Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2511-2020
© Author(s) 2020. 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-13-2511-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Jun 2020
Model evaluation paper |
| 02 Jun 2020
| 02 Jun 2020
Investigating the sensitivity to resolving aerosol interactions in downscaling regional model experiments with WRFv3.8.1 over Europe
Vasileios Pavlidis
CORRESPONDING AUTHOR
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Eleni Katragkou
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Andreas Prein
National Center for Atmospheric Research, Boulder, CO, USA
Aristeidis K. Georgoulias
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Stergios Kartsios
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Prodromos Zanis
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
Theodoros Karacostas
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Atmos. Chem. Phys., 25, 7343–7368, https://doi.org/10.5194/acp-25-7343-2025, https://doi.org/10.5194/acp-25-7343-2025, 2025
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This study proposes a novel inverse modeling framework coupled with remote sensing data for improving volcanic ash dispersion forecasts, essential for aviation safety. By integrating FLEXPART dispersion model outputs with ground-based ACTRIS lidar observations, the approach estimates Etna's volcanic particle emissions and highlights a significant enhancement in the forecast accuracy.
Alkiviadis Kalisoras, Aristeidis K. Georgoulias, Dimitris Akritidis, Robert J. Allen, Vaishali Naik, Chaincy Kuo, Sophie Szopa, Pierre Nabat, Dirk Olivié, Twan van Noije, Philippe Le Sager, David Neubauer, Naga Oshima, Jane Mulcahy, Larry W. Horowitz, and Prodromos Zanis
Atmos. Chem. Phys., 24, 7837–7872, https://doi.org/10.5194/acp-24-7837-2024, https://doi.org/10.5194/acp-24-7837-2024, 2024
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Effective radiative forcing (ERF) is a metric for estimating how human activities and natural agents change the energy flow into and out of the Earth’s climate system. We investigate the anthropogenic aerosol ERF, and we estimate the contribution of individual processes to the total ERF using simulations from Earth system models within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our findings highlight that aerosol–cloud interactions drive ERF variability during the last 150 years.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Peter Hoffmann, Vanessa Reinhart, Diana Rechid, Nathalie de Noblet-Ducoudré, Edouard L. Davin, Christina Asmus, Benjamin Bechtel, Jürgen Böhner, Eleni Katragkou, and Sebastiaan Luyssaert
Earth Syst. Sci. Data, 15, 3819–3852, https://doi.org/10.5194/essd-15-3819-2023, https://doi.org/10.5194/essd-15-3819-2023, 2023
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This paper introduces the new high-resolution land use and land cover change dataset LUCAS LUC for Europe (version 1.1), tailored for use in regional climate models. Historical and projected future land use change information from the Land-Use Harmonization 2 (LUH2) dataset is translated into annual plant functional type changes from 1950 to 2015 and 2016 to 2100, respectively, by employing a newly developed land use translator.
Maria Chara Karypidou, Stefan Pieter Sobolowski, Lorenzo Sangelantoni, Grigory Nikulin, and Eleni Katragkou
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.
James M. Done, Gary M. Lackmann, and Andreas F. Prein
Weather Clim. Dynam., 3, 693–711, https://doi.org/10.5194/wcd-3-693-2022, https://doi.org/10.5194/wcd-3-693-2022, 2022
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We know that warm oceans generally favour tropical cyclones (TCs). Less is known about the role of air temperature above the oceans extending into the lower stratosphere. Our global analysis of historical records and computer simulations suggests that TCs strengthen in response to historical temperature change while also being influenced by other environmental factors. Ocean warming drives much of the strengthening, with relatively small contributions from temperature changes aloft.
Anne Sophie Daloz, Clemens Schwingshackl, Priscilla Mooney, Susanna Strada, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Michal Belda, Tomas Halenka, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
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.
Dimitris Akritidis, Andrea Pozzer, Johannes Flemming, Antje Inness, Philippe Nédélec, and Prodromos Zanis
Atmos. Chem. Phys., 22, 6275–6289, https://doi.org/10.5194/acp-22-6275-2022, https://doi.org/10.5194/acp-22-6275-2022, 2022
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We perform a process-oriented evaluation of Copernicus Atmosphere Monitoring Service (CAMS) reanalysis (CAMSRA) O3 over Europe using WOUDC (World Ozone and Ultraviolet Radiation Data Centre) ozonesondes and IAGOS (In-service Aircraft for a Global Observing System) aircraft measurements. Chemical data assimilation assists CAMSRA to reproduce the observed O3 increases in the troposphere during the examined folding events, but it mostly results in O3 overestimation in the upper troposphere.
Maria Chara Karypidou, Eleni Katragkou, and Stefan Pieter Sobolowski
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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.
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
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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.
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.
Peter Hoffmann, Vanessa Reinhart, Diana Rechid, Nathalie de Noblet-Ducoudré, Edouard L. Davin, Christina Asmus, Benjamin Bechtel, Jürgen Böhner, Eleni Katragkou, and Sebastiaan Luyssaert
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-252, https://doi.org/10.5194/essd-2021-252, 2021
Manuscript not accepted for further review
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This paper introduces the new high-resolution land-use land-cover change dataset LUCAS LUC historical and future land use and land cover change dataset (Version 1.0), tailored for use in regional climate models. Historical and projected future land use change information from the Land-Use Harmonization 2 (LUH2) dataset is translated into annual plant functional type changes from 1950 to 2015 and 2016 to 2100, respectively, by employing a newly developed land use translator.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
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We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Dimitris Akritidis, Eleni Katragkou, Aristeidis K. Georgoulias, Prodromos Zanis, Stergios Kartsios, Johannes Flemming, Antje Inness, John Douros, and Henk Eskes
Atmos. Chem. Phys., 20, 13557–13578, https://doi.org/10.5194/acp-20-13557-2020, https://doi.org/10.5194/acp-20-13557-2020, 2020
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We assess the Copernicus Atmosphere Monitoring Service (CAMS) global and regional forecasts performance during a complex aerosol transport event over Europe induced by the passage of Storm Ophelia in mid-October 2017. Comparison with satellite observations reveals a satisfactory performance of CAMS global forecast assisted by data assimilation, while comparison with ground-based measurements indicates that the CAMS regional system over-performs compared to the global one in terms of air quality.
Robert J. Allen, Steven Turnock, Pierre Nabat, David Neubauer, Ulrike Lohmann, Dirk Olivié, Naga Oshima, Martine Michou, Tongwen Wu, Jie Zhang, Toshihiko Takemura, Michael Schulz, Kostas Tsigaridis, Susanne E. Bauer, Louisa Emmons, Larry Horowitz, Vaishali Naik, Twan van Noije, Tommi Bergman, Jean-Francois Lamarque, Prodromos Zanis, Ina Tegen, Daniel M. Westervelt, Philippe Le Sager, Peter Good, Sungbo Shim, Fiona O'Connor, Dimitris Akritidis, Aristeidis K. Georgoulias, Makoto Deushi, Lori T. Sentman, Jasmin G. John, Shinichiro Fujimori, and William J. Collins
Atmos. Chem. Phys., 20, 9641–9663, https://doi.org/10.5194/acp-20-9641-2020, https://doi.org/10.5194/acp-20-9641-2020, 2020
Prodromos Zanis, Dimitris Akritidis, Aristeidis K. Georgoulias, Robert J. Allen, Susanne E. Bauer, Olivier Boucher, Jason Cole, Ben Johnson, Makoto Deushi, Martine Michou, Jane Mulcahy, Pierre Nabat, Dirk Olivié, Naga Oshima, Adriana Sima, Michael Schulz, Toshihiko Takemura, and Konstantinos Tsigaridis
Atmos. Chem. Phys., 20, 8381–8404, https://doi.org/10.5194/acp-20-8381-2020, https://doi.org/10.5194/acp-20-8381-2020, 2020
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In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014.
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
Dimitris Akritidis, Andrea Pozzer, and Prodromos Zanis
Atmos. Chem. Phys., 19, 14387–14401, https://doi.org/10.5194/acp-19-14387-2019, https://doi.org/10.5194/acp-19-14387-2019, 2019
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We investigate the impact of future climate change under the RCP6.0 scenario on tropopause folds and tropospheric ozone, using a transient EMAC simulation and a tropopause fold detection algorithm. A strengthening of ozone stratosphere-to-troposphere transport (STT) is projected for the future, resulting in an increase in upper- and middle-tropospheric ozone. The maxima of future ozone STT increases are mainly projected for regions where tropopause folds are expected to occur more frequently.
Aristeidis K. Georgoulias, Ronald J. van der A, Piet Stammes, K. Folkert Boersma, and Henk J. Eskes
Atmos. Chem. Phys., 19, 6269–6294, https://doi.org/10.5194/acp-19-6269-2019, https://doi.org/10.5194/acp-19-6269-2019, 2019
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In this paper, a ∼21-year self-consistent global dataset from four different satellite sensors is compiled for the first time to study the long-term tropospheric NO2 patterns and trends. A novel method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe during the last 2 decades.
Lluís Fita, Jan Polcher, Theodore M. Giannaros, Torge Lorenz, Josipa Milovac, Giannis Sofiadis, Eleni Katragkou, and Sophie Bastin
Geosci. Model Dev., 12, 1029–1066, https://doi.org/10.5194/gmd-12-1029-2019, https://doi.org/10.5194/gmd-12-1029-2019, 2019
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Regional climate experiments coordinated throughout CORDEX aim to study and provide high-quality climate data over a given region. The data are used in climate change mitigation and adaptation policy studies and by stakeholders. CORDEX requires a list of variables, most of which are not provided by atmospheric models. Aiming to help the community and to maximize the use of CORDEX exercises, we create a new module for WRF models to directly produce them by adding
genericand
additionalones.
Larisa Sogacheva, Edith Rodriguez, Pekka Kolmonen, Timo H. Virtanen, Giulia Saponaro, Gerrit de Leeuw, Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos Kourtidis, and Ronald J. van der A
Atmos. Chem. Phys., 18, 16631–16652, https://doi.org/10.5194/acp-18-16631-2018, https://doi.org/10.5194/acp-18-16631-2018, 2018
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Understanding long-term trends in aerosol optical density (AOD) is essential for evaluating health and climate effects and the effectiveness of pollution control policies. A method to construct a combined AOD long time series (1995-2017) using ATSR and MODIS spaceborne instruments is introduced. The effect of changes in the emission regulation policy in China is seen in a gradual AOD decrease after 2011. The effect is more visible in highly populated and industrialized areas in southeast China.
Dimitris Akritidis, Eleni Katragkou, Prodromos Zanis, Ioannis Pytharoulis, Dimitris Melas, Johannes Flemming, Antje Inness, Hannah Clark, Matthieu Plu, and Henk Eskes
Atmos. Chem. Phys., 18, 15515–15534, https://doi.org/10.5194/acp-18-15515-2018, https://doi.org/10.5194/acp-18-15515-2018, 2018
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Analysis and evaluation of the Copernicus Atmosphere Monitoring Service (CAMS) global and regional forecast systems during a deep stratosphere-to-troposphere ozone transport event over Europe in January 2017. Radiosondes, satellite images, ozonesondes and aircraft measurements were used to investigate the folding of the tropopause at several European sites and the induced presence of dry and ozone-rich air in the troposphere.
Larisa Sogacheva, Gerrit de Leeuw, Edith Rodriguez, Pekka Kolmonen, Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos Kourtidis, Emmanouil Proestakis, Eleni Marinou, Vassilis Amiridis, Yong Xue, and Ronald J. van der A
Atmos. Chem. Phys., 18, 11389–11407, https://doi.org/10.5194/acp-18-11389-2018, https://doi.org/10.5194/acp-18-11389-2018, 2018
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Using AATSR ADV (1995–2011) and MODIS C6.1 (2000–2017) annual and seasonal aerosol optical depth (AOD) aggregates, we obtained information regarding the occurrence of aerosols and their spatial and temporal variation over China. We specifically focused on regional differences in annual and seasonal AOD behavior for selected regions. AOD dataset comparisons, validation results and AOD tendencies during the overlapping period (2000–2011) are discussed.
Aristeidis K. Georgoulias, Athanasios Tsikerdekis, Vassilis Amiridis, Eleni Marinou, Angela Benedetti, Prodromos Zanis, Georgia Alexandri, Lucia Mona, Konstantinos A. Kourtidis, and Jos Lelieveld
Atmos. Chem. Phys., 18, 8601–8620, https://doi.org/10.5194/acp-18-8601-2018, https://doi.org/10.5194/acp-18-8601-2018, 2018
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In this work, the MACC reanalysis dust product is evaluated over Europe, Northern Africa and the Middle East using the EARLINET-optimized CALIOP/CALIPSO pure dust satellite-based product LIVAS (2007–2012). As dust plays a determinant role in processes related to weather and climate, human healt, and the economy, it is obvious that adequately simulating the amount of dust and its optical properties is essential. Our results could be used as a reference in future climate model evaluations.
Stephen Blenkinsop, Hayley J. Fowler, Renaud Barbero, Steven C. Chan, Selma B. Guerreiro, Elizabeth Kendon, Geert Lenderink, Elizabeth Lewis, Xiao-Feng Li, Seth Westra, Lisa Alexander, Richard P. Allan, Peter Berg, Robert J. H. Dunn, Marie Ekström, Jason P. Evans, Greg Holland, Richard Jones, Erik Kjellström, Albert Klein-Tank, Dennis Lettenmaier, Vimal Mishra, Andreas F. Prein, Justin Sheffield, and Mari R. Tye
Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018, https://doi.org/10.5194/asr-15-117-2018, 2018
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Measurements of sub-daily (e.g. hourly) rainfall totals are essential if we are to understand short, intense bursts of rainfall that cause flash floods. We might expect the intensity of such events to increase in a warming climate but these are poorly realised in projections of future climate change. The INTENSE project is collating a global dataset of hourly rainfall measurements and linking with new developments in climate models to understand the characteristics and causes of these events.
Gerrit de Leeuw, Larisa Sogacheva, Edith Rodriguez, Konstantinos Kourtidis, Aristeidis K. Georgoulias, Georgia Alexandri, Vassilis Amiridis, Emmanouil Proestakis, Eleni Marinou, Yong Xue, and Ronald van der A
Atmos. Chem. Phys., 18, 1573–1592, https://doi.org/10.5194/acp-18-1573-2018, https://doi.org/10.5194/acp-18-1573-2018, 2018
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The complementary use of two sensors, ATSR and MODIS, to provide aerosol information over two decades (1995–2015) is described. To this end, the AOD retrieved from both instruments had to be compared, showing that ATSR slightly underestimates and MODIS overestimates by a similar amount. Results show the increase of aerosols over the years, with an indication of the onset of a decrease in recent years. The AOD spatial distribution shows seasonal variations across China.
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Aristeidis K. Georgoulias, Stavros Solomos, Stelios Kazadzis, Julien Chimot, Huizheng Che, Georgia Alexandri, Ioannis Binietoglou, Vasiliki Daskalopoulou, Konstantinos A. Kourtidis, Gerrit de Leeuw, and Ronald J. van der A
Atmos. Chem. Phys., 18, 1337–1362, https://doi.org/10.5194/acp-18-1337-2018, https://doi.org/10.5194/acp-18-1337-2018, 2018
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We provide a 3-D climatology of desert dust aerosols over South and East Asia, based on 9 years of CALIPSO observations and an EARLINET methodology. The results provide the horizontal, vertical and seasonal distribution of dust aerosols over SE Asia along with the change in dust transport pathways. The dataset is unique for its potential applications, including evaluation and assimilation activities in atmospheric simulations and the estimation of the climatic impact of dust aerosols.
Eleni Marinou, Vassilis Amiridis, Ioannis Binietoglou, Athanasios Tsikerdekis, Stavros Solomos, Emannouil Proestakis, Dimitra Konsta, Nikolaos Papagiannopoulos, Alexandra Tsekeri, Georgia Vlastou, Prodromos Zanis, Dimitrios Balis, Ulla Wandinger, and Albert Ansmann
Atmos. Chem. Phys., 17, 5893–5919, https://doi.org/10.5194/acp-17-5893-2017, https://doi.org/10.5194/acp-17-5893-2017, 2017
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We provide a 3D multiyear analysis on the evolution of Saharan dust over Europe, using a dust product retrieved from the CALIPSO satellite and using EARLINET methods. The results reveal for the first time the 9-year 3D seasonal patterns of dust over its transport paths from the Sahara towards the Mediterranean. The dataset is unique with respect to its potential applications, including the evaluation of dust models and the estimation of ice nuclei concentration profiles from space.
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
Atmos. Chem. Phys., 17, 1945–1983, https://doi.org/10.5194/acp-17-1945-2017, https://doi.org/10.5194/acp-17-1945-2017, 2017
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We combine satellite observations of carbon monoxide, ozone and aerosols with the results from a model using a technique called data assimilation. The generated global data set (CAMS interim reanalysis) covers the period 2003–2015 at a resolution of about 110 km. The CAMS interim reanalysis can be used to study global air pollution and climate forcing of aerosol and stratospheric ozone. It has been produced by the Copernicus Atmosphere Monitoring Service (http://atmosphere. copernicus.eu).
Athanasios Tsikerdekis, Prodromos Zanis, Allison L. Steiner, Fabien Solmon, Vassilis Amiridis, Eleni Marinou, Eleni Katragkou, Theodoros Karacostas, and Gilles Foret
Atmos. Chem. Phys., 17, 769–791, https://doi.org/10.5194/acp-17-769-2017, https://doi.org/10.5194/acp-17-769-2017, 2017
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Dust is the most abundant aerosol in the atmosphere, considerably affecting Earth's climate. We use a new dust size discretization that improves the physical representation of dust in a regional climate model. This study is among the first studies evaluating the vertical profile of simulated dust with a pure dust product. The new dust size discretization increases dust optical depth by 10 % over the desert and Mediterranean. Consequently, the dust SW and LW radiative forcing is enhanced by 10 %.
Dimitris Akritidis, Andrea Pozzer, Prodromos Zanis, Evangelos Tyrlis, Bojan Škerlak, Michael Sprenger, and Jos Lelieveld
Atmos. Chem. Phys., 16, 14025–14039, https://doi.org/10.5194/acp-16-14025-2016, https://doi.org/10.5194/acp-16-14025-2016, 2016
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We investigate the contribution of tropopause folds in the summertime tropospheric ozone pool over the eastern Mediterranean and the Middle East. For this purpose we use the EMAC atmospheric chemistry–climate model and a fold identification algorithm. A clear increase of ozone is found in the middle troposphere due to fold activity. The interannual variability of near-surface ozone over the eastern Mediterranean is related to that of both tropopause folds and ozone in the free troposphere.
Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos A. Kourtidis, Jos Lelieveld, Prodromos Zanis, Ulrich Pöschl, Robert Levy, Vassilis Amiridis, Eleni Marinou, and Athanasios Tsikerdekis
Atmos. Chem. Phys., 16, 13853–13884, https://doi.org/10.5194/acp-16-13853-2016, https://doi.org/10.5194/acp-16-13853-2016, 2016
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In this work, single pixel observations from MODIS Terra and Aqua are analyzed together with data from other satellite sensors, reanalysis projects and a chemistry–aerosol-transport model to study the spatiotemporal variability of different aerosol types. The results are in accordance with previous works and are a good reference for future studies in the area focusing on aerosols, clouds, radiation and the effects of particle pollution on human health.
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.
K. Kourtidis, S. Stathopoulos, A. K. Georgoulias, G. Alexandri, and S. Rapsomanikis
Atmos. Chem. Phys., 15, 10955–10964, https://doi.org/10.5194/acp-15-10955-2015, https://doi.org/10.5194/acp-15-10955-2015, 2015
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The impact of aerosols on cloud cover (CC) under the influence of water vapor is studied using a decade of satellite observations. Water vapor is found to have a stronger impact on CC than aerosols. The water vapor impact shows that the hydrological cycle interferes with the aerosol climatic impact, and we need to improve our understanding of this interference.
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. Pozzer, A. de Meij, J. Yoon, H. Tost, A. K. Georgoulias, and M. Astitha
Atmos. Chem. Phys., 15, 5521–5535, https://doi.org/10.5194/acp-15-5521-2015, https://doi.org/10.5194/acp-15-5521-2015, 2015
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Thanks to numerical simulations and satellite observations, it is shown that aerosol optical depth (AOD) trends (2000--2010 period) over the US and Europe are due to emission decrease, while over the Sahara Desert and the Middle East they are due to meteorological changes. Over Southeast Asia, both meteorology and emission changes are important for the AOD trends.
It is shown that soluble components strongly influence AOD, as their contribution is enhanced by the aerosol water content.
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
C. S. Zerefos, K. Tourpali, P. Zanis, K. Eleftheratos, C. Repapis, A. Goodman, D. Wuebbles, I. S. A. Isaksen, and J. Luterbacher
Atmos. Chem. Phys., 14, 7705–7720, https://doi.org/10.5194/acp-14-7705-2014, https://doi.org/10.5194/acp-14-7705-2014, 2014
P. Zanis, P. Hadjinicolaou, A. Pozzer, E. Tyrlis, S. Dafka, N. Mihalopoulos, and J. Lelieveld
Atmos. Chem. Phys., 14, 115–132, https://doi.org/10.5194/acp-14-115-2014, https://doi.org/10.5194/acp-14-115-2014, 2014
Related subject area
Climate and Earth system modeling
Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol–climate model ECHAM6.3–HAM2.3
Assessing the climate impact of an improved volcanic sulfate aerosol representation in E3SM
Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing
ICON-HAM-lite 1.0: simulating the Earth system with interactive aerosols at kilometer scales
Process-based modeling framework for sustainable irrigation management at the regional scale: integrating rice production, water use, and greenhouse gas emissions
Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration
Reducing time and computing costs in EC-Earth: an automatic load-balancing approach for coupled Earth system models
FLAME 1.0: a novel approach for modelling burned area in the Brazilian biomes using the maximum entropy concept
SURFER v3.0: a fast model with ice sheet tipping points and carbon cycle feedbacks for short- and long-term climate scenarios
NMH-CS 3.0: a C# programming language and Windows-system-based ecohydrological model derived from Noah-MP
A method for quantifying uncertainty in spatially interpolated meteorological data with application to daily maximum air temperature
Baseline Climate Variables for Earth System Modelling
PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
ZEMBA v1.0: an energy and moisture balance climate model to investigate Quaternary climate
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TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions
The ensemble consistency test: from CESM to MPAS and beyond
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models
Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data
OpenBench: a land models evaluation system
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A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
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Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7
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Anisbel Leon-Marcos, Moritz Zeising, Manuela van Pinxteren, Sebastian Zeppenfeld, Astrid Bracher, Elena Barbaro, Anja Engel, Matteo Feltracco, Ina Tegen, and Bernd Heinold
Geosci. Model Dev., 18, 4183–4213, https://doi.org/10.5194/gmd-18-4183-2025, https://doi.org/10.5194/gmd-18-4183-2025, 2025
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This study represents the primary marine organic aerosol (PMOA) emissions, focusing on their sea–atmosphere transfer. Using the FESOM2.1–REcoM3 model, concentrations of key organic biomolecules were estimated and integrated into the ECHAM6.3–HAM2.3 aerosol–climate model. Results highlight the influence of marine biological activity and surface winds on PMOA emissions, with reasonably good agreement with observations improving aerosol representation in the southern oceans.
Ziming Ke, Qi Tang, Jean-Christophe Golaz, Xiaohong Liu, and Hailong Wang
Geosci. Model Dev., 18, 4137–4153, https://doi.org/10.5194/gmd-18-4137-2025, https://doi.org/10.5194/gmd-18-4137-2025, 2025
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This study assesses volcanic aerosol representation in E3SM (Energy Exascale Earth System Model), showing that an emission-based approach moderately improves temperature variability and cloud responses compared to a prescribed forcing approach, yet significant bias persists.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev., 18, 4009–4021, https://doi.org/10.5194/gmd-18-4009-2025, https://doi.org/10.5194/gmd-18-4009-2025, 2025
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Philipp Weiss, Ross Herbert, and Philip Stier
Geosci. Model Dev., 18, 3877–3894, https://doi.org/10.5194/gmd-18-3877-2025, https://doi.org/10.5194/gmd-18-3877-2025, 2025
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Aerosols strongly influence Earth's climate as they interact with radiation and clouds. New Earth system models run at resolutions of a few kilometers. To simulate the Earth system with interactive aerosols, we developed a new aerosol module. It represents aerosols as an ensemble of lognormal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of 5 km. It captures key processes like the formation of dust storms in the Sahara.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev., 18, 3799–3817, https://doi.org/10.5194/gmd-18-3799-2025, https://doi.org/10.5194/gmd-18-3799-2025, 2025
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with vital physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for multi-objective optimization of rice irrigation schemes at a large scale.
Carolina A. Bieri, Francina Dominguez, Gonzalo Miguez-Macho, and Ying Fan
Geosci. Model Dev., 18, 3755–3779, https://doi.org/10.5194/gmd-18-3755-2025, https://doi.org/10.5194/gmd-18-3755-2025, 2025
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Access to deep moisture below the Earth's surface is important for vegetation in areas of the Amazon where there is little precipitation for part of the year. Most existing numerical models of the Earth system do not adequately capture where and when deep root water uptake occurs. We address this by adding deep soil layers and a root water uptake feature to an existing model. Out modifications lead to increased dry-month transpiration and improved simulation of the annual transpiration cycle.
Sergi Palomas, Mario C. Acosta, Gladys Utrera, and Etienne Tourigny
Geosci. Model Dev., 18, 3661–3679, https://doi.org/10.5194/gmd-18-3661-2025, https://doi.org/10.5194/gmd-18-3661-2025, 2025
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We present an automatic tool that optimizes resource distribution in coupled climate models, enhancing speed and reducing computational costs without requiring expert knowledge. Users can set energy/time criteria or limit resource usage. Tested on various European Community Earth System Model (EC-Earth) configurations and high-performance computing (HPC) platforms, it achieved up to 34 % faster simulations with fewer resources.
Maria Lucia Ferreira Barbosa, Douglas I. Kelley, Chantelle A. Burton, Igor J. M. Ferreira, Renata Moura da Veiga, Anna Bradley, Paulo Guilherme Molin, and Liana O. Anderson
Geosci. Model Dev., 18, 3533–3557, https://doi.org/10.5194/gmd-18-3533-2025, https://doi.org/10.5194/gmd-18-3533-2025, 2025
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As fire seasons in Brazil become increasingly severe, confidently understanding the factors driving fires is more critical than ever. To address this challenge, we developed FLAME (Fire Landscape Analysis using Maximum Entropy), a new model designed to predict fires and to analyse the spatial influence of both environmental and human factors while accounting for uncertainties. By adapting the model to different regions, we can enhance fire management strategies, making FLAME a powerful tool for protecting landscapes in Brazil and beyond.
Victor Couplet, Marina Martínez Montero, and Michel Crucifix
Geosci. Model Dev., 18, 3081–3129, https://doi.org/10.5194/gmd-18-3081-2025, https://doi.org/10.5194/gmd-18-3081-2025, 2025
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We present SURFER v3.0, a simple climate model designed to estimate the impact of CO2 and CH4 emissions on global temperatures, sea levels, and ocean pH. We added new carbon cycle processes and calibrated the model to observations and results from more complex models, enabling use over timescales ranging from decades to millions of years. SURFER v3.0 is fast, transparent, and easy to use, making it an ideal tool for policy assessments and suitable for educational purposes.
Yong-He Liu and Zong-Liang Yang
Geosci. Model Dev., 18, 3157–3174, https://doi.org/10.5194/gmd-18-3157-2025, https://doi.org/10.5194/gmd-18-3157-2025, 2025
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NMH-CS 3.0 is a C#-based ecohydrological model reconstructed from the WRF-Hydro/Noah-MP model by translating the Fortran code of WRF-Hydro 3.0 and integrating a parallel river routing module. It enables efficient execution on multi-core personal computers. Simulations in the Yellow River basin demonstrate its consistency with WRF-Hydro outputs, providing a reliable alternative to the original Noah-MP model.
Conor T. Doherty, Weile Wang, Hirofumi Hashimoto, and Ian G. Brosnan
Geosci. Model Dev., 18, 3003–3016, https://doi.org/10.5194/gmd-18-3003-2025, https://doi.org/10.5194/gmd-18-3003-2025, 2025
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We present, analyze, and validate a methodology for quantifying uncertainty in gridded meteorological data products produced by spatial interpolation. In a validation case study using daily maximum near-surface air temperature (Tmax), the method works well and produces predictive distributions with closely matching theoretical versus actual coverage levels. Application of the method reveals that the magnitude of uncertainty in interpolated Tmax varies significantly in both space and time.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O'Rourke, and Beth Dingley
Geosci. Model Dev., 18, 2639–2663, https://doi.org/10.5194/gmd-18-2639-2025, https://doi.org/10.5194/gmd-18-2639-2025, 2025
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used variables from Earth system models based on an assessment of data publication and download records from the largest archive of global climate projects.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, https://doi.org/10.5194/gmd-18-2609-2025, 2025
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PaleoSTeHM v1.0 is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo-records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
Geosci. Model Dev., 18, 2587–2608, https://doi.org/10.5194/gmd-18-2587-2025, https://doi.org/10.5194/gmd-18-2587-2025, 2025
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Tropical ocean basins influence each other through multiple pathways and mechanisms, referred to here as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models but have obtained conflicting results. This may be partly due to differences in experiment protocols and partly due to systematic model errors. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 2479–2508, https://doi.org/10.5194/gmd-18-2479-2025, https://doi.org/10.5194/gmd-18-2479-2025, 2025
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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 that 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.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025, https://doi.org/10.5194/gmd-18-2443-2025, 2025
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Improving climate predictions has significant socio-economic impacts. In this study, we develop and apply a new weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. This system is meant to advance our understanding of the ocean's role in climate predictability.
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Our research presents a novel deep learning approach called "TemDeep" for downscaling atmospheric variables at arbitrary time resolutions based on temporal coherence. Results show that our method can accurately recover evolution details superior to other methods, reaching 53.7 % in the restoration rate. Our findings are important for advancing weather forecasting models and enabling more precise and reliable predictions to support disaster preparedness, agriculture, and sustainable development.
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Zhongwang Wei, Qingchen Xu, Fan Bai, Xionghui Xu, Zixin Wei, Wenzong Dong, Hongbin Liang, Nan Wei, Xingjie Lu, Lu Li, Shupeng Zhang, Hua Yuan, Laibo Liu, and Yongjiu Dai
EGUsphere, https://doi.org/10.5194/egusphere-2025-1380, https://doi.org/10.5194/egusphere-2025-1380, 2025
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Land surface models are used for simulating earth's surface interacts with the atmosphere. As models grow more complex and detailed, researchers need better tools to evaluate their performance. OpenBench, a new software system that makes evaluation process more comprehensive and efficient. It stands out by incorporating various factors and working with data at any scale which enabling scientists to incorporate new types of models and measurements as our understanding of Earth’s systems evolves.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Kostas Tsigaridis, Andrew S. Ackerman, Igor Aleinov, Mark A. Chandler, Thomas L. Clune, Christopher M. Colose, Anthony D. Del Genio, Maxwell Kelley, Nancy Y. Kiang, Anthony Leboissetier, Jan P. Perlwitz, Reto A. Ruedy, Gary L. Russell, Linda E. Sohl, Michael J. Way, and Eric T. Wolf
EGUsphere, https://doi.org/10.5194/egusphere-2025-925, https://doi.org/10.5194/egusphere-2025-925, 2025
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We present the second generation of ROCKE-3D, a generalized 3-dimensional model for use in Solar System and exoplanetary simulations of rocky planet climates. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169, https://doi.org/10.5194/egusphere-2025-169, 2025
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Satellites have observed earth's emission of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about the earth and atmosphere. We present a tool that runs alongside global climate models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Maria Vittoria Struglia, Alessandro Anav, Marta Antonelli, Sandro Calmanti, Franco Catalano, Alessandro Dell'Aquila, Emanuela Pichelli, and Giovanna Pisacane
EGUsphere, https://doi.org/10.5194/egusphere-2025-387, https://doi.org/10.5194/egusphere-2025-387, 2025
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We present the results of downscaling global climate projections for the Mediterranean and Italian regions aiming to produce high-resolution climate information for the assessment of climate change signals, focusing on extreme events. A general warming is foreseen by the end of century with a mean precipitation reduction accompanied, over Italian Peninsula, by a strong increase in the intensity of extreme precipitation events, particularly relevant for the high emissions scenario during autumn
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Katherine Grayson, Stephan Thober, Aleksander Lacima-Nadolnik, Ehsan Sharifi, Llorenç Lledó, and Francisco Doblas-Reyes
EGUsphere, https://doi.org/10.5194/egusphere-2025-28, https://doi.org/10.5194/egusphere-2025-28, 2025
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To provide the most accurate climate adaptation information, climate models are being run with finer grid resolution, resulting in larger data output. This paper presents intelligent data reduction algorithms that act on streamed data, a novel way of processing climate data as soon as it is produced. Using these algorithms to calculate statistics, we show that the accuracy provided is well within acceptable bounds while still providing memory savings that bypass unfeasible storage requirements.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
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Short summary
Our study investigates the role of aerosols in the climate of Europe by using a computer model and exploring different aerosol options available in this model as well as different aerosol datasets. Results show that aerosols can have a considerable impact on many aspects of the climate. Aerosols reduce solar radiation and temperature at the surface. Precipitation is not particularly affected in any specific direction. The cloudiness amount change is small. Also, changes in wind pattern are seen.
Our study investigates the role of aerosols in the climate of Europe by using a computer model...
