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.
Methods for assessment of models
| 
26 Oct 2020
Methods for assessment of models |
| 26 Oct 2020
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 Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-1197, https://doi.org/10.5194/egusphere-2023-1197, 2023
Short summary
Short summary
We present a series of experiments conducted for the Last Glacial Maximum (~21000 years ago) over Europe using the regional climate Weather Research and Forecasting model (WRF) at convection-permitting resolutions. The model, with new developments better suitable for paleo studies, agrees well with pollen-based climate reconstructions. This agreement is improved when considering different sources of uncertainty. The added value of convection-permitting resolutions is also demonstrated.
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.
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
Preprint under review for CP
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.
Emmanuele Russo, Jonathan Buzan, Sebastian Lienert, Guillaume Jouvet, Patricio Velasquez Alvarez, Basil Davis, Patrick Ludwig, Fortunat Joos, and Christoph Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-1197, https://doi.org/10.5194/egusphere-2023-1197, 2023
Short summary
Short summary
We present a series of experiments conducted for the Last Glacial Maximum (~21000 years ago) over Europe using the regional climate Weather Research and Forecasting model (WRF) at convection-permitting resolutions. The model, with new developments better suitable for paleo studies, agrees well with pollen-based climate reconstructions. This agreement is improved when considering different sources of uncertainty. The added value of convection-permitting resolutions is also demonstrated.
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.
Woon Mi Kim, Santos J. González-Rojí, and Christoph C. Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-119, https://doi.org/10.5194/egusphere-2023-119, 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 uncertainties in model-proxy comparison and future projections of Mediterranean droughts.
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
A diffusion-based kernel density estimator (diffKDE, version 1) with optimal bandwidth approximation for the analysis of data in geoscience and ecological research
Monte Carlo drift correction – quantifying the drift uncertainty of global climate models
Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1
Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0
Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands
URock 2023a: an open-source GIS-based wind model for complex urban settings
DASH: a MATLAB toolbox for paleoclimate data assimilation
Comparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)
All aboard! Earth system investigations with the CH2O-CHOO TRAIN v1.0
The Canadian Atmospheric Model version 5 (CanAM5.0.3)
The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis
Assimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)
Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability
Simulated stable water isotopes during the mid-Holocene and pre-industrial periods using AWI-ESM-2.1-wiso
Rainbows and climate change: a tutorial on climate model diagnostics and parameterization
ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)
MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region
Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications
IceTFT v1.0.0: interpretable long-term prediction of Arctic sea ice extent with deep learning
Earth system modeling on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON 2.6.6-rc
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1
Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 model
The Regional Aerosol Model Intercomparison Project (RAMIP)
DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise
TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change
Recalibration of a three-dimensional water quality model with a newly developed autocalibration toolkit (EFDC-ACT v1.0.0): how much improvement will be achieved with a wider hydrological variability?
Description and evaluation of the JULES-ES set-up for ISIMIP2b
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses
Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2
Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM
Modeling river water temperature with limiting forcing data: Air2stream v1.0.0, machine learning and multiple regression
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
Resolving the mesoscale at reduced computational cost with FESOM 2.5: efficient modeling approaches applied to the Southern Ocean
Modeling and evaluating the effects of irrigation on land-atmosphere interaction in South-West Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies
A new simplified parameterization of secondary organic aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
Deep learning for stochastic precipitation generation – deep SPG v1.0
Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stress
Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0
The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
SMLFire1.0: a stochastic machine learning (SML) model for wildfire activity in the western United States
LandInG 1.0: a toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources
Conservation of heat and mass in P-SKRIPS version 1: the coupled atmosphere–ice–ocean model of the Ross Sea
Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53
Implementation of a machine-learned gas optics parameterization in the ECMWF Integrated Forecasting System: RRTMGP-NN 2.0
Differentiable programming for Earth system modeling
Maria-Theresia Pelz, Markus Schartau, Christopher J. Somes, Vanessa Lampe, and Thomas Slawig
Geosci. Model Dev., 16, 6609–6634, https://doi.org/10.5194/gmd-16-6609-2023, https://doi.org/10.5194/gmd-16-6609-2023, 2023
Short summary
Short summary
Kernel density estimators (KDE) approximate the probability density of a data set without the assumption of an underlying distribution. We used the solution of the diffusion equation, and a new approximation of the optimal smoothing parameter build on two pilot estimation steps, to construct such a KDE best suited for typical characteristics of geoscientific data. The resulting KDE is insensitive to noise and well resolves multimodal data structures as well as boundary-close data.
Benjamin S. Grandey, Zhi Yang Koh, Dhrubajyoti Samanta, Benjamin P. Horton, Justin Dauwels, and Lock Yue Chew
Geosci. Model Dev., 16, 6593–6608, https://doi.org/10.5194/gmd-16-6593-2023, https://doi.org/10.5194/gmd-16-6593-2023, 2023
Short summary
Short summary
Global climate models are susceptible to spurious trends known as drift. Fortunately, drift can be corrected when analysing data produced by models. To explore the uncertainty associated with drift correction, we develop a new method: Monte Carlo drift correction. For historical simulations of thermosteric sea level rise, drift uncertainty is relatively large. When analysing data susceptible to drift, researchers should consider drift uncertainty.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, https://doi.org/10.5194/gmd-16-6553-2023, 2023
Short summary
Short summary
We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, and Po-Lun Ma
Geosci. Model Dev., 16, 6355–6376, https://doi.org/10.5194/gmd-16-6355-2023, https://doi.org/10.5194/gmd-16-6355-2023, 2023
Short summary
Short summary
To assess the ability of Earth system model (ESM) predictions, we developed a tool called ESMAC Diags to understand how aerosols, clouds, and aerosol–cloud interactions are represented in ESMs. This paper describes its version 2 functionality. We compared the model predictions with measurements taken by planes, ships, satellites, and ground instruments over four regions across the world. Results show that this new tool can help identify model problems and guide future development of ESMs.
Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, and Bin Wang
Geosci. Model Dev., 16, 6285–6308, https://doi.org/10.5194/gmd-16-6285-2023, https://doi.org/10.5194/gmd-16-6285-2023, 2023
Short summary
Short summary
In this paper we propose a new common, flexible, and efficient parallel I/O framework for earth system modeling based on C-Coupler2.0. CIOFC1.0 can handle data I/O in parallel and provides a configuration file format that enables users to conveniently change the I/O configurations. It can automatically make grid and time interpolation, output data with an aperiodic time series, and accelerate data I/O when the field size is large.
Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima
Geosci. Model Dev., 16, 6211–6245, https://doi.org/10.5194/gmd-16-6211-2023, https://doi.org/10.5194/gmd-16-6211-2023, 2023
Short summary
Short summary
A particle-based cloud model was developed for meter- to submeter-scale resolution in cloud simulations. Our new cloud model's computational performance is superior to a bin method and comparable to a two-moment bulk method. A highlight of this study is the 2 m resolution shallow cloud simulations over an area covering ∼10 km2. This model allows for studying turbulence and cloud physics at spatial scales that overlap with those covered by direct numerical simulations and field studies.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
Geosci. Model Dev., 16, 5755–5782, https://doi.org/10.5194/gmd-16-5755-2023, https://doi.org/10.5194/gmd-16-5755-2023, 2023
Short summary
Short summary
The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
Jérémy Bernard, Fredrik Lindberg, and Sandro Oswald
Geosci. Model Dev., 16, 5703–5727, https://doi.org/10.5194/gmd-16-5703-2023, https://doi.org/10.5194/gmd-16-5703-2023, 2023
Short summary
Short summary
The UMEP plug-in integrated in the free QGIS software can now calculate the spatial variation of the wind speed within urban settings. This paper shows that the new wind model, URock, generally fits observations well and highlights the main needed improvements. According to this work, pedestrian wind fields and outdoor thermal comfort can now simply be estimated by any QGIS user (researchers, students, and practitioners).
Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, and Kevin J. Anchukaitis
Geosci. Model Dev., 16, 5653–5683, https://doi.org/10.5194/gmd-16-5653-2023, https://doi.org/10.5194/gmd-16-5653-2023, 2023
Short summary
Short summary
Paleoclimate data assimilation is a useful method that allows researchers to combine climate models with natural archives of past climates. However, it can be difficult to implement in practice. To facilitate this method, we present DASH, a MATLAB toolbox. The toolbox provides routines that implement common steps of paleoclimate data assimilation, and it can be used to implement assimilations for a wide variety of time periods, spatial regions, data networks, and analytical algorithms.
Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen
Geosci. Model Dev., 16, 5539–5559, https://doi.org/10.5194/gmd-16-5539-2023, https://doi.org/10.5194/gmd-16-5539-2023, 2023
Short summary
Short summary
Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Tyler Kukla, Daniel E. Ibarra, Kimberly V. Lau, and Jeremy K. C. Rugenstein
Geosci. Model Dev., 16, 5515–5538, https://doi.org/10.5194/gmd-16-5515-2023, https://doi.org/10.5194/gmd-16-5515-2023, 2023
Short summary
Short summary
The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth system.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
Short summary
Short summary
The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399, https://doi.org/10.5194/gmd-16-5383-2023, https://doi.org/10.5194/gmd-16-5383-2023, 2023
Short summary
Short summary
Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Young-Chan Noh, Yonghan Choi, Hyo-Jong Song, Kevin Raeder, Joo-Hong Kim, and Youngchae Kwon
Geosci. Model Dev., 16, 5365–5382, https://doi.org/10.5194/gmd-16-5365-2023, https://doi.org/10.5194/gmd-16-5365-2023, 2023
Short summary
Short summary
This is the first attempt to assimilate the observations of microwave temperature sounders into the global climate forecast model in which the satellite observations have not been assimilated in the past. To do this, preprocessing schemes are developed to make the satellite observations suitable to be assimilated. In the assimilation experiments, the model analysis is significantly improved by assimilating the observations of microwave temperature sounders.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
Short summary
Short summary
Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
Short summary
Short summary
We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
Short summary
Short summary
A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866, https://doi.org/10.5194/gmd-16-4853-2023, https://doi.org/10.5194/gmd-16-4853-2023, 2023
Short summary
Short summary
ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, https://doi.org/10.5194/gmd-16-4811-2023, 2023
Short summary
Short summary
Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747, https://doi.org/10.5194/gmd-16-4715-2023, https://doi.org/10.5194/gmd-16-4715-2023, 2023
Short summary
Short summary
Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
Geosci. Model Dev., 16, 4677–4697, https://doi.org/10.5194/gmd-16-4677-2023, https://doi.org/10.5194/gmd-16-4677-2023, 2023
Short summary
Short summary
To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
EGUsphere, https://doi.org/10.5194/egusphere-2023-1476, https://doi.org/10.5194/egusphere-2023-1476, 2023
Short summary
Short summary
We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere-ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 59 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023, https://doi.org/10.5194/gmd-16-4581-2023, 2023
Short summary
Short summary
The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Yi-Chi Wang, Wan-Ling Tseng, Yu-Luen Chen, Shih-Yu Lee, Huang-Hsiung Hsu, and Hsin-Chien Liang
Geosci. Model Dev., 16, 4599–4616, https://doi.org/10.5194/gmd-16-4599-2023, https://doi.org/10.5194/gmd-16-4599-2023, 2023
Short summary
Short summary
This study focuses on evaluating the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the El Niño–Southern Oscillation (ENSO), a significant tropical climate pattern with global impacts. Our findings reveal that TaiESM1 effectively captures several characteristics of ENSO, such as its seasonal variation and remote teleconnections. Its pronounced ENSO strength bias is also thoroughly investigated, aiming to gain insights to improve climate model performance.
Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik
Geosci. Model Dev., 16, 4501–4519, https://doi.org/10.5194/gmd-16-4501-2023, https://doi.org/10.5194/gmd-16-4501-2023, 2023
Short summary
Short summary
How can we create better climate models? We tackle this by proposing a data-driven successor to the existing approach for capturing key temporal trends in climate models. We combine probability, allowing us to represent uncertainty, with machine learning, a technique to learn relationships from data which are undiscoverable to humans. Our model is often superior to existing baselines when tested in a simple atmospheric simulation.
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, https://doi.org/10.5194/gmd-16-4451-2023, 2023
Short summary
Short summary
Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366, https://doi.org/10.5194/gmd-16-4331-2023, https://doi.org/10.5194/gmd-16-4331-2023, 2023
Short summary
Short summary
This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
Short summary
Short summary
Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Chen Zhang and Tianyu Fu
Geosci. Model Dev., 16, 4315–4329, https://doi.org/10.5194/gmd-16-4315-2023, https://doi.org/10.5194/gmd-16-4315-2023, 2023
Short summary
Short summary
A new automatic calibration toolkit was developed and implemented into the recalibration of a 3-D water quality model, with observations in a wider range of hydrological variability. Compared to the model calibrated with the original strategy, the recalibrated model performed significantly better in modeled total phosphorus, chlorophyll a, and dissolved oxygen. Our work indicates that hydrological variability in the calibration periods has a non-negligible impact on the water quality models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
Short summary
Short summary
This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines
Geosci. Model Dev., 16, 4233–4247, https://doi.org/10.5194/gmd-16-4233-2023, https://doi.org/10.5194/gmd-16-4233-2023, 2023
Short summary
Short summary
Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1263, https://doi.org/10.5194/egusphere-2023-1263, 2023
Short summary
Short summary
We performed systematic evaluation of clouds simulated in the E3SMv2 to document model performance on clouds and understand what updates in E3SMv2 have caused the changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved primarily due to the re-tuning of cloud macrophysics parameters. This study offers additional insights about clouds simulated in E3SMv2 and will benefit the future E3SM developments.
Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello
Geosci. Model Dev., 16, 4113–4136, https://doi.org/10.5194/gmd-16-4113-2023, https://doi.org/10.5194/gmd-16-4113-2023, 2023
Short summary
Short summary
In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Manuel C. Almeida and Pedro S. Coelho
Geosci. Model Dev., 16, 4083–4112, https://doi.org/10.5194/gmd-16-4083-2023, https://doi.org/10.5194/gmd-16-4083-2023, 2023
Short summary
Short summary
Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
Short summary
Short summary
Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
EGUsphere, https://doi.org/10.5194/egusphere-2023-1496, https://doi.org/10.5194/egusphere-2023-1496, 2023
Short summary
Short summary
Ocean models struggle to simulate small-scale ocean flows due to the computational cost of high-resolution simulations. Several cost-reducing strategies are applied to simulations of the Southern Ocean and evaluated with respect to observations and traditional, lower-resolution modelling methods. The high-resolution simulations effectively reproduce small-scale flows seen in satellite data and are largely consistent with traditional model simulations regarding their response to climate change.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
EGUsphere, https://doi.org/10.5194/egusphere-2023-890, https://doi.org/10.5194/egusphere-2023-890, 2023
Short summary
Short summary
Irrigation modifies the land surface and soil conditions. The caused effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which is simulating the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
Short summary
Short summary
High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
Short summary
Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906, https://doi.org/10.5194/gmd-16-3893-2023, https://doi.org/10.5194/gmd-16-3893-2023, 2023
Short summary
Short summary
A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808, https://doi.org/10.5194/gmd-16-3785-2023, https://doi.org/10.5194/gmd-16-3785-2023, 2023
Short summary
Short summary
Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
Short summary
Short summary
Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748, https://doi.org/10.5194/gmd-16-3723-2023, https://doi.org/10.5194/gmd-16-3723-2023, 2023
Short summary
Short summary
This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
Short summary
Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Jatan Buch, A. Park Williams, Caroline S. Juang, Winslow D. Hansen, and Pierre Gentine
Geosci. Model Dev., 16, 3407–3433, https://doi.org/10.5194/gmd-16-3407-2023, https://doi.org/10.5194/gmd-16-3407-2023, 2023
Short summary
Short summary
We leverage machine learning techniques to construct a statistical model of grid-scale fire frequencies and sizes using climate, vegetation, and human predictors. Our model reproduces the observed trends in fire activity across multiple regions and timescales. We provide uncertainty estimates to inform resource allocation plans for fuel treatment and fire management. Altogether the accuracy and efficiency of our model make it ideal for coupled use with large-scale dynamical vegetation models.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev., 16, 3375–3406, https://doi.org/10.5194/gmd-16-3375-2023, https://doi.org/10.5194/gmd-16-3375-2023, 2023
Short summary
Short summary
We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent so that users can make their own decisions on how to resolve these should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Alena Malyarenko, Alexandra Gossart, Rui Sun, and Mario Krapp
Geosci. Model Dev., 16, 3355–3373, https://doi.org/10.5194/gmd-16-3355-2023, https://doi.org/10.5194/gmd-16-3355-2023, 2023
Short summary
Short summary
Simultaneous modelling of ocean, sea ice, and atmosphere in coupled models is critical for understanding all of the processes that happen in the Antarctic. Here we have developed a coupled model for the Ross Sea, P-SKRIPS, that conserves heat and mass between the ocean and sea ice model (MITgcm) and the atmosphere model (PWRF). We have shown that our developments reduce the model drift, which is important for long-term simulations. P-SKRIPS shows good results in modelling coastal polynyas.
Feijia Yin, Volker Grewe, Federica Castino, Pratik Rao, Sigrun Matthes, Katrin Dahlmann, Simone Dietmüller, Christine Frömming, Hiroshi Yamashita, Patrick Peter, Emma Klingaman, Keith P. Shine, Benjamin Lührs, and Florian Linke
Geosci. Model Dev., 16, 3313–3334, https://doi.org/10.5194/gmd-16-3313-2023, https://doi.org/10.5194/gmd-16-3313-2023, 2023
Short summary
Short summary
This paper describes a newly developed submodel ACCF V1.0 based on the MESSy 2.53.0 infrastructure. The ACCF V1.0 is based on the prototype algorithmic climate change functions (aCCFs) v1.0 to enable climate-optimized flight trajectories. One highlight of this paper is that we describe a consistent full set of aCCFs formulas with respect to fuel scenario and metrics. We demonstrate the usage of the ACCF submodel using AirTraf V2.0 to optimize trajectories for cost and climate impact.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
Short summary
Short summary
Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, and Niklas Boers
Geosci. Model Dev., 16, 3123–3135, https://doi.org/10.5194/gmd-16-3123-2023, https://doi.org/10.5194/gmd-16-3123-2023, 2023
Short summary
Short summary
Differential programming is a technique that enables the automatic computation of derivatives of the output of models with respect to model parameters. Applying these techniques to Earth system modeling leverages the increasing availability of high-quality data to improve the models themselves. This can be done by either using calibration techniques that use gradient-based optimization or incorporating machine learning methods that can learn previously unresolved influences directly from data.
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...
