Articles | Volume 12, issue 4
https://doi.org/10.5194/gmd-12-1477-2019
© Author(s) 2019. 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-12-1477-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
12 Apr 2019
Model description paper |
| 12 Apr 2019
| 12 Apr 2019
Fldgen v1.0: an emulator with internal variability and space–time correlation for Earth system models
Pacific Northwest National Laboratory, Joint Global Change
Research Institute, 5825 University Research Ct., College Park, MD, USA
Abigail Snyder
Pacific Northwest National Laboratory, Joint Global Change
Research Institute, 5825 University Research Ct., College Park, MD, USA
Cary Lynch
Connecticut Department of Energy and Environmental
Protection, 10 Franklin Square, New Britain, CT, USA
Corinne Hartin
Pacific Northwest National Laboratory, Joint Global Change
Research Institute, 5825 University Research Ct., College Park, MD, USA
Ben Kravitz
Department of Earth and Atmospheric Sciences, Indiana
University, 1001 E. 10th St., Bloomington, IN, USA
Atmospheric Sciences and Global Change Division, Pacific
Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA, USA
Ben Bond-Lamberty
Pacific Northwest National Laboratory, Joint Global Change
Research Institute, 5825 University Research Ct., College Park, MD, USA
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We examined the potential effect of stratospheric aerosol injection (SAI) on extreme temperature and precipitation. SAI may cause daytime temperatures to cool but nighttime to warm. Daytime cooling may occur in all seasons across the globe, with the largest decreases in summer. In contrast, nighttime warming may be greatest at high latitudes in winter. SAI may reduce the frequency and intensity of extreme rainfall. The combined changes may exacerbate drying over parts of the global south.
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Huiying Ren, Erol Cromwell, Ben Kravitz, and Xingyuan Chen
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Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
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As carbon (C) and greenhouse gas (GHG) research has adopted appropriate technology and approach (AT&A), low-cost instruments, open-source software, and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility, and performance, the integration of low-cost and low-technology, participatory and networking-based research approaches can be AT&A for enhancing C and GHG research in developing countries.
Jinshi Jian, Xuan Du, Juying Jiao, Xiaohua Ren, Karl Auerswald, Ryan Stewart, Zeli Tan, Jianlin Zhao, Daniel L. Evans, Guangju Zhao, Nufang Fang, Wenyi Sun, Chao Yue, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-87, https://doi.org/10.5194/essd-2022-87, 2022
Manuscript not accepted for further review
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Field soil loss and sediment yield due to surface runoff observations were compiled into a database named AWESOME: Archive for Water Erosion and Sediment Outflow MEasurements. Annual soil erosion data from 1985 geographic sites and 75 countries have been compiled into AWESOME. This database aims to be an open framework for the scientific community to share field-based annual soil erosion measurements, enabling better understanding of the spatial and temporal variability of annual soil erosion.
Andy Jones, Jim M. Haywood, Adam A. Scaife, Olivier Boucher, Matthew Henry, Ben Kravitz, Thibaut Lurton, Pierre Nabat, Ulrike Niemeier, Roland Séférian, Simone Tilmes, and Daniele Visioni
Atmos. Chem. Phys., 22, 2999–3016, https://doi.org/10.5194/acp-22-2999-2022, https://doi.org/10.5194/acp-22-2999-2022, 2022
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Simulations by six Earth-system models of geoengineering by introducing sulfuric acid aerosols into the tropical stratosphere are compared. A robust impact on the northern wintertime North Atlantic Oscillation is found, exacerbating precipitation reduction over parts of southern Europe. In contrast, the models show no consistency with regard to impacts on the Quasi-Biennial Oscillation, although results do indicate a risk that the oscillation could become locked into a permanent westerly phase.
Daniele Visioni, Simone Tilmes, Charles Bardeen, Michael Mills, Douglas G. MacMartin, Ben Kravitz, and Jadwiga H. Richter
Atmos. Chem. Phys., 22, 1739–1756, https://doi.org/10.5194/acp-22-1739-2022, https://doi.org/10.5194/acp-22-1739-2022, 2022
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Aerosols are simulated in a simplified way in climate models: in the model analyzed here, they are represented in every grid as described by three simple logarithmic distributions, mixing all different species together. The size can evolve when new particles are formed, particles merge together to create a larger one or particles are deposited to the surface. This approximation normally works fairly well. Here we show however that when large amounts of sulfate are simulated, there are problems.
Yan Zhang, Douglas G. MacMartin, Daniele Visioni, and Ben Kravitz
Earth Syst. Dynam., 13, 201–217, https://doi.org/10.5194/esd-13-201-2022, https://doi.org/10.5194/esd-13-201-2022, 2022
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Adding SO2 to the stratosphere could temporarily cool the planet by reflecting more sunlight back to space. However, adding SO2 at different latitude(s) and season(s) leads to significant differences in regional surface climate. This study shows that, to cool the planet by 1–1.5 °C, there are likely six to eight choices of injection latitude(s) and season(s) that lead to meaningfully different distributions of climate impacts.
Katherine V. Calvin, Abigail Snyder, Xin Zhao, and Marshall Wise
Geosci. Model Dev., 15, 429–447, https://doi.org/10.5194/gmd-15-429-2022, https://doi.org/10.5194/gmd-15-429-2022, 2022
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Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. We identify parameter combinations that best replicate historical land use in the United States.
Dawn L. Woodard, Alexey N. Shiklomanov, Ben Kravitz, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 4751–4767, https://doi.org/10.5194/gmd-14-4751-2021, https://doi.org/10.5194/gmd-14-4751-2021, 2021
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We have added a representation of the permafrost carbon feedback to the simple, open-source global carbon–climate model Hector and calibrated the results to be consistent with historical data and Earth system model projections. Our results closely match previous work, estimating around 0.2 °C of warming from permafrost this century. This capability will be useful to explore uncertainties in this feedback and for coupling with integrated assessment models for policy and economic analysis.
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244, https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
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Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Daniele Visioni, Douglas G. MacMartin, Ben Kravitz, Olivier Boucher, Andy Jones, Thibaut Lurton, Michou Martine, Michael J. Mills, Pierre Nabat, Ulrike Niemeier, Roland Séférian, and Simone Tilmes
Atmos. Chem. Phys., 21, 10039–10063, https://doi.org/10.5194/acp-21-10039-2021, https://doi.org/10.5194/acp-21-10039-2021, 2021
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A new set of simulations is used to investigate commonalities, differences and sources of uncertainty when simulating the injection of SO2 in the stratosphere in order to mitigate the effects of climate change (solar geoengineering). The models differ in how they simulate the aerosols and how they spread around the stratosphere, resulting in differences in projected regional impacts. Overall, however, the models agree that aerosols have the potential to mitigate the warming produced by GHGs.
Nikolas O. Aksamit, Ben Kravitz, Douglas G. MacMartin, and George Haller
Atmos. Chem. Phys., 21, 8845–8861, https://doi.org/10.5194/acp-21-8845-2021, https://doi.org/10.5194/acp-21-8845-2021, 2021
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There exist robust and influential material features evolving within turbulent fluids that behave as the skeleton for fluid transport pathways. Recent developments in applied mathematics have made the identification of these time-varying structures more rigorous and insightful than ever. Using short-range wind forecasts, we detail how and why these material features can be exploited in an effort to optimize the spread of aerosols in the stratosphere for climate geoengineering.
Dong-Gill Kim, Ben Bond-Lamberty, Youngryel Ryu, Bumsuk Seo, and Dario Papale
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-85, https://doi.org/10.5194/bg-2021-85, 2021
Manuscript not accepted for further review
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While greenhouse gas (GHG) research has adopted highly advanced technology some have adopted appropriate technology and approach (AT&A) such as low-cost instrument, open source software and participatory research and their results were well accepted by scientific communities. In terms of cost, feasibility and performance, integration of low-cost and low-technology, participatory and networking based research approaches can be AT&A for enhancing GHG research in developing countries.
Ben Kravitz, Douglas G. MacMartin, Daniele Visioni, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Andy Jones, Thibaut Lurton, Pierre Nabat, Ulrike Niemeier, Alan Robock, Roland Séférian, and Simone Tilmes
Atmos. Chem. Phys., 21, 4231–4247, https://doi.org/10.5194/acp-21-4231-2021, https://doi.org/10.5194/acp-21-4231-2021, 2021
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This study investigates multi-model response to idealized geoengineering (high CO2 with solar reduction) across two different generations of climate models. We find that, with the exception of a few cases, the results are unchanged between the different generations. This gives us confidence that broad conclusions about the response to idealized geoengineering are robust.
Jeff W. Atkins, Elizabeth Agee, Alexandra Barry, Kyla M. Dahlin, Kalyn Dorheim, Maxim S. Grigri, Lisa T. Haber, Laura J. Hickey, Aaron G. Kamoske, Kayla Mathes, Catherine McGuigan, Evan Paris, Stephanie C. Pennington, Carly Rodriguez, Autym Shafer, Alexey Shiklomanov, Jason Tallant, Christopher M. Gough, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 943–952, https://doi.org/10.5194/essd-13-943-2021, https://doi.org/10.5194/essd-13-943-2021, 2021
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The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. The data included help to interpret how carbon cycling processes respond over time to disturbance.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
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Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Andy Jones, Jim M. Haywood, Anthony C. Jones, Simone Tilmes, Ben Kravitz, and Alan Robock
Atmos. Chem. Phys., 21, 1287–1304, https://doi.org/10.5194/acp-21-1287-2021, https://doi.org/10.5194/acp-21-1287-2021, 2021
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Two different methods of simulating a geoengineering scenario are compared using data from two different Earth system models. One method is very idealised while the other includes details of a plausible mechanism. The results from both models agree that the idealised approach does not capture an impact found when detailed modelling is included, namely that geoengineering induces a positive phase of the North Atlantic Oscillation which leads to warmer, wetter winters in northern Europe.
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375, https://doi.org/10.5194/gmd-14-365-2021, https://doi.org/10.5194/gmd-14-365-2021, 2021
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Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
Walker Lee, Douglas MacMartin, Daniele Visioni, and Ben Kravitz
Earth Syst. Dynam., 11, 1051–1072, https://doi.org/10.5194/esd-11-1051-2020, https://doi.org/10.5194/esd-11-1051-2020, 2020
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The injection of aerosols into the stratosphere to reflect sunlight could reduce global warming, but this type of
geoengineeringwould also impact other variables like precipitation and sea ice. In this study, we model various climate impacts of geoengineering on a 3-D graph to show how trying to meet one climate goal will affect other variables. We also present two computer simulations which validate our model and show that geoengineering could regulate precipitation as well as temperature.
Jinshi Jian, Xuan Du, Ryan D. Stewart, Zeli Tan, and Ben Bond-Lamberty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-283, https://doi.org/10.5194/essd-2020-283, 2020
Preprint withdrawn
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Field soil loss due to surface runoff observations were compiled into a global database (SoilErosionDB). The database focuses on three erosion-related metrics – surface runoff, soil erosion, and nutrient leaching – and also records background information. Data from 99 geographic sites and 22 countries around the world have been compiled into SoilErosionDB. SoilErosionDB aims to be a data framework for the scientific community to share field-based soil erosion measurements.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Abigail Snyder, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Karina Williams, Ziwei Wang, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 3995–4018, https://doi.org/10.5194/gmd-13-3995-2020, https://doi.org/10.5194/gmd-13-3995-2020, 2020
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Improving our understanding of the impacts of climate change on crop yields will be critical for global food security in the next century. The models often used to study the how climate change may impact agriculture are complex and costly to run. In this work, we describe a set of global crop model emulators (simplified models) developed under the Agricultural Model Intercomparison Project. Crop model emulators make agricultural simulations more accessible to policy or decision makers.
Bethany Sutherland, Ben Kravitz, Philip J. Rasch, and Hailong Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-228, https://doi.org/10.5194/gmd-2020-228, 2020
Preprint withdrawn
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Through a cascade of physical mechanisms, a change in one location can trigger a response in a different location. These responses and the mechanisms that cause them are difficult to detect. Here we propose a method, using global climate models, to detect possible relationships between changes in one region and responses throughout the globe caused by that change. A change in the Pacific ocean is used as a test case to determine the effectiveness of the method.
Simone Tilmes, Douglas G. MacMartin, Jan T. M. Lenaerts, Leo van Kampenhout, Laura Muntjewerf, Lili Xia, Cheryl S. Harrison, Kristen M. Krumhardt, Michael J. Mills, Ben Kravitz, and Alan Robock
Earth Syst. Dynam., 11, 579–601, https://doi.org/10.5194/esd-11-579-2020, https://doi.org/10.5194/esd-11-579-2020, 2020
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This paper introduces new geoengineering model experiments as part of a larger model intercomparison effort, using reflective particles to block some of the incoming solar radiation to reach surface temperature targets. Outcomes of these applications are contrasted based on a high greenhouse gas emission pathway and a pathway with strong mitigation and negative emissions after 2040. We compare quantities that matter for societal and ecosystem impacts between the different scenarios.
Theodore Weber, Austin Corotan, Brian Hutchinson, Ben Kravitz, and Robert Link
Atmos. Chem. Phys., 20, 2303–2317, https://doi.org/10.5194/acp-20-2303-2020, https://doi.org/10.5194/acp-20-2303-2020, 2020
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Climate model emulators can save computer time but are less accurate than full climate models. We use neural networks to build emulators of precipitation, trained on existing climate model runs. By doing so, we can capture nonlinearities and how the past state of a model (to some degree) shapes the future state. Our emulator outperforms a persistence forecast of precipitation.
Stephanie C. Pennington, Nate G. McDowell, J. Patrick Megonigal, James C. Stegen, and Ben Bond-Lamberty
Biogeosciences, 17, 771–780, https://doi.org/10.5194/bg-17-771-2020, https://doi.org/10.5194/bg-17-771-2020, 2020
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Soil respiration (Rs) is the flow of CO2 from the soil surface to the atmosphere and is one of the largest carbon fluxes on land. This study examined the effect of local basal area (tree area) on Rs in a coastal forest in eastern Maryland, USA. Rs measurements were taken as well as distance from soil collar, diameter, and species of each tree within a 15 m radius. We found that trees within 5 m of our sampling points had a positive effect on how sensitive soil respiration was to temperature.
Adria K. Schwarber, Steven J. Smith, Corinne A. Hartin, Benjamin Aaron Vega-Westhoff, and Ryan Sriver
Earth Syst. Dynam., 10, 729–739, https://doi.org/10.5194/esd-10-729-2019, https://doi.org/10.5194/esd-10-729-2019, 2019
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Simple climate models (SCMs) underlie many important scientific and decision-making endeavors. This illustrates the need for their use to be rooted in a clear understanding of their fundamental responses. In this study, we provide a comprehensive assessment of model performance by evaluating the fundamental responses of several SCMs. We find biases in some responses, which have implications for decision science. We conclude by recommending a standard set of validation tests for any SCM.
Abigail Snyder, Katherine V. Calvin, Meridel Phillips, and Alex C. Ruane
Geosci. Model Dev., 12, 1319–1350, https://doi.org/10.5194/gmd-12-1319-2019, https://doi.org/10.5194/gmd-12-1319-2019, 2019
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Future changes in Earth system state will impact agricultural yields and therefore the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields, but are often too computationally intensive to dynamically couple into global multi-sector economic models, such as GCAM and other similar-in-scale models. This work describes a new crop yield change emulator, Persephone, that can capture yield changes in a computationally efficient way.
Katherine Calvin, Pralit Patel, Leon Clarke, Ghassem Asrar, Ben Bond-Lamberty, Ryna Yiyun Cui, Alan Di Vittorio, Kalyn Dorheim, Jae Edmonds, Corinne Hartin, Mohamad Hejazi, Russell Horowitz, Gokul Iyer, Page Kyle, Sonny Kim, Robert Link, Haewon McJeon, Steven J. Smith, Abigail Snyder, Stephanie Waldhoff, and Marshall Wise
Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, https://doi.org/10.5194/gmd-12-677-2019, 2019
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This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. GCAM examines the future evolution of these systems through the end of the 21st century. It can be used to examine, for example, how changes in population, income, or technology cost might alter crop production, energy demand, or water withdrawals, or how changes in one region’s demand for energy affect energy, water, and land in other regions.
Christopher G. Fletcher, Ben Kravitz, and Bakr Badawy
Atmos. Chem. Phys., 18, 17529–17543, https://doi.org/10.5194/acp-18-17529-2018, https://doi.org/10.5194/acp-18-17529-2018, 2018
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The most important number for future climate projections is Earth's climate sensitivity (CS), or how much warming will result from increased carbon dioxide. We cannot know the true CS, and estimates of CS from climate models have a wide range. This study identifies the major factors that control this range, and we show that the choice of methods used in creating a climate model are three times more important than fine-tuning the details of the model after it is created.
Ben Kravitz, Philip J. Rasch, Hailong Wang, Alan Robock, Corey Gabriel, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Duoying Ji, Andy Jones, Andrew Lenton, John C. Moore, Helene Muri, Ulrike Niemeier, Steven Phipps, Hauke Schmidt, Shingo Watanabe, Shuting Yang, and Jin-Ho Yoon
Atmos. Chem. Phys., 18, 13097–13113, https://doi.org/10.5194/acp-18-13097-2018, https://doi.org/10.5194/acp-18-13097-2018, 2018
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Marine cloud brightening has been proposed as a means of geoengineering/climate intervention, or deliberately altering the climate system to offset anthropogenic climate change. In idealized simulations that highlight contrasts between land and ocean, we find that the globe warms, including the ocean due to transport of heat from land. This study reinforces that no net energy input into the Earth system does not mean that temperature will necessarily remain unchanged.
Duoying Ji, Songsong Fang, Charles L. Curry, Hiroki Kashimura, Shingo Watanabe, Jason N. S. Cole, Andrew Lenton, Helene Muri, Ben Kravitz, and John C. Moore
Atmos. Chem. Phys., 18, 10133–10156, https://doi.org/10.5194/acp-18-10133-2018, https://doi.org/10.5194/acp-18-10133-2018, 2018
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We examine extreme temperature and precipitation under climate-model-simulated solar dimming and stratospheric aerosol injection geoengineering schemes. Both types of geoengineering lead to lower minimum temperatures at higher latitudes and greater cooling of minimum temperatures and maximum temperatures over land compared with oceans. Stratospheric aerosol injection is more effective in reducing tropical extreme precipitation, while solar dimming is more effective over extra-tropical regions.
David P. Keller, Andrew Lenton, Vivian Scott, Naomi E. Vaughan, Nico Bauer, Duoying Ji, Chris D. Jones, Ben Kravitz, Helene Muri, and Kirsten Zickfeld
Geosci. Model Dev., 11, 1133–1160, https://doi.org/10.5194/gmd-11-1133-2018, https://doi.org/10.5194/gmd-11-1133-2018, 2018
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There is little consensus on the impacts and efficacy of proposed carbon dioxide removal (CDR) methods as a potential means of mitigating climate change. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDR-MIP) has been initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDR-MIP experiments.
Camilla W. Stjern, Helene Muri, Lars Ahlm, Olivier Boucher, Jason N. S. Cole, Duoying Ji, Andy Jones, Jim Haywood, Ben Kravitz, Andrew Lenton, John C. Moore, Ulrike Niemeier, Steven J. Phipps, Hauke Schmidt, Shingo Watanabe, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 18, 621–634, https://doi.org/10.5194/acp-18-621-2018, https://doi.org/10.5194/acp-18-621-2018, 2018
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Marine cloud brightening (MCB) has been proposed to help limit global warming. We present here the first multi-model assessment of idealized MCB simulations from the Geoengineering Model Intercomparison Project. While all models predict a global cooling as intended, there is considerable spread between the models both in terms of radiative forcing and the climate response, largely linked to the substantial differences in the models' representation of clouds.
Yannick Le Page, Douglas Morton, Corinne Hartin, Ben Bond-Lamberty, José Miguel Cardoso Pereira, George Hurtt, and Ghassem Asrar
Earth Syst. Dynam., 8, 1237–1246, https://doi.org/10.5194/esd-8-1237-2017, https://doi.org/10.5194/esd-8-1237-2017, 2017
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Fires damage large areas of eastern Amazon forests when ignitions from human activity coincide with droughts, while more humid central and western regions are less affected. Here, we use a fire model to estimate that fire activity could increase by an order of magnitude without climate mitigation. Our results show that avoiding further agricultural expansion can limit fire ignitions but that tackling climate change is essential to insulate the interior Amazon through the 21st century.
Abigail C. Snyder, Robert P. Link, and Katherine V. Calvin
Geosci. Model Dev., 10, 4307–4319, https://doi.org/10.5194/gmd-10-4307-2017, https://doi.org/10.5194/gmd-10-4307-2017, 2017
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Experiments conducting a model forecast for a period in which observational data are available are rarely undertaken in the integrated assessment model (IAM) community. When undertaken, results are often evaluated using global aggregates that mask deficiencies. Comparing land allocation simulations in GCAM with FAO observational data from 1990 to 2010, we find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs with global supply constraints similar to GCAM.
Lars Ahlm, Andy Jones, Camilla W. Stjern, Helene Muri, Ben Kravitz, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 17, 13071–13087, https://doi.org/10.5194/acp-17-13071-2017, https://doi.org/10.5194/acp-17-13071-2017, 2017
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We present results from coordinated simulations with three Earth system models focusing on the response of Earth’s radiation balance to the injection of sea salt particles. We find that in most regions the effective radiative forcing by the injected particles is equally large in cloudy and clear-sky conditions, suggesting a more important role of the aerosol direct effect in sea spray climate engineering than previously thought.
Cary Lynch, Corinne Hartin, Min Chen, and Ben Bond-Lamberty
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-405, https://doi.org/10.5194/bg-2017-405, 2017
Revised manuscript has not been submitted
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Heterotrophic respiration (RH) is a large part of the carbon cycle, but it is poorly simulated by climate models. We examine the relationships between RH and key climate variables to understand this uncertainty in observations and from climate models. Compared to observations, models overestimate both the RH trend and climatological relationships. In the future, the relationship between RH and temperature is strong and can be used to explore a wide range of future scenarios.
James C. Stegen, Carolyn G. Anderson, Ben Bond-Lamberty, Alex R. Crump, Xingyuan Chen, and Nancy Hess
Biogeosciences, 14, 4341–4354, https://doi.org/10.5194/bg-14-4341-2017, https://doi.org/10.5194/bg-14-4341-2017, 2017
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CO2 loss from soil to the atmosphere (
soil respiration) is a key ecosystem function, especially in systems with permafrost. We find that soil respiration shows a non-linear threshold at permafrost depths > 140 cm and that the number of large trees governs soil respiration. This suggests that remote sensing could be used to estimate spatial variation in soil respiration and (with knowledge of key thresholds) empirically constrain models that predict ecosystem responses to permafrost thaw.
Cary Lynch, Corinne Hartin, Ben Bond-Lamberty, and Ben Kravitz
Earth Syst. Sci. Data, 9, 281–292, https://doi.org/10.5194/essd-9-281-2017, https://doi.org/10.5194/essd-9-281-2017, 2017
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Pattern scaling climate model output is a computationally efficient way to produce a large amount of data for purposes of uncertainty quantification. Using a multi-model ensemble we explore pattern scaling methodologies across two future forcing scenarios. We find that the simple least squares approach to pattern scaling produces a close approximation of actual model output, and we use this as a justification for the creation of an open-access pattern library at multiple time increments.
Ben Kravitz, Cary Lynch, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 10, 1889–1902, https://doi.org/10.5194/gmd-10-1889-2017, https://doi.org/10.5194/gmd-10-1889-2017, 2017
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Pattern scaling is a way of approximating regional changes without needing to run a full, complex global climate model. We compare two methods of pattern scaling for precipitation and evaluate which methods is
betterin particular circumstances. We also decompose precipitation into a CO2 portion and a non-CO2 portion. The methodologies discussed in this paper can help provide precipitation fields for other models for a wide variety of scenarios of future climate change.
Hiroki Kashimura, Manabu Abe, Shingo Watanabe, Takashi Sekiya, Duoying Ji, John C. Moore, Jason N. S. Cole, and Ben Kravitz
Atmos. Chem. Phys., 17, 3339–3356, https://doi.org/10.5194/acp-17-3339-2017, https://doi.org/10.5194/acp-17-3339-2017, 2017
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This study analyses shortwave radiation (SW) in the G4 experiment of the Geoengineering Model Intercomparison Project. G4 involves stratospheric injection of 5 Tg yr−1 of SO2 against the RCP4.5 scenario. The global mean forcing of the sulphate geoengineering has an inter-model variablity of −3.6 to −1.6 W m−2, implying a high uncertainty in modelled processes of sulfate aerosols. Changes in water vapour and cloud amounts due to the SO2 injection weaken the forcing at the surface by around 50 %.
Ben Kravitz, Douglas G. MacMartin, Philip J. Rasch, and Hailong Wang
Atmos. Chem. Phys., 17, 2525–2541, https://doi.org/10.5194/acp-17-2525-2017, https://doi.org/10.5194/acp-17-2525-2017, 2017
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We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state.
Corey J. Gabriel, Alan Robock, Lili Xia, Brian Zambri, and Ben Kravitz
Atmos. Chem. Phys., 17, 595–613, https://doi.org/10.5194/acp-17-595-2017, https://doi.org/10.5194/acp-17-595-2017, 2017
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The National Center for Atmospheric Research CESM-CAM4-CHEM global climate model was modified to simulate a scheme in which the albedo of the ocean surface is raised over the subtropical ocean gyres in the Southern Hemisphere. Global mean surface temperature in G4Foam is 0.6K lower than RCP6.0, with statistically significant cooling relative to RCP6.0 south of 30° N and an increase in rainfall over land, most pronouncedly during the JJA season, relative to both G4SSA and RCP6.0.
Douglas G. MacMartin and Ben Kravitz
Atmos. Chem. Phys., 16, 15789–15799, https://doi.org/10.5194/acp-16-15789-2016, https://doi.org/10.5194/acp-16-15789-2016, 2016
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Solar geoengineering has been proposed as a possible additional approach for managing risks of climate change, by reflecting some sunlight back to space. To project climate effects resulting from future choices regarding both greenhouse gas emissions and solar geoengineering, it is useful to have a computationally efficient "emulator" that approximates the behavior of more complex climate models. We present such an emulator here, and validate the underlying assumption of linearity.
Ben Bond-Lamberty, A. Peyton Smith, and Vanessa Bailey
Biogeosciences, 13, 6669–6681, https://doi.org/10.5194/bg-13-6669-2016, https://doi.org/10.5194/bg-13-6669-2016, 2016
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We used a laboratory experiment to examine how climate change and permafrost melting might alter soils in high-latitude regions. Soils were subjected to two temperatures and drought, and gas emissions were monitored. Carbon dioxide fluxes were influenced by temperature, water, and soil nitrogen, while methane emissions were much smaller and linked only with nitrogen. This suggests that such soils may be very sensitive to changes in moisture as discontinuous permafrost thaws in interior Alaska.
Yannick Le Page, Tris O. West, Robert Link, and Pralit Patel
Geosci. Model Dev., 9, 3055–3069, https://doi.org/10.5194/gmd-9-3055-2016, https://doi.org/10.5194/gmd-9-3055-2016, 2016
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A computer program was developed to transform maps of regional land use (e.g., crops) and land cover (e.g., forests) areas into gridded maps actually representing their spatial distribution within each region. This is important for studies of future environmental change: economic models project agricultural activities at the regional scale, but Earth system models need gridded information to project the impact of such activities on climate, biodiversity, water availability, and other aspects.
Corinne A. Hartin, Benjamin Bond-Lamberty, Pralit Patel, and Anupriya Mundra
Biogeosciences, 13, 4329–4342, https://doi.org/10.5194/bg-13-4329-2016, https://doi.org/10.5194/bg-13-4329-2016, 2016
Cary Lynch, Corinne Hartin, Ben Bond-Lamberty, and Ben Kravitz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-170, https://doi.org/10.5194/gmd-2016-170, 2016
Revised manuscript not accepted
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Pattern scaling is used to explore uncertainty in future forcing scenarios and assess local climate sensitivity to global temperature change. This paper examines the two dominant pattern scaling methods using a multi-model ensemble with two future socio-economic storylines. We find that high latitudes show the strongest sensitivity to global temperature change and that the simple least squared regression approach to generation of patterns is a better fit to projected global temperature.
Ben Kravitz, Douglas G. MacMartin, Hailong Wang, and Philip J. Rasch
Earth Syst. Dynam., 7, 469–497, https://doi.org/10.5194/esd-7-469-2016, https://doi.org/10.5194/esd-7-469-2016, 2016
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Most simulations of solar geoengineering prescribe a particular strategy and evaluate its modeled effects. Here we first choose example climate objectives and then design a strategy to meet those objectives in climate models. We show that certain objectives can be met simultaneously even in the presence of uncertainty, and the strategy for meeting those objectives can be ported to other models. This is part of a broader illustration of how uncertainties in solar geoengineering can be managed.
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
W. D. Collins, A. P. Craig, J. E. Truesdale, A. V. Di Vittorio, A. D. Jones, B. Bond-Lamberty, K. V. Calvin, J. A. Edmonds, S. H. Kim, A. M. Thomson, P. Patel, Y. Zhou, J. Mao, X. Shi, P. E. Thornton, L. P. Chini, and G. C. Hurtt
Geosci. Model Dev., 8, 2203–2219, https://doi.org/10.5194/gmd-8-2203-2015, https://doi.org/10.5194/gmd-8-2203-2015, 2015
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The integrated Earth system model (iESM) has been developed as a
new tool for projecting the joint human-climate system. The
iESM is based upon coupling an integrated assessment model (IAM)
and an Earth system model (ESM) into a common modeling
infrastructure. By introducing heretofore-omitted
feedbacks between natural and societal drivers in iESM, we can improve
scientific understanding of the human-Earth system
dynamics.
C. A. Hartin, P. Patel, A. Schwarber, R. P. Link, and B. P. Bond-Lamberty
Geosci. Model Dev., 8, 939–955, https://doi.org/10.5194/gmd-8-939-2015, https://doi.org/10.5194/gmd-8-939-2015, 2015
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Simple climate models play an integral role in policy and scientific communities. Hector v1.0 is an open-source, object-oriented, simple global climate carbon-cycle model. Hector reproduces the global historical trends of atmospheric [CO2], radiative forcing, and surface temperatures. Hector simulates all four representative concentration pathways with equivalent rates of change of key variables over time compared to current observations and other models.
B. Bond-Lamberty, J. P. Fisk, J. A. Holm, V. Bailey, G. Bohrer, and C. M. Gough
Biogeosciences, 12, 513–526, https://doi.org/10.5194/bg-12-513-2015, https://doi.org/10.5194/bg-12-513-2015, 2015
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How will aging forests behave as they undergo ecological transitions? Can our models, which support scientific, policy, and management analyses, accurately simulate these transitions? We tested whether three forest ecosystem models could reproduce dynamics observed in an experimentally manipulated forest in northern Michigan, USA. None of the models fully captured the post-disturbance C fluxes observed, raising doubts about their ability to simulate tree death after moderate disturbances.
S. Tilmes, M. J. Mills, U. Niemeier, H. Schmidt, A. Robock, B. Kravitz, J.-F. Lamarque, G. Pitari, and J. M. English
Geosci. Model Dev., 8, 43–49, https://doi.org/10.5194/gmd-8-43-2015, https://doi.org/10.5194/gmd-8-43-2015, 2015
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A new Geoengineering Model Intercomparison Project (GeoMIP) experiment “G4 specified stratospheric aerosols” (G4SSA) is proposed to investigate the impact of stratospheric aerosol geoengineering on atmosphere, chemistry, dynamics, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulfur dioxide (SO2) into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments.
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Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
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.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a sub-sea CO2 injection.
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.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used for climate impact assessments, adaptation and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. 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.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged between WRF and any other model (e.g. an ocean model) using the coupling library Ocean-Atmosphere-Sea-Ice-Soil – Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
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We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
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.
Ulrich Georg Wortmann, Tina Tsan, Mahrukh Niazi, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
EGUsphere, https://doi.org/10.5194/egusphere-2024-1864, https://doi.org/10.5194/egusphere-2024-1864, 2024
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The Earth Science Box Modeling Toolkit (ESBMTK) is a Python library designed to separate model description from numerical implementation. This approach results in well-documented, easily readable, and maintainable model code, allowing students and researchers to concentrate on conceptual challenges rather than mathematical intricacies.
Malcolm John Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2582, https://doi.org/10.5194/egusphere-2024-2582, 2024
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HighResMIP2 is a model intercomparison project focussing on high resolution global climate models, that is those with grid spacings of 25 km or less in atmosphere and ocean, using simulations of decades to a century or so in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present day and future projections, and to build links with other communities to provide more robust climate information.
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.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O’Rourke, and Beth Dingley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2363, https://doi.org/10.5194/egusphere-2024-2363, 2024
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 132 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most heavily used variables from Earth System Models, based on an assessment of data publication and download records from the largest archive of global climate projects.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis O'Brien
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-142, https://doi.org/10.5194/gmd-2024-142, 2024
Revised manuscript accepted for GMD
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1. A metrics package designed for easy analysis of AR characteristics and statistics is presented. 2. The tool is efficient for diagnosing systematic AR bias in climate models, and useful for evaluating new AR characteristics in model simulations. 3. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the north and south Atlantic (south Pacific and Indian Ocean).
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.
Cited articles
Akhtar, M. K., Wibe, J., Simonovic, S. P., and MacGee, J.: Integrated
assessment model of society-biosphere-climate-economy-energy system,
Environ. Modell. Softw., 49, 1 – 21,
https://doi.org/10.1016/j.envsoft.2013.07.006,
2013. a
Alexeeff, S. E., Nychka, D., Sain, S. R., and Tebaldi, C.: Emulating mean
patterns and variability of temperature across and within scenarios in
anthropogenic climate change experiments, Climatic Change, 146, 319–333,
https://doi.org/10.1007/s10584-016-1809-8,
2016. a
Bodman, R. W. and Jones, R. N.: Bayesian estimation of climate sensitivity
using observationally constrained simple climate models, Wires. Clim. Change, 7, 461–473,
https://doi.org/10.1002/wcc.397,
2016. a
Calvin, K. and Bond-Lamberty, B.: Integrated human-earth system
modeling-state of the science and future directions, Environ. Res.
Lett., 13, 063006, https://doi.org/10.1088/1748-9326/aac642, 2018. a
Castruccio, S. and Stein, M.: Global space-time models for climate
ensembles,
Ann. Appl. Stat., 7, 1593–1611, 2013. a
Cui, Y., Calvin, K. V., Clarke, L., Hejazi, M., Kim, S., Kyle, G. P., Patel,
P., Turner, S. W., and Wise, M.: Regional responses to future, demand-driven
water scarcity, Environ. Res. Lett., 13, 094006, https://doi.org/10.1088/1748-9326/aad8f7,
2018. a
Elliott, J., Deryng, D., Müller, C., Frieler, K., Konzmann, M., Gerten,
D.,
Glotter, M., Flörke, M., Wada, Y., Best, N., Eisner, S., Fekete, B. M., Folberth, C., Foster, I., Gosling, S. N., Haddeland, I.,
Khabarov, N., Ludwig, F., Masaki, Y., Olin, S., Rosenzweig, C., Ruane, A. C., Satoh, Y.,
Schmid, E., Stacke, T., Tang, Q., and Wisser, D.: Constraints and
potentials of future irrigation water availability on agricultural production
under climate change, P. Natl. Acad. Sci. USA, 111,
3239–3244, 2014. a
Falloon, P., Challinor, A., Dessai, S., Hoang, L., Johnson, J., and Koehler,
A.-K.: Ensembles and uncertainty in climate change impacts, Front.
Environ. Sci., 2, 33 pp.,
https://doi.org/10.3389/fenvs.2014.00033,
2014. a
Field, C. B., Barros, V., Stocker, T. F., and Dahe, Q.:
Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate
change, Cambridge University Press,
2012. a
Golub, G. H. and Van Loan, C. F.: Matrix Computations, 3rd Edn., JHU Press,
Baltimore,
MD, 1996. a
Greenough, G., McGeehin, M., Bernard, S. M., Trtanj, J., Riad, J., and
Engelberg, D.: The potential impacts of climate variability and change on
health impacts of extreme weather events in the United States,
Environ. Health Persp., 109, 191–198, 2001. a
Hartin, C. A., Patel, P., Schwarber, A., Link, R. P., and Bond-Lamberty, B.
P.: A simple object-oriented and open-source model for scientific and policy
analyses of the global climate system – Hector v1.0, Geosci. Model Dev., 8,
939–955, https://doi.org/10.5194/gmd-8-939-2015, 2015. a
Holden, P. B. and Edwards, N. R.: Dimensionally reduced emulation of an
AOGCM for application to integrated assessment modelling, Geophys.
Res. Lett., 37, L21707, https://doi.org/10.1029/2010GL045137,
2010. a
Joshi, M., Lambert, F., and Webb, M.: An explanation for the difference
between twentieth and twenty-first century land–sea warming ratio in climate
models, Clim. Dynam., 41, 1853–1869, 2013. a
Kay, J., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G., Arblaster,
J., Bates, S., Danabasoglu, G., Edwards, J., Holland, M., Kushner, P., Lamarque, J. F., Lawrence, D.,
Lindsay, K., Middleton, A., Munoz, E., Neale, R., Oleson, K., Polvani, L., and
Vertenstein, M.: The Community Earth
System Model (CESM) large ensemble project: A community resource for studying
climate change in the presence of internal climate variability, B.
Am. Meteorol. Soc., 96, 1333–1349, 2015. a, b
Kutzbach, J. E.: Empirical eigenvectors of sea-level pressure, surface
temperature and precipitation complexes over North America, J.
Appl. Meteorol., 6, 791–802, 1967. a
Link, R.: JGCRI/fldgen: Version 1.0.0, https://doi.org/10.5281/zenodo.1183347, 2018. a
Link, R., Snyder, A., and Dorheim, K.:
Fldgen Software Repository,
available at: https://github.com/JGCRI/fldgen (last access:
10 April 2019), 2018a. a
Link, R., Snyder, A., Lynch, C., Hartin, C., Kravitz, B., and Bond-Lamberty, B.:
Data and analysis for “Fldgen v1.0: An Emulator with Internal Variability and Space-Time Correlation for Earth System Models” [Data set],
Zenodo, https://doi.org/10.5281/zenodo.2586040, 2018b. a
MacMartin, D. G. and Kravitz, B.: Dynamic climate emulators for solar
geoengineering, Atmos. Chem. Phys., 16, 15789–15799,
https://doi.org/10.5194/acp-16-15789-2016, 2016. a, b
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled
atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 –
Part 1: Model description and calibration, Atmos. Chem. Phys., 11,
1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011. a
Mitchell, T. D.: Pattern Scaling: An Examination of the Accuracy of the
Technique for Describing Future Climates, Climatic Change, 60, 217–242,
https://doi.org/10.1023/A:1026035305597,
2003. a
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J.,
Collins, M., and Stainforth, D. A.: Quantification of modelling
uncertainties in a large ensemble of climate change simulations, Nature,
430, 768–772, https://doi.org/10.1038/nature02771, 2004. a
Neelin, J. D., Bracco, A., Luo, H., McWilliams, J. C., and Meyerson, J. E.:
Considerations for parameter optimization and sensitivity in climate
models, P. Natl. Acad. Sci. USA, 107,
21349–21354, 2010. a
Nelson, G. C., Valin, H., Sands, R. D., Havlík, P., Ahammad, H., Deryng,
D., Elliott, J., Fujimori, S., Hasegawa, T., Heyhoe, E., Page, K., Von Lampe, M., Lotze-Campen, H.,
d'Croz, D. M., van Meijl, H., van der Mesnbrugghe, D.,
Müller, C., Popp, A., Robertson, R., Robinson, S.,
Schmid, E., Schmitz, C., Tabeau, A., and Willenbockel, D.: Climate
change effects on agriculture: Economic responses to biophysical shocks,
P. Natl. Acad. Sci. USA, 111, 3274–3279, 2014. a
Osborn, T. J., Wallace, C. J., Harris, I. C., and Melvin, T. M.: Pattern
scaling using ClimGen: monthly-resolution future climate scenarios
including changes in the variability of precipitation, Climatic Change, 134,
353–369,
https://doi.org/10.1007/s10584-015-1509-9,
2015. a
Rasmussen, D. J., Meinshausen, M., and Kopp, R. E.: Probability-Weighted
Ensembles of U.S. County-Level Climate Projections for Climate Risk
Analysis, J. Appl. Meteorol. Clim., 55, 2301–2322,
https://doi.org/10.1175/JAMC-D-15-0302.1,
2016. a
Ray, D. K., Gerber, J. S., MacDonald, G. K., and West, P. C.: Climate
variation
explains a third of global crop yield variability, Nat. Commun., 6,
5989, https://doi.org/10.1038/ncomms6989, 2015. a
Rosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C.,
Arneth,
A., Boote, K. J., Folberth, C., Glotter, M., Khabarov, N., Neumann, K., Piontek, F., Pugh, T. A.
M., Schmid, E., Stehfest, E., Yang, H., and Jones, J. W.: Assessing
agricultural risks of climate change in the 21st century in a global gridded
crop model intercomparison, P. Natl. Acad. Sci. USA,
111, 3268–3273, 2014. a
Sanderson, B. M., Oleson, K. W., Strand, W. G., Lehner, F., and O'Neill,
B. C.:
A new ensemble of GCM simulations to assess avoided impacts in a climate
mitigation scenario, Climatic Change, 146, 303–318,
https://doi.org/10.1007/s10584-015-1567-z,
2015. a
Tebaldi, C. and Arblaster, J. M.: Pattern scaling: Its strengths and
limitations, and an update on the latest model simulations, Climatic Change,
122, 459–471, https://doi.org/10.1007/s10584-013-1032-9,
2014. a
Turner, S. W., Hejazi, M., Kim, S. H., Clarke, L., and Edmonds, J.: Climate
impacts on hydropower and consequences for global electricity supply
investment needs, Energy, 141, 2081–2090, 2017. a
Voisin, N., Hejazi, M. I., Leung, L. R., Liu, L., Huang, M., Li, H.-Y., and
Tesfa, T.: Effects of spatially distributed sectoral water management on the
redistribution of water resources in an integrated water model, Water
Resour. Res., 53, 4253–4270, 2017. a
Short summary
Earth system models (ESMs) produce the highest-quality future climate data available, but they are costly to run, so only a few runs from each model are publicly available. What is needed are emulators that tell us what would have happened, if we had been able to perform as many ESM runs as we might have liked. Much of the existing work on emulators has focused on deterministic projections of average values. Here we present a way to imbue emulators with the variability seen in ESM runs.
Earth system models (ESMs) produce the highest-quality future climate data available, but they...
