Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-4117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-14-4117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Humboldt University of Berlin, Department of Physics,
12489 Berlin, Germany
Werner von Bloh
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Stefan Petri
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Boris Sakschewski
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Sibyll Schaphoff
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Matthias Forkel
Institute of Photogrammetry and Remote Sensing, Dresden University of Technology, 01069 Dresden, Germany
Willem Huiskamp
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Georg Feulner
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
Kirsten Thonicke
Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14412 Potsdam, Germany
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One limit of planetary habitability is defined by the threshold of global glaciation. If Earth cools, growing ice cover makes it brighter, leading to further cooling, since more sunlight is reflected, eventually leading to global ice cover (Snowball Earth). We study how much carbon dioxide is needed to prevent global glaciation in Earth's history given the slow increase in the Sun's brightness. We find an unexpected change in the characteristics of climate states close to the Snowball limit.
Hoontaek Lee, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala
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Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
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The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Phillip Papastefanou, Christian S. Zang, Zlatan Angelov, Aline Anderson de Castro, Juan Carlos Jimenez, Luiz Felipe Campos De Rezende, Romina C. Ruscica, Boris Sakschewski, Anna A. Sörensson, Kirsten Thonicke, Carolina Vera, Nicolas Viovy, Celso Von Randow, and Anja Rammig
Biogeosciences, 19, 3843–3861, https://doi.org/10.5194/bg-19-3843-2022, https://doi.org/10.5194/bg-19-3843-2022, 2022
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The Amazon rainforest has been hit by multiple severe drought events. In this study, we assess the severity and spatial extent of the extreme drought years 2005, 2010 and 2015/16 in the Amazon. Using nine different precipitation datasets and three drought indicators we find large differences in drought stress across the Amazon region. We conclude that future studies should use multiple rainfall datasets and drought indicators when estimating the impact of drought stress in the Amazon region.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Vera Porwollik, Susanne Rolinski, Jens Heinke, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Biogeosciences, 19, 957–977, https://doi.org/10.5194/bg-19-957-2022, https://doi.org/10.5194/bg-19-957-2022, 2022
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The study assesses impacts of grass cover crop cultivation on cropland during main-crop off-season periods applying the global vegetation model LPJmL (V.5.0-tillage-cc). Compared to simulated bare-soil fallowing practices, cover crops led to increased soil carbon content and reduced nitrogen leaching rates on the majority of global cropland. Yield responses of main crops following cover crops vary with location, duration of altered management, crop type, water regime, and tillage practice.
Willem Huiskamp and Shayne McGregor
Clim. Past, 17, 1819–1839, https://doi.org/10.5194/cp-17-1819-2021, https://doi.org/10.5194/cp-17-1819-2021, 2021
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This study investigates the reliability of paleo-reconstructions of the Southern Annular Mode (SAM) using climate model data. We find that reconstructions are able to capture ~ 60 % of the SAM variability at best, with poorer reconstructions managing only 35 %. Reconstructions perform best when they use more proxies sourced from the entire Southern Hemisphere land mass. Future reconstructions should endeavour to address both sampling and proxy–SAM correlation stability uncertainties.
Boris Sakschewski, Werner von Bloh, Markus Drüke, Anna Amelia Sörensson, Romina Ruscica, Fanny Langerwisch, Maik Billing, Sarah Bereswill, Marina Hirota, Rafael Silva Oliveira, Jens Heinke, and Kirsten Thonicke
Biogeosciences, 18, 4091–4116, https://doi.org/10.5194/bg-18-4091-2021, https://doi.org/10.5194/bg-18-4091-2021, 2021
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This study shows how local adaptations of tree roots across tropical and sub-tropical South America explain patterns of biome distribution, productivity and evapotranspiration on this continent. By allowing for high diversity of tree rooting strategies in a dynamic global vegetation model (DGVM), we are able to mechanistically explain patterns of mean rooting depth and the effects on ecosystem functions. The approach can advance DGVMs and Earth system models.
Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Matthias Forkel, I. Colin Prentice, and Sandy P. Harrison
Biogeosciences, 18, 3861–3879, https://doi.org/10.5194/bg-18-3861-2021, https://doi.org/10.5194/bg-18-3861-2021, 2021
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Along with current climate, vegetation, and human influences, long-term accumulation of biomass affects fires. Here, we find that including the influence of antecedent vegetation and moisture improves our ability to predict global burnt area. Additionally, the length of the preceding period which needs to be considered for accurate predictions varies across regions.
Moritz Kreuzer, Ronja Reese, Willem Nicholas Huiskamp, Stefan Petri, Torsten Albrecht, Georg Feulner, and Ricarda Winkelmann
Geosci. Model Dev., 14, 3697–3714, https://doi.org/10.5194/gmd-14-3697-2021, https://doi.org/10.5194/gmd-14-3697-2021, 2021
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We present the technical implementation of a coarse-resolution coupling between an ice sheet model and an ocean model that allows one to simulate ice–ocean interactions at timescales from centuries to millennia. As ice shelf cavities cannot be resolved in the ocean model at coarse resolution, we bridge the gap using an sub-shelf cavity module. It is shown that the framework is computationally efficient, conserves mass and energy, and can produce a stable coupled state under present-day forcing.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
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Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Yvonne Jans, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Hydrol. Earth Syst. Sci., 25, 2027–2044, https://doi.org/10.5194/hess-25-2027-2021, https://doi.org/10.5194/hess-25-2027-2021, 2021
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Growth of and irrigation water demand on cotton may be challenged by future climate change. To analyze the global cotton production and irrigation water consumption under spatially varying present and future climatic conditions, we use the global terrestrial biosphere model LPJmL. Our simulation results suggest that the beneficial effects of elevated [CO2] on cotton yields overcompensate yield losses from direct climate change impacts, i.e., without the beneficial effect of [CO2] fertilization.
Gerilyn S. Soreghan, Laurent Beccaletto, Kathleen C. Benison, Sylvie Bourquin, Georg Feulner, Natsuko Hamamura, Michael Hamilton, Nicholas G. Heavens, Linda Hinnov, Adam Huttenlocker, Cindy Looy, Lily S. Pfeifer, Stephane Pochat, Mehrdad Sardar Abadi, James Zambito, and the Deep Dust workshop participants
Sci. Dril., 28, 93–112, https://doi.org/10.5194/sd-28-93-2020, https://doi.org/10.5194/sd-28-93-2020, 2020
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The events of the Permian — the orogenies, biospheric turnovers, icehouse and greenhouse antitheses, and Mars-analog lithofacies — boggle the imagination and present us with great opportunities to explore Earth system behavior. Here we outline results of workshops to propose continuous coring of continental Permian sections in western (Anadarko Basin) and eastern (Paris Basin) equatorial Pangaea to retrieve continental records spanning 50 Myr of Earth's history.
Thomas A. M. Pugh, Tim Rademacher, Sarah L. Shafer, Jörg Steinkamp, Jonathan Barichivich, Brian Beckage, Vanessa Haverd, Anna Harper, Jens Heinke, Kazuya Nishina, Anja Rammig, Hisashi Sato, Almut Arneth, Stijn Hantson, Thomas Hickler, Markus Kautz, Benjamin Quesada, Benjamin Smith, and Kirsten Thonicke
Biogeosciences, 17, 3961–3989, https://doi.org/10.5194/bg-17-3961-2020, https://doi.org/10.5194/bg-17-3961-2020, 2020
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The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle. Estimates from six contemporary models found this time to range from 12.2 to 23.5 years for the global mean for 1985–2014. Future projections do not give consistent results, but 13 model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce large current uncertainty.
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, https://doi.org/10.5194/essd-12-177-2020, 2020
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Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass, and carbon stock monitoring. For the past 30 years there have been various VOD data sets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054, https://doi.org/10.5194/gmd-12-5029-2019, https://doi.org/10.5194/gmd-12-5029-2019, 2019
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This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
Maarten C. Braakhekke, Jonathan C. Doelman, Peter Baas, Christoph Müller, Sibyll Schaphoff, Elke Stehfest, and Detlef P. van Vuuren
Earth Syst. Dynam., 10, 617–630, https://doi.org/10.5194/esd-10-617-2019, https://doi.org/10.5194/esd-10-617-2019, 2019
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We developed a computer model that simulates forests plantations at global scale and how fast such forests can take up CO2 from the atmosphere. Using this new model, we performed simulations for a scenario in which a large fraction (14 %) of global croplands and pastures are either converted to planted forests or natural forests. We find that planted forests take up CO2 substantially faster than natural forests and are therefore a viable strategy for reducing climate change.
Kirsten Thonicke, Fanny Langerwisch, Matthias Baumann, Pedro J. Leitão, Tomáš Václavík, Ane Alencar, Margareth Simões, Simon Scheiter, Liam Langan, Mercedes Bustamante, Ignacio Gasparri, Marina Hirota, Jan Börner, Raoni Rajao, Britaldo Soares-Filho, Alberto Yanosky, José-Manuel Ochoa-Quinteiro, Lucas Seghezzo, Georgina Conti, and Anne Cristina de la Vega-Leinert
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-221, https://doi.org/10.5194/bg-2019-221, 2019
Publication in BG not foreseen
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Tropical dry forests and savannas harbor unique biodiversity and provide critical ecosystem services (ES), yet they are under severe pressure globally. We need to improve our understanding of how and when this pressure provokes tipping points in biodiversity and the associated social-ecological systems. We propose an approach to investigate how drivers leading to natural vegetation decline trigger biodiversity tipping and illustrate it using the example of the Dry Diagonal in South America.
Femke Lutz, Tobias Herzfeld, Jens Heinke, Susanne Rolinski, Sibyll Schaphoff, Werner von Bloh, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 12, 2419–2440, https://doi.org/10.5194/gmd-12-2419-2019, https://doi.org/10.5194/gmd-12-2419-2019, 2019
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Tillage practices are under-represented in global biogeochemical models so that assessments of agricultural greenhouse gas emissions and climate mitigation options are hampered. We describe the implementation of tillage modules into the model LPJmL5.0, including multiple feedbacks between soil water, nitrogen, and productivity. By comparing simulation results with observational data, we show that the model can reproduce reported tillage effects on carbon and water dynamics and crop yields.
Sonja Totz, Stefan Petri, Jascha Lehmann, Erik Peukert, and Dim Coumou
Nonlin. Processes Geophys., 26, 1–12, https://doi.org/10.5194/npg-26-1-2019, https://doi.org/10.5194/npg-26-1-2019, 2019
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019, https://doi.org/10.5194/bg-16-57-2019, 2019
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Weather, humans, and vegetation control the occurrence of fires. In this study we find that global fire–vegetation models underestimate the strong increase of burned area with higher previous-season plant productivity in comparison to satellite-derived relationships.
Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Philippe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, and Edna Rödig
Geosci. Model Dev., 11, 5203–5215, https://doi.org/10.5194/gmd-11-5203-2018, https://doi.org/10.5194/gmd-11-5203-2018, 2018
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We propose a generic approach for a pixel-to-point comparison applicable for evaluation of models and remote-sensing products. We provide statistical measures accounting for the uncertainty in ecosystem variables. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest.
Werner von Bloh, Sibyll Schaphoff, Christoph Müller, Susanne Rolinski, Katharina Waha, and Sönke Zaehle
Geosci. Model Dev., 11, 2789–2812, https://doi.org/10.5194/gmd-11-2789-2018, https://doi.org/10.5194/gmd-11-2789-2018, 2018
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The dynamics of the terrestrial carbon cycle are of central importance for Earth system science. Nutrient limitations, especially from nitrogen, are important constraints on vegetation growth and the terrestrial carbon cycle. We extended the well-established global vegetation, hydrology, and crop model LPJmL with a nitrogen cycle. We find significant improvement in global patterns of crop productivity. Regional differences in crop productivity can now be largely reproduced by the model.
Julia Brugger, Matthias Hofmann, Stefan Petri, and Georg Feulner
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-36, https://doi.org/10.5194/cp-2018-36, 2018
Manuscript not accepted for further review
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To get a deeper understanding of the various evolutionary changes, which took place during the Devonian (419 to 359 Ma), we here use a coupled climate model to investigate the sensitivity of the Devonian climate to changes in orbital forcing, continental configuration and vegetation cover. Our results are summarised by best-guess simulations for the Early, Middle and Late Devonian showing a decreasing temperature trend in accordance with the reconstructed decreasing atmospheric CO2.
Sibyll Schaphoff, Werner von Bloh, Anja Rammig, Kirsten Thonicke, Hester Biemans, Matthias Forkel, Dieter Gerten, Jens Heinke, Jonas Jägermeyr, Jürgen Knauer, Fanny Langerwisch, Wolfgang Lucht, Christoph Müller, Susanne Rolinski, and Katharina Waha
Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, https://doi.org/10.5194/gmd-11-1343-2018, 2018
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Here we provide a comprehensive model description of a global terrestrial biosphere model, named LPJmL4, incorporating the carbon and water cycle and the quantification of agricultural production. The model allows for the consistent and joint quantification of climate and land use change impacts on the biosphere. The model represents the key ecosystem functions, but also the influence of humans on the biosphere. It comes with an evaluation paper to demonstrate the credibility of LPJmL4.
Sibyll Schaphoff, Matthias Forkel, Christoph Müller, Jürgen Knauer, Werner von Bloh, Dieter Gerten, Jonas Jägermeyr, Wolfgang Lucht, Anja Rammig, Kirsten Thonicke, and Katharina Waha
Geosci. Model Dev., 11, 1377–1403, https://doi.org/10.5194/gmd-11-1377-2018, https://doi.org/10.5194/gmd-11-1377-2018, 2018
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Here we provide a comprehensive evaluation of the now launched version 4.0 of the LPJmL biosphere, water, and agricultural model. The article is the second part to a comprehensive description of the LPJmL4 model. We have evaluated the model against various datasets of satellite observations, agricultural statistics, and in situ measurements by applying a range of metrics. We are able to show that the LPJmL4 model simulates many parameters and relations reasonably.
Sonja Totz, Alexey V. Eliseev, Stefan Petri, Michael Flechsig, Levke Caesar, Vladimir Petoukhov, and Dim Coumou
Geosci. Model Dev., 11, 665–679, https://doi.org/10.5194/gmd-11-665-2018, https://doi.org/10.5194/gmd-11-665-2018, 2018
Susanne Rolinski, Christoph Müller, Jens Heinke, Isabelle Weindl, Anne Biewald, Benjamin Leon Bodirsky, Alberte Bondeau, Eltje R. Boons-Prins, Alexander F. Bouwman, Peter A. Leffelaar, Johnny A. te Roller, Sibyll Schaphoff, and Kirsten Thonicke
Geosci. Model Dev., 11, 429–451, https://doi.org/10.5194/gmd-11-429-2018, https://doi.org/10.5194/gmd-11-429-2018, 2018
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One-third of the global land area is covered with grasslands which are grazed by or mowed for livestock feed. These areas contribute significantly to the carbon capture from the atmosphere when managed sensibly. To assess the effect of this management, we included different options of grazing and mowing into the global model LPJmL 3.6. We found in polar regions even low grazing pressure leads to soil carbon loss whereas in temperate regions up to 1.4 livestock units per hectare can be sustained.
Matthias Forkel, Wouter Dorigo, Gitta Lasslop, Irene Teubner, Emilio Chuvieco, and Kirsten Thonicke
Geosci. Model Dev., 10, 4443–4476, https://doi.org/10.5194/gmd-10-4443-2017, https://doi.org/10.5194/gmd-10-4443-2017, 2017
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Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Finn Müller-Hansen, Maja Schlüter, Michael Mäs, Jonathan F. Donges, Jakob J. Kolb, Kirsten Thonicke, and Jobst Heitzig
Earth Syst. Dynam., 8, 977–1007, https://doi.org/10.5194/esd-8-977-2017, https://doi.org/10.5194/esd-8-977-2017, 2017
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Today, human interactions with the Earth system lead to complex feedbacks between social and ecological dynamics. Modeling such feedbacks explicitly in Earth system models (ESMs) requires making assumptions about individual decision making and behavior, social interaction, and their aggregation. In this overview paper, we compare different modeling approaches and techniques and highlight important consequences of modeling assumptions. We illustrate them with examples from land-use modeling.
Sonja Molnos, Stefan Petri, Jascha Lehmann, Erik Peukert, and Dim Coumou
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-65, https://doi.org/10.5194/esd-2017-65, 2017
Manuscript not accepted for further review
Matthieu Guimberteau, Philippe Ciais, Agnès Ducharne, Juan Pablo Boisier, Ana Paula Dutra Aguiar, Hester Biemans, Hannes De Deurwaerder, David Galbraith, Bart Kruijt, Fanny Langerwisch, German Poveda, Anja Rammig, Daniel Andres Rodriguez, Graciela Tejada, Kirsten Thonicke, Celso Von Randow, Rita C. S. Von Randow, Ke Zhang, and Hans Verbeeck
Hydrol. Earth Syst. Sci., 21, 1455–1475, https://doi.org/10.5194/hess-21-1455-2017, https://doi.org/10.5194/hess-21-1455-2017, 2017
Finn Müller-Hansen, Manoel F. Cardoso, Eloi L. Dalla-Nora, Jonathan F. Donges, Jobst Heitzig, Jürgen Kurths, and Kirsten Thonicke
Nonlin. Processes Geophys., 24, 113–123, https://doi.org/10.5194/npg-24-113-2017, https://doi.org/10.5194/npg-24-113-2017, 2017
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Deforestation and subsequent land uses in the Brazilian Amazon have huge impacts on greenhouse gas emissions, local climate and biodiversity. To better understand these land-cover changes, we apply complex systems methods uncovering spatial patterns in regional transition probabilities between land-cover types, which we estimate using maps derived from satellite imagery. The results show clusters of similar land-cover dynamics and thus complement studies at the local scale.
Sonja Molnos, Tarek Mamdouh, Stefan Petri, Thomas Nocke, Tino Weinkauf, and Dim Coumou
Earth Syst. Dynam., 8, 75–89, https://doi.org/10.5194/esd-8-75-2017, https://doi.org/10.5194/esd-8-75-2017, 2017
Fanny Langerwisch, Ariane Walz, Anja Rammig, Britta Tietjen, Kirsten Thonicke, and Wolfgang Cramer
Earth Syst. Dynam., 7, 953–968, https://doi.org/10.5194/esd-7-953-2016, https://doi.org/10.5194/esd-7-953-2016, 2016
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Amazonia is heavily impacted by climate change and deforestation. During annual flooding terrigenous material is imported to the river, converted and finally exported to the ocean or the atmosphere. Changes in the vegetation alter therefore riverine carbon dynamics. Our results show that due to deforestation organic carbon amount will strongly decrease both in the river and exported to the ocean, while inorganic carbon amounts will increase, in the river as well as exported to the atmosphere.
F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
Earth Syst. Dynam., 7, 559–582, https://doi.org/10.5194/esd-7-559-2016, https://doi.org/10.5194/esd-7-559-2016, 2016
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In Amazonia, carbon fluxes are considerably influenced by annual flooding. We applied the newly developed model RivCM to several climate change scenarios to estimate potential changes in riverine carbon. We find that climate change causes substantial changes in riverine organic and inorganic carbon, as well as changes in carbon exported to the atmosphere and ocean. Such changes could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean.
M. Fader, S. Shi, W. von Bloh, A. Bondeau, and W. Cramer
Hydrol. Earth Syst. Sci., 20, 953–973, https://doi.org/10.5194/hess-20-953-2016, https://doi.org/10.5194/hess-20-953-2016, 2016
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At present, the Mediterranean region could save 35 % of water by implementing more efficient irrigation and conveyance systems (EICS). By 2080–2090 the region may face an increase in gross irrigation requirements (IRs) of up to 74 % due to climate change and population growth. EICS may be able to compensate to some degree these increases. Most countries in the northern and eastern Mediterranean have a high risk of not being able to meet future IRs due to water scarcity.
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
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We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
M. Fader, W. von Bloh, S. Shi, A. Bondeau, and W. Cramer
Geosci. Model Dev., 8, 3545–3561, https://doi.org/10.5194/gmd-8-3545-2015, https://doi.org/10.5194/gmd-8-3545-2015, 2015
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This study presents the inclusion of 10 Mediterranean agricultural plants in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses.
The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With this development presented, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture.
W. Greuell, J. C. M. Andersson, C. Donnelly, L. Feyen, D. Gerten, F. Ludwig, G. Pisacane, P. Roudier, and S. Schaphoff
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-10289-2015, https://doi.org/10.5194/hessd-12-10289-2015, 2015
Revised manuscript has not been submitted
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The main aims of this paper are the evaluation of five large-scale hydrological models across Europe and the assessment of the suitability of the models for making projections under climate change. While we found large inter-model differences in biases, the skill to simulate interannual variability in discharge did not differ much between the models. Assuming that the skill of a model to simulate interannual variability provides a measure for the model’s ability to make projections under climate
K. Nishina, A. Ito, P. Falloon, A. D. Friend, D. J. Beerling, P. Ciais, D. B. Clark, R. Kahana, E. Kato, W. Lucht, M. Lomas, R. Pavlick, S. Schaphoff, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 6, 435–445, https://doi.org/10.5194/esd-6-435-2015, https://doi.org/10.5194/esd-6-435-2015, 2015
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Our study focused on uncertainties in terrestrial C cycling under newly developed scenarios with CMIP5. This study presents first results for examining relative uncertainties of projected terrestrial C cycling in multiple projection components. Only using our new model inter-comparison project data sets enables us to evaluate various uncertainty sources in projection periods. The information on relative uncertainties is useful for climate science and climate change impact evaluation.
T. Schneider von Deimling, G. Grosse, J. Strauss, L. Schirrmeister, A. Morgenstern, S. Schaphoff, M. Meinshausen, and J. Boike
Biogeosciences, 12, 3469–3488, https://doi.org/10.5194/bg-12-3469-2015, https://doi.org/10.5194/bg-12-3469-2015, 2015
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We have modelled the carbon release from thawing permafrost soils under various scenarios of future warming. Our results suggests that up to about 140Pg of carbon could be released under strong warming by end of the century. We have shown that abrupt thaw processes under thermokarst lakes can unlock large amounts of perennially frozen carbon stored in deep deposits (which extend many metres into the soil).
C. Yue, P. Ciais, P. Cadule, K. Thonicke, and T. T. van Leeuwen
Geosci. Model Dev., 8, 1321–1338, https://doi.org/10.5194/gmd-8-1321-2015, https://doi.org/10.5194/gmd-8-1321-2015, 2015
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We conducted parallel simulations using a global land surface model, with and without fires being included, respectively. When the anthropogenic land cover change fire is excluded, we find that natural wildfires have reduced the global land carbon uptake by 0.3Pg C per year over 1901-2012. This is equivalent to 20% of the land carbon uptake in a world without fire. This fire-induced reduction in carbon uptake could be partly explained by climate variability, in particular the ENSO events.
S. Rolinski, A. Rammig, A. Walz, W. von Bloh, M. van Oijen, and K. Thonicke
Biogeosciences, 12, 1813–1831, https://doi.org/10.5194/bg-12-1813-2015, https://doi.org/10.5194/bg-12-1813-2015, 2015
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Extreme weather events can but do not have to cause extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions.
We use a simple probabilistic risk assessment and apply it to terrestrial ecosystems, defining a hazard as negative net biome productivity. In Europe, ecosystems are vulnerable to drought in the Mediterranean and temperate region, whereas vulnerability in Scandinavia is not caused by water shortages.
A. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, and K. Thonicke
Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, https://doi.org/10.5194/bg-11-7025-2014, 2014
M. Van Oijen, J. Balkovi, C. Beer, D. R. Cameron, P. Ciais, W. Cramer, T. Kato, M. Kuhnert, R. Martin, R. Myneni, A. Rammig, S. Rolinski, J.-F. Soussana, K. Thonicke, M. Van der Velde, and L. Xu
Biogeosciences, 11, 6357–6375, https://doi.org/10.5194/bg-11-6357-2014, https://doi.org/10.5194/bg-11-6357-2014, 2014
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We use a new risk analysis method, and six vegetation models, to analyse how climate change may alter drought risks in European ecosystems. The conclusions are (1) drought will pose increasing risks to productivity in the Mediterranean area; (2) this is because severe droughts will become more frequent, not because ecosystems will become more vulnerable; (3) future C sequestration will be at risk because carbon gain in primary productivity will be more affected than carbon loss in respiration.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
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ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
K. Nishina, A. Ito, D. J. Beerling, P. Cadule, P. Ciais, D. B. Clark, P. Falloon, A. D. Friend, R. Kahana, E. Kato, R. Keribin, W. Lucht, M. Lomas, T. T. Rademacher, R. Pavlick, S. Schaphoff, N. Vuichard, L. Warszawaski, and T. Yokohata
Earth Syst. Dynam., 5, 197–209, https://doi.org/10.5194/esd-5-197-2014, https://doi.org/10.5194/esd-5-197-2014, 2014
M. Willeit, A. Ganopolski, and G. Feulner
Biogeosciences, 11, 17–32, https://doi.org/10.5194/bg-11-17-2014, https://doi.org/10.5194/bg-11-17-2014, 2014
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
A. V. Eliseev, D. Coumou, A. V. Chernokulsky, V. Petoukhov, and S. Petri
Geosci. Model Dev., 6, 1745–1765, https://doi.org/10.5194/gmd-6-1745-2013, https://doi.org/10.5194/gmd-6-1745-2013, 2013
J. Heinke, S. Ostberg, S. Schaphoff, K. Frieler, C. Müller, D. Gerten, M. Meinshausen, and W. Lucht
Geosci. Model Dev., 6, 1689–1703, https://doi.org/10.5194/gmd-6-1689-2013, https://doi.org/10.5194/gmd-6-1689-2013, 2013
S. Ostberg, W. Lucht, S. Schaphoff, and D. Gerten
Earth Syst. Dynam., 4, 347–357, https://doi.org/10.5194/esd-4-347-2013, https://doi.org/10.5194/esd-4-347-2013, 2013
H. Kienert, G. Feulner, and V. Petoukhov
Clim. Past, 9, 1841–1862, https://doi.org/10.5194/cp-9-1841-2013, https://doi.org/10.5194/cp-9-1841-2013, 2013
M. Willeit, A. Ganopolski, and G. Feulner
Clim. Past, 9, 1749–1759, https://doi.org/10.5194/cp-9-1749-2013, https://doi.org/10.5194/cp-9-1749-2013, 2013
C. F. Schleussner and G. Feulner
Clim. Past, 9, 1321–1330, https://doi.org/10.5194/cp-9-1321-2013, https://doi.org/10.5194/cp-9-1321-2013, 2013
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
P. B. Holden, N. R. Edwards, D. Gerten, and S. Schaphoff
Biogeosciences, 10, 339–355, https://doi.org/10.5194/bg-10-339-2013, https://doi.org/10.5194/bg-10-339-2013, 2013
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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
The very-high resolution configuration of the EC-Earth global model for HighResMIP
ZEMBA v1.0: An energy and moisture balance climate model to investigate Quaternary climate
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
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
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
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
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.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
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.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-119, https://doi.org/10.5194/gmd-2024-119, 2024
Revised manuscript accepted for GMD
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Daniel Francis James Gunning, Kerim Hestnes Nisancioglu, Emilie Capron, and Roderik van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1384, https://doi.org/10.5194/egusphere-2024-1384, 2024
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth’s orbit. We demonstrate ZEMBA reproduces many features of the Earth’s climate for both the pre-industrial period and the Earth’s most recent cold extreme- the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
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.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
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.
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.
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-73, https://doi.org/10.5194/gmd-2024-73, 2024
Revised manuscript accepted for GMD
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Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.
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.
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Short summary
In this study, we couple the well-established and comprehensively validated state-of-the-art dynamic LPJmL5 global vegetation model to the CM2Mc coupled climate model (CM2Mc-LPJmL v.1.0). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. The new climate model is able to capture important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the the impacts of managed land (crop growth and irrigation).
In this study, we couple the well-established and comprehensively validated state-of-the-art...
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