeling: 3. Simulated
groundwater influence on coupled land-atmosphere variability, J. Geophys.
Res.-Atmos., 113, 1–15, https://doi.org/10.1029/2007JD009087, 2008.
Ashby, S. F. and Falgout, R. D.: A Parallel Multigrid Preconditioned
Conjugate Gradient Algorithm for Groundwater Flow Simulations, Nucl. Sci.
Eng., 124, 145–159, 1996.
Ashby, S. F., Falgout, R. D., Smith, S. G., and Tompson, A. F. B.: Modeling
groundwater flow on MPPs, Proc. Scalable Parallel Libr. Conf., 17–25,
https://doi.org/10.1109/SPLC.1993.365586, 1993.
Ashby, S. F., Falgout, R. D., Tompson, A., and Fogwell, T.: Numerical
simulation of groundwater flow on MPPs, 17–25, 1994.
Ashby, S. F., Falgout, R. D., and Tompson, A. F. B.: A Scalable Approach to
Modeling Groundwater Flow on Massively Parallel Computers, in In Next
Generation Environmental Models and Computational Methods, Vol. 87, 201,
1997.
Atchley, A. L. and Maxwell, R. M.: Influences of subsurface heterogeneity
and vegetation cover on soil moisture, surface temperature and
evapotranspiration at hillslope scales, Hydrogeol. J., 19, 289–305,
https://doi.org/10.1007/s10040-010-0690-1, 2011.
Atchley, A. L., Maxwell, R. M., and Navarre-Sitchler, A. K.: Human health
risk assessment of CO2 leakage into overlying aquifers using a stochastic,
geochemical reactive transport approach, Environ. Sci. Technol., 47,
5954–5962, https://doi.org/10.1021/es400316c, 2013.
Baldauf, M., Seifert, A., Forstner, J., Majewski, D., and Raschendorfer, M.:
Operational Convective-Scale Numerical Weather Prediction with the COSMO
Model?: Description and Sensitivities, Am. Meteorol. Soc., 3887–3905,
https://doi.org/10.1175/MWR-D-10-05013.1, 2011.
Beisman, J.: Development of a parallel reactive transport model
with spatially variable nitrate reduction in a floodplain aquifer, A thesis submitted to the Faculty and the Board of Trustees of the Colorado School of Mines in partial fulfillment of the requirements for the degree of Master of Science (Hydrology), 2007.
Beisman, J. J., Maxwell, R. M., Navarre-Sitchler, A. K., Steefel, C. I., and
Molins, S.: ParCrunchFlow: an efficient, parallel reactive transport
simulation tool for physically and chemically heterogeneous saturated
subsurface environments, Comput. Geosci., 19, 403–422,
https://doi.org/10.1007/s10596-015-9475-x, 2015.
Benson, D. A., Aquino, T., Bolster, D., Engdahl, N., Henri, C. V., and Fernandez-Garcia, D.: A comparison of Eulerian and Lagrangian transport and non-linear reaction algorithms, Adv. Water Resour., 99, 15–37, 2017.
Bettems, J. M., Asensio, H., Bonafe, Duniec, G., Fuhrer, O., Helmert, J.,
Heret, C., Kazakova, E., Lange, Machulskaya, E., Mazur, A., De Morsier, G.,
Rianna, G., Rozinkina, I., Vieli, B., and Vogel, G.: The COSMO Priority Project
“COLOBOC”: Final Technical Report No 27, 2015.
Beven, K.: Robert E. Horton's perceptual model of infiltration processes,
Hydrol. Process., 18, 3447–3460, https://doi.org/10.1002/hyp.5740, 2004.
Bhaskar, A. S., Welty, C., Maxwell, R. M., and Miller, A. J.: Untangling the
effects of urban development on subsurface storage in Baltimore, Water
Resour. Res., 51, 1158–1181, https://doi.org/10.1002/2014WR016039, 2015.
Briggs, W. L., Henson, V. E., and McCormick, S. F.: A Multigrid Tutorial, 72, Siam, ISBN 13978-0898714623, https://doi.org/10.1137/1.9780898719505, 2000.
Brown, P. N. and Saad, Y.: Hybrid Krylov Methods for Nonlinear Systems of
Equations, SIAM J. Sci. Stat. Comput., 11, 450–481, https://doi.org/10.1137/0911026,
1990.
Burstedde, C., Fonseca, J. A., and Kollet, S.: Enhancing speed and
scalability of the ParFlow simulation code, Comput. Geosci., 22,
347–361, https://doi.org/10.1007/s10596-017-9696-2, 2018.
Camporese, M., Paniconi, C., Putti, M., and Orlandini, S.:
Surface-subsurface flow modeling with path-based runoff routing, boundary
condition-based coupling, and assimilation of multisource observation data,
Water Resour. Res., 46, W02512, https://doi.org/10.1029/2008WR007536, 2010.
Castronova, A. M., Goodall, J. L., and Ercan, M. B.: Integrated modeling within a hydrologic information system: an OpenMI based approach, Environ. Model. Softw., 39, 263–273, 2013.
Celia, M. A., Bouloutas, E. T., and Zarba, R. L.: A general
mass-conservative numerical solution for the unsaturated flow equation,
Water Resour. Res., 26, 1483–1496, https://doi.org/10.1029/WR026i007p01483, 1990.
Chow, F. K., Kollet, S. J., Maxwell, R. M., and Duan, Q.: Effects of Soil
Moisture Heterogeneity on Boundary Layer Flow with Coupled Groundwater,
Land-Surface, and Mesoscale Atmospheric Modeling, 17th Symp. Bound. Laters
Turbul., https://doi.org/10.1016/j.phrs.2010.10.003, 2006.
Collier, A. M., Hindmarsh, A. C., Serban, R., and Woodward, C. S.: User
Documentation for kinsol v2.8.2 (SUNDIALS v2.6.2), 1, 120, 2015.
Condon, L. E. and Maxwell, R. M.: Implementation of a linear optimization
water allocation algorithm into a fully integrated physical hydrology model,
Adv. Water Resour., 60, 135–147, https://doi.org/10.1016/j.advwatres.2013.07.012, 2013.
Condon, L. E. and Maxwell, R. M.: Groundwater-fed irrigation impacts
spatially distributed temporal scaling behavior of the natural system: a
spatio-temporal framework for understanding water management impacts,
Environ. Res. Lett., 9, 034009, https://doi.org/10.1088/1748-9326/9/3/034009, 2014.
Condon, L. E. and Maxwell, R. M.: Evaluating the relationship between
topography and groundwater using outputs from a continental-scale integrated
hydrology model, Water Resour. Res., 51, 6602–6621,
https://doi.org/10.1002/2014WR016774, 2015.
Condon, L. E., Maxwell, R. M., and Gangopadhyay, S.: The impact of
subsurface conceptualization on land energy fluxes, Adv. Water Resour., 60,
188–203, https://doi.org/10.1016/J.ADVWATRES.2013.08.001, 2013.
Condon, L. E., Hering, A. S., and Maxwell, R. M.: Quantitative assessment of
groundwater controls across major US river basins using a multi-model
regression algorithm, Adv. Water Resour., 82, 106–123,
https://doi.org/10.1016/J.ADVWATRES.2015.04.008, 2015.
Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich, M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G., and Oleson, K. W.: The Common Land Model, B. Am. Meteorol. Soc., 84,
1013–1023, https://doi.org/10.1175/BAMS-84-8-1013, 2003.
Dembo, R. S. and Eisenstat, S. C.: Inexact newton methods, in: SIAM J.
Numer. Anal., Vol. 19, 400–408, 1982.
Dennis Jr., J. E. and Schnabel, R. B.: Numerical methods for unconstrained optimization and nonlinear equations, Vol. 16, Siam, 1996.
Duniec, G. and Mazur, A.: COLOBOC-MOSAIC parameterization in COSMO model v. 4.8, COSMO Newsletter, 11, 69–81, 2011.
Durbin, P.: An Approach to Local Refinement of Structured Grids An Approach
to Local Refinement of Structured Grids, J. Comput. Phys., 181, 639–653,
https://doi.org/10.1006/jcph.2002.7147, 2002.
Eca, L.: 2D orthogonal grid generation with boundary point distribution
control, J. Comput. Phys., 125, 440–453, https://doi.org/10.1006/jcph.1996.0106,
1996.
Eisenstat, S. C. and Walker, H. F.: Choosing the Forcing Terms in an
Inexact Newton Method, SIAM J. Sci. Comput., 17, 16–32,
https://doi.org/10.1137/0917003, 1996.
Ek, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V.,
Gayno, G., and Tarpley, J. D.: Implementation of Noah land surface model
advances in the National Centers for Environmental Prediction operational
mesoscale Eta model, J. Geophys. Res.-Atmos., 108, 8851,
https://doi.org/10.1029/2002JD003296, 2003.
Engdahl, N. B. and Maxwell, R. M.: Quantifying changes in age distributions
and the hydrologic balance of a high-mountain watershed from climate induced
variations in recharge, J. Hydrol., 522, 152–162,
https://doi.org/10.1016/j.jhydrol.2014.12.032, 2015.
Engdahl, N. B., McCallum, J. L., and Massoudieh, A.: Transient age distributions in subsurface hydrologic systems, J. Hydrol., 543, 88–100, 2016.
Falgout, R. D. and Yang, U. M.: Hypre: A Library of High Performance
Preconditioners, in International Conference on Computational Science,
632–641, Springer, Berlin, 2002.
Falgout, R. D., Baldwin, C., Bosl, W., Hornung, R., Shumaker, D., Smith, S., Woodward, C. S., and Tompson, A. F. B.: Enabling computational technologies for subsurface simulations, No. UCRL-ID-133255, 97-ERD-035, WM1025000, Lawrence Livermore National Lab., CA (US), 1999.
Ferguson, I. M. and Maxwell, R. M.: Groundwater-Land Surface-Atmosphere
Feedbacks: Impacts of Groundwater Pumping and Irrigation on Land-Atmosphere
Interactions, Proc. xviii Int. Conf. Comput. Methods Water Resour.,
722–729, 2010.
Ferguson, I. M. and Maxwell, R. M.: Hydrologic and land-energy feedbacks of agricultural water management practices, Environ. Res. Lett., 6, 014006, https://doi.org/10.1088/1748-9326/6/1/014006, 2011.
Ferguson, I. M. and Maxwell, R. M.: Human impacts on terrestrial hydrology:
climate change versus pumping and irrigation, Environ. Res. Lett., 7,
044022, https://doi.org/10.1088/1748-9326/7/4/044022, 2012.
Ferguson, I. M., Jefferson, J. L., Maxwell, R. M., and Kollet, S. J.: Effects of root water uptake formulation on simulated water and energy budgets at local and basin scales, Environ. Earth Sci., 75, 316, https://doi.org/10.1007/s12665-015-5041-z, 2016.
Frei, S., Fleckenstein, J. H., Kollet, S. J., and Maxwell, R. M.: Patterns
and dynamics of river-aquifer exchange with variably-saturated flow using a
fully-coupled model, J. Hydrol., 375, 383–393,
https://doi.org/10.1016/j.jhydrol.2009.06.038, 2009.
Gasper, F., Goergen, K., Shrestha, P., Sulis, M., Rihani, J., Geimer, M., and Kollet, S.: Implementation and scaling of the fully coupled Terrestrial Systems Modeling Platform (TerrSysMP v1.0) in a massively parallel supercomputing environment – a case study on JUQUEEN (IBM Blue Gene/Q), Geosci. Model Dev., 7, 2531–2543, https://doi.org/10.5194/gmd-7-2531-2014, 2014.
Gebler, S., Kollet, S., Qu, W., and Vereecken, H.: High resolution modelling
of soil moisture patterns with ParFlow-CLM?: Comparison with sensor network
data, in: EGU General Assembly Conference Abstracts, 17, 2015.
Gilbert, J. M. and Maxwell, R. M.: Examining regional groundwater–surface water dynamics using an integrated hydrologic model of the San Joaquin River basin, Hydrol. Earth Syst. Sci., 21, 923–947, https://doi.org/10.5194/hess-21-923-2017, 2017.
Gustafson, J. L.: Reevaluating amdahl's law, Communications of the ACM, 31, 532–533, 1988.
Haussling, H. and Coleman, R.: A method for generation of orthogonal and
nearly orthogonal boundary-fitted coordinate systems, J. Comput. Phys.,
43, 373–381, https://doi.org/10.1016/0021-9991(81)90129-7, 1981.
Hindmarsh, A. C., Brown, P. N., Grant, K. E., Lee, S. L., Serban, R.,
Shumaker, D. E., and Woodward, C. S.: SUNDIALS: Suite of nonlinear and
differential/algebraic equation solvers, ACM Trans. Math. Softw., 31,
363–396, https://doi.org/10.1145/1089014.1089020, 2005.
Jefferson, J. L. and Maxwell, R. M.: Evaluation of simple to complex parameterizations of bare ground evaporation, J. Adv. Model. Earth Syst., 7, 1075–1092, https://doi.org/10.1002/2014MS000398, 2015.
Jefferson, J. L., Gilbert, J. M., Constantine, P. G., and Maxwell, R.M.:
Active subspaces for sensitivity analysis and dimension reduction of an
integrated hydrologic model, Comput. Geosci., 83, 127–138,
https://doi.org/10.1016/j.cageo.2015.07.001, 2015.
Jefferson, J. L., Maxwell,R. M., and Constantine, P. G.: Exploring the
Sensitivity of Photosynthesis and Stomatal Resistance Parameters in a Land
Surface Model, J. Hydrometeorol., 18, 897–915,
https://doi.org/10.1175/JHM-D-16-0053.1, 2017.
Jiang, X., Niu, G. Y., and Yang, Z. L.: Impacts of vegetation and
groundwater dynamics on warm season precipitation over the Central United
States, J. Geophys. Res.-Atmos., 114, 1–15, https://doi.org/10.1029/2008JD010756,
2009.
Jones, J. E. and Woodward, C. S.: Preconditioning Newton- Krylov Methods
for Variably Saturated Flow, in 13th International Conference on
Computational Methods in Water Resources, Calgary, Alberta, Canada, 2000.
Jones, J. E. and Woodward, C. S.: Newton-Krylov-multigrid solvers for
large-scale, highly heterogeneous, variably saturated flow problems, Adv.
Water Resour., 24, 763–774, https://doi.org/10.1016/S0309-1708(00)00075-0, 2001.
Keune, J., Gasper, F., Goergen, K., Hense, A., Shrestha, P., Sulis, M., and
Kollet, S.: Studying the influence of groundwater representations on land
surface-atmosphere feedbacks during the European heat wave in 2003, J.
Geophys. Res., 121, 13301–13325, https://doi.org/10.1002/2016JD025426, 2016.
Khorsandi, E., Kollet, S., Venema, V., and Simmer, C.: Investigating the
effect of bottom boundary condition placement on ground heat storage in
climate time scale simulations using ParflowE, Geophys. Res., 16, EGU2014-931,
https://doi.org/10.1029/2006GL028546, 2014.
Kirkner, D. J. and Reeves, H.: Multicomponent Mass Transport With
Homogeneous and Heterogeneous Chemical Reactions' Effect of the Chemistry on
the Choice of Numerical Algorithm 1. Theory, Water Resour. Res., 24, 1719–1729, 1988.
Koch, J., Cornelissen, T., Fang, Z., Bogena, H., Diekkrüger, B., Kollet,
S., and Stisen, S.: Inter-comparison of three distributed hydrological
models with respect to seasonal variability of soil moisture patterns at a
small forested catchment, J. Hydrol., 533, 234–249, https://doi.org/10.1016/j.jhydrol.2015.12.002,
2016.
Kollet, S., Sulis, M., Maxwell, R. M., Paniconi, C., Putti, M., Bertoldi, G., Coon, E. T., Cordano, E., Endrizzi S., Kikinzon, E., Mouche, E., Mugler, C., Park, Y., Refsgaard, J. C., Stisen, S., and Sudicky, E.: The integrated hydrologic model intercomparison project, IH‐MIP2: A second set of benchmark results to diagnose integrated hydrology and feedbacks, Water Resour. Res., 53, 867–890, 2017.
Kollet, S. J.: Influence of soil heterogeneity on evapotranspiration under
shallow water table conditions: transient, stochastic simulations, Environ.
Res. Lett., 4, 035007, https://doi.org/10.1088/1748-9326/4/3/035007, 2009.
Kollet, S. J.: Technical note: Inference in hydrology from entropy balance considerations, Hydrol. Earth Syst. Sci., 20, 2801–2809, https://doi.org/10.5194/hess-20-2801-2016, 2016.
Kollet, S. J. and Maxwell, R. M.: Integrated surface-groundwater flow
modeling: A free-surface overland flow boundary condition in a parallel
groundwater flow model, Adv. Water Resour., 29, 945–958,
https://doi.org/10.1016/j.advwatres.2005.08.006, 2006.
Kollet, S. J. and Maxwell, R. M.: Capturing the influence of groundwater
dynamics on land surface processes using an integrated, distributed
watershed model, Water Resour. Res., 44, 1–18, https://doi.org/10.1029/2007WR006004,
2008a.
Kollet, S. J. and Maxwell, R. M.: Demonstrating fractal scaling of baseflow
residence time distributions using a fully-coupled groundwater and land
surface model, Geophys. Res. Lett., 35, 1–6, https://doi.org/10.1029/2008GL033215,
2008b.
Kollet, S. J., Cvijanovic, I., Schüttemeyer, D., Maxwell, R. M., Moene,
A. F., and Bayer, P.: The Influence of Rain Sensible Heat and Subsurface
Energy Transport on the Energy Balance at the Land Surface, Vadose Zone J.,
8, 846, https://doi.org/10.2136/vzj2009.0005, 2009.
Kollet, S. J., Maxwell, R. M., Woodward, C. S., Smith, S., Vanderborght, J.,
Vereecken, H., and Simmer, C.: Proof of concept of regional scale hydrologic
simulations at hydrologic resolution utilizing massively parallel computer
resources, Water Resour. Res., 46, 1–7, https://doi.org/10.1029/2009WR008730, 2010.
Kuffour, B. N. O.: Parflow-350/parflow: ParFlow Version 3.5.0, Zenodo, https://doi.org/10.5281/zenodo.3555297, 2019.
Kumar, M., Duffy, C. J., and Salvage, K. M.: A second-order accurate, finite
volume–based, integrated hydrologic modeling (FIHM) framework for
simulation of surface and subsurface flow, Vadose Zone J., 8, 873,
https://doi.org/10.2136/vzj2009.0014, 2009.
LaBolle, E. M., Ahmed, A. A., and Fogg, G. E.: Review of the Integrated
Groundwater and Surface-Water Model (IGSM), Ground Water, 41, 238–246,
https://doi.org/10.1111/j.1745-6584.2003.tb02587.x, 2003.
Levis, S. and Jaeger, E. B.: COSMO-CLM2?: a new version of the COSMO- CLM
model coupled to the Community Land Model coupled to the Community Land
Model, Clim. Dynam., 37, 1889–1907, https://doi.org/10.1007/s00382-011-1019-z,
2011.
Li, L., Steefel, C. I., Kowalsky, M. B., Englert, A., and Hubbard, S. S.:
Effects of physical and geochemical heterogeneities on mineral
transformation and biomass accumulation during uranium bioremediation at
Rifle, Colorado, J. Contam. Hydrol., 11, 45–63, 2010.
Li, L., Steefel, C. I., and Yang, L.: Scale dependence of mineral
dissolution rates within single pores and fractures, Geochim. Cosmochim.
Acta, 72, 360–377, https://doi.org/10.1016/j.gca.2007.10.027, 2007.
Markstrom, S. L., Niswonger, R. G., Regan, R. S., Prudic, D. E., and Barlow,
P. M.: GSFLOW – Coupled Ground-Water and Surface-Water Flow Model Based on
the Integration of the Precipitation-Runoff Modeling System (PRMS) and the
Modular Ground-Water Flow Model (MODFLOW-2005), U.S. Geol. Surv.,
(Techniques and Methods 6-D1), 240, 2008.
Maxwell, R. M. and Miller, N. L.: Development of a Coupled Land Surface and
Groundwater Model, J. Hydrometeorol., 6, 233–247, https://doi.org/10.1175/JHM422.1,
2005.
Maxwell, R. M.: Infiltration in Arid Environments: Spatial Patterns between
Subsurface Heterogeneity and Water-Energy Balances, Vadose Zone J., 9,
970, https://doi.org/10.2136/vzj2010.0014, 2010.
Maxwell, R. M.: A terrain-following grid transform and preconditioner for
parallel, large-scale, integrated hydrologic modeling, Adv. Water Resour.,
53, 109–117, https://doi.org/10.1016/j.advwatres.2012.10.001, 2013.
Maxwell, R. M., Welty, C., and Tompson, A. F. B.: Streamline-based
simulation of virus transport resulting from long term artificial recharge
in a heterogeneous aquifer, Adv. Water Resour., 26, 1075–1096,
https://doi.org/10.1016/S0309-1708(03)00074-5, 2003.
Maxwell, R. M., Chow, F. K., and Kollet, S. J.: The
groundwater–land-surface–atmosphere connection: Soil moisture effects on
the atmospheric boundary layer in fully-coupled simulations, Adv. Water
Resour., 30, 2447–2466, https://doi.org/10.1016/j.advwatres.2007.05.018, 2007.
Maxwell, R. M., Lundquist, J. K., Mirocha, J. D., Smith, S. G., Woodward, C.
S., and Tompson, A. F. B.: Development of a Coupled Groundwater–Atmosphere
Model, Mon. Weather Rev., 139, 96–116, https://doi.org/10.1175/2010MWR3392.1, 2011.
Maxwell, R. M., Putti, M., Meyerhoff, S., Delfs, J., Ferguson, I. M., Ivanov, V., Kim, J., Kolditz, O., Kollet, S. J., Kumar, M., Lopez, S., Niu, J., Paniconi, C., Park, Y., Phanikumar, M. S., Shen, C., Sudicky, A., and Sulis, M.: Surface-subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks, Water Resour. Res., 50, 1531–1549, https://doi.org/10.1002/2013WR013725, 2014.
Maxwell, R. M., Condon, L. E., and Kollet, S. J.: A high-resolution simulation of groundwater and surface water over most of the continental US with the integrated hydrologic model ParFlow v3, Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, 2015.
Maxwell, R. M., Kollet, S. J., Smith, S. G., Woodward, C. S., Falgout, R. D., Ferguson, I. M., Engdahl, N. B., Condon, L. E., Hector, B., Lopez, S., Gilbert, J., Bearup, L., Jefferson, J., Collins, C., De Graaf, I., Pribulick, C., Baldwin, C., Bosl, W. J., Hornung, R., and Ashby, S.: ParFlow User's Manual, Integrated GroundWater Modeling Center Report GWMI, 167 p., 2016.
Meehl, G. A., Covey, C., McAvaney, B., Latif, M., and Stouffer, R. J.:
Overview of the coupled model intercomparison project, B. Am. Meteorol.
Soc., 86, 89–93, https://doi.org/10.1175/BAMS-86-1-89, 2005.
Meyerhoff, S. B. and Maxwell, R. M.: Using an integrated surface-subsurface
model to simulate runoff from heterogeneous hillslopes, in xviii
International Conference on Water Resources, CIMNE, Barcelona, 2010.
Michalakes, J., Dudhia, J., Gill, D., Klemp, J., and Skamarock, W.: Design
of a next-generation regional weather research and forecast model, Towar.
Teracomputing, 1999.
Michalakes, J., Chen, S., Dudhia, J., Hart, L., Klemp, J., Middlecoff, J.,
and Skamarock, W.: Development of a next-generation regional weather
research and forecast model, Towar. Teracomputing, 2001.
Mikkelson, K. M., Maxwell, R. M., Ferguson, I., Stednick, J. D., Mccray, J.
E., and Sharp, J. O.: Mountain pine beetle infestation impacts: Modeling
water and energy budgets at the hill-slope scale, Ecohydrology, 6,
64–72, https://doi.org/10.1002/eco.278, 2013.
Mironov, D., Heise, E., Kourzeneva, E., and Ritter, B.: Implementation of the
lake parameterisation scheme FLake into the numerical weather prediction
model COSMO, Boreal Environ. Res., 6095, 218–230, 2010.
Mobley, C. D. and Stewart, R. S.: On the numerical generation of
boundary-fitted orthogonal curvilinear coordinate systems, J. Comput. Phys.,
34, 124–135, https://doi.org/10.1016/0021-9991(80)90117-5, 1980.
Molders, N. and Ruhaak, W.: On the impact of explicitly predicted runoff on
the simulated atmospheric response to small-scale land-use changes – an
integrated modeling approach, Atmos. Res., 63, 3–38, 2002.
Navarre-Sitchler, A., Steefel, C. I., Sak, P. B., and Brantley, S. L.: A
reactive-transport model for weathering rind formation on basalt, Geochim.
Cosmochim. Acta, 75, 7644–7667, https://doi.org/10.1016/j.gca.2011.09.033, 2011.
Oleson, K. W., Niu, G. Y., Yang, Z. L., Lawrence, D. M., Thornton, P. E., Lawrence, P. J., Stockli, R., Dickinson, R. E., Bonan, G. B., Levis, S., Dai, A., and Qian, T.: Improvements to the Community Land Model and their
impact on the hydrological cycle, J. Geophys. Res.-Biogeosci., 113, G01021,
https://doi.org/10.1029/2007JG000563, 2008.
Osei-Kuffuor, D., Maxwell, R. M., and Woodward, C. S.: Improved numerical
solvers for implicit coupling of subsurface and overland flow, Adv. Water
Resour., 74, 185–195, https://doi.org/10.1016/j.advwatres.2014.09.006, 2014.
Panday, S. and Huyakorn, P. S.: A fully coupled physically-based
spatially-distributed model for evaluating surface/subsurface flow, Adv.
Water Resour., 27, 361–382, https://doi.org/10.1016/j.advwatres.2004.02.016, 2004.
Rahman, M., Sulis, M., and Kollet, S. J.: Evaluating the dual-boundary
forcing concept in subsurface-land surface interactions of the hydrological
cycle, Hydrol. Process., 30, 1563–1573, https://doi.org/10.1002/hyp.10702, 2016.
Ren, D. and Xue, M.: A revised force–restore model for land surface
modeling, Am. Meteorol. Soc., 43, 1768–1782, 2004.
Reyes, B., Maxwell, R. M., and Hogue, T. S.: Impact of lateral flow and
spatial scaling on the simulation of semi-arid urban land surfaces in an
integrated hydrologic and land surface model, Hydrol. Process., 30,
1192–1207, https://doi.org/10.1002/hyp.10683, 2016.
Richards, L. A.: Capillary conduction of liquids through porous mediums, J.
Appl. Phys., 1, 318–333, https://doi.org/10.1063/1.1745010, 1931.
Rihani, J. F., Maxwell, M. R., and Chow, F. K.: Coupling groundwater and
land surface processes: Idealized simulations to identify effects of terrain
and subsurface heterogeneity on land surface energy fluxes, Water Resour.
Res., 46, 1–14, https://doi.org/10.1029/2010WR009111, 2010.
Rihani, J. F., Chow, F. K., Fotini K., and Maxwell, R. M.: Isolating effects
of terrain and soil moisture heterogeneity on the atmospheric boundary
layer: Idealized simulations to diagnose land-atmosphere feedbacks, J. Adv.
Model. Earth Syst., 6, 513–526, https://doi.org/10.1002/2014MS000371.Received, 2015.
Ryskin, G. and Leal, L.: Orthogonal mapping, J. Comput. Phys., 50,
71–100, https://doi.org/10.1016/0021-9991(83)90042-6, 1983.
Saad, Y. and Schultz, M. H.: GMRES: A Generalized Minimal Residual
Algorithm for Solving Nonsymmetric Linear Systems, SIAM J. Sci. Stat.
Comput., 7, 856–869, https://doi.org/10.1137/0907058, 1986.
Seck, A., Welty, C., and Maxwell, R. M.: Spin-up behavior and effects of initial conditions for an integrated hydrologic model, Water Resour. Res., 51, 2188–2210, https://doi.org/10.1002/2014WR016371, 2015.
Seuffert, G., Gross, P., Simmer, A. C., and Wood, E. F.: The Influence of Hydrologic Modeling on the Predicted Local Weather: Two-Way Coupling of a Mesoscale Weather Prediction Model and a Land Surface Hydrologic Model, J. Hydrometeorol., 3, 505–523, 2002.
Shen, C. and Phanikumar, M. S.: A process-based, distributed hydrologic
model based on a large-scale method for surface-subsurface coupling, Adv.
Water Resour., 33, 1524–1541, https://doi.org/10.1016/j.advwatres.2010.09.002,
2010.
Shi, Y., Davis, K. J., Zhang, F., and Duffy, C. J.: Evaluation of the
Parameter Sensitivities of a Coupled Land Surface Hydrologic Model at a
Critical Zone Observatory, J. Hydrometeorol., 15, 279–299,
https://doi.org/10.1175/JHM-D-12-0177.1, 2014.
Shrestha, P., Sulis, M., Masbou, M., Kollet, S., and Simmer, C.: A.: Scale-Consistent Terrestrial Systems Modeling Platform Based on COSMO, CLM, and ParFlow, Mon. Weather Rev., 142, 3466–3483, https://doi.org/10.1175/MWR-D-14-00029.1, 2014.
Shrestha, P., Sulis, M., Simmer, C., and Kollet, S.: Impacts of grid resolution on surface energy fluxes simulated with an integrated surface-groundwater flow model, Hydrol. Earth Syst. Sci., 19, 4317–4326, https://doi.org/10.5194/hess-19-4317-2015, 2015.
Simmer, C., Thiele-Eich, I., Masbou, M., Amelung, W., Bogena, H., Crewell, S., Diekkruger, B., Ewert, F., Franssen, H. H., Huisman, J. A., Kemna, A., Klitzsch, N., Kollet, S., Langensiepen, M., Lohnert, U., Mostaquimur Rhaman, A. S. M., Rascher, U., Schneider, K., Schween, J., Shao, Y., Shrestha, P., Stiebler, M., Sulis, M., Vanderborght, J., Vereecken, H., Kruk, J. V. D., Waldhoff, G., and Zerenner, T. : Monitoring and modeling the terrestrial system from pores to catchments: The transregional collaborative research center on patterns in the soil-vegetation-atmosphere system, B. Am. Meteorol. Soc., 96, 1765–1787, https://doi.org/10.1175/BAMS-D-13-00134.1, 2015.
Skamarock, W. C. and Klemp, J. B.: A Time-Split Nonhydrostatic
Atmospheric Model for Weather Research and Forecasting Applications, J. Comput. Phys, 7,
1–43, 2007.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M.,
Wang, W., and Powers, J. G.: A description of the advanced research WRF
Version 2, NCAR Tech, p. 88, Note NCAR/TN-4681STR, 2005.
Smith, S.: ParFlow Version 3.6.0, available at: https://github.com/parflow/parflow/releases/tag/v3.6.0, last access: 4 September 2019.
Smith, S. G., Ashby, S. F., Falgout, R. D., and Tompsom, A. F. B.: The
parallel performance of a groundwater flow code on the CRAY T3D, in:
Proceedings of the Seventh SIAM Conference on Parallel Processing for
Scientific Computing, 131, 1995.
Srivastava, V., Graham, W., Muñoz-Carpena, R., and Maxwell, R. M.:
Insights on geologic and vegetative controls over hydrologic behavior of a
large complex basin – Global Sensitivity Analysis of an integrated parallel
hydrologic model, J. Hydrol., 519, 2238–2257, 2014.
Steefel, C. I.: CrunchFlow Software for Modeling Multicomponent Reactive
Flow and Transport User's Manual, 2009.
Steefel, C. I. and Lasaga, A. C.: A coupled model for transport of multiple
chemical species and kinetic precipitation/dissolution reactions with
application to reactive flow in single phase hydrothermal systems, Am. J.
Sci., 294, 529–592, https://doi.org/10.2475/ajs.294.5.529, 1994.
Steefel, C. I. and Van Cappellen, P.: A new kinetic approach to modeling
water-rock interaction: The role of nucleation, precursors, and Ostwald
ripening, Geochim. Cosmochim. Acta, 54, 2657–2677,
https://doi.org/10.1016/0016-7037(90)90003-4, 1990.
Steefel, C. I. and Yabusaki, S. B.: OS3D/GIMRT software for modeling
multicomponent-multidimensional reactive transport, Richland, WA, 1996.
Steiner, A. L., Pal, J. S., Giorgi, F., Dickinson, R. E., and Chameides, W.
L.: The coupling of the Common Land Model (CLM0) to a regional climate model
(RegCM), Theor. Appl. Climatol., 82, 225–243,
https://doi.org/10.1007/s00704-005-0132-5, 2005.
Steiner, A. L., Pal, J. S., Rauscher, S. A., Bell, J. L., Diffenbaugh, N.
S., Boone, A., Sloan, L. C., and Giorgi, F.: Land surface coupling in
regional climate simulations of the West African monsoon, Clim. Dynam., 33,
869–892, https://doi.org/10.1007/s00382-009-0543-6, 2009.
Sudicky, E. A., Jones, J. P., Park, Y. J., Brookfield, A. E., and Colautti,
D.: Simulating complex flow and transport dynamics in an integrated
surface-subsurface modeling framework, Geosci. J., 12, 107–122,
https://doi.org/10.1007/s12303-008-0013-x, 2008.
Sulis, M., Meyerhoff, S. B., Paniconi, C., Maxwell, R. M., Putti, M., and
Kollet, S. J.: A comparison of two physics-based numerical models for
simulating surface water-groundwater interactions, Adv. Water Resour.,
33, 456–467, https://doi.org/10.1016/j.advwatres.2010.01.010, 2010.
Sulis, M., Williams, J. L., Shrestha, P., Diederich, M., Simmer, C., Kollet,
S. J., and. Maxwell, R. M.: Coupling Groundwater, Vegetation, and
Atmospheric Processes: A Comparison of Two Integrated Models, J.
Hydrometeorol., 18, 1489–1511, https://doi.org/10.1175/JHM-D-16-0159.1, 2017.
Therrien, R. and Sudicky, E.: Three-dimensional analysis of
variably-saturated flow and solute transport in discretely- fractured porous
media, J. Contam. Hydrol., 23, 1–44, https://doi.org/10.1016/0169-7722(95)00088-7,
1996.
Tompson, A. F. B., Ashby, S. F., and Falgout, R. D.: Use of high performance
computing to examine the effectiveness of aquifer remediation, (No. UCRL-JC–115374), Lawrence Livermore National Lab, 1994.
Tompson, A. F. B., Falgout, R. D., Smith, S. G., Bosl, W. J., and Ashby, S.
F.: Analysis of subsurface contaminant migration and remediation using high
performance computing, Adv. Water Resour., 22, 203–221,
https://doi.org/10.1016/S0309-1708(98)00013-X, 1998.
Tompson, A. F. B., Carle, S. F., Rosenberg, N. D., and Maxwell, R. M.:
Analysis of groundwater migration from artificial recharge in a large urban
aquifer: A simulation perspective, Water Resour. Res., 35, 2981–2998,
https://doi.org/10.1029/1999WR900175, 1999.
Valcke, S.: The OASIS3 coupler: a European climate modelling community software, Geosci. Model Dev., 6, 373–388, https://doi.org/10.5194/gmd-6-373-2013, 2013.
Valcke, S., Balaji, V., Bentley, P., Guilyardi, E., Lawrence, B., and
Pascoe, C.: Developing a Common Information Model for climate models and
data, Geophys. Res. Abstr., 11, 10592, 2009.
Valcke, S., Balaji, V., Craig, A., DeLuca, C., Dunlap, R., Ford, R. W., Jacob, R., Larson, J., O'Kuinghttons, R., Riley, G. D., and Vertenstein, M.: Coupling technologies for Earth System Modelling, Geosci. Model Dev., 5, 1589–1596, https://doi.org/10.5194/gmd-5-1589-2012, 2012.
VanderKwaak, J. E.: Numerical simulation of flow and chemical transport in integrated surface-subsurface hydrologic systems, A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy Earth Sciences Waterloo, Ontario, Canada, 1999.
Van Genuchten, M. T.: A Closed-form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, 892–898,
https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Visbal, M. and Knight, D.: Generation of orthogonal and nearly orthogonal
coordinates with gridcontrol near boundaries, AIAA J., 20, 305–306,
https://doi.org/10.2514/3.7915, 1982.
Vogel, B., Vogel, H., Bäumer, D., Bangert, M., Lundgren, K., Rinke, R., and Stanelle, T.: The comprehensive model system COSMO-ART – Radiative impact of aerosol on the state of the atmosphere on the regional scale, Atmos. Chem. Phys., 9, 8661–8680, https://doi.org/10.5194/acp-9-8661-2009, 2009.
Wagner, S., Fersch, B., Yuan, Y.,Yu, Z., and Kunstmann, H.: Fully coupled
atmospheric-hydrological modeling at regional and long-term scales:
Development, application, and analysis of WRF-HMS, Water Resour. Res.,
52, 3187–3211, https://doi.org/10.1002/2015WR018185, 2016.
Weill, S., Mouche, E., and Patin, J.: A generalized Richards equation for
surface/subsurface flow modelling, J. Hydrol., 366, 9–20,
https://doi.org/10.1016/j.jhydrol.2008.12.007, 2009.
Weill, S., Mazzia, A., Putti, M., and Paniconi, C.: Coupling water flow and
solute transport into a physically-based surface-subsurface hydrological
model, Adv. Water Resour., 34, 128–136,
https://doi.org/10.1016/j.advwatres.2010.10.001, 2011.
Williams, J. L. and Maxwell, R. M.: Propagating Subsurface Uncertainty to
the Atmosphere Using Fully Coupled Stochastic Simulations, J.
Hydrometeorol., 12, 690–701, https://doi.org/10.1175/2011JHM1363.1, 2011.
Williams, J. L., Maxwell, R. M., and Monache, L. D.: Development and
verification of a new wind speed forecasting system using an ensemble Kalman
filter data assimilation technique in a fully coupled hydrologic and
atmospheric model, J. Adv. Model. Earth Syst., 5, 785–800,
https://doi.org/10.1002/jame.20051, 2013.
Wood, B. D.: The role of scaling laws in upscaling, Adv. Water Resour.,
32, 723–736, https://doi.org/10.1016/j.advwatres.2008.08.015, 2009.
Woodward, S. C.: A Newton-Krylov-multigrid solver for variably saturated
flow problems, Proceedings on the Twelfth International Conference on
Computational Methods in Water Resources, in Computational Mechanics
Publications, vol. 2, 609–616, 1998.
Xu, L., Raman, S., and Madala, R. V.: A review of non-hydrostatic numerical
models for the atmosphere, Math. Subj. Classif, 1991.
Xue, M., Droegemeier, K. K., and Wong, V.: The Advanced Regional Prediction
System (ARPS) – A multi-scale nonhydrostatic atmospheric simulation and
prediction tool. Part II: Model dynamics and verification, Meteorol. Atmos.
Phys., 75, 161–193, https://doi.org/10.1007/s007030170027, 2000.
Zhufeng, F., Bogena, H., Kollet, S., and Koch, J. H. V.: Spatio-temporal
validation of long-term 3D hydrological simulations of a forested catchment
using empirical orthogonal functions and wavelet coherence analysis,
Hydrology, 529, 1754–1767, 2015.
Short summary
Integrated hydrologic models (IHMs) were developed in order to allow for more accurate simulations of real-world ecohydrologic conditions. Many IHMs exist, and the literature can be dense, so it is often difficult to understand what a specific model can and cannot do. We provide a review of the current core capabilities, solution techniques, communication structure with other models, some limitations, and potential future improvements of one such open-source integrated model called ParFlow.
Integrated hydrologic models (IHMs) were developed in order to allow for more accurate...
