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
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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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.
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-2022-431, https://doi.org/10.5194/essd-2022-431, 2022
Revised manuscript under review for ESSD
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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 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.
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
Geosci. Model Dev., 15, 3387–3404, https://doi.org/10.5194/gmd-15-3387-2022, https://doi.org/10.5194/gmd-15-3387-2022, 2022
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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
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.
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
Differentiable programming for Earth system modeling
Evaluation of CMIP6 model performances in simulating fire weather spatiotemporal variability on global and regional scales
Data-driven aeolian dust emission scheme for climate modelling evaluated with EMAC 2.55.2
Testing the reconstruction of modelled particulate organic carbon from surface ecosystem components using PlankTOM12 and machine learning
An improved method of the Globally Resolved Energy Balance model by the Bayesian networks
Assessing predicted cirrus ice properties between two deterministic ice formation parameterizations
Various ways of using empirical orthogonal functions for climate model evaluation
C-Coupler3.0: an integrated coupler infrastructure for Earth system modelling
FEOTS v0.0.0: a new offline code for the fast equilibration of tracers in the ocean
Pace v0.2: a Python-based performance-portable atmospheric model
Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water
The sea level simulator v1.0: a model for integration of mean sea level change and sea level extremes into a joint probabilistic framework
Structural k-means (S k-means) and clustering uncertainty evaluation framework (CUEF) for mining climate data
The emergence of the Gulf Stream and interior western boundary as key regions to constrain the future North Atlantic carbon uptake
Evaluating wind profiles in a numerical weather prediction model with Doppler lidar
Evaluation of bias correction methods for a multivariate drought index: case study of the Upper Jhelum Basin
The impact of lateral boundary forcing in the CORDEX-Africa ensemble over southern Africa
Effects of complex terrain on the shortwave radiative balance: a sub-grid-scale parameterization for the GFDL Earth System Model version 4.1
Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project
Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1
Nudging allows direct evaluation of coupled climate models with in situ observations: a case study from the MOSAiC expedition
Importance of ice nucleation and precipitation on climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)
UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model
A New Simplified Parameterization of Secondary Organic Aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
Porting the WAVEWATCH III (v6.07) wave action source terms to GPU
Yeti 1.0: a generalized framework for constructing bottom-up emission inventories from traffic sources at road-link resolutions
The Mixed Layer Depth in the Ocean Model Intercomparison Project (OMIP): Impact of Resolving Mesoscale Eddies
Analysis of systematic biases in tropospheric hydrostatic delay models and construction of a correction model
A new precipitation emulator (PREMU v1.0) for lower-complexity models
Simulating marine neodymium isotope distributions using Nd v1.0 coupled to the ocean component of the FAMOUS–MOSES1 climate model: sensitivities to reversible scavenging efficiency and benthic source distributions
CMIP6 simulations with the compact Earth system model OSCAR v3.1
Application of a satellite-retrieved sheltering parameterization (v1.0) for dust event simulation with WRF-Chem v4.1
The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses
AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics
Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)
ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales
Ocean Modeling with Adaptive REsolution (OMARE; version 1.0) – refactoring the NEMO model (version 4.0.1) with the parallel computing framework of JASMIN – Part 1: Adaptive grid refinement in an idealized double-gyre case
Monthly-scale extended predictions using the atmospheric model coupled with a slab ocean
Developing Spring Wheat in the Noah-MP LSM (v4.4) for Growing Season Dynamics and Responses to Temperature Stress
stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1
Evaluation of native Earth system model output with ESMValTool v2.6.0
WRF–ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer
The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system
LandInG 1.0: A toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources
Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2
Accelerated photosynthesis routine in LPJmL4
Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system
Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, and Niklas Boers
Geosci. Model Dev., 16, 3123–3135, https://doi.org/10.5194/gmd-16-3123-2023, https://doi.org/10.5194/gmd-16-3123-2023, 2023
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Differential programming is a technique that enables the automatic computation of derivatives of the output of models with respect to model parameters. Applying these techniques to Earth system modeling leverages the increasing availability of high-quality data to improve the models themselves. This can be done by either using calibration techniques that use gradient-based optimization or incorporating machine learning methods that can learn previously unresolved influences directly from data.
Carolina Gallo, Jonathan M. Eden, Bastien Dieppois, Igor Drobyshev, Peter Z. Fulé, Jesús San-Miguel-Ayanz, and Matthew Blackett
Geosci. Model Dev., 16, 3103–3122, https://doi.org/10.5194/gmd-16-3103-2023, https://doi.org/10.5194/gmd-16-3103-2023, 2023
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This study conducts the first global evaluation of the latest generation of global climate models to simulate a set of fire weather indicators from the Canadian Fire Weather Index System. Models are shown to perform relatively strongly at the global scale, but they show substantial regional and seasonal differences. The results demonstrate the value of model evaluation and selection in producing reliable fire danger projections, ultimately to support decision-making and forest management.
Klaus Klingmüller and Jos Lelieveld
Geosci. Model Dev., 16, 3013–3028, https://doi.org/10.5194/gmd-16-3013-2023, https://doi.org/10.5194/gmd-16-3013-2023, 2023
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Desert dust has significant impacts on climate, public health, infrastructure and ecosystems. An impact assessment requires numerical predictions, which are challenging because the dust emissions are not well known. We present a novel approach using satellite observations and machine learning to more accurately estimate the emissions and to improve the model simulations.
Anna Denvil-Sommer, Erik T. Buitenhuis, Rainer Kiko, Fabien Lombard, Lionel Guidi, and Corinne Le Quéré
Geosci. Model Dev., 16, 2995–3012, https://doi.org/10.5194/gmd-16-2995-2023, https://doi.org/10.5194/gmd-16-2995-2023, 2023
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Using outputs of global biogeochemical ocean model and machine learning methods, we demonstrate that it will be possible to identify linkages between surface environmental and ecosystem structure and the export of carbon to depth by sinking organic particles using real observations. It will be possible to use this knowledge to improve both our understanding of ecosystem dynamics and of their functional representation within models.
Zhenxia Liu, Zengjie Wang, Jian Wang, Zhengfang Zhang, Dongshuang Li, Zhaoyuan Yu, Linwang Yuan, and Wen Luo
Geosci. Model Dev., 16, 2939–2955, https://doi.org/10.5194/gmd-16-2939-2023, https://doi.org/10.5194/gmd-16-2939-2023, 2023
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This study introduces an improved method of the Globally Resolved Energy Balance (GREB) model by the Bayesian network. The improved method constructs a coarse–fine structure that combines a dynamical model with a statistical model based on employing the GREB model as the global framework and utilizing Bayesian networks as the local optimization. The results show that the improved model has better applicability and stability on a global scale and maintains good robustness on the timescale.
Colin Tully, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 16, 2957–2973, https://doi.org/10.5194/gmd-16-2957-2023, https://doi.org/10.5194/gmd-16-2957-2023, 2023
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A new method to simulate deterministic ice nucleation processes based on the differential activated fraction was evaluated against a cumulative approach. Box model simulations of heterogeneous-only ice nucleation within cirrus suggest that the latter approach likely underpredicts the ice crystal number concentration. Longer simulations with a GCM show that choosing between these two approaches impacts ice nucleation competition within cirrus but leads to small and insignificant climate effects.
Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023, https://doi.org/10.5194/gmd-16-2899-2023, 2023
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A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.
Li Liu, Chao Sun, Xinzhu Yu, Hao Yu, Qingu Jiang, Xingliang Li, Ruizhe Li, Bin Wang, Xueshun Shen, and Guangwen Yang
Geosci. Model Dev., 16, 2833–2850, https://doi.org/10.5194/gmd-16-2833-2023, https://doi.org/10.5194/gmd-16-2833-2023, 2023
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C-Coupler3.0 is an integrated coupler infrastructure with new features, i.e. a series of parallel-optimization technologies, a common halo-exchange library, a common module-integration framework, a common framework for conveniently developing a weakly coupled ensemble data assimilation system, and a common framework for flexibly inputting and outputting fields in parallel. It is able to handle coupling under much finer resolutions (e.g. more than 100 million horizontal grid cells).
Joseph Schoonover, Wilbert Weijer, and Jiaxu Zhang
Geosci. Model Dev., 16, 2795–2809, https://doi.org/10.5194/gmd-16-2795-2023, https://doi.org/10.5194/gmd-16-2795-2023, 2023
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FEOTS aims to enhance the value of data produced by state-of-the-art climate models by providing a framework to diagnose and use ocean transport operators for offline passive tracer simulations. We show that we can capture ocean transport operators from a validated climate model and employ these operators to estimate water mass budgets in an offline regional simulation, using a small fraction of the compute resources required to run a full climate simulation.
Johann Dahm, Eddie Davis, Florian Deconinck, Oliver Elbert, Rhea George, Jeremy McGibbon, Tobias Wicky, Elynn Wu, Christopher Kung, Tal Ben-Nun, Lucas Harris, Linus Groner, and Oliver Fuhrer
Geosci. Model Dev., 16, 2719–2736, https://doi.org/10.5194/gmd-16-2719-2023, https://doi.org/10.5194/gmd-16-2719-2023, 2023
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It is hard for scientists to write code which is efficient on different kinds of supercomputers. Python is popular for its user-friendliness. We converted a Fortran code, simulating Earth's atmosphere, into Python. This new code auto-converts to a faster language for processors or graphic cards. Our code runs 3.5–4 times faster on graphic cards than the original on processors in a specific supercomputer system.
Jan Polcher, Anthony Schrapffer, Eliott Dupont, Lucia Rinchiuso, Xudong Zhou, Olivier Boucher, Emmanuel Mouche, Catherine Ottlé, and Jérôme Servonnat
Geosci. Model Dev., 16, 2583–2606, https://doi.org/10.5194/gmd-16-2583-2023, https://doi.org/10.5194/gmd-16-2583-2023, 2023
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The proposed graphs of hydrological sub-grid elements for atmospheric models allow us to integrate the topographical elements needed in land surface models for a realistic representation of horizontal water and energy transport. The study demonstrates the numerical properties of the automatically built graphs and the simulated water flows.
Magnus Hieronymus
Geosci. Model Dev., 16, 2343–2354, https://doi.org/10.5194/gmd-16-2343-2023, https://doi.org/10.5194/gmd-16-2343-2023, 2023
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A statistical model called the sea level simulator is presented and made freely available. The sea level simulator integrates mean sea level rise and sea level extremes into a joint probabilistic framework that is useful for flood risk estimation. These flood risk estimates are contingent on probabilities given to different emission scenarios and the length of the planning period. The model is also useful for uncertainty quantification and in decision and adaptation problems.
Quang-Van Doan, Toshiyuki Amagasa, Thanh-Ha Pham, Takuto Sato, Fei Chen, and Hiroyuki Kusaka
Geosci. Model Dev., 16, 2215–2233, https://doi.org/10.5194/gmd-16-2215-2023, https://doi.org/10.5194/gmd-16-2215-2023, 2023
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This study proposes (i) the structural k-means (S k-means) algorithm for clustering spatiotemporally structured climate data and (ii) the clustering uncertainty evaluation framework (CUEF) based on the mutual-information concept.
Nadine Goris, Klaus Johannsen, and Jerry Tjiputra
Geosci. Model Dev., 16, 2095–2117, https://doi.org/10.5194/gmd-16-2095-2023, https://doi.org/10.5194/gmd-16-2095-2023, 2023
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Climate projections of a high-CO2 future are highly uncertain. A new study provides a novel approach to identifying key regions that dynamically explain the model uncertainty. To yield an accurate estimate of the future North Atlantic carbon uptake, we find that a correct simulation of the upper- and interior-ocean volume transport at 25–30° N is key. However, results indicate that models rarely perform well for both indicators and point towards inconsistencies within the model ensemble.
Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua
Geosci. Model Dev., 16, 2077–2094, https://doi.org/10.5194/gmd-16-2077-2023, https://doi.org/10.5194/gmd-16-2077-2023, 2023
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We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
Rubina Ansari, Ana Casanueva, Muhammad Usman Liaqat, and Giovanna Grossi
Geosci. Model Dev., 16, 2055–2076, https://doi.org/10.5194/gmd-16-2055-2023, https://doi.org/10.5194/gmd-16-2055-2023, 2023
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Bias correction (BC) has become indispensable to climate model output as a post-processing step to render output more useful for impact assessment studies. The current work presents a comparison of different state-of-the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) for climate model simulations from three initiatives (CMIP6, CORDEX, and CORDEX-CORE) for a multivariate drought index (i.e., standardized precipitation evapotranspiration index).
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.
Enrico Zorzetto, Sergey Malyshev, Nathaniel Chaney, David Paynter, Raymond Menzel, and Elena Shevliakova
Geosci. Model Dev., 16, 1937–1960, https://doi.org/10.5194/gmd-16-1937-2023, https://doi.org/10.5194/gmd-16-1937-2023, 2023
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In this paper we develop a methodology to model the spatial distribution of solar radiation received by land over mountainous terrain. The approach is designed to be used in Earth system models, where coarse grid cells hinder the description of fine-scale land–atmosphere interactions. We adopt a clustering algorithm to partition the land domain into a set of homogeneous sub-grid
tiles, and for each tile we evaluate solar radiation received by land based on terrain properties.
Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev., 16, 1975–1995, https://doi.org/10.5194/gmd-16-1975-2023, https://doi.org/10.5194/gmd-16-1975-2023, 2023
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The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult; however, it is unclear whether TPs exist in global climate models. Here, we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP).
Heather S. Rumbold, Richard J. J. Gilham, and Martin J. Best
Geosci. Model Dev., 16, 1875–1886, https://doi.org/10.5194/gmd-16-1875-2023, https://doi.org/10.5194/gmd-16-1875-2023, 2023
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The Joint UK Land Environment Simulator (JULES) uses a tiled representation of land cover but can only model a single dominant soil type within a grid box; hence there is no representation of sub-grid soil heterogeneity. This paper evaluates a new surface–soil tiling scheme in JULES and demonstrates the impacts of the scheme using several soil tiling approaches. Results show that soil tiling has an impact on the water and energy exchanges due to the way vegetation accesses the soil moisture.
Felix Pithan, Marylou Athanase, Sandro Dahlke, Antonio Sánchez-Benítez, Matthew D. Shupe, Anne Sledd, Jan Streffing, Gunilla Svensson, and Thomas Jung
Geosci. Model Dev., 16, 1857–1873, https://doi.org/10.5194/gmd-16-1857-2023, https://doi.org/10.5194/gmd-16-1857-2023, 2023
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Evaluating climate models usually requires long observational time series, but we present a method that also works for short field campaigns. We compare climate model output to observations from the MOSAiC expedition in the central Arctic Ocean. All models show how the arrival of a warm air mass warms the Arctic in April 2020, but two models do not show the response of snow temperature to the diurnal cycle. One model has too little liquid water and too much ice in clouds during cold days.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
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Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
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Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-42, https://doi.org/10.5194/gmd-2023-42, 2023
Revised manuscript accepted for GMD
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The new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM), based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Olawale James Ikuyajolu, Luke Van Roekel, Steven R. Brus, Erin E. Thomas, Yi Deng, and Sarat Sreepathi
Geosci. Model Dev., 16, 1445–1458, https://doi.org/10.5194/gmd-16-1445-2023, https://doi.org/10.5194/gmd-16-1445-2023, 2023
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Wind-generated waves play an important role in modifying physical processes at the air–sea interface, but they have been traditionally excluded from climate models due to the high computational cost of running spectral wave models for climate simulations. To address this, our work identified and accelerated the computationally intensive section of WAVEWATCH III on GPU using OpenACC. This allows for high-resolution modeling of atmosphere–wave–ocean feedbacks in century-scale climate integrations.
Edward C. Chan, Joana Leitão, Andreas Kerschbaumer, and Timothy M. Butler
Geosci. Model Dev., 16, 1427–1444, https://doi.org/10.5194/gmd-16-1427-2023, https://doi.org/10.5194/gmd-16-1427-2023, 2023
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Yeti is a Handbook Emission Factors for Road Transport-based traffic emission inventory written in the Python 3 scripting language, which adopts a generalized treatment for activity data using traffic information of varying levels of detail introduced in a systematic and consistent manner, with the ability to maximize reusability. Thus, Yeti has been conceived and implemented with a high degree of data and process symmetry, allowing scalable and flexible execution while affording ease of use.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteacino Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
EGUsphere, https://doi.org/10.5194/egusphere-2023-310, https://doi.org/10.5194/egusphere-2023-310, 2023
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The ocean mixed layer is the interface between the ocean interior and the atmosphere, and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve "ocean eddies", which are the largest source of ocean variability and modulate the mixed layer properties. We find that the mixed layer depth is better represented in eddy-rich models, but unfortunately, not uniformly across the globe and not in all models.
Haopeng Fan, Siran Li, Zhongmiao Sun, Guorui Xiao, Xinxing Li, and Xiaogang Liu
Geosci. Model Dev., 16, 1345–1358, https://doi.org/10.5194/gmd-16-1345-2023, https://doi.org/10.5194/gmd-16-1345-2023, 2023
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The traditional tropospheric zenith hydrostatic delay (ZHD) model's bias is usually thought negligible, yet it still reaches 10 mm sometimes and would lead to millimeter-level position errors for space geodetic observations. Therefore, we analyzed the bias’ characteristics and present a grid model to correct the traditional ZHD formula. When verifying the efficiency based on data from the ECMWF (European Centre for Medium-Range Weather Forecasts), ZHD biases were rectified by ~50 %.
Gang Liu, Shushi Peng, Chris Huntingford, and Yi Xi
Geosci. Model Dev., 16, 1277–1296, https://doi.org/10.5194/gmd-16-1277-2023, https://doi.org/10.5194/gmd-16-1277-2023, 2023
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Due to computational limits, lower-complexity models (LCMs) were developed as a complementary tool for accelerating comprehensive Earth system models (ESMs) but still lack a good precipitation emulator for LCMs. Here, we developed a data-calibrated precipitation emulator (PREMU), a computationally effective way to better estimate historical and simulated precipitation by current ESMs. PREMU has potential applications related to land surface processes and their interactions with climate change.
Suzanne Robinson, Ruza F. Ivanovic, Lauren J. Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul J. Valdes
Geosci. Model Dev., 16, 1231–1264, https://doi.org/10.5194/gmd-16-1231-2023, https://doi.org/10.5194/gmd-16-1231-2023, 2023
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We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (Nd v1.0). Nd fluxes from seafloor sediment and incorporation of Nd onto sinking particles represent the major global sources and sinks, respectively. However, model–data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Yann Quilcaille, Thomas Gasser, Philippe Ciais, and Olivier Boucher
Geosci. Model Dev., 16, 1129–1161, https://doi.org/10.5194/gmd-16-1129-2023, https://doi.org/10.5194/gmd-16-1129-2023, 2023
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The model OSCAR is a simple climate model, meaning its representation of the Earth system is simplified but calibrated on models of higher complexity. Here, we diagnose its latest version using a total of 99 experiments in a probabilistic framework and under observational constraints. OSCAR v3.1 shows good agreement with observations, complex Earth system models and emerging properties. Some points for improvements are identified, such as the ocean carbon cycle.
Sandra L. LeGrand, Theodore W. Letcher, Gregory S. Okin, Nicholas P. Webb, Alex R. Gallagher, Saroj Dhital, Taylor S. Hodgdon, Nancy P. Ziegler, and Michelle L. Michaels
Geosci. Model Dev., 16, 1009–1038, https://doi.org/10.5194/gmd-16-1009-2023, https://doi.org/10.5194/gmd-16-1009-2023, 2023
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Ground cover affects dust emissions by reducing wind flow over the immediate soil surface. This study reviews a method for estimating ground cover effects on wind erosion from satellite-detected terrain shadows. We conducted a case study for a US dust event using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Adding the shadow-based method for ground cover effects markedly improved simulated results and may lead to better dust modeling outcomes in vegetated drylands.
Roman Brogli, Christoph Heim, Jonas Mensch, Silje Lund Sørland, and Christoph Schär
Geosci. Model Dev., 16, 907–926, https://doi.org/10.5194/gmd-16-907-2023, https://doi.org/10.5194/gmd-16-907-2023, 2023
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The pseudo-global-warming (PGW) approach is a downscaling methodology that imposes the large-scale GCM-based climate change signal on the boundary conditions of a regional climate simulation. It offers several benefits in comparison to conventional downscaling. We present a detailed description of the methodology, provide companion software to facilitate the preparation of PGW simulations, and present validation and sensitivity studies.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Edmund P. Meredith, Uwe Ulbrich, and Henning W. Rust
Geosci. Model Dev., 16, 851–867, https://doi.org/10.5194/gmd-16-851-2023, https://doi.org/10.5194/gmd-16-851-2023, 2023
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Cell-tracking algorithms allow for the study of properties of a convective cell across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm's criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Yan Zhang, Xuantong Wang, Yuhao Sun, Chenhui Ning, Shiming Xu, Hengbin An, Dehong Tang, Hong Guo, Hao Yang, Ye Pu, Bo Jiang, and Bin Wang
Geosci. Model Dev., 16, 679–704, https://doi.org/10.5194/gmd-16-679-2023, https://doi.org/10.5194/gmd-16-679-2023, 2023
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We construct a new ocean model, OMARE, that can carry out multi-scale ocean simulation with adaptive mesh refinement. OMARE is based on the refactorization of NEMO with a third-party, high-performance piece of middleware. We report the porting process and experiments of an idealized western-boundary current system. The new model simulates turbulent and temporally varying mesoscale and submesoscale processes via adaptive refinement. Related topics and future work with OMARE are also discussed.
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 16, 705–717, https://doi.org/10.5194/gmd-16-705-2023, https://doi.org/10.5194/gmd-16-705-2023, 2023
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To improve the numerical model predictability of monthly extended-range scales, we use the simplified slab ocean model (SOM) to restrict the complicated sea surface temperature (SST) bias from a 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have better performance than the WRF-ROMS, which has a significant impact on the atmosphere. For extreme weather events such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-311, https://doi.org/10.5194/gmd-2022-311, 2023
Revised manuscript accepted for GMD
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Crop models incorporated in earth system models are essential to accurately simulate crop growth processes on Earth’s surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at point-scale; (2) apply dynamic planting/harvest schedules; (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Dagmawi Teklu Asfaw, Michael Bliss Singer, Rafael Rosolem, David MacLeod, Mark Cuthbert, Edisson Quichimbo Miguitama, Manuel F. Rios Gaona, and Katerina Michaelides
Geosci. Model Dev., 16, 557–571, https://doi.org/10.5194/gmd-16-557-2023, https://doi.org/10.5194/gmd-16-557-2023, 2023
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stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.
Markus Köhli, Martin Schrön, Steffen Zacharias, and Ulrich Schmidt
Geosci. Model Dev., 16, 449–477, https://doi.org/10.5194/gmd-16-449-2023, https://doi.org/10.5194/gmd-16-449-2023, 2023
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In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
Xiaohui Zhong, Zhijian Ma, Yichen Yao, Lifei Xu, Yuan Wu, and Zhibin Wang
Geosci. Model Dev., 16, 199–209, https://doi.org/10.5194/gmd-16-199-2023, https://doi.org/10.5194/gmd-16-199-2023, 2023
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More and more researchers use deep learning models to replace physics-based parameterizations to accelerate weather simulations. However, embedding the ML models within the weather models is difficult as they are implemented in different languages. This work proposes a coupling framework to allow ML-based parameterizations to be coupled with the Weather Research and Forecasting (WRF) model. We also demonstrate using the coupler to couple the ML-based radiation schemes with the WRF model.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-307, https://doi.org/10.5194/gmd-2022-307, 2023
Revised manuscript accepted for GMD
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to >100,000 years. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate-carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
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Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-291, https://doi.org/10.5194/gmd-2022-291, 2023
Revised manuscript accepted for GMD
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We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent, so that users can make their own decisions on how to resolve these, should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Ming Yin, Yilun Han, Yong Wang, Wenqi Sun, Jianbo Deng, Daoming Wei, Ying Kong, and Bin Wang
Geosci. Model Dev., 16, 135–156, https://doi.org/10.5194/gmd-16-135-2023, https://doi.org/10.5194/gmd-16-135-2023, 2023
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All global climate models (GCMs) use the grid-averaged surface heat fluxes to drive the atmosphere, and thus their horizontal variations within the grid cell are averaged out. In this regard, a novel scheme considering the variation and partitioning of the surface heat fluxes within the grid cell is developed. The scheme reduces the long-standing rainfall biases on the southern and eastern margins of the Tibetan Plateau. The performance of key variables at the global scale is also evaluated.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
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In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
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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...
