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.
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
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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
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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.
Benjamin D. West, Reed M. Maxwell, and Laura E. Condon
EGUsphere, https://doi.org/10.5194/egusphere-2024-965, https://doi.org/10.5194/egusphere-2024-965, 2024
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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 better able to understand both our impacts on the environment, and how to adjust our management of reservoirs to changing conditions.
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
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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
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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
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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
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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
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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.
Bamidele Joseph Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2023-3132, https://doi.org/10.5194/egusphere-2023-3132, 2024
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This study uses simulations to understand how the soil information across Africa affects the water balance, using 4 soil databases and 3 different rainfall datasets. Results show that the soil information impacts water balance estimates, especially with a higher rate of rainfall.
Max Berkelhammer, Gerald F. Page, Frank Zurek, Christopher Still, Mariah S. Carbone, William Talavera, Laura Hildebrand, James Byron, Kyle Inthabandith, Angellica Kucinski, Melissa Carter, Kelsey Foss, Wendy Brown, Rosemary W. H. Carroll, Austin Simonpietri, Marshall Worsham, Ian Breckheimer, Anna Ryken, Reed Maxwell, David Gochis, Mark Raleigh, Eric Small, and Kenneth H. Williams
EGUsphere, https://doi.org/10.5194/egusphere-2023-3063, https://doi.org/10.5194/egusphere-2023-3063, 2024
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Warming in montane systems is affecting the amount of snowmelt inputs. This will affect subalpine forests globally that rely on spring snowmelt to support their water demands. We use a network of sensors across in the Upper Colorado Basin to show that changing spring primarily impacts dense forest stands that have high peak water demands. On the other hand, open forest stands show a higher reliance on summer rain and were minimally sensitive to even historically low snow conditions like 2019.
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-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Revised manuscript accepted for HESS
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Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under 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 with a set of experiments in the Upper Colorado River Basin.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim 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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1460, https://doi.org/10.5194/egusphere-2023-1460, 2023
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Europe is regularly affected by compound events and natural hazards that occur simultaneously or with a temporal lag and are connected with disproportional impacts. Within the interdisciplinary project climXtreme (https://climxtreme.net/) we investigate the interplay of these events, their characteristics and changes, intensity, frequency and uncertainties in the past, present and future, as well as the associated impacts on different socio-economic sectors in Germany and Central Europe.
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
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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
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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.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Joni-Pekka Pietikaeinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
EGUsphere, https://doi.org/10.5194/egusphere-2023-1463, https://doi.org/10.5194/egusphere-2023-1463, 2023
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With a team of 20 authors from different countries, we tried to compile the impacts of drought and heat on European forests in the period 2018–2022. This is a research approach that transcends subject and country borders.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Robust handling of extremes in quantile mapping – "Murder your darlings"
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Evaluating downscaled products with expected hydroclimatic co-variances
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Introducing the MESMER-M-TPv0.1.0 module: Spatially Explicit Earth System Model Emulation for Monthly Precipitation and Temperature
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
A computationally light-weight model for ensemble forecasting of environmental hazard: General TAMSAT-ALERT v1.2.1
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
Coupling the regional climate model ICON-CLM v2.6.6 into the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
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. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting 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 to generate monthly means of local precipitation and temperature at low computational costs.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Emily Black, John Ellis, and Ross Maidment
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-75, https://doi.org/10.5194/gmd-2024-75, 2024
Revised manuscript accepted for GMD
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We present General TAMSAT-ALERT: a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and forecasting data into probabilistic hazard assessments. As such, it complements existing systems and enhances their utility for actionable hazard assessment.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
EGUsphere, https://doi.org/10.5194/egusphere-2024-923, https://doi.org/10.5194/egusphere-2024-923, 2024
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The regional Earth system model GCOAST-AHOI version 2.0 including the regional climate model ICON-CLM coupled with 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 the ICON-CLM model makes it more flexible to couple with an external ocean model and an external hydrological discharge model.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
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...