Articles | Volume 15, issue 6
https://doi.org/10.5194/gmd-15-2653-2022
© 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-15-2653-2022
© 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
| 
01 Apr 2022
Model evaluation paper |
| 01 Apr 2022
| 01 Apr 2022
Added value of EURO-CORDEX high-resolution downscaling over the Iberian Peninsula revisited – Part 2: Max and min temperature
João António Martins Careto
CORRESPONDING AUTHOR
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Ed. C8, 1749-016 Lisbon, Portugal
Pedro Miguel Matos Soares
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Ed. C8, 1749-016 Lisbon, Portugal
Rita Margarida Cardoso
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Ed. C8, 1749-016 Lisbon, Portugal
Sixto Herrera
Meteorology Group, Dept. of Applied Mathematics and Computer Science,
Universidad de Cantabria, Santander, Spain
José Manuel Gutiérrez
Meteorology Group, Instituto de Física de Cantabria,
CSIC-University of Cantabria, Santander, Spain
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João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2635–2652, https://doi.org/10.5194/gmd-15-2635-2022, https://doi.org/10.5194/gmd-15-2635-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with a recent observational gridded dataset as a reference, covering the entire Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional climate models encouraged this study. For precipitation, most models reveal added value. The gains are even more evident for precipitation extremes, particularly at a more local scale.
Colin Gareth Jones, Fanny Adloff, Ben Booth, Peter Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene Hewitt, Hazel Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm Roberts, Benjamin Sanderson, Roland Séférian, Samuel Somot, Pier-Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco J. Doblas-Reyes, Markus G. Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Froelicher, Neven Fuckar, Matthew Gidden, Helge Goessling, Rune Grand Graversen, Silvio Gualdi, Jose Manuel Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason A. Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Melia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard Wood, Shuting Yang, and Sönke Zaehle
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We propose a number of priority areas for the international climate research community to address over the coming ~6 years (i.e. to 2030). Advances in these areas will increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, as well as deliver significantly improved scientific support to international climate policy, such as the 7th IPCC Assessment Report and the UNFCCC Global Stocktake under the Paris Climate Agreement.
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Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
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EGUsphere, https://doi.org/10.5194/egusphere-2023-1402, https://doi.org/10.5194/egusphere-2023-1402, 2023
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We developed an adaptive method for calibrating TRMM precipitation in the South Pacific. By classifying data into weather types and applying different techniques, we achieve improved calibration. Results showed enhanced accuracy in mean and extreme precipitation indices across locations. The method offers customization options and effectively addresses intense rainfall events. Its versatility allows for application in diverse scenarios, supporting a better understanding of climate impacts.
Miguel Nogueira, Alexandra Hurduc, Sofia Ermida, Daniela C. A. Lima, Pedro M. M. Soares, Frederico Johannsen, and Emanuel Dutra
Geosci. Model Dev., 15, 5949–5965, https://doi.org/10.5194/gmd-15-5949-2022, https://doi.org/10.5194/gmd-15-5949-2022, 2022
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We evaluated the quality of the ERA5 reanalysis representation of the urban heat island (UHI) over the city of Paris and performed a set of offline runs using the SURFEX land surface model. They were compared with observations (satellite and in situ). The SURFEX-TEB runs showed the best performance in representing the UHI, reducing its bias significantly. We demonstrate the ability of the SURFEX-TEB framework to simulate urban climate, which is crucial for studying climate change in cities.
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The Cryosphere, 16, 2403–2419, https://doi.org/10.5194/tc-16-2403-2022, https://doi.org/10.5194/tc-16-2403-2022, 2022
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Snow plays a major role in the regulation of the Earth's surface temperature. Together with climate change, rising temperatures are already altering snow in many ways. In this context, it is crucial to better understand the ability of climate models to represent snow and snow processes. This work focuses on Europe and shows that the melting season in spring still represents a challenge for climate models and that more work is needed to accurately simulate snow–atmosphere interactions.
Priscilla A. Mooney, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Natalie de Noblet-Ducoudré, Marcus Breil, Rita M. Cardoso, Anne Sophie Daloz, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 1383–1397, https://doi.org/10.5194/tc-16-1383-2022, https://doi.org/10.5194/tc-16-1383-2022, 2022
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We use multiple regional climate models to show that afforestation in sub-polar and alpine regions reduces the radiative impact of snow albedo on the atmosphere, reduces snow cover, and delays the start of the snowmelt season. This is important for local communities that are highly reliant on snowpack for water resources and winter tourism. However, models disagree on the amount of change particularly when snow is melting. This shows that more research is needed on snow–vegetation interactions.
João António Martins Careto, Pedro Miguel Matos Soares, Rita Margarida Cardoso, Sixto Herrera, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 2635–2652, https://doi.org/10.5194/gmd-15-2635-2022, https://doi.org/10.5194/gmd-15-2635-2022, 2022
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This work focuses on the added value of high-resolution models relative to their forcing simulations, with a recent observational gridded dataset as a reference, covering the entire Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional climate models encouraged this study. For precipitation, most models reveal added value. The gains are even more evident for precipitation extremes, particularly at a more local scale.
Giannis Sofiadis, Eleni Katragkou, Edouard L. Davin, Diana Rechid, Nathalie de Noblet-Ducoudre, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Lisa Jach, Ronny Meier, Priscilla A. Mooney, Pedro M. M. Soares, Susanna Strada, Merja H. Tölle, and Kirsten Warrach Sagi
Geosci. Model Dev., 15, 595–616, https://doi.org/10.5194/gmd-15-595-2022, https://doi.org/10.5194/gmd-15-595-2022, 2022
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Afforestation is currently promoted as a greenhouse gas mitigation strategy. In our study, we examine the differences in soil temperature and moisture between grounds covered either by forests or grass. The main conclusion emerged is that forest-covered grounds are cooler but drier than open lands in summer. Therefore, afforestation disrupts the seasonal cycle of soil temperature, which in turn could trigger changes in crucial chemical processes such as soil carbon sequestration.
Manuel C. Almeida, Yurii Shevchuk, Georgiy Kirillin, Pedro M. M. Soares, Rita M. Cardoso, José P. Matos, Ricardo M. Rebelo, António C. Rodrigues, and Pedro S. Coelho
Geosci. Model Dev., 15, 173–197, https://doi.org/10.5194/gmd-15-173-2022, https://doi.org/10.5194/gmd-15-173-2022, 2022
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Maialen Iturbide, José M. Gutiérrez, Lincoln M. Alves, Joaquín Bedia, Ruth Cerezo-Mota, Ezequiel Cimadevilla, Antonio S. Cofiño, Alejandro Di Luca, Sergio Henrique Faria, Irina V. Gorodetskaya, Mathias Hauser, Sixto Herrera, Kevin Hennessy, Helene T. Hewitt, Richard G. Jones, Svitlana Krakovska, Rodrigo Manzanas, Daniel Martínez-Castro, Gemma T. Narisma, Intan S. Nurhati, Izidine Pinto, Sonia I. Seneviratne, Bart van den Hurk, and Carolina S. Vera
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We present an update of the IPCC WGI reference regions used in AR5 for the synthesis of climate change information. This revision was guided by the basic principles of climatic consistency and model representativeness (in particular for the new CMIP6 simulations). We also present a new dataset of monthly CMIP5 and CMIP6 spatially aggregated information using the new reference regions and describe a worked example of how to use this dataset to inform regional climate change studies.
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Geosci. Model Dev., 13, 2109–2124, https://doi.org/10.5194/gmd-13-2109-2020, https://doi.org/10.5194/gmd-13-2109-2020, 2020
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In this study we intercompare different deep learning topologies for statistical downscaling purposes. As compared to the top-ranked methods in the largest-to-date downscaling intercomparison study, our results better predict the local climate variability. Moreover, deep learning approaches can be suitably applied to large regions (e.g., continents), which can therefore foster the use of statistical downscaling in flagship initiatives such as CORDEX.
Joaquín Bedia, Jorge Baño-Medina, Mikel N. Legasa, Maialen Iturbide, Rodrigo Manzanas, Sixto Herrera, Ana Casanueva, Daniel San-Martín, Antonio S. Cofiño, and José Manuel Gutiérrez
Geosci. Model Dev., 13, 1711–1735, https://doi.org/10.5194/gmd-13-1711-2020, https://doi.org/10.5194/gmd-13-1711-2020, 2020
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We introduce downscaleR, an open-source tool for statistical downscaling (SD) of climate information, implementing the most popular approaches and state-of-the-art techniques. It makes possible the development of end-to-end downscaling applications, from data retrieval to model building, validation, and prediction, bringing to climate scientists and practitioners a unique comprehensive framework for the development of complex and fully reproducible SD experiments.
Edouard L. Davin, Diana Rechid, Marcus Breil, Rita M. Cardoso, Erika Coppola, Peter Hoffmann, Lisa L. Jach, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Kai Radtke, Mario Raffa, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Tölle, Kirsten Warrach-Sagi, and Volker Wulfmeyer
Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, https://doi.org/10.5194/esd-11-183-2020, 2020
Sixto Herrera, Rita Margarida Cardoso, Pedro Matos Soares, Fátima Espírito-Santo, Pedro Viterbo, and José Manuel Gutiérrez
Earth Syst. Sci. Data, 11, 1947–1956, https://doi.org/10.5194/essd-11-1947-2019, https://doi.org/10.5194/essd-11-1947-2019, 2019
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A new observational dataset of daily precipitation and temperatures for the Iberian Peninsula and the Balearic Islands has been developed and made publicly available for the community. In this work the capabilities of the new dataset to reproduce the mean and extreme regimes of precipitation and temperature are assessed and compared with the E-OBS dataset (including the ensemble version for observational uncertainty assessment).
Inês Gomes Marques, João Nascimento, Rita M. Cardoso, Filipe Miguéns, Maria Teresa Condesso de Melo, Pedro M. M. Soares, Célia M. Gouveia, and Cathy Kurz Besson
Hydrol. Earth Syst. Sci., 23, 3525–3552, https://doi.org/10.5194/hess-23-3525-2019, https://doi.org/10.5194/hess-23-3525-2019, 2019
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Mediterranean cork woodlands are very particular agroforestry systems present in a confined area of the Mediterranean Basin. They are of great importance due to their high socioeconomic value; however, a decrease in water availability has put this system in danger. In this paper we build a model that explains this system's tree-species distribution in southern Portugal from environmental variables. This could help predict their future distribution under changing climatic conditions.
Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz
Geosci. Model Dev., 12, 3419–3438, https://doi.org/10.5194/gmd-12-3419-2019, https://doi.org/10.5194/gmd-12-3419-2019, 2019
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Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely used to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical post-processing (bias correction).
Pere Quintana-Seguí, Marco Turco, Sixto Herrera, and Gonzalo Miguez-Macho
Hydrol. Earth Syst. Sci., 21, 2187–2201, https://doi.org/10.5194/hess-21-2187-2017, https://doi.org/10.5194/hess-21-2187-2017, 2017
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The quality of two high-resolution precipitation datasets for Spain at the daily time scale is reported: the new SAFRAN-based dataset and Spain02. ERA-Interim is also included. The precipitation products are compared with observations. SAFRAN and Spain02 have very similar scores, and they perform better than ERA-Interim. The high-resolution gridded products overestimate the number of precipitation days. Both SAFRAN and Spain02 underestimate high precipitation events.
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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Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
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The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
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The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
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This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
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Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
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Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
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Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Baiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1733, https://doi.org/10.5194/egusphere-2023-1733, 2023
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For the first time, we coupled a regional climate chemistry model RegCM-Chem with a dynamic vegetation model YIBs to create a regional climate-chemistry-ecology model RegCM-Chem-YIBs. We applied it to simulate climatic, chemical and ecological parameters in East Asia and fully validated it on a variety of observational data. The research results show that RegCM-Chem-YIBs model is a valuable tool for studying terrestrial carbon cycle, atmospheric chemistry, and climate change in regional scale.
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, https://doi.org/10.5194/gmd-16-7171-2023, 2023
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We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.
Cited articles
Azorin-Molina, C., Tijm, S., Ebert, E. E., Vicente-Serrano, S. M., and Estrela,
M. J.: Sea breeze thunderstorms in the eastern Iberian Peninsula.
Neighborhood verification of HIRLAM and HARMONIE precipitation forecasts,
Atmos. Res., 139, 101–115,
https://doi.org/10.1016/j.atmosres.2014.01.010, 2014.
Ban, N., Caillaud, C., Coppola, E., Pichelli, E., Sobolowski, S., Adinolfi,
M., Ahrens, B., Alias, A., Anders, I., Bastin, S., and Belušić, D.:
The first multi-model ensemble of regional climate simulations at
kilometer-scale resolution, Part I: Evaluation of precipitation, Clim.
Dynam., 57, 275–302, https://doi.org/10.1007/s00382-021-05708-w, 2021.
Brands, S., Herrera, S., Fernández, J., and Gutiérrez, J. M.: How well
do CMIP5 Earth System Models simulate present climate conditions in Europe
and Africa?, Clim. Dynam., 41, 803–817, https://doi.org/10.1007/s00382-013-1742-8, 2013.
Cardoso, R. M., and Soares, P. M. M.: Is there added value in the EURO-CORDEX hindcast temperature simulations? Assessing the added value using climate distributions in Europe, Int. J. Climatol., 1–16, https://doi.org/10.1002/joc.7472, 2022.
Cardoso, R. M., Soares, P. M. M., Miranda, P. M. A., and Belo-Pereira, M.: WRF
high resolution simulation of Iberian mean and extreme precipitation
climate, Int. J. Climatol., 33, 2591–2608, https://doi.org/10.1002/joc.3616, 2013.
Cardoso, R. M., Soares, P. M., Lima, D. C., and Miranda, P. M.: Mean and extreme
temperatures in a warming climate: EURO CORDEX and WRF regional climate
high-resolution projections for Portugal, Clim. Dynam., 52, 129–157,
https://doi.org/10.1007/s00382-018-4124-4, 2019.
Careto, J. A. M., Soares, P. M. M., Cardoso, R. M., Herrera, S., and Guttiérrez, J. M.: Added value of EURO-CORDEX high-resolution downscaling over the Iberian
Peninsula revisited – Part 1: Precipitation, Geosci. Model Dev., 15, 2635–2652, https://doi.org/10.5194/gmd-15-2635-2022, 2022.
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model
projections of changes in European climate by the end of this century,
Climatic Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007.
Christensen, J. H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I.,
Jones, R., Kolli, R. K., Kwon, W.-T., Laprise, R., Magaña Rueda, V.,
Mearns, L., Menéndez, C. G., Räisänen, J., Rinke, A., Sarr, A., and
Whetton, P.: Regional climate projections, in: Climate Change 2007: The
Physical Science Basis. Contribution of Working Group I to the Fourth
Assessment Report of the Intergovernmental Panel on Climate Change, edited
by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B.,
Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, UK and New
York, NY, TRN: GB07CC205, 2007.
Christensen, O. B., Drews, M., Christensen, J. H., Dethloff, K., Ketelsen, K.,
Hebestadt, I., and Rinke, A.: The HIRHAM regional climate model, Version 5
(beta), https://www.dmi.dk/fileadmin/Rapporter/TR/tr06-17.pdf (last access: 29
April 2021), 2007.
Ciarlo, J. M., Coppola, E., Fantini, A., Giorgi, F., Gao, X., Tong, Y.,
Glazer, R. H., Alavez, J. A. T., Sines, T., Pichelli, E., and Raffaele, F.: A
new spatially distributed added value index for regional climate models: the
EURO-CORDEX and the CORDEX-CORE highest resolution ensembles, Clim. Dynam., 57, 1403–1424, https://doi.org/10.1007/s00382-020-05400-5,
2020.
Coppola, E., Sobolowski, S., Pichelli, E., Raffaele, F., Ahrens, B., Anders,
I., Ban, N., Bastin, S., Belda, M., Belusic, D., and Caldas-Alvarez, A.: A
first-of-its-kind multi-model convection permitting ensemble for
investigating convective phenomena over Europe and the Mediterranean, Clim. Dynam., 55, 3–34, https://doi.org/10.1007/s00382-018-4521-8, 2020.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, D. P., and Bechtold, P.:
The ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Di Luca, A., de Elía, R., and Laprise, R.: Potential for added value in
precipitation simulated by high-resolution nested regional climate models
and observations, Clim. Dynam., 38, 1229–1247, https://doi.org/10.1007/s00382-011-1068-3, 2012.
Di Luca, A., de Elía, R., and Laprise, R.: Potential for small scale
added value of RCM's downscaled climate change signal, Clim. Dynam., 40,
601–618, https://doi.org/10.1007/s00382-012-1415-z, 2013.
Froidevaux, P., Schlemmer, L., Schmidli, J., Langhans, W., and Schär, C.:
Influence of the background wind on the local soil moisture–precipitation
feedback, J. Atmos. Sci., 71, 782–799, https://doi.org/10.1175/JAS-D-13-0180.1, 2014.
García-Díez, M., Fernández, J., and Vautard, R.: An RCM
multi-physics ensemble over Europe: multi-variable evaluation to avoid error
compensation, Clim. Dynam., 45, 3141–3156,
https://doi.org/10.1007/2Fs00382-015-2529-x, 2015.
Giorgi, F. and Bates, G. T.: The climatological skill of a regional model
over complex terrain, Mon. Weather Rev., 117, 2325–2347, https://doi.org/10.1175/1520-0493(1989)117<2325:TCSOAR>2.0.CO;2, 1989.
Giorgi, F. and Mearns, L. O.: Approaches to the simulation of regional
climate change: a review, Rev. Geophys., 29, 191–216, https://doi.org/10.1029/90RG02636, 1991.
Giorgi, F. and Mearns, L. O.: Introduction to special section: Regional
climate modeling revisited, J. Geophys. Res.-Atmos.,
104, 6335–6352, https://doi.org/10.1029/98JD02072, 1999.
Giorgi, F., Jones, C. and Asrar, G. R.: Addressing climate information needs
at the regional level: the CORDEX framework, World Meteorological
Organization (WMO) Bulletin, 58, 175–183, 2009.
Gutowski Jr., W. J., Takle, E. S., Kozak, K. A., Patton, J. C., Arritt, R. W., and
Christensen, J. H.: A possible constraint on regional precipitation intensity
changes under global warming, J. Hydrometeorol., 8, 1382–1396,
https://doi.org/10.1175/2007JHM817.1, 2007.
Gutowski Jr., W. J., Giorgi, F., Timbal, B., Frigon, A., Jacob, D., Kang, H.-S., Raghavan, K., Lee, B., Lennard, C., Nikulin, G., O'Rourke, E., Rixen, M., Solman, S., Stephenson, T., and Tangang, F.: WCRP COordinated Regional Downscaling EXperiment (CORDEX): a diagnostic MIP for CMIP6, Geosci. Model Dev., 9, 4087–4095, https://doi.org/10.5194/gmd-9-4087-2016, 2016.
Herrera, S., Cardoso, R. M., Soares, P. M. M., Espírio-Santo, F., Viterbo, P., and Gutiérrez, J. M.: “Iberia01: Daily gridded (0.1º resolution) dataset of precipitation and temperatures over the Iberian Peninsula”, DIGITAL.CSIC [data set], https://doi.org/10.20350/digitalCSIC/8641, 2019a.
Herrera, S., Cardoso, R. M., Soares, P. M., Espírito-Santo, F., Viterbo, P., and Gutiérrez, J. M.: Iberia01: a new gridded dataset of daily precipitation and temperatures over Iberia, Earth Syst. Sci. Data, 11, 1947–1956, https://doi.org/10.5194/essd-11-1947-2019, 2019b.
Herrera, S., Soares, P. M., Cardoso, R. M., and Gutiérrez, J. M.: Evaluation
of the EURO-CORDEX Regional Climate Models Over the Iberian Peninsula:
Observational Uncertainty Analysis, J. Geophys. Res.-Atmos., 125, e2020JD032880, https://doi.org/10.1029/2020JD032880, 2020.
Hohenegger, C., Brockhaus, P., Bretherton, C. S., and Schär, C.: The soil
moisture–precipitation feedback in simulations with explicit and
parameterized convection, J. Climate, 22, 5003–5020, https://doi.org/10.1175/2009JCLI2604.1, 2009.
Imamovic, A., Schlemmer, L., and Schär, C.: Collective impacts of
orography and soil moisture on the soil moisture-precipitation feedback,
Geophys. Res. Lett., 44, 11682–11691, https://doi.org/10.1002/2017GL075657, 2017.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer,
L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., and
Georgopoulou, E.: EURO-CORDEX: new high-resolution climate change
projections for European impact research, Reg. Environ. Change, 14,
563–578, https://doi.org/10.1007/s10113-013-0499-2,
2014.
Jacob, D., Teichmann, C., Sobolowski, S., Katragkou, E., Anders, I., Belda,
M., Benestad, R., Boberg, F., Buonomo, E., Cardoso, R. M., Casanueva, A.,
Christensen, O. B., Christensen, J. H., Coppola, E., De Cruz, L., Davin, E. L.,
Dobler, A., Domínguez, M., Fealy, R., Fernandez, J., Gaertner, M. A.,
García-Díez, M., Giorgi, F., Gobiet, A., Goergen, K.,
Gómez-Navarro, J. J., Alemán, J. J. G., Gutiérrez, C.,
Gutiérrez, J. M., Güttler, I., Haensler, A., Halenka, T., Jerez, S.,
Jiménez-Guerrero, P., Jones, R. G., Keuler, K., Kjellström, E.,
Knist, S., Kotlarski, S., Maraun, D., van Meijgaard, E., Mercogliano, P.,
Montávez, J. P., Navarra, A., Nikulin, G., Noblet-Ducoudré, N.,
Panitz, H. J., Pfeifer, S., Piazza, M., Pichelli, E., Pietikäinen, J. P.,
Prein, A. F., Preuschmann, S., Rechid, D., Rockel, B., Romera, R.,
Sánchez, E., Sieck, K., Soares, P. M. M., Somot, S., Srnec, L.,
Sørland, S. L., Termonia, P., Truhetz, H., Vautard, R., Warrach-Sagi, K.,
and Wulfmeyer, V.: Regional climate downscaling over Europe: perspectives
from the EURO-CORDEX community, Reg. Environ. Change, 20, 51, https://doi.org/10.1007/s10113-020-01606-9, 2020.
Khan, M. S., Coulibaly, P., and Dibike, Y.: Uncertainty analysis of
statistical downscaling methods, J. Hydrol., 319, 357–382,
https://doi.org/10.1016/j.jhydrol.2005.06.035, 2006.
Kirshbaum, D. J., Adler, B., Kalthoff, N., Barthlott, C., and Serafin, S.:
Moist orographic convection: Physical mechanisms and links to
surface-exchange processes, Atmosphere, 9, 80, https://doi.org/10.3390/atmos9030080, 2018.
Klein Tank, A. M. G., Wijngaard, J. B., Können, G. P., Böhm, R.,
Demarée, G., Gocheva, A., Mileta, M., Pashiardis, S., Hejkrlik, L.,
Kern-Hansen, C., and Heino, R.: Daily dataset of 20th-century surface air
temperature and precipitation series for the European Climate Assessment,
Int. J. Climatol., 22, 1441–1453, https://doi.org/10.1002/joc.773, 2002.
Klok, E. J. and Klein Tank, A. M. G.: Updated and extended European dataset of
daily climate observations, Int. J. Climatol., 29, 1182–1191, https://doi.org/10.1002/joc.1779, 2009.
Knist, S., Goergen, K., and Simmer, C.: Evaluation and projected changes of precipitation statistics in convection-permitting WRF climate simulations over Central Europe, Clim. Dynam., 55, 325–341, https://doi.org/10.1007/s00382-018-4147-x, 2020.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Laprise, R.: Regional climate modelling, J. Comput. Phys.,
227, 3641–3666, https://doi.org/10.1016/j.jcp.2006.10.024,
2008.
Leung, L. R., Mearns, L. O., Giorgi, F., and Wilby, R. L.: Regional climate
research: Needs and opportunities, B. Am. Meteorol.
Soc., 84, 89–95, 2003.
Lhotka, O., Kyselý, J., and Plavcová, E.: Evaluation of major heat
waves' mechanisms in EURO-CORDEX RCMs over Central Europe, Clim. Dynam.,
50, 4249–4262, https://doi.org/10.1007/s00382-017-3873-9, 2018.
McGregor, J. L.: Regional climate modelling, Meteorol. Atmos.
Phys., 63, 105–117, https://doi.org/10.1007/BF01025367, 1997.
McSweeney, C. F., Jones, R. G., Lee, R. W., and Rowell, D. P.: Selecting CMIP5
GCMs for downscaling over multiple regions, Clim. Dynam., 44, 3237–3260,
https://doi.org/10.1007/s00382-014-2418-8, 2015.
Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T.,
Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., and Raper,
S. C.: Global climate projections In Climate Change 2007: The Physical
Science Basis, Contribution of Working Group I to the Fourth Assessment
Report of the Intergovernmental Panel on Climate Change, edited by: Solomon,
S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M.,
Miller, H. L., Cambridge University Press, Cambridge, UK and New York, NY,
TRN: GB07CC205, 2007.
Minder, J. R., Letcher, T. W., and Skiles, S. M.: An evaluation of
high-resolution regional climate model simulations of snow cover and albedo
over the Rocky Mountains, with implications for the simulated snow-albedo
feedback, J. Geophys. Res.-Atmos., 121, 9069–9088,
https://doi.org/10.1002/2016JD024995, 2016.
Perkins, S. E., Pitman, A. J., Holbrook, N. J., and McAneney, J.: Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions, J. Climate, 20, 4356–4376, https://doi.org/10.1175/JCLI4253.1, 2007.
Pichelli, E., Coppola, E., Sobolowski, S., Ban, N., Giorgi, F., Stocchi, P.,
Alias, A., Belušić, D., Berthou, S., Caillaud, C., and Cardoso, R. M.:
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.
Prein, A. F., Gobiet, A., Suklitsch, M., Truhetz, H., Awan, N. K., Keuler, K.,
and Georgievski, G.: Added value of convection permitting seasonal
simulations, Clim. Dynam., 41, 2655–2677, https://doi.org/10.1007/s00382-013-1744-6, 2013.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., and Brisson, E.: A review
on regional convection-permitting climate modeling: Demonstrations,
prospects, and challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015.
Prein, A. F., Gobiet, A., Truhetz, H., Keuler, K., Goergen, K., Teichmann,
C., Maule, C. F., Van Meijgaard, E., Déqué, M., Nikulin, G., and
Vautard, R.: Precipitation in the EURO-CORDEX 0.11∘ and 0.44∘
simulations: high resolution, high benefits?, Clim. Dynam., 46, 383,
https://doi.org/10.1007/s00382-015-2589-y, 2016.
Randall, D. A., Wood, R. A., Bony, S., Colman, R., Fichefet, T., Fyfe, J.,
Kattsov, V., Pitman, A., Shukla, J., Srinivasan, J., and Stouffer, R. J.:
Climate models and their evaluation. In Climate change 2007: The
physical science basis. Contribution of Working Group I to the Fourth
Assessment Report of the Intergovernmental Panel on Climate Change, edited
by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B.,
Tignor, M., and Miller, H. L., Cambridge University Press: Cambridge, UK and New
York, NY, TRN: GB07CC205, 2007.
Prömmel, K., Geyer, B., Jones, J. M., and Widmann, M.: Evaluation of the
skill and added value of a reanalysis-driven regional simulation for Alpine
temperature, Int. J. Climatol., 30, 760–773, https://doi.org/10.1002/joc.1916, 2010.
Rios-Entenza, A., Soares, P. M. M., Trigo, R. M., Cardoso, R. M., and
Miguez-Macho, G.: Precipitation recycling in the Iberian Peninsula: spatial
patterns and temporal variability, J. Geophys. Res.-Atmos., 119, 5895–5912, https://doi.org/10.1002/2013JD021274, 2014.
Rummukainen, M.: State-of-the-art with regional climate models, Wires Clim. Change, 1, 82–96, https://doi.org/10.1002/wcc.8, 2010.
Rummukainen, M.: Added value in regional climate modeling, Wires Clim. Change, 7, 145–159, https://doi.org/10.1002/wcc.378, 2016.
Schulzweida, U.: Climate Data Operators, User's Guide, Version 1.1.9,
Max-Planck Institute for Meteorology, Hamburg, Germany, https://code.mpimet.mpg.de/projects/cdo/embedded/cdo.pdf, last access: 29
April 2021.
Smiatek, G., Kunstmann, H., and Senatore, A.: EUROCORDEX regional climate model analysis for the Greater Alpine Region: Performance and expected future change, J. Geophys. Res.-Atmos., 121, 7710–7728, https://doi.org/10.1002/2015JD024727, 2016.
Soares, P. M. and Cardoso, R. M.: A simple method to assess the added value
using high-resolution climate distributions: application to the EURO-CORDEX
daily precipitation, Int. J. Climatol., 38, 1484–1498,
https://doi.org/10.1002/joc.5261, 2018.
Soares, P. M., Cardoso, R. M., Miranda, P. M., de Medeiros, J., Belo-Pereira,
M., and Espirito-Santo, F: WRF high resolution dynamical downscaling of
ERA-Interim for Portugal, Clim. Dynam., 39, 2497–2522, https://doi.org/10.1007/s00382-012-1315-2, 2012a.
Soares, P. M., Cardoso, R. M., Miranda, P. M., Viterbo, P., and Belo-Pereira, M.:
Assessment of the ENSEMBLES regional climate models in the representation of
precipitation variability and extremes over Portugal, J. Geophys. Res.-Atmos., 117, D07114, https://doi.org/10.1029/2011JD016768, 2012b.
Soares, P. M., Cardoso, R. M., Semedo, Á., Chinita, M. J., and Ranjha, R.:
Climatology of the Iberia coastal low-level wind jet: weather research
forecasting model high-resolution results, Tellus A, 66, 22377, https://doi.org/10.3402/tellusa.v66.22377, 2014.
Smiatek, G., Kunstmann, H., and Senatore, A.: EURO-CORDEX regional climate
model analysis for the Greater Alpine Region: Performance and expected
future change, J. Geophys. Res.-Atmos., 121, 7710–7728,
https://doi.org/10.1002/2015JD024727, 2016.
Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M. M., Allen, S. K., Boschung,
J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M. (Eds.): Climate Change
2013: The physical science basis. contribution of working group I to the
fifth assessment report of IPCC the intergovernmental panel on climate
change, Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, https://doi.org/10.1017/CBO9781107415324, 2014.
Terzago, S., von Hardenberg, J., Palazzi, E., and Provenzale, A.: Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models, The Cryosphere, 11, 1625–1645, https://doi.org/10.5194/tc-11-1625-2017, 2017.
Torma, C., Giorgi, F., and Coppola, E.: Added value of regional climate
modeling over areas characterized by complex terrain – Precipitation over
the Alps, J. Geophys. Res.-Atmos., 120, 3957–3972,
https://doi.org/10.1002/2014JD022781, 2015.
van der Linden, P. and Mitchell, J. E.: ENSEMBLES: Climate Change and its
Impacts: Summary of research and results from the ENSEMBLES project, Met
Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK, 160 pp., 2009.
Vautard, R., Gobiet, A., Jacob, D., Belda, M., Colette, A., Déqué,
M., Fernández, J., García-Díez, M., Goergen, K., Güttler,
I., and Halenka, T.: The simulation of European heat waves from an ensemble
of regional climate models within the EURO-CORDEX project, Clim. Dynam.,
4, 2555–2575, https://doi.org/10.1007/s00382-013-1714-z, 2013.
Vautard, R., Kadygrov, N., Iles, C., Boberg, F., Buonomo, E., Buelow, K.,
Coppola, E., Corre, L., van Meijgaard, E., Nogherotto, R., Sandstad, M.,
Schwingshakl, C., Somot, S., Aalbers, E. E., Christensen, O., Ciarlo, J.,
Demory, M.-E., Giorgi, F., Jacob, D., Jones, R. G., Keuler, K.,
Kjellström, E., Lenderink, G., Levavasseur, G., Nikulin, G., Sillmann,
J., Solidoro, C., Sørland, S., Steger, C., Teichmann, C., Warrach-Sagi,
K., and Wulfmeyer, V.: Evaluation of the large EURO-CORDEX regional climate
model ensemble, J. Geophys. Res.-Atmos., 126, 1–28, https://doi.org/10.1029/2019JD032344, 2020.
Wilby, R. L., Wigley, T. M. L., Conway, D., Jones, P. D., Hewitson, B. C., Main,
J., and Wilks, D. S.: Statistical downscaling of general circulation model
output: A comparison of methods, Water Resour. Res., 34, 2995–3008,
https://doi.org/10.1029/98WR02577, 1998.
Williams, D. N., Taylor, K. E., Cinquini, L., Evans, B., Kawamiya, M., Lautenschlager, M., Lawrence, B., Middleton, D., and ESGF Contributors: The Earth System Grid Federation: Software framework supporting CMIP5 data analysis and dissemination, ClIVAR Exchanges, 56, 40–42, http://centaur.reading.ac.uk/25732/1/WilEA11_CE.pdf (last access: 29 April
2021), 2011.
Zappa, G., Shaffrey, L. C., and Hodges, K. I.: The ability of CMIP5 models to simulate North Atlantic extratropical cyclones, J. Climate, 26, 5379–5396, https://doi.org/10.1175/JCLI-D-12-00501.1, 2013.
Short summary
This work focuses on the added value of high-resolution models relative to their forcing simulations, with an observational gridded dataset as a reference covering the Iberian Peninsula. The availability of such datasets with a spatial resolution close to that of regional models encouraged this study. For the max and min temperature, although most models reveal added value, some display losses. At more local scales, coastal sites display important gains, contrasting with the interior.
This work focuses on the added value of high-resolution models relative to their forcing...
