Articles | Volume 15, issue 8
https://doi.org/10.5194/gmd-15-3387-2022
© Author(s) 2022. 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-15-3387-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
22 Apr 2022
Model evaluation paper |
| 22 Apr 2022
| 22 Apr 2022
Precipitation over southern Africa: is there consensus among global climate models (GCMs), regional climate models (RCMs) and observational data?
Maria Chara Karypidou
CORRESPONDING AUTHOR
Department of Meteorology and Climatology, School of Geology,
Faculty of Sciences, Aristotle University of Thessaloniki, Thessaloniki,
Greece
Eleni Katragkou
Department of Meteorology and Climatology, School of Geology,
Faculty of Sciences, Aristotle University of Thessaloniki, Thessaloniki,
Greece
Stefan Pieter Sobolowski
NORCE Norwegian Research Centre, Bjerknes Centre for Climate
Research, Bergen, Norway
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Geosci. Model Dev., 16, 1887–1908, https://doi.org/10.5194/gmd-16-1887-2023, https://doi.org/10.5194/gmd-16-1887-2023, 2023
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Southern Africa is listed among the climate change hotspots; hence, accurate climate change information is vital for the optimal preparedness of local communities. In this work we assess the degree to which regional climate models (RCMs) are influenced by the global climate models (GCMs) from which they receive their lateral boundary forcing. We find that although GCMs exert a strong impact on RCMs, RCMs are still able to display substantial improvement relative to the driving GCMs.
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Johannes Flemming, Angela Benedetti, Antje Inness, Richard J. Engelen, Luke Jones, Vincent Huijnen, Samuel Remy, Mark Parrington, Martin Suttie, Alessio Bozzo, Vincent-Henri Peuch, Dimitris Akritidis, and Eleni Katragkou
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G. Alexandri, A. K. Georgoulias, P. Zanis, E. Katragkou, A. Tsikerdekis, K. Kourtidis, and C. Meleti
Atmos. Chem. Phys., 15, 13195–13216, https://doi.org/10.5194/acp-15-13195-2015, https://doi.org/10.5194/acp-15-13195-2015, 2015
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It is shown here that RegCM4 regional climate model adequately simulates surface solar radiation (SSR) over Europe but significantly over/underestimates several parameters that determine the transmission of solar radiation in the atmosphere. The agreement between RegCM4 and satellite-based SSR observations is actually a result of the conflicting effect of these parameters. We suggest that there should be a reassessment of the way these parameters are represented within this and other models.
H. Eskes, V. Huijnen, A. Arola, A. Benedictow, A.-M. Blechschmidt, E. Botek, O. Boucher, I. Bouarar, S. Chabrillat, E. Cuevas, R. Engelen, H. Flentje, A. Gaudel, J. Griesfeller, L. Jones, J. Kapsomenakis, E. Katragkou, S. Kinne, B. Langerock, M. Razinger, A. Richter, M. Schultz, M. Schulz, N. Sudarchikova, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Geosci. Model Dev., 8, 3523–3543, https://doi.org/10.5194/gmd-8-3523-2015, https://doi.org/10.5194/gmd-8-3523-2015, 2015
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The MACC project is preparing the operational atmosphere service of the European Copernicus Programme, and uses data assimilation to combine atmospheric models with available observations. Our paper provides an overview of the aerosol and trace gas validation activity of MACC. Topics are the validation requirements, the measurement data, the assimilation systems, the upgrade procedure, operational aspects and the scoring methods. A summary is provided of recent results, including special events.
E. Katragkou, P. Zanis, A. Tsikerdekis, J. Kapsomenakis, D. Melas, H. Eskes, J. Flemming, V. Huijnen, A. Inness, M. G. Schultz, O. Stein, and C. S. Zerefos
Geosci. Model Dev., 8, 2299–2314, https://doi.org/10.5194/gmd-8-2299-2015, https://doi.org/10.5194/gmd-8-2299-2015, 2015
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This work is an extended evaluation of near-surface ozone as part of the global reanalysis of atmospheric composition, produced within the European-funded project MACC (Monitoring Atmospheric Composition and Climate). It includes an evaluation over the period 2003-2012 and provides an overall assessment of the modelling system performance with respect to near surface ozone for specific European subregions.
A. Inness, A.-M. Blechschmidt, I. Bouarar, S. Chabrillat, M. Crepulja, R. J. Engelen, H. Eskes, J. Flemming, A. Gaudel, F. Hendrick, V. Huijnen, L. Jones, J. Kapsomenakis, E. Katragkou, A. Keppens, B. Langerock, M. de Mazière, D. Melas, M. Parrington, V. H. Peuch, M. Razinger, A. Richter, M. G. Schultz, M. Suttie, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Atmos. Chem. Phys., 15, 5275–5303, https://doi.org/10.5194/acp-15-5275-2015, https://doi.org/10.5194/acp-15-5275-2015, 2015
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The paper presents results from data assimilation studies with the new Composition-IFS model developed in the MACC project. This system was used in MACC to produce daily analyses and 5-day forecasts of atmospheric composition and is now run daily in the EU’s Copernicus Atmosphere Monitoring Service. The paper looks at the quality of the CO, O3 and NO2 analysis fields obtained with this system, comparing them against observations, a control run and an older version of the model.
E. Katragkou, M. García-Díez, R. Vautard, S. Sobolowski, P. Zanis, G. Alexandri, R. M. Cardoso, A. Colette, J. Fernandez, A. Gobiet, K. Goergen, T. Karacostas, S. Knist, S. Mayer, P. M. M. Soares, I. Pytharoulis, I. Tegoulias, A. Tsikerdekis, and D. Jacob
Geosci. Model Dev., 8, 603–618, https://doi.org/10.5194/gmd-8-603-2015, https://doi.org/10.5194/gmd-8-603-2015, 2015
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
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.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-119, https://doi.org/10.5194/gmd-2024-119, 2024
Revised manuscript accepted for GMD
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Daniel Francis James Gunning, Kerim Hestnes Nisancioglu, Emilie Capron, and Roderik van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1384, https://doi.org/10.5194/egusphere-2024-1384, 2024
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth’s orbit. We demonstrate ZEMBA reproduces many features of the Earth’s climate for both the pre-industrial period and the Earth’s most recent cold extreme- the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Cited articles
Adler, R. F., Gu, G., and Huffman, G. J.: Estimating Climatological Bias Errors for the Global Precipitation 118 Climatology Project (GPCP), J. Appl. Meteorol. Clim., 51, 84–99 https://doi.org/10.1175/JAMC-D-11-052.1, 2012.
African Development Bank Group (AFDBG): Southern Africa Economic Outlook 2019, African Development Bank, 2019.
Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R.,
Cecil, L. D., Nelson, B. R., and Prat, O. P.: PERSIANN-CDR: Daily
Precipitation Climate Data Record from Multisatellite Observations for
Hydrological and Climate Studies, B. Am. Meteorol. Soc., 96, 69–83,
https://doi.org/10.1175/BAMS-D-13-00068.1, 2015.
Azzarri, C. and Signorelli, S.: Climate and poverty in Africa South of the
Sahara, World Dev., 125, 104691,
https://doi.org/10.1016/j.worlddev.2019.104691, 2020.
Ban, N., Caillaud, C., Coppola, E., Pichelli, E., Sobolowski, S., Adinolfi,
M., Ahrens, B., Alias, A., Anders, I., Bastin, S., Belusic, D., Berthou, S.,
Brisson, E., Cardoso, R. M., Chan, S., Christensen, O. B., Fernandez, J.,
Fita, L., Frisius, T., Gasparac, G., Giorgi, F., Goergen, K., Haugen, J. E.,
Hodnebrog, O., Kartsios, S., Katragkou, E., Kendon, E. J., Keuler, K.,
Lavin-Gullon, A., Lenderink, G., Leutwyler, D., Lorenz, T., Maraun, D.,
Mercogliano, P., Milovac, J., Panitz, H.-J., Raffa, M., Remedio, A. R.,
Schar, C., Soares, P. M. M., Srnec, L., Steensen, B. M., Stocchi, P., Tolle,
M. H., Truhetz, H., Vergara-Temprado, J., de Vries, H., Warrach-Sagi, K.,
Wulfmeyer, V., and Zander, M.: The first multi-model ensemble of regional
climate simulations at the kilometer-scale resolution, Part I: Evaluation of
precipitation, Clim. Dynam., 57, 275–302, https://doi.org/10.1007/s00382-021-05708-w, 2021.
Chen, M., Shi, W., Xie, P., Silva, V. B. S., Kousky, V. E., Higgins, R. W., and Janowiak, J. E.: Assessing objective techniques for gauge-based analyses of global daily precipitation, J. Geophys. Res.-Atmos., 113, D04110, https://doi.org/10.1029/2007JD009132, 2008.
Chen, M., Xie, P., Janowiak, J. E., and Arkin, P. A.: Global Land Precipitation: A 50-yr Monthly Analysis Based on 136 Gauge Observations, J. Hydrometeorol., 3, 249–266, https://doi.org/10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO;2, 2002.
Chinowsky, P. S., Schweikert, A. E., Strzepek, N. L., and Strzepek, K.:
Infrastructure and climate change: a study of impacts and adaptations in
Malawi, Mozambique, and Zambia, Climatic Change, 130, 49–62,
https://doi.org/10.1007/s10584-014-1219-8, 2015.
Climate Data Store (CDS): https://cds.climate.copernicus.eu/#!/home, last access: 1 September 2021.
Coppola, E., Raffaele, F., Giorgi, F., Giuliani, G., Xuejie, G., Ciarlo, J.
M., Sines, T. R., Torres-Alavez, J. A., Das, S., di Sante, F., Pichelli, E.,
Glazer, R., Müller, S. K., Abba Omar, S., Ashfaq, M., Bukovsky, M., Im,
E.-S., Jacob, D., Teichmann, C., Remedio, A., Remke, T., Kriegsmann, A.,
Bülow, K., Weber, T., Buntemeyer, L., Sieck, K., and Rechid, D.: Climate
hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble,
Clim. Dynam., 57, 1293–1383, https://doi.org/10.1007/s00382-021-05640-z,
2021.
Crétat, J., Pohl, B., Dieppois, B., Berthou, S., and Pergaud, J.: The
Angola Low: relationship with southern African rainfall and ENSO, Clim.
Dynam., 52, 1783–1803, https://doi.org/10.1007/s00382-018-4222-3, 2019.
Daron, J., Burgin, L., Janes, T., Jones, R. G., and Jack, C.: Climate
process chains: Examples from southern Africa, Int. J. Climatol., 39,
4784–4797, https://doi.org/10.1002/joc.6106, 2019.
Davis-Reddy, C. L. and Vincent, K.: Climate Risk and Vulnerability: A Handbook for Southern Africa, 2nd Edn., CSIR, Pretoria, South Africa, 2017.
Denis, B., Laprise, R., and Caya, D.: Sensitivity of a regional climate
model to the resolution of the lateral boundary conditions, Clim. Dynam., 20,
107–126, https://doi.org/10.1007/s00382-002-0264-6, 2003.
Desbiolles, F., Howard, E., Blamey, R. C., Barimalala, R., Hart, N. C. G.,
and Reason, C. J. C.: Role of ocean mesoscale structures in shaping the
Angola-Low pressure system and the southern Africa rainfall, Clim. Dynam., 54,
3685–3704, https://doi.org/10.1007/s00382-020-05199-1, 2020.
Dieppois, B., Pohl, B., Crétat, J., Eden, J., Sidibe, M., New, M.,
Rouault, M., and Lawler, D.: Southern African summer-rainfall variability,
and its teleconnections, on interannual to interdecadal timescales in CMIP5
models, Clim. Dynam., 53, 3505–3527,
https://doi.org/10.1007/s00382-019-04720-5, 2019.
Diffenbaugh, N. S. and Giorgi, F.: Climate change hotspots in the CMIP5
global climate model ensemble, Climatic Change, 114, 813–822,
https://doi.org/10.1007/s10584-012-0570-x, 2012.
Di Luca, A., de Elía, R., and Laprise, R.: Potential for added value in
temperature simulated by high-resolution nested RCMs in present climate and
in the climate change signal, Clim. Dynam., 40, 443–464,
https://doi.org/10.1007/s00382-012-1384-2, 2013.
Dosio, A. and Panitz, H.-J.: Climate change projections for CORDEX-Africa
with COSMO-CLM regional climate model and differences with the driving
global climate models, Clim. Dynam., 46, 1599–1625,
https://doi.org/10.1007/s00382-015-2664-4, 2016.
Dosio, A., Panitz, H.-J., Schubert-Frisius, M., and Lüthi, D.: Dynamical
downscaling of CMIP5 global circulation models over CORDEX-Africa with
COSMO-CLM: evaluation over the present climate and analysis of the added
value, Clim. Dynam., 44, 2637–2661,
https://doi.org/10.1007/s00382-014-2262-x, 2015.
Dosio, A., Jones, R. G., Jack, C., Lennard, C., Nikulin, G., and Hewitson,
B.: What can we know about future precipitation in Africa? Robustness,
significance and added value of projections from a large ensemble of
regional climate models, Clim. Dynam., 53, 5833–5858,
https://doi.org/10.1007/s00382-019-04900-3, 2019.
Dosio, A., Jury, M. W., Almazroui, M., Ashfaq, M., Diallo, I., Engelbrecht,
F. A., Klutse, N. A. B., Lennard, C., Pinto, I., Sylla, M. B., and Tamoffo,
A. T.: Projected future daily characteristics of African precipitation based
on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models,
Clim. Dynam., 57, 3135–3158, https://doi.org/10.1007/s00382-021-05859-w,
2021.
Duan, H., Zhang, G., Wang, S., and Fan, Y.: Robust climate change research:
a review on multi-model analysis, Environ. Res. Lett., 14, 033001,
https://doi.org/10.1088/1748-9326/aaf8f9, 2019.
ESGF-DKRZ: https://esgf-data.dkrz.de/projects/esgf-dkrz/, last access: 1 September 2021.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf,
D.: The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004,
https://doi.org/10.1029/2005RG000183, 2007.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,
Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.: The
climate hazards infrared precipitation with stations – a new environmental
record for monitoring extremes, Sci. Data, 2, 150066,
https://doi.org/10.1038/sdata.2015.66, 2015.
Giesen, N. van de, Hut, R., and Selker, J.: The Trans-African
Hydro-Meteorological Observatory (TAHMO), WIREs Water, 1, 341–348,
https://doi.org/10.1002/wat2.1034, 2014.
Giorgi, F.: Thirty Years of Regional Climate Modeling: Where Are We and
Where Are We Going next?, J. Geophys. Res.-Atmos., 124, 5696–5723,
https://doi.org/10.1029/2018JD030094, 2019.
Giorgi, F. and Gutowski, W. J.: Regional Dynamical Downscaling and the
CORDEX Initiative, Annu. Rev. Environ. Res., 40, 467–490,
https://doi.org/10.1146/annurev-environ-102014-021217, 2015.
Giorgi, F., Coppola, E., Raffaele, F., Diro, G. T., Fuentes-Franco, R.,
Giuliani, G., Mamgain, A., Llopart, M. P., Mariotti, L., and Torma, C.:
Changes in extremes and hydroclimatic regimes in the CREMA ensemble
projections, Climatic Change, 125, 39–51,
https://doi.org/10.1007/s10584-014-1117-0, 2014.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated high-resolution grids of monthly climatic 169 observations – the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hart, N. C. G., Reason, C. J. C., and Fauchereau, N.:
Tropical–Extratropical Interactions over Southern Africa: Three Cases of
Heavy Summer Season Rainfall, Mon. Weather Rev., 138, 2608–2623,
https://doi.org/10.1175/2010MWR3070.1, 2010.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P.
de, Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Houze, R. A.: Orographic effects on precipitating clouds, Rev. Geophys., 50, RG1001,
https://doi.org/10.1029/2011RG000365, 2012.
Howard, E. and Washington, R.: Characterizing the Synoptic Expression of the
Angola Low, J. Climate, 31, 7147–7165,
https://doi.org/10.1175/JCLI-D-18-0017.1, 2018.
Howard, E. and Washington, R.: Drylines in Southern Africa: Rediscovering
the Congo Air Boundary, J. Climate, 32, 8223–8242,
https://doi.org/10.1175/JCLI-D-19-0437.1, 2019.
IPCC: Annex I: Atlas of Global and Regional Climate Projections, in: Climate
Change 2013: The Physical Science Basis, Contribution of Working Group I to
the Fifth Assessment Report of the Intergovernmental Panel on Climate
Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M.,
Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.
M., Cambridge University Press, Cambridge, United Kingdom and New York, NY,
USA, 1311–1394, https://doi.org/10.1017/CBO9781107415324.029, 2013.
Janowiak, J. E.: An Investigation of Interannual Rainfall Variability in
Africa, J. Climate, 1, 240–255,
https://doi.org/10.1175/1520-0442(1988)001<0240:AIOIRV>,2.0.CO;2, 1988.
Kalognomou, E.-A., Lennard, C., Shongwe, M., Pinto, I., Favre, A., Kent, M.,
Hewitson, B., Dosio, A., Nikulin, G., Panitz, H.-J., and Büchner, M.: A
Diagnostic Evaluation of Precipitation in CORDEX Models over Southern
Africa, J. Climate, 26, 9477–9506, https://doi.org/10.1175/JCLI-D-12-00703.1,
2013.
Karypidou, M. C.: Precipitation over southern Africa: Is there consensus among GCMs, RCMs and observational data? (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.4725441, 2021.
Kendall, M. G.: Rank correlation methods, Griffin, Oxford, England, 1948.
Kim, J., Waliser, D. E., Mattmann, C. A., Goodale, C. E., Hart, A. F.,
Zimdars, P. A., Crichton, D. J., Jones, C., Nikulin, G., Hewitson, B., Jack,
C., Lennard, C., and Favre, A.: Evaluation of the CORDEX-Africa multi-RCM
hindcast: systematic model errors, Clim. Dynam., 42, 1189–1202,
https://doi.org/10.1007/s00382-013-1751-7, 2014.
Kim, Y.-H., Min, S.-K., Zhang, X., Sillmann, J., and Sandstad, M.:
Evaluation of the CMIP6 multi-model ensemble for climate extreme indices,
Weather Clim. Extrem., 29, 100269,
https://doi.org/10.1016/j.wace.2020.100269, 2020.
Kula, N., Haines, A., and Fryatt, R.: Reducing Vulnerability to Climate
Change in Sub-Saharan Africa: The Need for Better Evidence, PLoS Med., 10, e1001374,
https://doi.org/10.1371/journal.pmed.1001374, 2013.
Laprise, R., de Elía, R., Caya, D., Biner, S., Lucas-Picher, P.,
Diaconescu, E., Leduc, M., Alexandru, A., Separovic, L., and Canadian
Network for Regional Climate Modelling and Diagnostics: Challenging some
tenets of Regional Climate Modelling, Meteorol. Atmos. Phys., 100,
3–22, https://doi.org/10.1007/s00703-008-0292-9, 2008.
Le Coz, C. and van de Giesen, N.: Comparison of Rainfall Products over
Sub-Saharan Africa, J. Hydrometeorol., 21, 553–596,
https://doi.org/10.1175/JHM-D-18-0256.1, 2020.
L'Heureux, M. L., Lee, S., and Lyon, B.: Recent multidecadal strengthening
of the Walker circulation across the tropical Pacific, Nat. Clim. Change, 3,
571–576, https://doi.org/10.1038/nclimate1840, 2013.
Lorenz, C. and Kunstmann, H.: The Hydrological Cycle in Three
State-of-the-Art Reanalyses: Intercomparison and Performance Analysis, J.
Hydrometeorol., 13, 1397–1420, https://doi.org/10.1175/JHM-D-11-088.1,
2012.
Lyon, B. and Mason, S. J.: The 1997–98 Summer Rainfall Season in Southern
Africa. Part I: Observations, J. Climate, 20, 5134–5148,
https://doi.org/10.1175/JCLI4225.1, 2007.
Mabhaudhi, T., Mpandeli, S., Nhamo, L., Chimonyo, V. G. P., Nhemachena, C.,
Senzanje, A., Naidoo, D., and Modi, A. T.: Prospects for Improving Irrigated
Agriculture in Southern Africa: Linking Water, Energy and Food, Water, 10,
1881, https://doi.org/10.3390/w10121881, 2018.
Maidment, R. I., Grimes, D., Allan, R. P., Tarnavsky, E., Stringer, M.,
Hewison, T., Roebeling, R., and Black, E.: The 30 year TAMSAT African
Rainfall Climatology And Time series (TARCAT) data set, J. Geophys. Res.-Atmos., 119, 10619–10644, https://doi.org/10.1002/2014JD021927, 2014.
Maidment, R. I., Allan, R. P., and Black, E.: Recent observed and simulated
changes in precipitation over Africa, Geophys. Res. Lett., 42, 8155–8164,
https://doi.org/10.1002/2015GL065765, 2015.
Mann, H. B.: Nonparametric Tests Against Trend, Econometrica, 13, 245–259,
https://doi.org/10.2307/1907187, 1945.
Meque, A. and Abiodun, B. J.: Simulating the link between ENSO and summer
drought in Southern Africa using regional climate models, Clim. Dynam., 44,
1881–1900, https://doi.org/10.1007/s00382-014-2143-3, 2015.
Munday, C. and Washington, R.: Circulation controls on southern African
precipitation in coupled models: The role of the Angola Low, J. Geophys.
Res. Atmospheres, 122, 861–877, https://doi.org/10.1002/2016JD025736, 2017.
Munday, C. and Washington, R.: Systematic Climate Model Rainfall Biases over
Southern Africa: Links to Moisture Circulation and Topography, J. Climate, 31,
7533–7548, https://doi.org/10.1175/JCLI-D-18-0008.1, 2018.
Nikulin, G., Jones, C., Giorgi, F., Asrar, G., Büchner, M., Cerezo-Mota,
R., Christensen, O. B., Déqué, M., Fernandez, J., Hänsler, A.,
Meijgaard, E. van, Samuelsson, P., Sylla, M. B., and Sushama, L.:
Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate
Simulations, J. Climate, 25, 6057–6078,
https://doi.org/10.1175/JCLI-D-11-00375.1, 2012.
Novella, N. S. and Thiaw, W. M.: African Rainfall Climatology Version 2 for Famine Early Warning Systems, J. Appl. Meteorol. Clim., 52, 588–606, https://doi.org/10.1175/JAMC-D-11-0238.1, 2013.
Onyutha, C.: Trends and variability in African long-term precipitation,
Stoch. Environ. Res. Risk Ass., 32, 2721–2739,
https://doi.org/10.1007/s00477-018-1587-0, 2018.
Peterson, T. C. and Manton, M. J.: Monitoring Changes in Climate Extremes: A
Tale of International Collaboration, B. Am. Meteorol. Soc., 89,
1266–1271, 2008.
Pichelli, E., Coppola, E., Sobolowski, S., Ban, N., Giorgi, F., Stocchi, P.,
Alias, A., Belušić, D., Berthou, S., Caillaud, C., Cardoso, R. M.,
Chan, S., Christensen, O. B., Dobler, A., de Vries, H., Goergen, K., Kendon,
E. J., Keuler, K., Lenderink, G., Lorenz, T., Mishra, A. N., Panitz, H.-J.,
Schär, C., Soares, P. M. M., Truhetz, H., and Vergara-Temprado, J.: The
first multi-model ensemble of regional climate simulations at
kilometer-scale resolution part 2: historical and future simulations of
precipitation, Clim. Dynam., 56, 3581–3602, https://doi.org/10.1007/s00382-021-05657-4, 2021.
Pierce, D. W., Barnett, T. P., Santer, B. D., and Gleckler, P. J.: Selecting
global climate models for regional climate change studies, P. Natl. Acad.
Sci. USA, 106, 8441–8446, https://doi.org/10.1073/pnas.0900094106, 2009.
Pinto, I., Lennard, C., Tadross, M., Hewitson, B., Dosio, A., Nikulin, G.,
Panitz, H.-J., and Shongwe, M. E.: Evaluation and projections of extreme
precipitation over southern Africa from two CORDEX models, Climatic Change,
135, 655–668, https://doi.org/10.1007/s10584-015-1573-1, 2016.
R Core Team: A language and environment for statistical computing, R Foundation for Statistical Computing, https://www.r-project.org/, last access: 31 October 2021.
Reason, C. J. C. and Jagadheesha, D.: A model investigation of recent ENSO
impacts over southern Africa, Meteorol. Atmos. Phys., 89, 181–205,
https://doi.org/10.1007/s00703-005-0128-9, 2005.
Rocklöv, J. and Dubrow, R.: Climate change: an enduring challenge for
vector-borne disease prevention and control, Nat. Immunol., 21, 479–483,
https://doi.org/10.1038/s41590-020-0648-y, 2020.
Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., and Ziese, M.: GPCC Full Data Reanalysis Version 7.0 at 0.5°: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data, Global Precipitation Climatology Centre [data set], https://doi.org/10.5676/DWD_GPCC/FD_M_V7_050, 2015.
Schulzweida, U.: CDO User Guide (Version 2.0.0), https://code.mpimet.mpg.de/projects/cdo/, last access: 31 October 2021.
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's Tau,
J. Am. Stat. Assoc., 63, 1379–1389,
https://doi.org/10.1080/01621459.1968.10480934, 1968.
Serdeczny, O., Adams, S., Baarsch, F., Coumou, D., Robinson, A., Hare, W.,
Schaeffer, M., Perrette, M., and Reinhardt, J.: Climate change impacts in
Sub-Saharan Africa: from physical changes to their social repercussions,
Reg. Environ. Change, 17, 1585–1600,
https://doi.org/10.1007/s10113-015-0910-2, 2017.
Tarnavsky, E., Grimes, D., Maidment, R., Black, E., Allan, R. P., Stringer,
M., Chadwick, R., and Kayitakire, F.: Extension of the TAMSAT
Satellite-Based Rainfall Monitoring over Africa and from 1983 to Present, J.
Appl. Meteorol. Clim., 53, 2805–2822,
https://doi.org/10.1175/JAMC-D-14-0016.1, 2014.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498,
https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Theil, H.: A Rank-Invariant Method of Linear and Polynomial Regression
Analysis, in: Henri Theil's Contributions to Economics and Econometrics:
Econometric Theory and Methodology, edited by: Raj, B. and Koerts, J.,
Springer Netherlands, Dordrecht, 345–381,
https://doi.org/10.1007/978-94-011-2546-8_20, 1992.
Tirado, M. C., Hunnes, D., Cohen, M. J., and Lartey, A.: Climate Change and
Nutrition in Africa, J. Hunger Environ. Nutr., 10, 22–46,
https://doi.org/10.1080/19320248.2014.908447, 2015.
Toté, C., Patricio, D., Boogaard, H., Van der Wijngaart, R., Tarnavsky,
E., and Funk, C.: Evaluation of Satellite Rainfall Estimates for Drought and
Flood Monitoring in Mozambique, Remote Sens., 7, 1758–1776,
https://doi.org/10.3390/rs70201758, 2015.
Ukkola, A. M., Kauwe, M. G. D., Roderick, M. L., Abramowitz, G., and Pitman,
A. J.: Robust Future Changes in Meteorological Drought in CMIP6 Projections
Despite Uncertainty in Precipitation, Geophys. Res. Lett., 47,
e2020GL087820, https://doi.org/10.1029/2020GL087820, 2020.
Warnatzsch, E. A. and Reay, D. S.: Temperature and precipitation change in
Malawi: Evaluation of CORDEX-Africa climate simulations for climate change
impact assessments and adaptation planning, Sci. Total Environ., 654,
378–392, https://doi.org/10.1016/j.scitotenv.2018.11.098, 2019.
Willmott, C. J. and Matsuura, K.: Smart Interpolation of Annually Averaged Air Temperature in the United States, J. Appl. Meteorol. 34, 2577–2586, https://doi.org/10.1175/1520-0450(1995)034<2577:SIOAAA>2.0.CO;2, 1995.
Wyser, K., van Noije, T., Yang, S., von Hardenberg, J., O'Donnell, D., and Döscher, R.: On the increased climate sensitivity in the EC-Earth model from CMIP5 to CMIP6, Geosci. Model Dev., 13, 3465–3474, https://doi.org/10.5194/gmd-13-3465-2020, 2020.
Xie, P. and Arkin, P. A.: Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite 269 Estimates, and Numerical Model Outputs, B. Am. Meteorol. Soc., 78, 2539–2558, 1997.
https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2
Yim, B. Y., Yeh, S.-W., and Sohn, B.-J.: ENSO-Related Precipitation and Its
Statistical Relationship with the Walker Circulation Trend in CMIP5 AMIP
Models, Atmosphere, 7, 19, https://doi.org/10.3390/atmos7020019, 2016.
Short summary
The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Reliable climatic information is therefore necessary for the optimal adaptation of local communities. In this work we show that regional climate models are reliable tools for the simulation of precipitation over southern Africa. However, there is still a great need for the expansion and maintenance of observational data.
The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is...
