Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-985-2021
© Author(s) 2021. 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-14-985-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model
Trang Van Pham
CORRESPONDING AUTHOR
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Christian Steger
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Burkhardt Rockel
Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Klaus Keuler
Brandenburg University of Technology, P.O. Box 10 13 44, 03013 Cottbus, Germany
Ingo Kirchner
Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6-10, 12165 Berlin, Germany
Mariano Mertens
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Daniel Rieger
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Günther Zängl
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Barbara Früh
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Related authors
Wolfgang A. Müller, Stephan Lorenz, Trang V. Pham, Andrea Schneidereit, Renate Brokopf, Victor Brovkin, Nils Brüggemann, Fatemeh Chegini, Dietmar Dommenget, Kristina Fröhlich, Barbara Früh, Veronika Gayler, Helmuth Haak, Stefan Hagemann, Moritz Hanke, Tatiana Ilyina, Johann Jungclaus, Martin Köhler, Peter Korn, Luis Kornblüh, Clarissa Kroll, Julian Krüger, Karel Castro-Morales, Ulrike Niemeier, Holger Pohlmann, Iuliia Polkova, Roland Potthast, Thomas Riddick, Manuel Schlund, Tobias Stacke, Roland Wirth, Dakuan Yu, and Jochem Marotzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-2473, https://doi.org/10.5194/egusphere-2025-2473, 2025
Short summary
Short summary
ICON XPP is a newly developed Earth System model configuration based on the ICON modeling framework. It merges accomplishments from the recent operational numerical weather prediction model with well-established climate components for the ocean, land and ocean-biogeochemistry. ICON XPP reaches typical targets of a coupled climate simulation, and is able to run long integrations and large-ensemble experiments, making it suitable for climate predictions and projections, and for climate research.
William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
Short summary
Short summary
We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Omar Abdelazim Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-2198, https://doi.org/10.5194/egusphere-2025-2198, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of climate projections. The system produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
Steven T. Turnock, Dimitris Akritidis, Larry Horowitz, Mariano Mertens, Andrea Pozzer, Carly L. Reddington, Hantao Wang, Putian Zhou, and Fiona O'Connor
Atmos. Chem. Phys., 25, 7111–7136, https://doi.org/10.5194/acp-25-7111-2025, https://doi.org/10.5194/acp-25-7111-2025, 2025
Short summary
Short summary
We assess the drivers behind changes in peak-season surface ozone concentrations and risks to human health between 1850 and 2014. Substantial increases in surface ozone have occurred over this period, resulting in an increased risk to human health, driven mainly by increases in anthropogenic NOx emissions and global CH4 concentrations. Fixing anthropogenic NOx emissions at 1850 values in the near-present-day period can eliminate the risk to human health associated with exposure to surface ozone.
Wolfgang A. Müller, Stephan Lorenz, Trang V. Pham, Andrea Schneidereit, Renate Brokopf, Victor Brovkin, Nils Brüggemann, Fatemeh Chegini, Dietmar Dommenget, Kristina Fröhlich, Barbara Früh, Veronika Gayler, Helmuth Haak, Stefan Hagemann, Moritz Hanke, Tatiana Ilyina, Johann Jungclaus, Martin Köhler, Peter Korn, Luis Kornblüh, Clarissa Kroll, Julian Krüger, Karel Castro-Morales, Ulrike Niemeier, Holger Pohlmann, Iuliia Polkova, Roland Potthast, Thomas Riddick, Manuel Schlund, Tobias Stacke, Roland Wirth, Dakuan Yu, and Jochem Marotzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-2473, https://doi.org/10.5194/egusphere-2025-2473, 2025
Short summary
Short summary
ICON XPP is a newly developed Earth System model configuration based on the ICON modeling framework. It merges accomplishments from the recent operational numerical weather prediction model with well-established climate components for the ocean, land and ocean-biogeochemistry. ICON XPP reaches typical targets of a coupled climate simulation, and is able to run long integrations and large-ensemble experiments, making it suitable for climate predictions and projections, and for climate research.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
Short summary
Short summary
The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Laura Stecher, Franziska Winterstein, Patrick Jöckel, Michael Ponater, Mariano Mertens, and Martin Dameris
Atmos. Chem. Phys., 25, 5133–5158, https://doi.org/10.5194/acp-25-5133-2025, https://doi.org/10.5194/acp-25-5133-2025, 2025
Short summary
Short summary
Methane, the second most important anthropogenic greenhouse gas, is chemically decomposed in the atmosphere. The chemical sink of atmospheric methane is not constant but depends on the temperature and on the abundance of its reaction partners. In this study, we use a global chemistry–climate model to assess the feedback of atmospheric methane induced by changes in the chemical sink in a warming climate and its implications for the chemical composition and the surface air temperature change.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
Short summary
Short summary
The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Catherine Acquah, Laura Stecher, Mariano Mertens, and Patrick Jöckel
EGUsphere, https://doi.org/10.5194/egusphere-2025-294, https://doi.org/10.5194/egusphere-2025-294, 2025
Short summary
Short summary
Short-lived ozone precursor species influence the formation of ozone and also the atmospheric lifetime of methane. Our study assesses the effect of two widely used emission inventories of these species on ozone and the methane lifetime. Our results indicate tropospheric ozone and methane lifetime differences of around 4 % even though both emission inventories aim at representing present-day conditions. We further attribute the differences to emissions of individual sectors, e.g. land traffic.
Hossein Maazallahi, Foteini Stavropoulou, Samuel Jonson Sutanto, Michael Steiner, Dominik Brunner, Mariano Mertens, Patrick Jöckel, Antoon Visschedijk, Hugo Denier van der Gon, Stijn Dellaert, Nataly Velandia Salinas, Stefan Schwietzke, Daniel Zavala-Araiza, Sorin Ghemulet, Alexandru Pana, Magdalena Ardelean, Marius Corbu, Andreea Calcan, Stephen A. Conley, Mackenzie L. Smith, and Thomas Röckmann
Atmos. Chem. Phys., 25, 1497–1511, https://doi.org/10.5194/acp-25-1497-2025, https://doi.org/10.5194/acp-25-1497-2025, 2025
Short summary
Short summary
This article presents insights from airborne in situ measurements collected during the ROmanian Methane Emissions from Oil and gas (ROMEO) campaign supported by two models. Results reveal Romania's oil and gas methane emissions were significantly under-reported to the United Nations Framework Convention on Climate Change (UNFCCC) in 2019. A large underestimation was also found in the Emissions Database for Global Atmospheric Research (EDGAR) v7.0 for the study domain in the same year.
Markus Kilian, Volker Grewe, Patrick Jöckel, Astrid Kerkweg, Mariano Mertens, Andreas Zahn, and Helmut Ziereis
Atmos. Chem. Phys., 24, 13503–13523, https://doi.org/10.5194/acp-24-13503-2024, https://doi.org/10.5194/acp-24-13503-2024, 2024
Short summary
Short summary
Anthropogenic emissions are a major source of precursors of tropospheric ozone. As ozone formation is highly non-linear, we apply a global–regional chemistry–climate model with a source attribution method (tagging) to quantify the contribution of anthropogenic emissions to ozone. Our analysis shows that the contribution of European anthropogenic emissions largely increases during large ozone periods, indicating that emissions from these sectors drive ozone values.
Mariano Mertens, Sabine Brinkop, Phoebe Graf, Volker Grewe, Johannes Hendricks, Patrick Jöckel, Anna Lanteri, Sigrun Matthes, Vanessa S. Rieger, Mattia Righi, and Robin N. Thor
Atmos. Chem. Phys., 24, 12079–12106, https://doi.org/10.5194/acp-24-12079-2024, https://doi.org/10.5194/acp-24-12079-2024, 2024
Short summary
Short summary
We quantified the contributions of land transport, shipping, and aviation emissions to tropospheric ozone; its radiative forcing; and the reductions of the methane lifetime using chemistry-climate model simulations. The contributions were analysed for the conditions of 2015 and for three projections for the year 2050. The results highlight the challenges of mitigating ozone formed by emissions of the transport sector, caused by the non-linearitiy of the ozone chemistry and the long lifetime.
Young-Ha Kim, Georg Sebastian Voelker, Gergely Bölöni, Günther Zängl, and Ulrich Achatz
Atmos. Chem. Phys., 24, 3297–3308, https://doi.org/10.5194/acp-24-3297-2024, https://doi.org/10.5194/acp-24-3297-2024, 2024
Short summary
Short summary
The quasi-biennial oscillation, which governs the tropical stratospheric circulation, is driven primarily by small-scale wave processes. We employ a novel method to realistically represent these wave processes in a global model, thereby revealing an aspect of the oscillation that has not been identified before. We find that the oblique propagation of waves, a process neglected by existing climate models, plays a pivotal role in the stratospheric circulation and its oscillation.
Zhihong Zhuo, Ingo Kirchner, and Ulrich Cubasch
Clim. Past, 19, 835–849, https://doi.org/10.5194/cp-19-835-2023, https://doi.org/10.5194/cp-19-835-2023, 2023
Short summary
Short summary
Precipitation distribution is uneven in monsoon and westerlies-dominated subregions of Asia. Multi-model data from PMIP3 and CMIP5 show a distinct inverse pattern of climatological conditions after NHVAI, with an intensified aridity in the relatively wettest area but a weakened aridity in the relatively driest area of the AMR. The hydrological impacts relate to the dynamical response of the climate system to the radiative effect of volcanic aerosol and the subsequent local physical feedbacks.
Veronika Ettrichrätz, Christian Beier, Klaus Keuler, and Katja Trachte
EGUsphere, https://doi.org/10.5194/egusphere-2023-552, https://doi.org/10.5194/egusphere-2023-552, 2023
Preprint archived
Short summary
Short summary
Will heavy precipitation increase under climate change by the end of this century? The analyses of 40 regional climate simulations for two climate scenarios show that large parts of northern, central, and eastern Europe will be affected by a robust increase in heavy and extreme precipitation, while southwestern Europe will rather experience a slight decrease. Both the increase and the affected areas can be up to twice as large in an extreme than in a more moderate greenhouse gas scenario.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev., 16, 1459–1466, https://doi.org/10.5194/gmd-16-1459-2023, https://doi.org/10.5194/gmd-16-1459-2023, 2023
Short summary
Short summary
We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry–climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated with aviation ozone is 7.6 % higher when using the less recent version of the data.
Günther Zängl, Daniel Reinert, and Florian Prill
Geosci. Model Dev., 15, 7153–7176, https://doi.org/10.5194/gmd-15-7153-2022, https://doi.org/10.5194/gmd-15-7153-2022, 2022
Short summary
Short summary
This article describes the implementation of grid refinement in the ICOsahedral Nonhydrostatic (ICON) model, which has been jointly developed at several German institutions and constitutes a unified modeling system for global and regional numerical weather prediction and climate applications. The grid refinement allows using a higher resolution in regional domains and transferring the information back to the global domain by means of a feedback mechanism.
M. Dolores Andrés Hernández, Andreas Hilboll, Helmut Ziereis, Eric Förster, Ovid O. Krüger, Katharina Kaiser, Johannes Schneider, Francesca Barnaba, Mihalis Vrekoussis, Jörg Schmidt, Heidi Huntrieser, Anne-Marlene Blechschmidt, Midhun George, Vladyslav Nenakhov, Theresa Harlass, Bruna A. Holanda, Jennifer Wolf, Lisa Eirenschmalz, Marc Krebsbach, Mira L. Pöhlker, Anna B. Kalisz Hedegaard, Linlu Mei, Klaus Pfeilsticker, Yangzhuoran Liu, Ralf Koppmann, Hans Schlager, Birger Bohn, Ulrich Schumann, Andreas Richter, Benjamin Schreiner, Daniel Sauer, Robert Baumann, Mariano Mertens, Patrick Jöckel, Markus Kilian, Greta Stratmann, Christopher Pöhlker, Monica Campanelli, Marco Pandolfi, Michael Sicard, José L. Gómez-Amo, Manuel Pujadas, Katja Bigge, Flora Kluge, Anja Schwarz, Nikos Daskalakis, David Walter, Andreas Zahn, Ulrich Pöschl, Harald Bönisch, Stephan Borrmann, Ulrich Platt, and John P. Burrows
Atmos. Chem. Phys., 22, 5877–5924, https://doi.org/10.5194/acp-22-5877-2022, https://doi.org/10.5194/acp-22-5877-2022, 2022
Short summary
Short summary
EMeRGe provides a unique set of in situ and remote sensing airborne measurements of trace gases and aerosol particles along selected flight routes in the lower troposphere over Europe. The interpretation uses also complementary collocated ground-based and satellite measurements. The collected data help to improve the current understanding of the complex spatial distribution of trace gases and aerosol particles resulting from mixing, transport, and transformation of pollution plumes over Europe.
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Panitz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev., 14, 5125–5154, https://doi.org/10.5194/gmd-14-5125-2021, https://doi.org/10.5194/gmd-14-5125-2021, 2021
Short summary
Short summary
We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia, and Africa. How the model configuration, horizontal and vertical resolutions, and choice of driving data influence the model results for the five domains is assessed, with the purpose of aiding the planning and design of regional climate simulations in the future.
Vinod Kumar, Julia Remmers, Steffen Beirle, Joachim Fallmann, Astrid Kerkweg, Jos Lelieveld, Mariano Mertens, Andrea Pozzer, Benedikt Steil, Marc Barra, Holger Tost, and Thomas Wagner
Atmos. Meas. Tech., 14, 5241–5269, https://doi.org/10.5194/amt-14-5241-2021, https://doi.org/10.5194/amt-14-5241-2021, 2021
Short summary
Short summary
We present high-resolution regional atmospheric chemistry model simulations focused around Germany. We highlight the importance of spatial resolution of the model itself as well as the input emissions inventory and short-scale temporal variability of emissions for simulations. We propose a consistent approach for evaluating the simulated vertical distribution of NO2 using MAX-DOAS measurements while also considering its spatial sensitivity volume and change in sensitivity within this volume.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
Short summary
Short summary
We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Torben Schmith, Peter Thejll, Peter Berg, Fredrik Boberg, Ole Bøssing Christensen, Bo Christiansen, Jens Hesselbjerg Christensen, Marianne Sloth Madsen, and Christian Steger
Hydrol. Earth Syst. Sci., 25, 273–290, https://doi.org/10.5194/hess-25-273-2021, https://doi.org/10.5194/hess-25-273-2021, 2021
Short summary
Short summary
European extreme precipitation is expected to change in the future; this is based on climate model projections. But, since climate models have errors, projections are uncertain. We study this uncertainty in the projections by comparing results from an ensemble of 19 climate models. Results can be used to give improved estimates of future extreme precipitation for 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.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
Short summary
Short summary
Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
Cited articles
Anders, I. and Rockel, B.: The influence of prescribed soil type distribution
on the representation of present climate in a regional climate model, Clim.
Dynam., 33, 177–186, 2009. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M.,
and Reinhardt, T.: Operational convective-scale numerical weather prediction
with the COSMO model: description and sensitivities, Mon. Weather Rev.,
139, 3887–3905, 2011. a
Barker, H. W., Stephens, G., Partain, P., Bergman, J., Bonnel, B., Campana, K., Clothiaux, E., Clough, S., Cusack, S., Delamere, J., Edwards, J., Evans, K. F., Fouquart, Y., Freidenreich, S., Galin, V., Hou, Y., Kato, S., Li, J., Mlawer, E., Morcrette, J.-J., O'Hirok, W., Räisänen, P., Ramaswamy, V., Ritter, B., Rozanov, E., Schlesinger, M., Shibata, K., Sporyshev, P., Sun, Z., Wendisch, M., Wood, N., and Yang, F.: Assessing 1D
atmospheric solar radiative transfer models: Interpretation and handling of
unresolved clouds, J. Climate, 16, 2676–2699, 2003. a, b
Brovkin, V., Boysen, L., Raddatz, T., Gayler, V., Loew, A., and Claussen, M.:
Evaluation of vegetation cover and land-surface albedo in MPI-ESM CMIP5
simulations, J. Adv. Model. Earth Sy., 5, 48–57, 2013. a
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model
projections of changes in European climate by the end of this century,
Climatic Change, 81, 7–30, 2007. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge‐Sanz, B. M., Morcrette, J.‐J., Park, B.‐K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.‐N., and Vitart, F.
: The
ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011. a, b
Doms, G. and Schättler, U.: The nonhydrostatic limited-area model LM
(Lokal-Modell) of DWD, Part I: Scientific documentation, Deutscher
Wetterdienst (DWD), Offenbach, Germany, 10, 1999. a
Doms, G., Förstner, J., Heise, E., Herzog, H.,Mironov, D., Raschendorfer, M., Reinhardt, T., Ritter, B., Schrodin, R., Schulz, J.-P., and Vogel, G.: A
description of the nonhydrostatic regional COSMO model, Part II: Physical
parameterization, Deutscher Wetterdienst, Offenbach, Germany, 2011. a, b, c
Gal-Chen, T. and Somerville, R. C.: On the use of a coordinate transformation
for the solution of the Navier-Stokes equations, J. Comput.
Phys., 17, 209–228, 1975. a
Gampe, D. and Ludwig, R.: Evaluation of gridded precipitation data products for
hydrological applications in complex topography, Hydrology, 4, https://doi.org/10.3390/hydrology4040053, 2017. a
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen,T., Mikolajewicz, U., Müller,W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., D. Six, K., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K-H., Claussen, M., Marotzke, J., and Stevens, B.:
Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for
the Coupled Model Intercomparison Project phase 5, J. Adv.
Model. Earth Sy., 5, 572–597, 2013. a
Giorgetta, M. A., Brokopf, R., Crueger, T., Esch, M., Fiedler, S., Helmert, J., Hohenegger, C., Kornblueh, L., Köhler, M., Manzini, E., Mauritsen, T., Nam, C., Raddatz, T., Rast, S., Reinert, D., Sakradzija, M., Schmidt, H.,
Schneck, R., Schnur, R., Silvers, L., Wan, H., Zängl, G., Stevens, B.: ICON-A,
the atmosphere component of the ICON Earth System Model. Part I: Model
Description, J. Adv. Model. Earth Sy., 10, 1613–1637,
https://doi.org/10.1029/2017MS001242, 2018. a, b
Giorgi, F., Jones, C., and Asrar, G. R.: Addressing climate information
needs at the regional level: the CORDEX framework, World Meteorological
Organization (WMO) Bulletin, 58, 175 pp., 2009. a
Haylock, M., Hofstra, N., Klein Tank, A., Klok, E., Jones, P., and New, M.: A
European daily high-resolution gridded data set of surface temperature and
precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113, D20119,
https://doi.org/10.1029/2008JD010201, 2008. a, b
Heinze, R., Dipankar, A., Henken, C. C., Moseley, C., Sourdeval, O., Trömel, S., Xie, X., Adamidis, P., Ament, F., Baars, H., Barthlott, C., Behrendt, A., Blahak, U., Bley, S., Brdar, S., Brueck, M., Crewell, S., Deneke,H., Di Girolamo,P., Evaristo, R., Fischer, J., Frank, C., Friederichs, P., Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A., Hege, H-C., Hoose, C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S., Knippertz, P., Kuhn, A., van Laar, T., Macke, A., Maurer, V., Mayer, B., Meyer, C. I., Muppa, S. K., Neggers, R. A. J., Orlandi, E., Pantillon, F., Pospichal, B., Röber,N., Scheck, L., Seifert, A., Seifert, P., Senf, F., Siligam, P., Simmer, C., Steinke, S., Stevens, B., Wapler, K., Weniger, M., Wulfmeyer, V., Zängl, G., Zhang, D., and Quaas, J.:
Large-eddy simulations over Germany using ICON: A comprehensive evaluation,
Q. J. Roy. Meteor. Soc., 143, 69–100, 2017. a
Hofstra, N., Haylock, M., New, M., and Jones, P. D.: Testing E-OBS European
high-resolution gridded data set of daily precipitation and surface
temperature, J. Geophys. Res.-Atmos., 114, D21101, https://doi.org/10.1029/2009JD011799,
2009. a
Korn, P.: Formulation of an unstructured grid model for global ocean dynamics,
J. Comput. Phys., 339, 525–552, 2017. a
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014. a, b, c, d, e
Majewski, D. and Ritter, B.: Das Global-Modell GME, Promet, 27, 111–122, 2002. a
Orr, A., Bechtold, P., Scinocca, J., Ern, M., and Janiskova, M.: Improved
middle atmosphere climate and forecasts in the ECMWF model through a
nonorographic gravity wave drag parameterization, J. Climate, 23,
5905–5926, 2010. a
Pham, T. V. and Rockel, B.: Starter Package ICON-CLM_SP (Version ICON-CLM_SP_beta1), Zenodo, https://doi.org/10.5281/zenodo.3896136, 2020. a
Pham, T. V., Brauch, J., Dieterich, C., Früh, B., and Ahrens, B.: New
coupled atmosphere-ocean-ice system COSMO-CLM/NEMO: assessing air
temperature sensitivity over the North and Baltic Seas, Oceanologia,
56, 167–189, https://doi.org/10.5697/oc.56-2.167, 2014. a
Rieger, D., Köhler, M., Hogan, R., Schäfer, S., Seifert, A., Lozar,
A. D., and Zängl, G.: ecRad in ICON – Implementation Overview, Reports
on ICON, Deutscher Wetterdienst, Offenbach, Germany, https://doi.org/10.5676/DWDpub/nwv/icon004, 2019. a
Ritter, B. and Geleyn, J.-F.: A comprehensive radiation scheme for numerical
weather prediction models with potential applications in climate simulations,
Mon. Weather Rev., 120, 303–325, 1992. a
Rockel, B., Will, A., and Hense, A.: The regional climate model COSMO-CLM
(CCLM), Meteorol. Z., 17, 347–348, https://doi.org/10.1127/0941-2948/2008/0309, 2008. a
Sanchez-Gomez, E., Somot, S., and Déqué, M.: Ability of an ensemble of
regional climate models to reproduce weather regimes over Europe-Atlantic
during the period 1961–2000, Clim. Dynam., 33, 723–736, 2009. a
Schrodin, R. and Heise, E.: The multi-layer version of the DWD soil model
TERRA_LM, Deutscher Wetterdienst, Offenbach, Germany, https://doi.org/10.5676/DWD_pub/nwv/cosmo-tr_2,
2001. a
Schulz, J.-P., Vogel, G., Becker, C., Kothe, S., Rummel, U., and Ahrens, B.:
Evaluation of the ground heat flux simulated by a multi-layer land surface
scheme using high-quality observations at grass land and bare soil,
Meteorol. Z., 25, 607–620, https://doi.org/10.1127/metz/2016/0537,
2016. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric
component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model
Earth Sy., 5, 146–172, https://doi.org/10.1002/jame.20015, 2013. a
Tegen, I., Hollrig, P., Chin, M., Fung, I., Jacob, D., and Penner, J.:
Contribution of different aerosol species to the global aerosol extinction
optical thickness: Estimates from model results, J. Geophys.
Res.-Atmos., 102, 23895–23915, 1997. a
Trusilova, K., Früh, B., Brienen, S., and Keuler, K.: Urban effects in
climate simulations for CORDEX Europe, CLM-Community Newsletter, 2, 4–7,
2014. a
Van den Besselaar, E., Haylock, M., Van der Schrier, G., and Klein Tank, A.: A
European daily high-resolution observational gridded data set of sea level
pressure, J. Geophys. Res.-Atmos., 116, D11110, https://doi.org/10.1029/2010JD015468, 2011. a, b
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J.
Roy. Meteor. Soc., 141, 563–579,
https://doi.org/10.1002/qj.2378, 2015. a
Short summary
A new regional climate model was prepared based on a weather forecast model. Slow processes of the climate system such as ocean state development and greenhouse gas emissions were implemented. A model infrastructure and evaluation tools were also prepared to facilitate long-term simulations and model evalution. The first ICON-CLM results were close to observations and comparable to those from COSMO-CLM, the recommended model being used at the Deutscher Wetterdienst and CLM Community.
A new regional climate model was prepared based on a weather forecast model. Slow processes of...