Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-5007-2020
© 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-13-5007-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new bias-correction method for precipitation over complex terrain suitable for different climate states: a case study using WRF (version 3.8.1)
Patricio Velasquez
CORRESPONDING AUTHOR
Climate and Environmental Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Martina Messmer
Climate and Environmental Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
School of Earth Sciences, University of Melbourne, Melbourne, Victoria, Australia
Christoph C. Raible
Climate and Environmental Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Related authors
Emmanuele Russo, Jonathan Buzan, Sebastian Lienert, Guillaume Jouvet, Patricio Velasquez Alvarez, Basil Davis, Patrick Ludwig, Fortunat Joos, and Christoph C. Raible
Clim. Past, 20, 449–465, https://doi.org/10.5194/cp-20-449-2024, https://doi.org/10.5194/cp-20-449-2024, 2024
Short summary
Short summary
We present a series of experiments conducted for the Last Glacial Maximum (~21 ka) over Europe using the regional climate Weather Research and Forecasting model (WRF) at convection-permitting resolutions. The model, with new developments better suited to paleo-studies, agrees well with pollen-based climate reconstructions. This agreement is improved when considering different sources of uncertainty. The effect of convection-permitting resolutions is also assessed.
Patricio Velasquez, Martina Messmer, and Christoph C. Raible
Clim. Past, 18, 1579–1600, https://doi.org/10.5194/cp-18-1579-2022, https://doi.org/10.5194/cp-18-1579-2022, 2022
Short summary
Short summary
We investigate the sensitivity of the glacial Alpine hydro-climate to northern hemispheric and local ice-sheet changes. We perform sensitivity simulations of up to 2 km horizontal resolution over the Alps for glacial periods. The findings demonstrate that northern hemispheric and local ice-sheet topography are important role in regulating the Alpine hydro-climate and permits a better understanding of the Alpine precipitation patterns at glacial times.
Patricio Velasquez, Jed O. Kaplan, Martina Messmer, Patrick Ludwig, and Christoph C. Raible
Clim. Past, 17, 1161–1180, https://doi.org/10.5194/cp-17-1161-2021, https://doi.org/10.5194/cp-17-1161-2021, 2021
Short summary
Short summary
This study assesses the importance of resolution and land–atmosphere feedbacks for European climate. We performed an asynchronously coupled experiment that combined a global climate model (~ 100 km), a regional climate model (18 km), and a dynamic vegetation model (18 km). Modelled climate and land cover agree reasonably well with independent reconstructions based on pollen and other paleoenvironmental proxies. The regional climate is significantly influenced by land cover.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
Short summary
Short summary
The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Martine Collaud Coen, Elisabeth Andrews, Diego Aliaga, Marcos Andrade, Hristo Angelov, Nicolas Bukowiecki, Marina Ealo, Paulo Fialho, Harald Flentje, A. Gannet Hallar, Rakesh Hooda, Ivo Kalapov, Radovan Krejci, Neng-Huei Lin, Angela Marinoni, Jing Ming, Nhat Anh Nguyen, Marco Pandolfi, Véronique Pont, Ludwig Ries, Sergio Rodríguez, Gerhard Schauer, Karine Sellegri, Sangeeta Sharma, Junying Sun, Peter Tunved, Patricio Velasquez, and Dominique Ruffieux
Atmos. Chem. Phys., 18, 12289–12313, https://doi.org/10.5194/acp-18-12289-2018, https://doi.org/10.5194/acp-18-12289-2018, 2018
Short summary
Short summary
High altitude stations are often emphasized as free tropospheric measuring sites but they remain influenced by atmospheric boundary layer. An ABL-TopoIndex is defined from a topography analysis around the stations. This new index allows ranking stations as a function of the ABL influence due to topography or help to choose a new site to sample FT. The ABL-TopoIndex is validated by aerosol optical properties and number concentration measured at 29 high altitude stations of five continents.
Julien G. Anet, Martin Steinbacher, Laura Gallardo, Patricio A. Velásquez Álvarez, Lukas Emmenegger, and Brigitte Buchmann
Atmos. Chem. Phys., 17, 6477–6492, https://doi.org/10.5194/acp-17-6477-2017, https://doi.org/10.5194/acp-17-6477-2017, 2017
Short summary
Short summary
There are less long-term surface ozone measurements on the Southern than on the Northern Hemisphere, which makes it difficult to thoroughly understand global ozone chemistry. We have analyzed a new, 20-year-long ozone dataset measured at 2200 m asl at El Tololo, Chile, and show that the annual cycle of ozone is mainly driven by ozone transport from the stratosphere to the troposphere. As well, we illustrate that the timing of the annual maximum is regressing to earlier in the year.
Evelien J. C. van Dijk, Christoph C. Raible, Michael Sigl, Johann Jungclaus, and Heinz Wanner
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-79, https://doi.org/10.5194/cp-2024-79, 2024
Manuscript not accepted for further review
Short summary
Short summary
The temperature in the past 4000 years consisted of warm and cold periods, initiated by external forcing. But, these periods are not consistent through time and space. We use climate models and reconstructions to study to which extent the periods are reflected in the European climate. We find that on local scales, the chaotic nature of the climate system is larger than the external forcing. This study shows that these periods have to be used very carefully when studying a local site.
Onno Doensen, Martina Messmer, Christoph C. Raible, and Woon Mi Kim
EGUsphere, https://doi.org/10.5194/egusphere-2024-2731, https://doi.org/10.5194/egusphere-2024-2731, 2024
Short summary
Short summary
Extratropical cyclones are crucial systems in the Mediterranean. While extensively studied, their late Holocene variability is poorly understood. Using a climate model spanning 3350-years, we find Mediterranean cyclones show significant multi-decadal variability. Extreme cyclones tend to be more extreme in the central Mediterranean in terms of wind speed. Our work creates a reference baseline to better understand the impact of climate change on Mediterranean cyclones.
Emmanuele Russo, Jonathan Buzan, Sebastian Lienert, Guillaume Jouvet, Patricio Velasquez Alvarez, Basil Davis, Patrick Ludwig, Fortunat Joos, and Christoph C. Raible
Clim. Past, 20, 449–465, https://doi.org/10.5194/cp-20-449-2024, https://doi.org/10.5194/cp-20-449-2024, 2024
Short summary
Short summary
We present a series of experiments conducted for the Last Glacial Maximum (~21 ka) over Europe using the regional climate Weather Research and Forecasting model (WRF) at convection-permitting resolutions. The model, with new developments better suited to paleo-studies, agrees well with pollen-based climate reconstructions. This agreement is improved when considering different sources of uncertainty. The effect of convection-permitting resolutions is also assessed.
Woon Mi Kim, Santos J. González-Rojí, and Christoph C. Raible
Clim. Past, 19, 2511–2533, https://doi.org/10.5194/cp-19-2511-2023, https://doi.org/10.5194/cp-19-2511-2023, 2023
Short summary
Short summary
In this study, we investigate circulation patterns associated with Mediterranean droughts during the last millennium using global climate simulations. Different circulation patterns driven by internal interactions in the climate system contribute to the occurrence of droughts in the Mediterranean. The detected patterns are different between the models, and this difference can be a potential source of uncertainty in model–proxy comparison and future projections of Mediterranean droughts.
Eric Samakinwa, Christoph C. Raible, Ralf Hand, Andrew R. Friedman, and Stefan Brönnimann
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-67, https://doi.org/10.5194/cp-2023-67, 2023
Publication in CP not foreseen
Short summary
Short summary
In this study, we nudged a stand-alone ocean model MPI-OM to proxy-reconstructed SST. Based on these model simulations, we introduce new estimates of the AMOC variations during the period 1450–1780 through a 10-member ensemble simulation with a novel nudging technique. Our approach reaffirms the known mechanisms of AMOC variability and also improves existing knowledge of the interplay between the AMOC and the NAO during the AMOC's weak and strong phases.
Jonathan Robert Buzan, Emmanuele Russo, Woon Mi Kim, and Christoph C. Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-324, https://doi.org/10.5194/egusphere-2023-324, 2023
Preprint archived
Short summary
Short summary
Paleoclimate is used to test climate models to verify that simulations accurately project both future and past climate states. We present fully coupled climate sensitivity simulations of Preindustrial, Last Glacial Maximum, and the Quaternary climate periods. We show distinct climate states derived from non-linear responses to ice sheet heights and orbits. The implication is that as paleo proxy data become more reliable, they may constrain the specific climate states produced by climate models.
Patricio Velasquez, Martina Messmer, and Christoph C. Raible
Clim. Past, 18, 1579–1600, https://doi.org/10.5194/cp-18-1579-2022, https://doi.org/10.5194/cp-18-1579-2022, 2022
Short summary
Short summary
We investigate the sensitivity of the glacial Alpine hydro-climate to northern hemispheric and local ice-sheet changes. We perform sensitivity simulations of up to 2 km horizontal resolution over the Alps for glacial periods. The findings demonstrate that northern hemispheric and local ice-sheet topography are important role in regulating the Alpine hydro-climate and permits a better understanding of the Alpine precipitation patterns at glacial times.
Helen Mackay, Gill Plunkett, Britta J. L. Jensen, Thomas J. Aubry, Christophe Corona, Woon Mi Kim, Matthew Toohey, Michael Sigl, Markus Stoffel, Kevin J. Anchukaitis, Christoph Raible, Matthew S. M. Bolton, Joseph G. Manning, Timothy P. Newfield, Nicola Di Cosmo, Francis Ludlow, Conor Kostick, Zhen Yang, Lisa Coyle McClung, Matthew Amesbury, Alistair Monteath, Paul D. M. Hughes, Pete G. Langdon, Dan Charman, Robert Booth, Kimberley L. Davies, Antony Blundell, and Graeme T. Swindles
Clim. Past, 18, 1475–1508, https://doi.org/10.5194/cp-18-1475-2022, https://doi.org/10.5194/cp-18-1475-2022, 2022
Short summary
Short summary
We assess the climatic and societal impact of the 852/3 CE Alaska Mount Churchill eruption using environmental reconstructions, historical records and climate simulations. The eruption is associated with significant Northern Hemisphere summer cooling, despite having only a moderate sulfate-based climate forcing potential; however, evidence of a widespread societal response is lacking. We discuss the difficulties of confirming volcanic impacts of a single eruption even when it is precisely dated.
Emmanuele Russo, Bijan Fallah, Patrick Ludwig, Melanie Karremann, and Christoph C. Raible
Clim. Past, 18, 895–909, https://doi.org/10.5194/cp-18-895-2022, https://doi.org/10.5194/cp-18-895-2022, 2022
Short summary
Short summary
In this study a set of simulations are performed with the regional climate model COSMO-CLM for Europe, for the mid-Holocene and pre-industrial periods. The main aim is to better understand the drivers of differences between models and pollen-based summer temperatures. Results show that a fundamental role is played by spring soil moisture availability. Additionally, results suggest that model bias is not stationary, and an optimal configuration could not be the best under different forcing.
Santos J. González-Rojí, Martina Messmer, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 15, 2859–2879, https://doi.org/10.5194/gmd-15-2859-2022, https://doi.org/10.5194/gmd-15-2859-2022, 2022
Short summary
Short summary
Different configurations of physics parameterizations of a regional climate model are tested over southern Peru at fine resolution. The most challenging regions compared to observational data are the slopes of the Andes. Model configurations for Europe and East Africa are not perfectly suitable for southern Peru. The experiment with the Stony Brook University microphysics scheme and the Grell–Freitas cumulus parameterization provides the most accurate results over Madre de Dios.
Woon Mi Kim, Richard Blender, Michael Sigl, Martina Messmer, and Christoph C. Raible
Clim. Past, 17, 2031–2053, https://doi.org/10.5194/cp-17-2031-2021, https://doi.org/10.5194/cp-17-2031-2021, 2021
Short summary
Short summary
To understand the natural characteristics and future changes of the global extreme daily precipitation, it is necessary to explore the long-term characteristics of extreme daily precipitation. Here, we used climate simulations to analyze the characteristics and long-term changes of extreme precipitation during the past 3351 years. Our findings indicate that extreme precipitation in the past is associated with internal climate variability and regional surface temperatures.
Patricio Velasquez, Jed O. Kaplan, Martina Messmer, Patrick Ludwig, and Christoph C. Raible
Clim. Past, 17, 1161–1180, https://doi.org/10.5194/cp-17-1161-2021, https://doi.org/10.5194/cp-17-1161-2021, 2021
Short summary
Short summary
This study assesses the importance of resolution and land–atmosphere feedbacks for European climate. We performed an asynchronously coupled experiment that combined a global climate model (~ 100 km), a regional climate model (18 km), and a dynamic vegetation model (18 km). Modelled climate and land cover agree reasonably well with independent reconstructions based on pollen and other paleoenvironmental proxies. The regional climate is significantly influenced by land cover.
Martina Messmer, Santos J. González-Rojí, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 14, 2691–2711, https://doi.org/10.5194/gmd-14-2691-2021, https://doi.org/10.5194/gmd-14-2691-2021, 2021
Short summary
Short summary
Sensitivity experiments with the WRF model are run to find an optimal parameterization setup for precipitation around Mount Kenya at a scale that resolves convection (1 km). Precipitation is compared against many weather stations and gridded observational data sets. Both the temporal correlation of precipitation sums and pattern correlations show that fewer nests lead to a more constrained simulation with higher correlation. The Grell–Freitas cumulus scheme obtains the most accurate results.
Woon Mi Kim and Christoph C. Raible
Clim. Past, 17, 887–911, https://doi.org/10.5194/cp-17-887-2021, https://doi.org/10.5194/cp-17-887-2021, 2021
Short summary
Short summary
The analysis of the dynamics of western central Mediterranean droughts for 850–2099 CE in the Community Earth System Model indicates that past Mediterranean droughts were driven by the internal variability. This internal variability is more important during the initial years of droughts. During the transition years, the longevity of droughts is defined by the land–atmosphere feedbacks. In the future, this land–atmosphere feedbacks are intensified, causing a constant dryness over the region.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021, https://doi.org/10.5194/esd-12-1-2021, 2021
Short summary
Short summary
Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
Short summary
Short summary
The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Paolo Laj, Alessandro Bigi, Clémence Rose, Elisabeth Andrews, Cathrine Lund Myhre, Martine Collaud Coen, Yong Lin, Alfred Wiedensohler, Michael Schulz, John A. Ogren, Markus Fiebig, Jonas Gliß, Augustin Mortier, Marco Pandolfi, Tuukka Petäja, Sang-Woo Kim, Wenche Aas, Jean-Philippe Putaud, Olga Mayol-Bracero, Melita Keywood, Lorenzo Labrador, Pasi Aalto, Erik Ahlberg, Lucas Alados Arboledas, Andrés Alastuey, Marcos Andrade, Begoña Artíñano, Stina Ausmeel, Todor Arsov, Eija Asmi, John Backman, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Sébastien Conil, Cedric Couret, Derek Day, Wan Dayantolis, Anna Degorska, Konstantinos Eleftheriadis, Prodromos Fetfatzis, Olivier Favez, Harald Flentje, Maria I. Gini, Asta Gregorič, Martin Gysel-Beer, A. Gannet Hallar, Jenny Hand, Andras Hoffer, Christoph Hueglin, Rakesh K. Hooda, Antti Hyvärinen, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Jeong Eun Kim, Giorgos Kouvarakis, Irena Kranjc, Radovan Krejci, Markku Kulmala, Casper Labuschagne, Hae-Jung Lee, Heikki Lihavainen, Neng-Huei Lin, Gunter Löschau, Krista Luoma, Angela Marinoni, Sebastiao Martins Dos Santos, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Nhat Anh Nguyen, Jakub Ondracek, Noemi Pérez, Maria Rita Perrone, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Natalia Prats, Anthony Prenni, Fabienne Reisen, Salvatore Romano, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Maik Schütze, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Martin Steinbacher, Junying Sun, Gloria Titos, Barbara Toczko, Thomas Tuch, Pierre Tulet, Peter Tunved, Ville Vakkari, Fernando Velarde, Patricio Velasquez, Paolo Villani, Sterios Vratolis, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Jesus Yus-Diez, Vladimir Zdimal, Paul Zieger, and Nadezda Zikova
Atmos. Meas. Tech., 13, 4353–4392, https://doi.org/10.5194/amt-13-4353-2020, https://doi.org/10.5194/amt-13-4353-2020, 2020
Short summary
Short summary
The paper establishes the fiducial reference of the GAW aerosol network providing the fully characterized value chain to the provision of four climate-relevant aerosol properties from ground-based sites. Data from almost 90 stations worldwide are reported for a reference year, 2017, providing a unique and very robust view of the variability of these variables worldwide. Current gaps in the GAW network are analysed and requirements for the Global Climate Monitoring System are proposed.
Thomas L. Frölicher, Luca Ramseyer, Christoph C. Raible, Keith B. Rodgers, and John Dunne
Biogeosciences, 17, 2061–2083, https://doi.org/10.5194/bg-17-2061-2020, https://doi.org/10.5194/bg-17-2061-2020, 2020
Short summary
Short summary
Climate variations can have profound impacts on marine ecosystems. Here we show that on global scales marine ecosystem drivers such as temperature, pH, O2 and NPP are potentially predictable 3 (at the surface) and more than 10 years (subsurface) in advance. However, there are distinct regional differences in the potential predictability of these drivers. Our study suggests that physical–biogeochemical forecast systems have considerable potential for use in marine resource management.
Peter Stucki, Paul Froidevaux, Marcelo Zamuriano, Francesco Alessandro Isotta, Martina Messmer, and Andrey Martynov
Nat. Hazards Earth Syst. Sci., 20, 35–57, https://doi.org/10.5194/nhess-20-35-2020, https://doi.org/10.5194/nhess-20-35-2020, 2020
Short summary
Short summary
In 1876, 1910, and 2005, Switzerland was impacted by extreme rainfall and floods. All events were linked to a Vb cyclone. We test a range of weather model setups (short spinup and standard physics are best) to understand the sensitivity of atmospheric dynamics. The simulated Vb cyclones are (not) well defined for 2005 and 1910 (1876). To reproduce the events, intense moisture flux from the right direction is needed. Storms that slightly deviate from an ideal path produce erroneous precipitation.
Christoph C. Raible, Martina Messmer, Flavio Lehner, Thomas F. Stocker, and Richard Blender
Clim. Past, 14, 1499–1514, https://doi.org/10.5194/cp-14-1499-2018, https://doi.org/10.5194/cp-14-1499-2018, 2018
Short summary
Short summary
Extratropical cyclones in winter and their characteristics are investigated in depth for the Atlantic European region from 850 to 2100 CE. During the Common Era, cyclone characteristics show pronounced variations mainly caused by internal variability of the coupled climate system. When anthropogenic forcing becomes dominant, a strong increase of extreme cyclone-related precipitation is found due to thermodynamics, though dynamical processes can play an important role during the last millennium.
Martine Collaud Coen, Elisabeth Andrews, Diego Aliaga, Marcos Andrade, Hristo Angelov, Nicolas Bukowiecki, Marina Ealo, Paulo Fialho, Harald Flentje, A. Gannet Hallar, Rakesh Hooda, Ivo Kalapov, Radovan Krejci, Neng-Huei Lin, Angela Marinoni, Jing Ming, Nhat Anh Nguyen, Marco Pandolfi, Véronique Pont, Ludwig Ries, Sergio Rodríguez, Gerhard Schauer, Karine Sellegri, Sangeeta Sharma, Junying Sun, Peter Tunved, Patricio Velasquez, and Dominique Ruffieux
Atmos. Chem. Phys., 18, 12289–12313, https://doi.org/10.5194/acp-18-12289-2018, https://doi.org/10.5194/acp-18-12289-2018, 2018
Short summary
Short summary
High altitude stations are often emphasized as free tropospheric measuring sites but they remain influenced by atmospheric boundary layer. An ABL-TopoIndex is defined from a topography analysis around the stations. This new index allows ranking stations as a function of the ABL influence due to topography or help to choose a new site to sample FT. The ABL-TopoIndex is validated by aerosol optical properties and number concentration measured at 29 high altitude stations of five continents.
Stefan Brönnimann, Jan Rajczak, Erich M. Fischer, Christoph C. Raible, Marco Rohrer, and Christoph Schär
Nat. Hazards Earth Syst. Sci., 18, 2047–2056, https://doi.org/10.5194/nhess-18-2047-2018, https://doi.org/10.5194/nhess-18-2047-2018, 2018
Short summary
Short summary
Heavy precipitation events in Switzerland are expected to become more intense, but the seasonality also changes. Analysing a large set of model simulations, we find that annual maximum rainfall events become less frequent in late summer and more frequent in early summer and early autumn. The seasonality shift is arguably related to summer drying. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events.
Juan José Gómez-Navarro, Christoph C. Raible, Denica Bozhinova, Olivia Martius, Juan Andrés García Valero, and Juan Pedro Montávez
Geosci. Model Dev., 11, 2231–2247, https://doi.org/10.5194/gmd-11-2231-2018, https://doi.org/10.5194/gmd-11-2231-2018, 2018
Short summary
Short summary
We carry out and compare two high-resolution simulations of the Alpine region in the period 1979–2005. We aim to improve the understanding of the local mechanisms leading to extreme events in this complex region. We compare both simulations to precipitation observations to assess the model performance, and attribute major biases to either model or boundary conditions. Further, we develop a new bias correction technique to remove systematic errors in simulated precipitation for impact studies.
PAGES Hydro2k Consortium
Clim. Past, 13, 1851–1900, https://doi.org/10.5194/cp-13-1851-2017, https://doi.org/10.5194/cp-13-1851-2017, 2017
Short summary
Short summary
Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited due to a paucity of modern instrumental observations. We review how proxy records of past climate and climate model simulations can be used in tandem to understand hydroclimate variability over the last 2000 years and how these tools can also inform risk assessments of future hydroclimatic extremes.
Martina Messmer, Juan José Gómez-Navarro, and Christoph C. Raible
Earth Syst. Dynam., 8, 477–493, https://doi.org/10.5194/esd-8-477-2017, https://doi.org/10.5194/esd-8-477-2017, 2017
Short summary
Short summary
Low-pressure systems of type Vb may trigger heavy rainfall events over central Europe. This study aims at analysing the relative role of their moisture sources. For this, a set of sensitivity experiments encompassing changes in soil moisture and Atlantic Ocean and Mediterranean Sea SSTs are carried out with WRF. The latter moisture source stands out as the most relevant one. Furthermore, the regions most affected by Vb events in the future might be shifted from the Alps to the Balkan Peninsula.
Juan José Gómez-Navarro, Eduardo Zorita, Christoph C. Raible, and Raphael Neukom
Clim. Past, 13, 629–648, https://doi.org/10.5194/cp-13-629-2017, https://doi.org/10.5194/cp-13-629-2017, 2017
Short summary
Short summary
This contribution aims at assessing to what extent the analogue method, a classic technique used in other branches of meteorology and climatology, can be used to perform gridded reconstructions of annual temperature based on the limited information from available but un-calibrated proxies spread across different locations of the world. We conclude that it is indeed possible, albeit with certain limitations that render the method comparable to more classic techniques.
Julien G. Anet, Martin Steinbacher, Laura Gallardo, Patricio A. Velásquez Álvarez, Lukas Emmenegger, and Brigitte Buchmann
Atmos. Chem. Phys., 17, 6477–6492, https://doi.org/10.5194/acp-17-6477-2017, https://doi.org/10.5194/acp-17-6477-2017, 2017
Short summary
Short summary
There are less long-term surface ozone measurements on the Southern than on the Northern Hemisphere, which makes it difficult to thoroughly understand global ozone chemistry. We have analyzed a new, 20-year-long ozone dataset measured at 2200 m asl at El Tololo, Chile, and show that the annual cycle of ozone is mainly driven by ozone transport from the stratosphere to the troposphere. As well, we illustrate that the timing of the annual maximum is regressing to earlier in the year.
Stefan Brönnimann, Abdul Malik, Alexander Stickler, Martin Wegmann, Christoph C. Raible, Stefan Muthers, Julien Anet, Eugene Rozanov, and Werner Schmutz
Atmos. Chem. Phys., 16, 15529–15543, https://doi.org/10.5194/acp-16-15529-2016, https://doi.org/10.5194/acp-16-15529-2016, 2016
Short summary
Short summary
The Quasi-Biennial Oscillation is a wind oscillation in the equatorial stratosphere. Effects on climate have been found, which is relevant for seasonal forecasts. However, up to now only relatively short records were available, and even within these the climate imprints were intermittent. Here we analyze a 108-year long reconstruction as well as four 405-year long simulations. We confirm most of the claimed QBO effects on climate, but they are small, which explains apparently variable effects.
Chantal Camenisch, Kathrin M. Keller, Melanie Salvisberg, Benjamin Amann, Martin Bauch, Sandro Blumer, Rudolf Brázdil, Stefan Brönnimann, Ulf Büntgen, Bruce M. S. Campbell, Laura Fernández-Donado, Dominik Fleitmann, Rüdiger Glaser, Fidel González-Rouco, Martin Grosjean, Richard C. Hoffmann, Heli Huhtamaa, Fortunat Joos, Andrea Kiss, Oldřich Kotyza, Flavio Lehner, Jürg Luterbacher, Nicolas Maughan, Raphael Neukom, Theresa Novy, Kathleen Pribyl, Christoph C. Raible, Dirk Riemann, Maximilian Schuh, Philip Slavin, Johannes P. Werner, and Oliver Wetter
Clim. Past, 12, 2107–2126, https://doi.org/10.5194/cp-12-2107-2016, https://doi.org/10.5194/cp-12-2107-2016, 2016
Short summary
Short summary
Throughout the last millennium, several cold periods occurred which affected humanity. Here, we investigate an exceptionally cold decade during the 15th century. The cold conditions challenged the food production and led to increasing food prices and a famine in parts of Europe. In contrast to periods such as the “Year Without Summer” after the eruption of Tambora, these extreme climatic conditions seem to have occurred by chance and in relation to the internal variability of the climate system.
Stefan Muthers, Christoph C. Raible, Eugene Rozanov, and Thomas F. Stocker
Earth Syst. Dynam., 7, 877–892, https://doi.org/10.5194/esd-7-877-2016, https://doi.org/10.5194/esd-7-877-2016, 2016
Short summary
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is an important oceanic circulation system which transports large amounts of heat from the tropics to the north. This circulation is strengthened when less solar irradiance reaches the Earth, e.g. due to reduced solar activity or geoengineering techniques. In climate models, however, this response is overestimated when chemistry–climate interactions and the following shift in the atmospheric circulation systems are not considered.
Niklaus Merz, Andreas Born, Christoph C. Raible, and Thomas F. Stocker
Clim. Past, 12, 2011–2031, https://doi.org/10.5194/cp-12-2011-2016, https://doi.org/10.5194/cp-12-2011-2016, 2016
Short summary
Short summary
The last (Eemian) interglacial is studied with a global climate model focusing on Greenland and the adjacent high latitudes. A set of model experiments demonstrates the crucial role of changes in sea ice and sea surface temperatures for the magnitude of Eemian atmospheric warming. Greenland temperatures are found highly sensitive to sea ice changes in the Nordic Seas but rather insensitive to changes in the Labrador Sea. This behavior has important implications for Greenland ice core signals.
Amaelle Landais, Valérie Masson-Delmotte, Emilie Capron, Petra M. Langebroek, Pepijn Bakker, Emma J. Stone, Niklaus Merz, Christoph C. Raible, Hubertus Fischer, Anaïs Orsi, Frédéric Prié, Bo Vinther, and Dorthe Dahl-Jensen
Clim. Past, 12, 1933–1948, https://doi.org/10.5194/cp-12-1933-2016, https://doi.org/10.5194/cp-12-1933-2016, 2016
Short summary
Short summary
The last lnterglacial (LIG; 116 000 to 129 000 years before present) surface temperature at the upstream Greenland NEEM deposition site is estimated to be warmer by +7 to +11 °C compared to the preindustrial period. We show that under such warm temperatures, melting of snow probably led to a significant surface melting. There is a paradox between the extent of the Greenland ice sheet during the LIG and the strong warming during this period that models cannot solve.
J. J. Gómez-Navarro, C. C. Raible, and S. Dierer
Geosci. Model Dev., 8, 3349–3363, https://doi.org/10.5194/gmd-8-3349-2015, https://doi.org/10.5194/gmd-8-3349-2015, 2015
S. Muthers, F. Arfeuille, C. C. Raible, and E. Rozanov
Atmos. Chem. Phys., 15, 11461–11476, https://doi.org/10.5194/acp-15-11461-2015, https://doi.org/10.5194/acp-15-11461-2015, 2015
Short summary
Short summary
After volcanic eruptions different radiative and chemical processes take place in the stratosphere which perturb the ozone layer and cause pronounced dynamical changes. In idealized chemistry-climate model simulations the importance of these processes and the modulating role of the climate state is analysed. The chemical effect strongly differs between a preindustrial and present-day climate, but the effect on the dynamics is weak. Radiative processes dominate the dynamics in all climate states.
M. Messmer, J. J. Gómez-Navarro, and C. C. Raible
Earth Syst. Dynam., 6, 541–553, https://doi.org/10.5194/esd-6-541-2015, https://doi.org/10.5194/esd-6-541-2015, 2015
J. J. Gómez-Navarro, O. Bothe, S. Wagner, E. Zorita, J. P. Werner, J. Luterbacher, C. C. Raible, and J. P Montávez
Clim. Past, 11, 1077–1095, https://doi.org/10.5194/cp-11-1077-2015, https://doi.org/10.5194/cp-11-1077-2015, 2015
F. Lehner, F. Joos, C. C. Raible, J. Mignot, A. Born, K. M. Keller, and T. F. Stocker
Earth Syst. Dynam., 6, 411–434, https://doi.org/10.5194/esd-6-411-2015, https://doi.org/10.5194/esd-6-411-2015, 2015
Short summary
Short summary
We present the first last-millennium simulation with the Community Earth System Model (CESM) including an interactive carbon cycle in both ocean and land component. Volcanic eruptions emerge as the strongest forcing factor for the preindustrial climate and carbon cycle. We estimate the climate-carbon-cycle feedback in CESM to be at the lower bounds of empirical estimates (1.3ppm/°C). The time of emergence for interannual global land and ocean carbon uptake rates are 1947 and 1877, respectively.
D. Zanchettin, O. Bothe, F. Lehner, P. Ortega, C. C. Raible, and D. Swingedouw
Clim. Past, 11, 939–958, https://doi.org/10.5194/cp-11-939-2015, https://doi.org/10.5194/cp-11-939-2015, 2015
Short summary
Short summary
A discrepancy exists between reconstructed and simulated Pacific North American pattern (PNA) features during the early 19th century. Pseudo-reconstructions demonstrate that the available PNA reconstruction is potentially skillful but also potentially affected by a number of sources of uncertainty and deficiencies especially at multidecadal and centennial timescales. Simulations and reconstructions can be reconciled by attributing the reconstructed PNA features to internal variability.
S. Muthers, J. G. Anet, A. Stenke, C. C. Raible, E. Rozanov, S. Brönnimann, T. Peter, F. X. Arfeuille, A. I. Shapiro, J. Beer, F. Steinhilber, Y. Brugnara, and W. Schmutz
Geosci. Model Dev., 7, 2157–2179, https://doi.org/10.5194/gmd-7-2157-2014, https://doi.org/10.5194/gmd-7-2157-2014, 2014
K. M. Keller, F. Joos, and C. C. Raible
Biogeosciences, 11, 3647–3659, https://doi.org/10.5194/bg-11-3647-2014, https://doi.org/10.5194/bg-11-3647-2014, 2014
N. Merz, A. Born, C. C. Raible, H. Fischer, and T. F. Stocker
Clim. Past, 10, 1221–1238, https://doi.org/10.5194/cp-10-1221-2014, https://doi.org/10.5194/cp-10-1221-2014, 2014
J. G. Anet, S. Muthers, E. V. Rozanov, C. C. Raible, A. Stenke, A. I. Shapiro, S. Brönnimann, F. Arfeuille, Y. Brugnara, J. Beer, F. Steinhilber, W. Schmutz, and T. Peter
Clim. Past, 10, 921–938, https://doi.org/10.5194/cp-10-921-2014, https://doi.org/10.5194/cp-10-921-2014, 2014
C. C. Raible, F. Lehner, J. F. González-Rouco, and L. Fernández-Donado
Clim. Past, 10, 537–550, https://doi.org/10.5194/cp-10-537-2014, https://doi.org/10.5194/cp-10-537-2014, 2014
J. G. Anet, S. Muthers, E. Rozanov, C. C. Raible, T. Peter, A. Stenke, A. I. Shapiro, J. Beer, F. Steinhilber, S. Brönnimann, F. Arfeuille, Y. Brugnara, and W. Schmutz
Atmos. Chem. Phys., 13, 10951–10967, https://doi.org/10.5194/acp-13-10951-2013, https://doi.org/10.5194/acp-13-10951-2013, 2013
N. Merz, C. C. Raible, H. Fischer, V. Varma, M. Prange, and T. F. Stocker
Clim. Past, 9, 2433–2450, https://doi.org/10.5194/cp-9-2433-2013, https://doi.org/10.5194/cp-9-2433-2013, 2013
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
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
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
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
ROCKE-3D 2.0: An updated general circulation model for simulating the climates of rocky planets
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
COSP-RTTOV-1.0: Flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design
Impact of spatial resolution on CMIP6-driven Mediterranean climate simulations: a focus on precipitation distribution over Italy
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7
Statistical summaries for streamed data from climate simulations: One-pass algorithms (v0.6.2)
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and
the hydrologic cycle, Nature, 419, 228–232, https://doi.org/10.1038/nature01092, 2002. a
Amengual, A., Homar, V., Romero, R., Alonso, S., and Ramis, C.: A statistical
adjustment of regional climate model outputs to local scales: Application
to Platja de Palma, Spain, J. Climate, 25, 939–957,
https://doi.org/10.1175/JCLI-D-10-05024.1, 2011. a
Andréasson, J., Bergström, S., Carlsson, B., Graham, L. P., and
Lindström, G.: Hydrological change – climate change impact
simulations for Sweden, Ambio, 33, 228–234,
https://doi.org/10.1579/0044-7447-33.4.228, 2004. a
Auer, I., Böhm, R., and Schöner, W.: Austrian long-term climate
1767–2000, Osterreichische Beiträge zu Meteorologie und
Geophysik, 25, 147, ISSN 1016-6254, 2001. a
Ban, N., Schmidli, J., and Schär, C.: Evaluation of the
convection-resolving regional climate modeling approach in decade-long
simulations, J. Geophys. Res.-Atmos., 119, 7889–7907,
https://doi.org/10.1002/2014JD021478, 2014. a, b, c, d
Bartlein, P. J., Harrison, S. P., Brewer, S., Connor, S., Davis, B. A. S.,
Gajewski, K., Guiot, J., Harrison-Prentice, T. I., Henderson, A., Peyron, O.,
Prentice, I. C., Scholze, M., Seppä, H., Shuman, B., Sugita, S.,
Thompson, R. S., Viau, A. E., Williams, J., and Wu, H.: Pollen-based
continental climate reconstructions at 6 and 21 ka: a global synthesis,
Clim. Dynam., 37, 775–802, https://doi.org/10.1007/s00382-010-0904-1, 2011. a
Becker, P., Seguinot, J., Jouvet, G., and Funk, M.: Last Glacial Maximum precipitation pattern in the Alps inferred from glacier modelling, Geogr. Helv., 71, 173–187, https://doi.org/10.5194/gh-71-173-2016, 2016. a
Bennett, J. C., Grose, M. R., Corney, S. P., White, C. J., Holz, G. K.,
Katzfey, J. J., Post, D. A., and Bindoff, N. L.: Performance of an empirical
bias-correction of a high-resolution climate dataset, Int. J. Climatol., 34, 2189–2204, https://doi.org/10.1002/joc.3830, 2014. a
Berg, P., Feldmann, H., and Panitz, H. J.: Bias correction of high resolution
regional climate model data, J. Hydrol., 448-449, 80–92,
https://doi.org/10.1016/j.jhydrol.2012.04.026, 2012. a, b
Berthou, S., Kendon, E. J., Chan, S. C., Ban, N., Leutwyler, D., Schär, C.,
and Fosser, G.: Pan-European climate at convection-permitting scale: a
model intercomparison study, Clim. Dynam., 55, 35–59,
https://doi.org/10.1007/s00382-018-4114-6, 2018. a
Boer, G. J.: Climate change and the regulation of the surface moisture and
energy budgets, Clim. Dynam., 8, 225–239, https://doi.org/10.1007/BF00198617,
1993. a
Burke, A., Kageyama, M., Latombe, G., Fasel, M., Vrac, M., Ramstein, G., and
James, P. M. A.: Risky business: The impact of climate and climate
variability on human population dynamics in Western Europe during the
Last Glacial Maximum, Quaternary Sci. Rev., 164, 217–229,
https://doi.org/10.1016/j.quascirev.2017.04.001, 2017. a, b
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias correction of GCM
precipitation by quantile mapping: How well do methods preserve changes in
quantiles and extremes?, J. Climate, 28, 6938–6959,
https://doi.org/10.1175/JCLI-D-14-00754.1, 2015. a
Carril, A. F., Menéndez, C. G., Remedio, A. R. C., Robledo, F.,
Sörensson, A., Tencer, B., Boulanger, J.-P., de Castro, M., Jacob, D.,
Le Treut, H., Li, L. Z. X., Penalba, O., Pfeifer, S., Rusticucci, M., Salio,
P., Samuelsson, P., Sanchez, E., and Zaninelli, P.: Performance of a
multi-RCM ensemble for south eastern South America, Clim. Dynam.,
39, 2747–2768, https://doi.org/10.1007/s00382-012-1573-z, 2012. a
Casanueva, A., Kotlarski, S., Herrera, S., Fernández, J., Gutiérrez,
J. M., Boberg, F., Colette, A., Christensen, O. B., Goergen, K., Jacob, D.,
Keuler, K., Nikulin, G., Teichmann, C., and Vautard, R.: Daily precipitation
statistics in a EURO-CORDEX RCM ensemble: Added value of raw and
bias-corrected high-resolution simulations, Clim. Dynam., 47, 719–737,
https://doi.org/10.1007/s00382-015-2865-x, 2016. a, b, c
Chen, H., Xu, C.-Y., and Guo, S.: Comparison and evaluation of multiple GCMs,
statistical downscaling and hydrological models in the study of climate
change impacts on runoff, J. Hydrol., 434–435, 36–45,
https://doi.org/10.1016/j.jhydrol.2012.02.040, 2012. a
Chen, J., Brissette, F. P., Chaumont, D., and Braun, M.: Finding appropriate
bias correction methods in downscaling precipitation for hydrologic impact
studies over North America, Water Resour. Res., 49, 4187–4205,
https://doi.org/10.1002/wrcr.20331, 2013. a
Chen, W., Zhu, D., Ciais, P., Huang, C., Viovy, N., and Kageyama, M.: Response
of vegetation cover to CO2 and climate changes between Last Glacial
Maximum and pre-industrial period in a dynamic global vegetation model,
Quaternary Sci. Rev., 218, 293–305,
https://doi.org/10.1016/j.quascirev.2019.06.003, 2019. a
Clark, P. U., Dyke, A. S., Shakun, J. D., Carlson, A. E., Clark, J., Wohlfarth,
B., Mitrovica, J. X., Hostetler, S. W., and McCabe, A. M.: The Last
Glacial Maximum, Science, 325, 710–714, https://doi.org/10.1126/science.1172873,
2009. a
Ehlers, J., Gibbard, P., and Hughes, P.: Quaternary glaciations-extent and
chronology: a closer look, 15, Elsevier, Amsterdam, the Netherlands, 2011. a
Fang, G. H., Yang, J., Chen, Y. N., and Zammit, C.: Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China, Hydrol. Earth Syst. Sci., 19, 2547–2559, https://doi.org/10.5194/hess-19-2547-2015, 2015. a, b, c
Felder, G., Gómez-Navarro, J. J., Zischg, A. P., Raible, C. C.,
Röthlisberger, V., Bozhinova, D., Martius, O., and Weingartner, R.: From
global circulation to local flood loss: Coupling models across the scales,
Sci. Total Environ., 635, 1225–1239,
https://doi.org/10.1016/j.scitotenv.2018.04.170, 2018. a
Finney, D. L., Marsham, J. H., Jackson, L. S., Kendon, E. J., Rowell, D. P.,
Boorman, P. M., Keane, R. J., Stratton, R. A., and Senior, C. A.:
Implications of improved representation of convection for the East Africa
water budget using a convection-permitting model, J. Climate, 32,
2109–2129, https://doi.org/10.1175/JCLI-D-18-0387.1, 2019. a
Florineth, D. and Schlüchter, C.: Alpine Evidence for Atmospheric
Circulation Patterns in Europe during the Last Glacial Maximum,
Quaternary Res., 54, 295–308, https://doi.org/10.1006/qres.2000.2169, 2000. a
Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Linking climate change
modelling to impacts studies: Recent advances in downscaling techniques for
hydrological modelling, Int. J. Climatol., 27, 1547–1578,
https://doi.org/10.1002/joc.1556, 2007a. a
Fowler, H. J., Ekström, M., Blenkinsop, S., and Smith, A. P.: Estimating
change in extreme European precipitation using a multimodel ensemble,
J. Geophys. Res.-Atmos., 112, D18 104,
https://doi.org/10.1029/2007JD008619, 2007b. a, b, c
Frei, C., Christensen, J. H., Déqué, M., Jacob, D., Jones, R. G., and
Vidale, P. L.: Daily precipitation statistics in regional climate models:
Evaluation and intercomparison for the European Alps, J. Geophys. Res.-Atmos., 108, 4124, https://doi.org/10.1029/2002JD002287, 2003. a
Fu, Q.: An accurate parameterization of the solar radiative properties of
cirrus clouds for climate models, J. Climate, 9, 2058–2082,
https://doi.org/10.1175/1520-0442(1996)009<2058:AAPOTS>2.0.CO;2, 1996. a
Ganopolski, A. and Calov, R.: The role of orbital forcing, carbon dioxide and regolith in 100 kyr glacial cycles, Clim. Past, 7, 1415–1425, https://doi.org/10.5194/cp-7-1415-2011, 2011. a
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C.,
Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M.,
Worley, P. H., Yang, Z.-L., and Zhang, M.: The Community Climate System
Model Version 4, J. Climate, 24, 4973–4991,
https://doi.org/10.1175/2011JCLI4083.1, 2011. a, b
Gianotti, R. L., Zhang, D., and Eltahir, E. A. B.: Assessment of the regional
climate model version 3 over the maritime continent using different cumulus
parameterization and land surface schemes, J. Climate, 25, 638–656,
https://doi.org/10.1175/JCLI-D-11-00025.1, 2011. a
Giorgi, F., Torma, C., Coppola, E., Ban, N., Schär, C., and Somot, S.:
Enhanced summer convective rainfall at Alpine high elevations in response
to climate warming, Nat. Geosci., 9, 584–589, https://doi.org/10.1038/ngeo2761,
2016. a, b
Gómez-Navarro, J. J., Raible, C. C., Bozhinova, D., Martius, O., García Valero, J. A., and Montávez, J. P.: A new region-aware bias-correction method for simulated precipitation in areas of complex orography, Geosci. Model Dev., 11, 2231–2247, https://doi.org/10.5194/gmd-11-2231-2018, 2018. a, b, c, d, e, f, g
Güttler, I., Stepanov, I., Branković, Č., Nikulin, G., and Jones,
C.: Impact of horizontal resolution on precipitation in complex orography
simulated by the regional climate model RCA3, Mon. Weather Rev., 143,
3610–3627, https://doi.org/10.1175/MWR-D-14-00302.1, 2015. a
Haslinger, K., Anders, I., and Hofstätter, M.: Regional climate modelling
over complex terrain: An evaluation study of COSMO-CLM hindcast model
runs for the greater Alpine region, Clim. Dynam., 40, 511–529,
https://doi.org/10.1007/s00382-012-1452-7, 2013. a
Hay, L. E., Wilby, R. L., and Leavesley, G. H.: A Comparison of delta change
and downscaled GCM scenarios for three mountainous basins in the United
States, J. Am. Water Resour. As., 36, 387–397,
https://doi.org/10.1111/j.1752-1688.2000.tb04276.x, 2000. a
Hofer, D., Raible, C. C., Merz, N., Dehnert, A., and Kuhlemann, J.: Simulated
winter circulation types in the North Atlantic and European region for
preindustrial and glacial conditions: Glacial circulation types,
Geophys. Res. Lett., 39, L15805, https://doi.org/10.1029/2012GL052296,
2012b. a, b, c, d, e, f
Hui, P., Tang, J., Wang, S., Wu, J., Niu, X., and Kang, Y.: Impact of
resolution on regional climate modeling in the source region of Yellow
River with complex terrain using RegCM3, Theor. Appl.
Climatol., 125, 365–380, https://doi.org/10.1007/s00704-015-1514-y, 2016. a
Isotta, F. A., Frei, C., Weilguni, V., Perčec Tadić, M.,
Lassègues, P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G.,
Ratto, S. M., Munari, M., Micheletti, S., Bonati, V., Lussana, C., Ronchi,
C., Panettieri, E., Marigo, G., and Vertačnik, G.: The climate of daily
precipitation in the Alps: Development and analysis of a high-resolution
grid dataset from pan-Alpine rain-gauge data, Int. J. Climatol., 34, 1657–1675, https://doi.org/10.1002/joc.3794, 2014. a, b, c, d, e, f, g, h, i, j, k, l
Ivanov, M. A., Luterbacher, J., and Kotlarski, S.: Climate model biases and
modification of the climate change signal by intensity-dependent bias
correction, J. Climate, 31, 6591–6610,
https://doi.org/10.1175/JCLI-D-17-0765.1, 2018. a
Jerez, S., Montavez, J. P., Jimenez-Guerrero, P., Gomez-Navarro, J. J.,
Lorente-Plazas, R., and Zorita, E.: A multi-physics ensemble of present-day
climate regional simulations over the Iberian Peninsula, Clim. Dynam., 40, 3023–3046, https://doi.org/10.1007/s00382-012-1539-1, 2013. a
Jouvet, G. and Huss, M.: Future retreat of Great Aletsch Glacier, J. Glaciol., 65, 869–872, https://doi.org/10.1017/jog.2019.52, 2019. a, b, c
Jouvet, G., Seguinot, J., Ivy-Ochs, S., and Funk, M.: Modelling the diversion
of erratic boulders by the Valais Glacier during the last glacial
maximum, J. Glaciol., 63, 487–498, https://doi.org/10.1017/jog.2017.7, 2017. a, b, c
Kageyama, M., Harrison, S. P., Kapsch, M.-L., Löfverström, M., Lora, J. M., Mikolajewicz, U., Sherriff-Tadano, S., Vadsaria, T., Abe-Ouchi, A., Bouttes, N., Chandan, D., LeGrande, A. N., Lhardy, F., Lohmann, G., Morozova, P. A., Ohgaito, R., Peltier, W. R., Quiquet, A., Roche, D. M., Shi, X., Schmittner, A., Tierney, J. E., and Volodin, E.: The PMIP4-CMIP6 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3-CMIP5 simulations, Clim. Past Discuss., https://doi.org/10.5194/cp-2019-169, in review, 2020. a
Kaplan, J. O., Pfeiffer, M., Kolen, J. C. A., and Davis, B. A. S.: Large scale
anthropogenic reduction of forest cover in Last Glacial Maximum
Europe, PLoS One, 11, e0166 726, https://doi.org/10.1371/journal.pone.0166726, 2016. a, b
Kendon, E. J., Ban, N., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan,
S. C., Evans, J. P., Fosser, G., and Wilkinson, J. M.: Do
convection-permitting regional climate models improve projections of future
precipitation change?, B. Am. Meteorol. Soc., 98,
79–93, https://doi.org/10.1175/BAMS-D-15-0004.1, 2017. a
Knist, S., Goergen, K., and Simmer, C.: Evaluation and projected changes of
precipitation statistics in convection-permitting WRF climate simulations
over Central Europe, Clim. Dynam., 55, 325–341, https://doi.org/10.1007/s00382-018-4147-x,
2018. a
Lambeck, K., Rouby, H., Purcell, A., Sun, Y., and Sambridge, M.: Sea level and
global ice volumes from the Last Glacial Maximum to the Holocene,
P. Natl. Acad. Sci. USA, 111, 15 296–15 303,
https://doi.org/10.1073/pnas.1411762111, 2014. a
Leung, L. R., Mearns, L. O., Giorgi, F., and Wilby, R. L.: Regional climate
research, B. Am. Meteorol. Soc., 84, 89–95,
https://doi.org/10.1175/BAMS-84-1-89, 2003. a
Liu, Z., Wang, Y., Gallimore, R., Notaro, M., and Prentice, I. C.: On the cause
of abrupt vegetation collapse in North Africa during the Holocene:
Climate variability vs. vegetation feedback, Geophys. Res. Lett.,
33, L22709, https://doi.org/10.1029/2006GL028062, 2006. a
Liu, Z., Ballantyne, A. P., Poulter, B., Anderegg, W. R. L., Li, W., Bastos,
A., and Ciais, P.: Precipitation thresholds regulate net carbon exchange at
the continental scale, Nat. Commun., 9, 3596,
https://doi.org/10.1038/s41467-018-05948-1, 2018. a
Ludwig, P., Schaffernicht, E. J., Shao, Y., and Pinto, J. G.: Regional
atmospheric circulation over Europe during the Last Glacial Maximum
and its links to precipitation, J. Geophys. Res.-Atmos.,
121, 2130–2145, https://doi.org/10.1002/2015JD024444, 2016. a
Ludwig, P., Pinto, J. G., Raible, C. C., and Shao, Y.: Impacts of surface
boundary conditions on regional climate model simulations of European
climate during the Last Glacial Maximum, Geophys. Res. Lett.,
44, 5086–5095, https://doi.org/10.1002/2017GL073622, 2017. a
Luetscher, M., Boch, R., Sodemann, H., Spötl, C., Cheng, H., Edwards,
R. L., Frisia, S., Hof, F., and Müller, W.: North Atlantic storm track
changes during the Last Glacial Maximum recorded by Alpine
speleothems, Nat. Commun., 6, 6344, https://doi.org/10.1038/ncomms7344, 2015. a
Maraun, D.: Bias correction, quantile mapping, and downscaling: Revisiting
the inflation issue, J. Climate, 26, 2137–2143,
https://doi.org/10.1175/JCLI-D-12-00821.1, 2013. a, b, c
Maraun, D.: Bias correcting climate change simulations - a critical review,
Curr. Clim. Change Rep., 2, 211–220, https://doi.org/10.1007/s40641-016-0050-x, 2016. a, b
Maraun, D. and Widmann, M.: The representation of location by a regional climate model in complex terrain, Hydrol. Earth Syst. Sci., 19, 3449–3456, https://doi.org/10.5194/hess-19-3449-2015, 2015. a
Maraun, D. and Widmann, M.: Cross-validation of bias-corrected climate simulations is misleading, Hydrol. Earth Syst. Sci., 22, 4867–4873, https://doi.org/10.5194/hess-22-4867-2018, 2018a. a, b
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J.,
Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema,
V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and
Thiele-Eich, I.: Precipitation downscaling under climate change: Recent
developments to bridge the gap between dynamical models and the end user,
Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009RG000314, 2010. a, b
Maraun, D., Shepherd, T. G., Widmann, M., Zappa, G., Walton, D., Gutiérrez,
J. M., Hagemann, S., Richter, I., Soares, P. M. M., Hall, A., and Mearns,
L. O.: Towards process-informed bias correction of climate change
simulations, Nat. Clim. Change, 7, 764–773, https://doi.org/10.1038/nclimate3418,
2017. a, b, c, d
Mayewski, P. A., Rohling, E. E., Stager, J. C., Karlén, W., Maasch, K. A.,
Meeker, L. D., Meyerson, E. A., Gasse, F., Kreveld, S. v., Holmgren, K.,
Lee-Thorp, J., Rosqvist, G., Rack, F., Staubwasser, M., Schneider, R. R., and
Steig, E. J.: Holocene climate variability, Quaternary Res., 62,
243–255, https://doi.org/10.1016/j.yqres.2004.07.001, 2004. a
Menéndez, C. G., de Castro, M., Boulanger, J.-P.,
D'Onofrio, A., Sanchez, E., Sörensson, A. A., Blazquez,
J., Elizalde, A., Jacob, D., Le Treut, H., Li, Z. X., Núñez, M. N.,
Pessacg, N., Pfeiffer, S., Rojas, M., Rolla, A., Samuelsson, P., Solman,
S. A., and Teichmann, C.: Downscaling extreme month-long anomalies in
southern South America, Climatic Change, 98, 379–403,
https://doi.org/10.1007/s10584-009-9739-3, 2010. a
Merz, N., Raible, C. C., Fischer, H., Varma, V., Prange, M., and Stocker, T. F.: Greenland accumulation and its connection to the large-scale atmospheric circulation in ERA-Interim and paleoclimate simulations, Clim. Past, 9, 2433–2450, https://doi.org/10.5194/cp-9-2433-2013, 2013. a
Merz, N., Born, A., Raible, C. C., Fischer, H., and Stocker, T. F.: Dependence of Eemian Greenland temperature reconstructions on the ice sheet topography, Clim. Past, 10, 1221–1238, https://doi.org/10.5194/cp-10-1221-2014, 2014a. a
Merz, N., Gfeller, G., Born, A., Raible, C. C., Stocker, T. F., and Fischer,
H.: Influence of ice sheet topography on Greenland precipitation during the
Eemian interglacial, J. Geophys. Res.-Atmos., 119,
10,749–10,768, https://doi.org/10.1002/2014JD021940, 2014b. a
Merz, N., Raible, C. C., and Woollings, T.: North Atlantic Eddy-Driven
jet in interglacial and glacial winter climates, J. Climate, 28,
3977–3997, https://doi.org/10.1175/JCLI-D-14-00525.1, 2015. a
Messmer, M., Gómez-Navarro, J. J., and Raible, C. C.: Sensitivity experiments on the response of Vb cyclones to sea surface temperature and soil moisture changes, Earth Syst. Dynam., 8, 477–493, https://doi.org/10.5194/esd-8-477-2017, 2017. a
MeteoSwiss: Documentation of MeteoSwiss gridded data product, daily
precipitation: RhiresD, available at:
http://www.meteoschweiz.admin.ch/content/dam/meteoswiss/de/service-und-publikationen/produkt/raeumliche-daten-niederschlag/doc/ProdDoc_RhiresD.pdf (last access: 12 October 2020),
2013. a, b, c, d
Mitchell, D., Davini, P., Harvey, B., Massey, N., Haustein, K., Woollings, T.,
Jones, R., Otto, F., Guillod, B., Sparrow, S., Wallom, D., and Allen, M.:
Assessing mid-latitude dynamics in extreme event attribution systems, Clim. Dynam., 48, 3889–3901, https://doi.org/10.1007/s00382-016-3308-z, 2017. a
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van
Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A.,
Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer,
R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next
generation of scenarios for climate change research and assessment, Nature,
463, 747–756, https://doi.org/10.1038/nature08823, 2010. a
Murphy, J.: An evaluation of statistical and dynamical techniques for
downscaling local climate, J. Climate, 12, 2256–2284,
https://doi.org/10.1175/1520-0442(1999)012<2256:AEOSAD>2.0.CO;2, 1999. a, b, c
Neale, R. B., Richter, J. H., Conley, A. J., Park, S., Lauritzen, P. H.,
Gettelman, A., Rasch, P. J., and Vavrus, J.: Description of the NCAR
community atmosphere model (CAM4), National Center for Atmospheric Research
Tech. Rep. NCAR/TN+ STR, available at: http://www.cesm.ucar.edu/models/ccsm4.0/cam/docs/description/cam4_desc.pdf (last access: 12 October 2020), 2010. a
Nešpor, V. and Sevruk, B.: Estimation of wind-induced error of rainfall
gauge measurements using a numerical simulation, J. Atmos. Ocean. Tech., 16, 450–464,
https://doi.org/10.1175/1520-0426(1999)016<0450:EOWIEO>2.0.CO;2, 1999. a
Oleson, W., Lawrence, M., Bonan, B., Flanner, G., Kluzek, E., Lawrence, J.,
Levis, S., Swenson, C., Thornton, E., Dai, A., Decker, M., Dickinson, R.,
Feddema, J., Heald, L., Hoffman, F., Lamarque, J.-F., Mahowald, N., Niu,
G.-Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A.,
Stockli, R., Wang, A., Yang, Z.-L., Zeng, X., and Zeng, X.: Technical
description of version 4.0 of the community land model (CLM), NCAR
Technical Note NCAR/TN-478+STR, National Center for Atmospheric
Research, National Center for Atmospheric Research, Boulder, CO, ISSN 2153-2397, available at: http://www.cesm.ucar.edu/models/cesm1.0/clm/CLM4_Tech_Note.pdf (last access: 12 October 2020), 2010. a
Otto-Bliesner, B. L., Brady, E. C., Clauzet, G., Tomas, R., Levis, S., and
Kothavala, Z.: Last Glacial Maximum and Holocene Climate in CCSM3,
J. Climate, 19, 2526–2544, https://doi.org/10.1175/JCLI3748.1, 2006. a
Peltier, W. R. and Fairbanks, R. G.: Global glacial ice volume and Last
Glacial Maximum duration from an extended Barbados sea level record,
Quaternary Sci. Rev., 25, 3322–3337,
https://doi.org/10.1016/j.quascirev.2006.04.010, 2006. a
Piani, C., Haerter, J. O., and Coppola, E.: Statistical bias correction for
daily precipitation in regional climate models over Europe, Theor.
Appl. Climatol., 99, 187–192, https://doi.org/10.1007/s00704-009-0134-9,
2010a. a
Piani, C., Weedon, G. P., Best, M., Gomes, S. M., Viterbo, P., Hagemann, S.,
and Haerter, J. O.: Statistical bias correction of global simulated daily
precipitation and temperature for the application of hydrological models,
J. Hydrol., 395, 199–215, https://doi.org/10.1016/j.jhydrol.2010.10.024,
2010b. a
Pinto, J. G. and Ludwig, P.: Extratropical cyclones over the North Atlantic and western Europe during the Last Glacial Maximum and implications for proxy interpretation, Clim. Past, 16, 611–626, https://doi.org/10.5194/cp-16-611-2020, 2020. a
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., Lipzig, N. P. M. v., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475,
2015. a
Raible, C. C., Stocker, T. F., Yoshimori, M., Renold, M., Beyerle, U., Casty,
C., and Luterbacher, J.: Northern hemispheric trends of pressure indices and
atmospheric circulation patterns in observations, reconstructions, and
coupled GCM simulations, J. Climate, 18, 3968–3982,
https://doi.org/10.1175/JCLI3511.1, 2005. a
Raible, C. C., Lehner, F., González-Rouco, J. F., and Fernández-Donado, L.: Changing correlation structures of the Northern Hemisphere atmospheric circulation from 1000 to 2100 AD, Clim. Past, 10, 537–550, https://doi.org/10.5194/cp-10-537-2014, 2014. a
Raible, C. C., Brönnimann, S., Auchmann, R., Brohan, P., Frölicher,
T. L., Graf, H.-F., Jones, P., Luterbacher, J., Muthers, S., Neukom, R.,
Robock, A., Self, S., Sudrajat, A., Timmreck, C., and Wegmann, M.: Tambora
1815 as a test case for high impact volcanic eruptions: Earth system
effects, Wiley Interdiscip. Rev. Clim. Change, 7, 569–589,
https://doi.org/10.1002/wcc.407, 2016. a
Rajczak, J. and Schär, C.: Projections of future precipitation extremes
over Europe: A multimodel assessment of climate simulations, J. Geophys. Res.-Atmos., 122, 10 773–10 800,
https://doi.org/10.1002/2017JD027176, 2017. a
Rajczak, J., Kotlarski, S., and Schär, C.: Does quantile mapping of
simulated precipitation correct for biases in transition probabilities and
spell lengths?, J. Climate, 29, 1605–1615,
https://doi.org/10.1175/JCLI-D-15-0162.1, 2016. a, b
Richter, D.: Ergebnisse methodischer untersuchungen zur korrektur des
systematischen messfehlers des hellmann-niederschlagsmessers,
Deutscher Wetterdienst, Offenbach, 1995. a
Rougier, J., Sexton, D. M. H., Murphy, J. M., and Stainforth, D.: Analyzing the
climate sensitivity of the HadSM3 climate model using ensembles from
different but related experiments, J. Climate, 22, 3540–3557,
https://doi.org/10.1175/2008JCLI2533.1, 2009. a
RStudio Team: RStudio: Integrated Development Environment for R,
RStudio, Inc., Boston, MA, available at: http://www.rstudio.com/ (last access: 12 October 2020), 2015. a
Schmidli, J., Schmutz, C., Frei, C., Wanner, H., and Schär, C.: Mesoscale
precipitation variability in the region of the European Alps during the
20th century, Int. J. Climatol., 22, 1049–1074,
https://doi.org/10.1002/joc.769, 2002. a
Schmidli, J., Frei, C., and Vidale, P. L.: Downscaling from GCM
precipitation: A benchmark for dynamical and statistical downscaling
methods, Int. J. Climatol., 26, 679–689, https://doi.org/10.1002/joc.1287,
2006. a
Schulzweida, U.: CDO User Guide (Version 1.9.6), Zenodo,
https://doi.org/10.5281/zenodo.2558193, 2019. a, b
Seguinot, J., Khroulev, C., Rogozhina, I., Stroeven, A. P., and Zhang, Q.: The effect of climate forcing on numerical simulations of the Cordilleran ice sheet at the Last Glacial Maximum, The Cryosphere, 8, 1087–1103, https://doi.org/10.5194/tc-8-1087-2014, 2014. a, b, c
Seguinot, J., Ivy-Ochs, S., Jouvet, G., Huss, M., Funk, M., and Preusser, F.: Modelling last glacial cycle ice dynamics in the Alps, The Cryosphere, 12, 3265–3285, https://doi.org/10.5194/tc-12-3265-2018, 2018. a
Sevruk, B.: Systematischer Niederschlagsmessfehler in der Schweiz, Der Niederschlag in der Schweiz. Beiträge zur Geologie der Schweiz – Hydrologie, 31, 65–75, 1985. a
Shepard, D. S.: Computer mapping: The SYMAP interpolation algorithm, in:
Spatial Statistics and Models, Theory and Decision Library, pp.
133–145, Springer, Dordrecht, https://doi.org/10.1007/978-94-017-3048-8_7, 1984. a
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric
model for weather research and forecasting applications, J.
Comput. Physics, 227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037,
2008. a, b
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 2, available at: https://www2.mmm.ucar.edu/wrf/users/index.html (last access: 12 October 2020), National center for atmospheric research, Boulder, CO, USA, 2005. a
Solman, S. A., Nuñez, M. N., and Cabré, M. F.: Regional climate change
experiments over southern South America. I: Present climate, Clim. Dynam., 30, 533–552, https://doi.org/10.1007/s00382-007-0304-3, 2008. a
Stocker, T., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A.,
Xia, Y., Bex, V., and Midgley, P., eds.: Climate change 2013: The physical
science basis. Contribution of working group I to the fifth assessment
report of IPCC the Intergovernmental Panel on Climate Change,
Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA,
https://doi.org/10.1017/CBO9781107415324, 2013. a, b
Su, F., Duan, X., Chen, D., Hao, Z., and Cuo, L.: Evaluation of the global
climate models in the CMIP5 over the Tibetan Plateau, J. Climate, 26, 3187–3208, https://doi.org/10.1175/JCLI-D-12-00321.1, 2012. a
Sun, F., Roderick, M. L., Lim, W. H., and Farquhar, G. D.: Hydroclimatic
projections for the Murray-Darling Basin based on an ensemble derived
from Intergovernmental Panel on Climate Change AR4 climate models,
Water Resour. Res., 47, W00G02, https://doi.org/10.1029/2010WR009829, 2011. a, b
Teutschbein, C. and Seibert, J.: Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions?, Hydrol. Earth Syst. Sci., 17, 5061–5077, https://doi.org/10.5194/hess-17-5061-2013, 2013. a, b, c
Themessl, M. J., Gobiet, A., and Leuprecht, A.: Empirical-statistical
downscaling and error correction of daily precipitation from regional climate
models, Int. J. Climatol., 31, 1530–1544,
https://doi.org/10.1002/joc.2168, 2011. a, b
Themessl, M. J., Gobiet, A., and Heinrich, G.: Empirical-statistical
downscaling and error correction of regional climate models and its impact on
the climate change signal, Climatic Change, 112, 449–468,
https://doi.org/10.1007/s10584-011-0224-4, 2012. a, b
UCAR/NCAR/CISL/TDD: The NCAR Command Language (Version 6.6.2)
[Software], https://doi.org/10.5065/D6WD3XH5, 2019. a, b
Ungersböck, M., Auer, I., Rubel, F., Schöner, W., and Skomorowski, P.:
Zur Korrektur des systematischen Fehlers bei der Niederschlagsmessung:
Anwendung des Verfahrens für die ÖKLIM Karten, 5, 2001. a
Velasquez, P., Messmer, M., and Raible, C. C.: Code and Dataset,
Zenodo, https://doi.org/10.5281/zenodo.4009101, 2019. a, b
Wang, Z., Wen, X., Lei, X., Tan, Q., Fang, G., and Zhang, X.: Effects of
different statistical distribution and threshold criteria in extreme
precipitation modelling over global land areas, Int. J. Climatol., 40, 1838–1850, https://doi.org/10.1002/joc.6305, 2020. a
Warrach-Sagi, K., Schwitalla, T., Wulfmeyer, V., and Bauer, H.-S.: Evaluation
of a climate simulation in Europe based on the WRF–NOAH
model system: Precipitation in Germany, Clim. Dynam., 41, 755–774,
https://doi.org/10.1007/s00382-013-1727-7, 2013.
a
Wilcke, R. A. I., Mendlik, T., and Gobiet, A.: Multi-variable error correction
of regional climate models, Climatic Change, 120, 871–887,
https://doi.org/10.1007/s10584-013-0845-x, 2013. a
Wilks, D. S.: Statistical methods in the atmospheric sciences, Academic Press, 2011. a
Wren, C. D. and Burke, A.: Habitat suitability and the genetic structure of
human populations during the Last Glacial Maximum (LGM) in Western
Europe, PLoS One, 14, e0217 996, https://doi.org/10.1371/journal.pone.0217996, 2019. a, b
Wu, H., Guiot, J., Brewer, S., and Guo, Z.: Climatic changes in Eurasia and
Africa at the last glacial maximum and mid-Holocene: reconstruction from
pollen data using inverse vegetation modelling, Clim. Dynam., 29,
211–229, https://doi.org/10.1007/s00382-007-0231-3, 2007. a
Xu, C.-y.: Modelling the effects of climate change on water resources in
central sweden, Water Resources Management, 14, 177–189,
https://doi.org/10.1023/A:1026502114663, 2000. a
Xu, C.-y., Widén, E., and Halldin, S.: Modelling hydrological consequences
of climate change – Progress and challenges, Advances in
Atmospheric Sciences, 22, 789–797, https://doi.org/10.1007/BF02918679, 2005. a
Yang, B., Qian, Y., Lin, G., Leung, L. R., Rasch, P. J., Zhang, G. J.,
McFarlane, S. A., Zhao, C., Zhang, Y., Wang, H., Wang, M., and Liu, X.:
Uncertainty quantification and parameter tuning in the CAM5
Zhang-McFarlane convection scheme and impact of improved convection on
the global circulation and climate, J. Geophys. Res.-Atmos., 118, 395–415, https://doi.org/10.1029/2012JD018213, 2013. a
Yang, W., Andréasson, J., Graham, L. P., Olsson, J., Rosberg, J., and
Wetterhall, F.: Distribution-based scaling to improve usability of regional
climate model projections for hydrological climate change impacts studies,
Hydrology Research, 41, 211–229, https://doi.org/10.2166/nh.2010.004, 2010. a
Yokoyama, Y., Lambeck, K., De Deckker, P., Johnston, P., and Fifield, L. K.:
Timing of the Last Glacial Maximum from observed sea-level minima,
Nature, 406, 713–716, https://doi.org/10.1038/35021035, 2000. a
Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to the
parameterization of cumulus convection in the Canadian climate centre
general circulation model, Atmosphere-Ocean, 33, 407–446,
https://doi.org/10.1080/07055900.1995.9649539, 1995. a
Zhao, Y., Liu, Y., Guo, Z., Fang, K., Li, Q., and Cao, X.: Abrupt vegetation
shifts caused by gradual climate changes in central Asia during the
Holocene, Science China Earth Sciences, 60, 1317–1327,
https://doi.org/10.1007/s11430-017-9047-7, 2017. a
Short summary
This work presents a new bias-correction method for precipitation that considers orographic characteristics, which can be used in studies where the latter strongly changes. The three-step correction method consists of a separation into orographic features, correction of low-intensity precipitation, and application of empirical quantile mapping. Seasonal bias induced by the global climate model is fully corrected. Rigorous cross-validations illustrate the method's applicability and robustness.
This work presents a new bias-correction method for precipitation that considers orographic...