Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-779-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-779-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
25 Feb 2016
Development and technical paper |
| 25 Feb 2016
Impact of surface coupling grids on tropical cyclone extremes in high-resolution atmospheric simulations
National Center for Atmospheric Research, Boulder, Colorado, USA
Kevin A. Reed
School of Marine and Atmospheric Sciences, State University of New
York at Stony Brook, Stony Brook, New York, USA
Julio T. Bacmeister
National Center for Atmospheric Research, Boulder, Colorado, USA
Anthony P. Craig
National Center for Atmospheric Research, Boulder, Colorado, USA
Susan C. Bates
National Center for Atmospheric Research, Boulder, Colorado, USA
Nan A. Rosenbloom
National Center for Atmospheric Research, Boulder, Colorado, USA
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Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
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Keith B. Rodgers, Sun-Seon Lee, Nan Rosenbloom, Axel Timmermann, Gokhan Danabasoglu, Clara Deser, Jim Edwards, Ji-Eun Kim, Isla R. Simpson, Karl Stein, Malte F. Stuecker, Ryohei Yamaguchi, Tamás Bódai, Eui-Seok Chung, Lei Huang, Who M. Kim, Jean-François Lamarque, Danica L. Lombardozzi, William R. Wieder, and Stephen G. Yeager
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Zixuan Han, Qiong Zhang, Qiang Li, Ran Feng, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Bette L. Otto-Bliesner, Esther C. Brady, Nan Rosenbloom, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Charles J. R. Williams, Daniel J. Lunt, Jianbo Cheng, Qin Wen, and Natalie J. Burls
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Paul A. Ullrich, Colin M. Zarzycki, Elizabeth E. McClenny, Marielle C. Pinheiro, Alyssa M. Stansfield, and Kevin A. Reed
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Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
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Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
Lei Lin, Andrew Gettelman, Yangyang Xu, Chenglai Wu, Zhili Wang, Nan Rosenbloom, Susan C. Bates, and Wenjie Dong
Geosci. Model Dev., 12, 3773–3793, https://doi.org/10.5194/gmd-12-3773-2019, https://doi.org/10.5194/gmd-12-3773-2019, 2019
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Here we evaluate the performance of the Community Atmosphere Model version 6 (CAM6) released in 2018, with the default 1º horizontal resolution and a higher-resolution simulation (approximately 0.25º), against various precipitation observational datasets over Asia. With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia.
Leonardus van Kampenhout, Alan M. Rhoades, Adam R. Herrington, Colin M. Zarzycki, Jan T. M. Lenaerts, William J. Sacks, and Michiel R. van den Broeke
The Cryosphere, 13, 1547–1564, https://doi.org/10.5194/tc-13-1547-2019, https://doi.org/10.5194/tc-13-1547-2019, 2019
Short summary
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A new tool is evaluated in which the climate and surface mass balance (SMB) of the Greenland ice sheet are resolved at 55 and 28 km resolution, while the rest of the globe is modelled at ~110 km. The local refinement of resolution leads to improved accumulation (SMB > 0) compared to observations; however ablation (SMB < 0) is deteriorated in some regions. This is attributed to changes in cloud cover and a reduced effectiveness of a model-specific vertical downscaling technique.
Colin M. Zarzycki, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Paul A. Ullrich, David M. Hall, Mark A. Taylor, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Xi Chen, Lucas Harris, Marco Giorgetta, Daniel Reinert, Christian Kühnlein, Robert Walko, Vivian Lee, Abdessamad Qaddouri, Monique Tanguay, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Sang-Hun Park, Joseph B. Klemp, and William C. Skamarock
Geosci. Model Dev., 12, 879–892, https://doi.org/10.5194/gmd-12-879-2019, https://doi.org/10.5194/gmd-12-879-2019, 2019
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Taylor M. Hughlett, Arne M. E. Winguth, and Nan Rosenbloom
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-23, https://doi.org/10.5194/cp-2018-23, 2018
Revised manuscript has not been submitted
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This study used the Community Earth System Model version 1.2 to isolate and compare changes in radiative forcing due to orbital and atmospheric pCO2 concentrations for the Younger Dryas cooling event. It was determined that while neither parameter alone could induce a cooling comparative to the Younger Dryas, the changes in orbital parameters and the resultant changing of radiative forcing imparts a more pronounced effect on the climate than radiative changes due to pCO2.
Allison A. Wing, Kevin A. Reed, Masaki Satoh, Bjorn Stevens, Sandrine Bony, and Tomoki Ohno
Geosci. Model Dev., 11, 793–813, https://doi.org/10.5194/gmd-11-793-2018, https://doi.org/10.5194/gmd-11-793-2018, 2018
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RCEMIP, an intercomparison of multiple types of numerical models, is proposed. In RCEMIP, the climate system is modeled in an idealized manner with no spatial dependence of boundary conditions (i.e., sea surface temperature) or forcing (i.e., incoming sunlight). This set of simulations will be used to investigate how the amount of cloudiness changes with warming, how the clustering of clouds changes with warming, and how the state of the atmosphere in this idealized setup varies between models.
Michael F. Wehner, Kevin A. Reed, Burlen Loring, Dáithí Stone, and Harinarayan Krishnan
Earth Syst. Dynam., 9, 187–195, https://doi.org/10.5194/esd-9-187-2018, https://doi.org/10.5194/esd-9-187-2018, 2018
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The United Nations Framework Convention on Climate Change invited the scientific community to explore the impacts of a world in which anthropogenic global warming is stabilized at only 1.5 °C above preindustrial average temperatures. We present a projection of future tropical cyclone statistics for both 1.5 and 2.0 °C stabilized warming scenarios using a high-resolution global climate model. We find more frequent and intense tropical cyclones, but a reduction in weaker storms.
Paul A. Ullrich, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Kevin A. Reed, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Joseph Klemp, Sang-Hun Park, William Skamarock, Hiroaki Miura, Tomoki Ohno, Ryuji Yoshida, Robert Walko, Alex Reinecke, and Kevin Viner
Geosci. Model Dev., 10, 4477–4509, https://doi.org/10.5194/gmd-10-4477-2017, https://doi.org/10.5194/gmd-10-4477-2017, 2017
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Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school.
Paul A. Ullrich and Colin M. Zarzycki
Geosci. Model Dev., 10, 1069–1090, https://doi.org/10.5194/gmd-10-1069-2017, https://doi.org/10.5194/gmd-10-1069-2017, 2017
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Automated pointwise feature tracking is used for objective identification and tracking of meteorological features, such as extratropical cyclones, tropical cyclones and tropical easterly waves, and has emerged as an important and desirable data-processing capability in climate science. In the interest of exploring tracking functionality, this paper introduces a framework for the development of robust tracking algorithms that is useful for intercomparison and optimization of tracking schemes.
Fergus W. Howell, Alan M. Haywood, Bette L. Otto-Bliesner, Fran Bragg, Wing-Le Chan, Mark A. Chandler, Camille Contoux, Youichi Kamae, Ayako Abe-Ouchi, Nan A. Rosenbloom, Christian Stepanek, and Zhongshi Zhang
Clim. Past, 12, 749–767, https://doi.org/10.5194/cp-12-749-2016, https://doi.org/10.5194/cp-12-749-2016, 2016
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Simulations of pre-industrial and mid-Pliocene Arctic sea ice by eight GCMs are analysed. Ensemble variability in sea ice extent is greater in the mid-Pliocene summer, when half of the models simulate sea-ice-free conditions. Weaker correlations are seen between sea ice extent and temperatures in the pre-industrial era compared to the mid-Pliocene. The need for more comprehensive sea ice proxy data is highlighted, in order to better compare model performances.
P. H. Lauritzen, J. T. Bacmeister, P. F. Callaghan, and M. A. Taylor
Geosci. Model Dev., 8, 3975–3986, https://doi.org/10.5194/gmd-8-3975-2015, https://doi.org/10.5194/gmd-8-3975-2015, 2015
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This paper documents the NCAR global model topography generation software. The software generates elevation and related data for global atmospheric models based in GTOPO30 or GMTED2010/MODIS source data.
S. Albani, N. M. Mahowald, G. Winckler, R. F. Anderson, L. I. Bradtmiller, B. Delmonte, R. François, M. Goman, N. G. Heavens, P. P. Hesse, S. A. Hovan, S. G. Kang, K. E. Kohfeld, H. Lu, V. Maggi, J. A. Mason, P. A. Mayewski, D. McGee, X. Miao, B. L. Otto-Bliesner, A. T. Perry, A. Pourmand, H. M. Roberts, N. Rosenbloom, T. Stevens, and J. Sun
Clim. Past, 11, 869–903, https://doi.org/10.5194/cp-11-869-2015, https://doi.org/10.5194/cp-11-869-2015, 2015
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We propose an innovative framework to organize paleodust records, formalized in a publicly accessible database, and discuss the emerging properties of the global dust cycle during the Holocene by integrating our analysis with simulations performed with the Community Earth System Model. We show how the size distribution of dust is intrinsically related to the dust mass accumulation rates and that only considering a consistent size range allows for a consistent analysis of the global dust cycle.
A. Molod, L. Takacs, M. Suarez, and J. Bacmeister
Geosci. Model Dev., 8, 1339–1356, https://doi.org/10.5194/gmd-8-1339-2015, https://doi.org/10.5194/gmd-8-1339-2015, 2015
A. M. Dolan, S. J. Hunter, D. J. Hill, A. M. Haywood, S. J. Koenig, B. L. Otto-Bliesner, A. Abe-Ouchi, F. Bragg, W.-L. Chan, M. A. Chandler, C. Contoux, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, G. Ramstein, N. A. Rosenbloom, L. Sohl, C. Stepanek, H. Ueda, Q. Yan, and Z. Zhang
Clim. Past, 11, 403–424, https://doi.org/10.5194/cp-11-403-2015, https://doi.org/10.5194/cp-11-403-2015, 2015
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Climate and ice sheet models are often used to predict the nature of ice sheets in Earth history. It is important to understand whether such predictions are consistent among different models, especially in warm periods of relevance to the future. We use input from 15 different climate models to run one ice sheet model and compare the predictions over Greenland. We find that there are large differences between the predicted ice sheets for the warm Pliocene (c. 3 million years ago).
A. V. Di Vittorio, L. P. Chini, B. Bond-Lamberty, J. Mao, X. Shi, J. Truesdale, A. Craig, K. Calvin, A. Jones, W. D. Collins, J. Edmonds, G. C. Hurtt, P. Thornton, and A. Thomson
Biogeosciences, 11, 6435–6450, https://doi.org/10.5194/bg-11-6435-2014, https://doi.org/10.5194/bg-11-6435-2014, 2014
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Economic models provide scenarios of land use and greenhouse gas emissions to earth system models to project global change. We found, and partially addressed, inconsistencies in land cover between an economic and an earth system model that effectively alter a prescribed scenario, causing significant differences in projected terrestrial carbon and atmospheric CO2 between prescribed and altered scenarios. We outline a solution to this current problem in scenario-based global change projections.
D. Barahona, A. Molod, J. Bacmeister, A. Nenes, A. Gettelman, H. Morrison, V. Phillips, and A. Eichmann
Geosci. Model Dev., 7, 1733–1766, https://doi.org/10.5194/gmd-7-1733-2014, https://doi.org/10.5194/gmd-7-1733-2014, 2014
D. J. Hill, A. M. Haywood, D. J. Lunt, S. J. Hunter, F. J. Bragg, C. Contoux, C. Stepanek, L. Sohl, N. A. Rosenbloom, W.-L. Chan, Y. Kamae, Z. Zhang, A. Abe-Ouchi, M. A. Chandler, A. Jost, G. Lohmann, B. L. Otto-Bliesner, G. Ramstein, and H. Ueda
Clim. Past, 10, 79–90, https://doi.org/10.5194/cp-10-79-2014, https://doi.org/10.5194/cp-10-79-2014, 2014
R. Zhang, Q. Yan, Z. S. Zhang, D. Jiang, B. L. Otto-Bliesner, A. M. Haywood, D. J. Hill, A. M. Dolan, C. Stepanek, G. Lohmann, C. Contoux, F. Bragg, W.-L. Chan, M. A. Chandler, A. Jost, Y. Kamae, A. Abe-Ouchi, G. Ramstein, N. A. Rosenbloom, L. Sohl, and H. Ueda
Clim. Past, 9, 2085–2099, https://doi.org/10.5194/cp-9-2085-2013, https://doi.org/10.5194/cp-9-2085-2013, 2013
Z.-S. Zhang, K. H. Nisancioglu, M. A. Chandler, A. M. Haywood, B. L. Otto-Bliesner, G. Ramstein, C. Stepanek, A. Abe-Ouchi, W.-L. Chan, F. J. Bragg, C. Contoux, A. M. Dolan, D. J. Hill, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, N. A. Rosenbloom, L. E. Sohl, and H. Ueda
Clim. Past, 9, 1495–1504, https://doi.org/10.5194/cp-9-1495-2013, https://doi.org/10.5194/cp-9-1495-2013, 2013
N. A. Rosenbloom, B. L. Otto-Bliesner, E. C. Brady, and P. J. Lawrence
Geosci. Model Dev., 6, 549–561, https://doi.org/10.5194/gmd-6-549-2013, https://doi.org/10.5194/gmd-6-549-2013, 2013
A. M. Haywood, D. J. Hill, A. M. Dolan, B. L. Otto-Bliesner, F. Bragg, W.-L. Chan, M. A. Chandler, C. Contoux, H. J. Dowsett, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, A. Abe-Ouchi, S. J. Pickering, G. Ramstein, N. A. Rosenbloom, U. Salzmann, L. Sohl, C. Stepanek, H. Ueda, Q. Yan, and Z. Zhang
Clim. Past, 9, 191–209, https://doi.org/10.5194/cp-9-191-2013, https://doi.org/10.5194/cp-9-191-2013, 2013
Related subject area
Climate and Earth system modeling
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
PaleoSTeHM v1.0-rc: a modern, scalable spatio-temporal hierarchical modeling framework for paleo-environmental data
From Weather Data to River Runoff: Leveraging Spatiotemporal Convolutional Networks for Comprehensive Discharge Forecasting
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
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.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
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We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
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.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
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Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
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.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2183, https://doi.org/10.5194/egusphere-2024-2183, 2024
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PaleoSTeHM v1.0-rc is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
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Forecasting river runoff, crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using Convolutional Long Short-Term Memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Cited articles
Bacmeister, J. T., Wehner, M. F., Neale, R. B., Gettelman, A.,
Hannay, C., Lauritzen,, P. H., Caron, J. M., and Truesdale, J. E.:
Exploratory High-Resolution Climate Simulations using the Community
Atmosphere Model (CAM), J. Climate, 27, 3073–3099,
https://doi.org/10.1175/JCLI-D-13-00387.1, 2014.
Balaji, V., Anderson, J., Held, I., Winton, M., Durachta, J., Malyshev, S.,
and
Stouffer, R. J.: The Exchange Grid: a mechanism for data exchange
between earth system components on independant grids, in: 2005 International
Conference on Parallel Computational Fluid Dynamics, Elsevier Acadamic Press,
College Park, MD, USA, 2006.
Bengtsson, L., Hodges, K. I., and Esch, M.: Tropical cyclones in a T159
resolution global climate model: comparison with observations and
re-analyses, Tellus A, 59, 396–416,
https://doi.org/10.1111/j.1600-0870.2007.00236.x, 2007.
Camargo, S. J.: Global and Regional Aspects of Tropical Cyclone Activity in
the CMIP5 Models, J. Climate, 26, 9880–9902,
https://doi.org/10.1175/JCLI-D-12-00549.1,
2013.
Chan, J. C. L., Duan, Y., and Shay, L. K.: Tropical Cyclone Intensity Change
from a Simple Ocean–Atmosphere Coupled Model, J. Atmos.
Sci., 58, 154–172,
https://doi.org/10.1175/1520-0469(2001)058<0154:TCICFA>2.0.CO;2, 2001.
Craig, A. P., Vertenstein, M., and Jacob, R.: A new flexible coupler for
earth system modeling developed for CCSM4 and CESM1, Int. J. High Perf.
Comput. Appl., 26, 31–42, https://doi.org/10.1177/1094342011428141, 2012.
Dennis, J. M., Edwards, J., Evans, K. J., Guba, O., Lauritzen, P. H., Mirin,
A. A., St-Cyr, A., Taylor, M. A., and Worley, P. H.: CAM-SE: A scalable
spectral element dynamical core for the Community Atmosphere Model,
Int. J. High Perf. Comput. Appl., 26, 74–89, https://doi.org/10.1177/1094342011428142,
2012.
Evans, K. J., Lauritzen, P. H., Mishra, S. K., Neale, R. B., Taylor, M. A.,
and Tribbia, J. J.: AMIP Simulation with the CAM4 Spectral Element
Dynamical Core, J. Climate, 26, 689–709, https://doi.org/10.1175/JCLI-D-11-00448.1,
2013.
Gates, W. L.: AMIP: The Atmospheric Model Intercomparison Project, B.
Am. Meteorol. Soc., 73, 1962–1970, 1992.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman,
K. P., Hong, Y., Stocker, E. F., and Wolff, D. B.: The TRMM
Multisatellite Precipitation Analysis (TMPA): Quasi-global,
multiyear, combined-sensor precipitation estimates at fine scales, J.
Hydrometeorol., 8, 38–55, https://doi.org/10.1175/JHM560.1, 2007.
Hurrell, J. W., Hack, J. J., Shea, D., Caron, J. M., and Rosinski,
J.: A New Sea Surface Temperature and Sea Ice Boundary Dataset for the
Community Atmosphere Model, J. Climate, 21, 5145–5153,
https://doi.org/10.1175/2008JCLI2292.1, 2008.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner,
P. J., Lamarque, J. F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb,
W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P.,
Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J. J., Kiehl,
J., and Marshall, S.: The Community Earth System Model: A Framework
for Collaborative Research, B. Am. Meteorol. Soc., 94, 1339–1360,
https://doi.org/10.1175/BAMS-D-12-00121.1, 2013.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A.,
Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo,
K. C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-Year Reanalysis Project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Kim, D., Sobel, A. H., Del Genio, A. D., Chen, Y., Camargo, S. J.,
Yao, M.-S., Kelley, M., and Nazarenko, L.: The Tropical Subseasonal
Variability Simulated in the NASA GISS General Circulation Model, J.
Climate, 25, 4641–4659, https://doi.org/10.1175/JCLI-D-11-00447.1, 2012.
Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J., and
Neumann, C. J.: The International Best Track Archive for Climate
Stewardship (IBTrACS), B. Am. Meteorol. Soc., 91, 363–376,
https://doi.org/10.1175/2009BAMS2755.1, 2010.
Knutson, T. R., Sirutis, J. J., Garner, S. T., Held, I. M., and
Tuleya, R. E.: Simulation of the Recent Multidecadal Increase of Atlantic
Hurricane Activity Using an 18-km-Grid Regional Model, B. Am. Meteorol.
Soc., 88, 1549, https://doi.org/10.1175/BAMS-88-10-1549, 2007.
Knutson, T. R., McBride, J. L., Chan, J., Emanuel, K., Holland, G.,
Landsea, C., Held, I., Kossin, J. P., Srivastava, A. K., and Sugi,
M.: Tropical cyclones and climate change, Nat. Geosci., 3, 157–163,
https://doi.org/10.1038/ngeo779, 2010.
Lim, Y.-K., Schubert, S. D., Reale, O., Lee, M.-I., Molod, A. M., and Suarez,
M. J.: Sensitivity of Tropical Cyclones to Parameterized Convection in the
NASA GEOS-5 Model, J. Climate, 28, 551–573, https://doi.org/10.1175/JCLI-D-14-00104.1,
2014.
Manganello, J. V., Hodges, K. I., Kinter, J. L., Cash, B. A., Marx, L., Jung,
T., Achuthavarier, D., Adams, J. M., Altshuler, E. L., Huang, B., Jin, E. K.,
Stan, C., Towers, P., and Wedi, N.: Tropical Cyclone Climatology in a 10-km
Global Atmospheric GCM: Toward Weather-Resolving Climate Modeling, J.
Climate, 25, 3867–3893, https://doi.org/10.1175/JCLI-D-11-00346.1, 2012.
Murakami, H., Wang, Y., Yoshimura, H., Mizuta, R., Sugi, M., Shindo, E.,
Adachi, Y., Yukimoto, S., Hosaka, M., Kusunoki, S., Ose, T., and Kitoh, A.:
Future Changes in Tropical Cyclone Activity Projected by the New
High-Resolution MRI-AGCM, J. Climate, 25, 3237–3260,
https://doi.org/10.1175/JCLI-D-11-00415.1, 2012.
Neale, R. B., Chen, C.-C., Gettelman, A., Lauritzen, P. H., Park, S.,
Williamson, D. L., Conley, A. J., Garcia, R., Kinnison, D., Lamarque, J.-F.,
Marsh, D., Mills, M., Smith, A. K., Tilmes, S., Vitt, F., Cameron-Smith, P.,
Collins, W. D., Iacono, M. J., Easter, R. C., Liu, X., Ghan, S. J., Rasch,
P. J., and Taylor, M. A.: Description of the NCAR Community Atmosphere
Model (CAM 5.0), NCAR Technical Note NCAR/TN-486+STR, National Center for
Atmospheric Research, Boulder, Colorado, 2012.
Oleson, K., Lawrence, D., Bonan, G., Flanner, M., Kluzek, E., Lawrence, P.,
Levis, S., Swenson, S., Thornton, P., Dai, A., Decker, M., Dickinson, R.,
Feddema, J., Heald, C., Hoffman, F., Lamarque, J., Mahowald, N., Niu, G.,
Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stockli, R.,
Wang, A., Yang, Z., Zeng, X., and Zeng, X.: Technical Description of version
4.0 of the Community Land Model (CLM), NCAR Technical Note
NCAR/TN-478+STR, National Center for Atmospheric Research, Boulder, Colorado,
https://doi.org/10.5065/D6FB50WZ, 2010.
Oouchi, K., Yoshimura, J., Yoshimura, H., Mizuta, R., Kusunoki, S., and Noda,
A.: Tropical Cyclone Climatology in a Global-Warming Climate as Simulated in
a 20 km-Mesh Global Atmospheric Model: Frequency and Wind Intensity Analyses,
J. Meteorol. Soc. Jpn., 84, 259–276, 2006.
Peng, M. S., Jeng, B.-F., and Williams, R. T.: A Numerical Study on Tropical
Cyclone Intensification. Part I: Beta Effect and Mean Flow Effect,
J. Atmos. Sci., 56, 1404–1423,
https://doi.org/10.1175/1520-0469(1999)056<1404:ANSOTC>2.0.CO;2, 1999.
Reed, K. A. and Jablonowski, C.: Impact of physical parameterizations on
idealized tropical cyclones in the Community Atmosphere Model, Geophys.
Res. Lett., 38, L04805, https://doi.org/10.1029/2010GL046297, 2011a.
Reed, K. A. and Jablonowski, C.: Assessing the Uncertainty of Tropical
Cyclone Simulations in NCAR's Community Atmosphere Model, J. Adv. Model.
Earth Syst., 3, M08002, https://doi.org/10.1029/2011MS000076, 2011b.
Reed, K. A. and Jablonowski, C.: Idealized tropical cyclone simulations of
intermediate complexity: A test case for AGCMs, J. Adv. Model. Earth Syst.,
4, M04001, https://doi.org/10.1029/2011MS000099, 2012.
Reed, K. A., Bacmeister, J. T., Wehner, Rosenbloom, N. A., F., M.,
Bates, S. C., Lauritzen, P. H., Truesdale, J. T., and Hannay, C.:
Impact of the dynamical core on the direct simulation of tropical cyclones in
a high-resolution global model, Geophys. Res. Lett., 42, GL063974,
https://doi.org/10.1002/2015GL063974, 2015.
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and
Schlax, M. G.: Daily High-Resolution-Blended Analyses for Sea Surface
Temperature, J. Climate, 20, 5473–5496,
https://doi.org/10.1175/2007JCLI1824.1, 2007.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J.,
Liu,
E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G.-K., Bloom, S.,
Chen, J., Collins, D., Conaty, A., da Silva, A., Gu, W., Joiner, J., Koster,
R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder,
C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and
Woollen, J.: MERRA: NASA's Modern-Era Retrospective Analysis for
Research and Applications, J. Climate, 24, 3624–3648,
https://doi.org/10.1175/JCLI-D-11-00015.1, 2011.
Satoh, M., Oouchi, K., Nasuno, T., Taniguchi, H., Yamada, Y., Tomita, H.,
Kodama, C., Kinter, J., Achuthavarier, D., Manganello, J., Cash, B., Jung,
T., Palmer, T., and Wedi, N.: The Intra-Seasonal Oscillation and its control
of tropical cyclones simulated by high-resolution global atmospheric models,
Clim. Dynam., 39, 2185–2206, https://doi.org/10.1007/s00382-011-1235-6, 2012.
Simpson, R. H.: The Hurricane Disaster – Potential Scale, Weatherwise, 27,
169–186, https://doi.org/10.1080/00431672.1974.9931702, 1974.
Strachan, J., Vidale, P. L., Hodges, K., Roberts, M., and Demory, M.-E.:
Investigating Global Tropical Cyclone Activity with a Hierarchy of AGCMs:
The Role of Model Resolution, J. Climate, 26, 133–152,
https://doi.org/10.1175/JCLI-D-12-00012.1, 2013.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos, 106, 7183–7192, https://doi.org/10.1029/2000JD900719,
2001.
Taylor, M., Tribbia, J., and Iskandarani, M.: The Spectral Element Method for
the Shallow Water Equations on the Sphere, J. Comput. Phys., 130, 92–108,
1997.
Taylor, M. A.: Conservation of Mass and Energy for the Moist Atmospheric
Primitive Equations on Unstructured Grids, in: Numerical Techniques for
Global Atmospheric Models, edited by: Lauritzen, P. H., Jablonowski, C.,
Taylor, M. A., and Nair, R. D., Vol. 80 of Lecture Notes in
Computational Science and Engineering, Springer, 357–380, 2011.
Taylor, M. A. and Fournier, A.: A compatible and conservative spectral
element method on unstructured grids, J. Comput. Phys., 229, 5879–5895,
2010.
Thomas, S. and Loft, R.: The NCAR Spectral Element Climate Dynamical Core:
Semi-Implicit Eulerian Formulation, J. Sci. Comput., 25, 307–322,
https://doi.org/10.1007/s10915-004-4646-2, 2005.
Valcke, S., Balaji, V., Craig, A., DeLuca, C., Dunlap, R., Ford, R. W.,
Jacob, R., Larson, J., O'Kuinghttons, R., Riley, G. D., and Vertenstein, M.:
Coupling technologies for Earth System Modelling, Geosci. Model Dev., 5,
1589–1596, https://doi.org/10.5194/gmd-5-1589-2012, 2012.
Vitart, F., Anderson, J. L., and Stern, W. F.: Simulation of interannual
variability of tropical storm frequency in an ensemble of GCM integrations,
J. Climate, 10, 745–760, 1997.
Walsh, K. J. E., Camargo, S. J., Vecchi, G. A., Daloz, A. S., Elsner, J.,
Emanuel, K., Horn, M., Lim, Y.-K., Roberts, M., Patricola, C., Scoccimarro,
E., Sobel, A. H., Strazzo, S., Villarini, G., Wehner, M., Zhao, M., Kossin,
J. P., LaRow, T., Oouchi, K., Schubert, S., Wang, H., Bacmeister, J., Chang,
P., Chauvin, F., Jablonowski, C., Kumar, A., Murakami, H., Ose, T., Reed,
K. A., Saravanan, R., Yamada, Y., Zarzycki, C. M., Vidale, P. L., Jonas,
J. A., and Henderson, N.: Hurricanes and climate: the U.S. CLIVAR working
group on hurricanes, B. Am. Meteorol. Soc., 96,
997–1017, https://doi.org/10.1175/BAMS-D-13-00242.1, 2015.
Wang, Y. and Wu, C.-C.: Current understanding of tropical cyclone structure and
intensity changes–a review, Meteorol. Atmos. Phys., 87,
257–278, 2004.
Wehner, M. F., Reed, K. A., Li, F., Prabhat, Bacmeister, J., Chen, C.-T.,
Paciorek, C., Gleckler, P. J., Sperber, K. R., Collins, W. D., Gettelman, A.,
and Jablonowski, C.: The effect of horizontal resolution on simulation
quality in the Community Atmospheric Model, CAM5.1, J. Adv. Model.
Earth Syst., 6, 980–997, https://doi.org/10.1002/2013MS000276, 2014.
Wehner, M. F., Prabhat, Reed, K. A., Stone, D., Collins, W. D., and
Bacmeister, J. T.: Resolution dependence of future tropical cyclone
projections of CAM5.1 in the US CLIVAR Hurricane Working Group idealized
configurations, J. Climate, 28, 3905–3925, https://doi.org/10.1175/JCLI-D-14-00311.1,
2015.
Zarzycki, C. M. and Jablonowski, C.: A multidecadal simulation of Atlantic
tropical cyclones using a variable-resolution global atmospheric general
circulation model, J. Adv. Model. Earth Syst., 6, 805–828,
https://doi.org/10.1002/2014MS000352, 2014.
Zarzycki, C. M. and Jablonowski, C.: Experimental tropical cyclone forecasts
using a variable-resolution global model, Mon. Weather Rev., 143,
4012–4037,
https://doi.org/10.1175/MWR-D-15-0159.1, 2015.
Zarzycki, C. M., Jablonowski, C., and Taylor, M. A.: Using Variable
Resolution Meshes to Model Tropical Cyclones in the Community Atmosphere
Model, Mon. Weather Rev., 142, 1221–1239, https://doi.org/10.1175/MWR-D-13-00179.1,
2014a.
Zarzycki, C. M., Levy, M. N., Jablonowski, C., Overfelt, J. R., Taylor,
M. A., and Ullrich, P. A.: Aquaplanet Experiments Using CAM's
Variable-Resolution Dynamical Core, J. Climate, 27, 5481–5503,
https://doi.org/10.1175/JCLI-D-14-00004.1,
2014b.
Zarzycki, C. M., Jablonowski, C., Thatcher, D. R., and Taylor, M. A.: Effects
of localized grid refinement on the general circulation and climatology in
the Community Atmosphere Model, J. Climate, 28, 2777—2803,
https://doi.org/10.1175/JCLI-D-14-00599.1, 2015.
Zhao, M., Held, I. M., Lin, S. J., and Vecchi, G. A.: Simulations of Global
Hurricane Climatology, Interannual Variability, and Response to Global
Warming Using a 50-km Resolution GCM, J. Climate, 22, 6653–6678, 2009.
Zhao, M., Held, I. M., and Lin, S.-J.: Some Counterintuitive Dependencies of
Tropical Cyclone Frequency on Parameters in a GCM, J. Atmos. Sci., 69,
2272–2283, https://doi.org/10.1175/JAS-D-11-0238.1, 2012.
Short summary
This paper highlights the sensitivity of simulated tropical cyclone climatology to the choice of ocean coupling grid in high-resolution climate simulations. When computations of atmosphere–ocean interactions are carried out on the coarser grid in the system, key quantities such as surface wind drag and heat fluxes are incorrectly calculated. In the case of a coarser ocean grid, significantly stronger cyclone winds result, due to misaligned frictional vectors in the atmospheric dynamical core.
This paper highlights the sensitivity of simulated tropical cyclone climatology to the choice of...
