Articles | Volume 14, issue 8
Geosci. Model Dev., 14, 5269–5284, 2021
https://doi.org/10.5194/gmd-14-5269-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 14, 5269–5284, 2021
https://doi.org/10.5194/gmd-14-5269-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper 20 Aug 2021
Model experiment description paper | 20 Aug 2021
ATTRICI v1.1 – counterfactual climate for impact attribution
Matthias Mengel et al.
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Hélène Seroussi, Sophie Nowicki, Erika Simon, Ayako Abe-Ouchi, Torsten Albrecht, Julien Brondex, Stephen Cornford, Christophe Dumas, Fabien Gillet-Chaulet, Heiko Goelzer, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Thomas Kleiner, Eric Larour, Gunter Leguy, William H. Lipscomb, Daniel Lowry, Matthias Mengel, Mathieu Morlighem, Frank Pattyn, Anthony J. Payne, David Pollard, Stephen F. Price, Aurélien Quiquet, Thomas J. Reerink, Ronja Reese, Christian B. Rodehacke, Nicole-Jeanne Schlegel, Andrew Shepherd, Sainan Sun, Johannes Sutter, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, and Tong Zhang
The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, https://doi.org/10.5194/tc-13-1441-2019, 2019
Short summary
Short summary
We compare a wide range of Antarctic ice sheet simulations with varying initialization techniques and model parameters to understand the role they play on the projected evolution of this ice sheet under simple scenarios. Results are improved compared to previous assessments and show that continued improvements in the representation of the floating ice around Antarctica are critical to reduce the uncertainty in the future ice sheet contribution to sea level rise.
Ronja Reese, Torsten Albrecht, Matthias Mengel, Xylar Asay-Davis, and Ricarda Winkelmann
The Cryosphere, 12, 1969–1985, https://doi.org/10.5194/tc-12-1969-2018, https://doi.org/10.5194/tc-12-1969-2018, 2018
Short summary
Short summary
Floating ice shelves surround most of Antarctica and ocean-driven melting at their bases is a major reason for its current sea-level contribution. We developed a simple model based on a box model approach that captures the vertical ocean circulation generally present in ice-shelf cavities and allows simulating melt rates in accordance with physical processes beneath the ice. We test the model for all Antarctic ice shelves and find that melt rates and melt patterns agree well with observations.
Alexander Nauels, Malte Meinshausen, Matthias Mengel, Katja Lorbacher, and Tom M. L. Wigley
Geosci. Model Dev., 10, 2495–2524, https://doi.org/10.5194/gmd-10-2495-2017, https://doi.org/10.5194/gmd-10-2495-2017, 2017
Short summary
Short summary
The MAGICC sea level model projects global sea level rise by emulating process-based estimates for all major sea level drivers and applying them to available climate scenarios and their extensions to 2300. The MAGICC sea level projections are well within the ranges of the fifth IPCC assessment report. Due to its efficient structure, this emulator is a powerful tool for exploring sea level uncertainties and investigating sea level responses for a wide range of climate mitigation pathways.
Carl-Friedrich Schleussner, Tabea K. Lissner, Erich M. Fischer, Jan Wohland, Mahé Perrette, Antonius Golly, Joeri Rogelj, Katelin Childers, Jacob Schewe, Katja Frieler, Matthias Mengel, William Hare, and Michiel Schaeffer
Earth Syst. Dynam., 7, 327–351, https://doi.org/10.5194/esd-7-327-2016, https://doi.org/10.5194/esd-7-327-2016, 2016
Short summary
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We present for the first time a comprehensive assessment of key climate impacts for the policy relevant warming levels of 1.5 °C and 2 °C above pre-industrial levels. We report substantial impact differences in intensity and frequency of extreme weather events, regional water availability and agricultural yields, sea-level rise and risk of coral reef loss. The increase in climate impacts is particularly pronounced in tropical and sub-tropical regions.
K. Frieler, M. Mengel, and A. Levermann
Earth Syst. Dynam., 7, 203–210, https://doi.org/10.5194/esd-7-203-2016, https://doi.org/10.5194/esd-7-203-2016, 2016
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Sea level will continue to rise for centuries. We investigate the option of delaying sea-level rise by pumping ocean water onto Antarctica. Due to wave propagation ice is discharged much faster back into the ocean than expected from pure advection. A millennium-scale storage of > 80 % of the additional ice requires a distance of > 700 km from the coastline. The pumping energy required to elevate ocean water to mitigate a sea-level rise of 3 mm yr−1 exceeds 7 % of current global primary energy supply.
Marco Cucchi, Graham P. Weedon, Alessandro Amici, Nicolas Bellouin, Stefan Lange, Hannes Müller Schmied, Hans Hersbach, and Carlo Buontempo
Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, https://doi.org/10.5194/essd-12-2097-2020, 2020
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WFDE5 is a novel meteorological forcing dataset for running land surface and global hydrological models. It has been generated using the WATCH Forcing Data methodology applied to surface meteorological variables from the ERA5 reanalysis. It is publicly available, along with its source code, through the C3S Climate Data Store at ECMWF. Results of the evaluations described in the paper highlight the benefits of using WFDE5 compared to both ERA5 and its predecessor WFDEI.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Falko Ueckerdt, Katja Frieler, Stefan Lange, Leonie Wenz, Gunnar Luderer, and Anders Levermann
Earth Syst. Dynam., 10, 741–763, https://doi.org/10.5194/esd-10-741-2019, https://doi.org/10.5194/esd-10-741-2019, 2019
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We compute the global mean temperature increase at which the costs from climate-change damages and climate-change mitigation are minimal. This temperature is computed robustly around 2 degrees of global warming across a wide range of normative assumptions on the valuation of future welfare and inequality aversion.
Stefan Lange
Geosci. Model Dev., 12, 3055–3070, https://doi.org/10.5194/gmd-12-3055-2019, https://doi.org/10.5194/gmd-12-3055-2019, 2019
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Compared to their predecessors, the new Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) methods for bias adjustment and statistical downscaling allow for a more robust adjustment of extreme values and spatial variability, preserve trends more accurately across quantiles, and facilitate a clearer separation of bias adjustment and statistical downscaling.
Hélène Seroussi, Sophie Nowicki, Erika Simon, Ayako Abe-Ouchi, Torsten Albrecht, Julien Brondex, Stephen Cornford, Christophe Dumas, Fabien Gillet-Chaulet, Heiko Goelzer, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Thomas Kleiner, Eric Larour, Gunter Leguy, William H. Lipscomb, Daniel Lowry, Matthias Mengel, Mathieu Morlighem, Frank Pattyn, Anthony J. Payne, David Pollard, Stephen F. Price, Aurélien Quiquet, Thomas J. Reerink, Ronja Reese, Christian B. Rodehacke, Nicole-Jeanne Schlegel, Andrew Shepherd, Sainan Sun, Johannes Sutter, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, and Tong Zhang
The Cryosphere, 13, 1441–1471, https://doi.org/10.5194/tc-13-1441-2019, https://doi.org/10.5194/tc-13-1441-2019, 2019
Short summary
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We compare a wide range of Antarctic ice sheet simulations with varying initialization techniques and model parameters to understand the role they play on the projected evolution of this ice sheet under simple scenarios. Results are improved compared to previous assessments and show that continued improvements in the representation of the floating ice around Antarctica are critical to reduce the uncertainty in the future ice sheet contribution to sea level rise.
Jakob Zscheischler, Erich M. Fischer, and Stefan Lange
Earth Syst. Dynam., 10, 31–43, https://doi.org/10.5194/esd-10-31-2019, https://doi.org/10.5194/esd-10-31-2019, 2019
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Many climate models have biases in different variables throughout the world. Adjusting these biases is necessary for estimating climate impacts. Here we demonstrate that widely used univariate bias adjustment methods do not work well for multivariate impacts. We illustrate this problem using fire risk and heat stress as impact indicators. Using an approach that adjusts not only biases in the individual climate variables but also biases in the correlation between them can resolve these problems.
Martin Rückamp, Ulrike Falk, Katja Frieler, Stefan Lange, and Angelika Humbert
Earth Syst. Dynam., 9, 1169–1189, https://doi.org/10.5194/esd-9-1169-2018, https://doi.org/10.5194/esd-9-1169-2018, 2018
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Sea-level rise associated with changing climate is expected to pose a major challenge for societies. Based on the efforts of COP21 to limit global warming to 2.0 °C by the end of the 21st century (Paris Agreement), we simulate the future contribution of the Greenland ice sheet (GrIS) to sea-level change. The projected sea-level rise ranges between 21–38 mm by 2100
and 36–85 mm by 2300. Our results indicate that uncertainties in the projections stem from the underlying climate data.
Fahad Saeed, Ingo Bethke, Stefan Lange, Ludwig Lierhammer, Hideo Shiogama, Dáithí A. Stone, Tim Trautmann, and Carl-Friedrich Schleussner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-107, https://doi.org/10.5194/gmd-2018-107, 2018
Revised manuscript has not been submitted
Ronja Reese, Torsten Albrecht, Matthias Mengel, Xylar Asay-Davis, and Ricarda Winkelmann
The Cryosphere, 12, 1969–1985, https://doi.org/10.5194/tc-12-1969-2018, https://doi.org/10.5194/tc-12-1969-2018, 2018
Short summary
Short summary
Floating ice shelves surround most of Antarctica and ocean-driven melting at their bases is a major reason for its current sea-level contribution. We developed a simple model based on a box model approach that captures the vertical ocean circulation generally present in ice-shelf cavities and allows simulating melt rates in accordance with physical processes beneath the ice. We test the model for all Antarctic ice shelves and find that melt rates and melt patterns agree well with observations.
Stefan Lange
Earth Syst. Dynam., 9, 627–645, https://doi.org/10.5194/esd-9-627-2018, https://doi.org/10.5194/esd-9-627-2018, 2018
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The bias correction of surface downwelling longwave and shortwave radiation using parametric quantile mapping methods is shown to be more effective (i) at the daily than at the monthly timescale, (ii) if the spatial resolution gap between the reference data and the data to be corrected is bridged in a more suitable manner than by bilinear interpolation, and (iii) if physical upper limits are taken into account during the adjustment of either radiation component.
Sebastian Ostberg, Jacob Schewe, Katelin Childers, and Katja Frieler
Earth Syst. Dynam., 9, 479–496, https://doi.org/10.5194/esd-9-479-2018, https://doi.org/10.5194/esd-9-479-2018, 2018
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It has been shown that regional temperature and precipitation changes in future climate change scenarios often scale quasi-linearly with global mean temperature change (∆GMT). We show that an important consequence of these physical climate changes, namely changes in agricultural crop yields, can also be described in terms of ∆GMT to a large extent. This makes it possible to efficiently estimate future crop yield changes for different climate change scenarios without need for complex models.
Tobias Geiger, Katja Frieler, and David N. Bresch
Earth Syst. Sci. Data, 10, 185–194, https://doi.org/10.5194/essd-10-185-2018, https://doi.org/10.5194/essd-10-185-2018, 2018
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Tropical cyclones (TCs) pose a major risk to societies worldwide but very limited data exist on their socioeconomic impacts. Here, we apply a common wind field model to comprehensively and consistently estimate the number of people and the sum of assets exposed by all TCs between 1950 and 2015. This information is crucial to assess changes in societal vulnerabilites, to calibrate TC damage functions, and to make risk data more accessible to non-experts and stakeholders.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Alexander Nauels, Malte Meinshausen, Matthias Mengel, Katja Lorbacher, and Tom M. L. Wigley
Geosci. Model Dev., 10, 2495–2524, https://doi.org/10.5194/gmd-10-2495-2017, https://doi.org/10.5194/gmd-10-2495-2017, 2017
Short summary
Short summary
The MAGICC sea level model projects global sea level rise by emulating process-based estimates for all major sea level drivers and applying them to available climate scenarios and their extensions to 2300. The MAGICC sea level projections are well within the ranges of the fifth IPCC assessment report. Due to its efficient structure, this emulator is a powerful tool for exploring sea level uncertainties and investigating sea level responses for a wide range of climate mitigation pathways.
Alex C. Ruane, Claas Teichmann, Nigel W. Arnell, Timothy R. Carter, Kristie L. Ebi, Katja Frieler, Clare M. Goodess, Bruce Hewitson, Radley Horton, R. Sari Kovats, Heike K. Lotze, Linda O. Mearns, Antonio Navarra, Dennis S. Ojima, Keywan Riahi, Cynthia Rosenzweig, Matthias Themessl, and Katharine Vincent
Geosci. Model Dev., 9, 3493–3515, https://doi.org/10.5194/gmd-9-3493-2016, https://doi.org/10.5194/gmd-9-3493-2016, 2016
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The Vulnerability, Impacts, Adaptation, and Climate Services (VIACS) Advisory Board for CMIP6 was created to improve communications between communities that apply climate model output for societal benefit and the climate model centers. This manuscript describes the establishment of the VIACS Advisory Board as a coherent avenue for communication utilizing leading networks, experts, and programs; results of initial interactions during the development of CMIP6; and its potential next activities.
Carl-Friedrich Schleussner, Tabea K. Lissner, Erich M. Fischer, Jan Wohland, Mahé Perrette, Antonius Golly, Joeri Rogelj, Katelin Childers, Jacob Schewe, Katja Frieler, Matthias Mengel, William Hare, and Michiel Schaeffer
Earth Syst. Dynam., 7, 327–351, https://doi.org/10.5194/esd-7-327-2016, https://doi.org/10.5194/esd-7-327-2016, 2016
Short summary
Short summary
We present for the first time a comprehensive assessment of key climate impacts for the policy relevant warming levels of 1.5 °C and 2 °C above pre-industrial levels. We report substantial impact differences in intensity and frequency of extreme weather events, regional water availability and agricultural yields, sea-level rise and risk of coral reef loss. The increase in climate impacts is particularly pronounced in tropical and sub-tropical regions.
K. Frieler, M. Mengel, and A. Levermann
Earth Syst. Dynam., 7, 203–210, https://doi.org/10.5194/esd-7-203-2016, https://doi.org/10.5194/esd-7-203-2016, 2016
Short summary
Short summary
Sea level will continue to rise for centuries. We investigate the option of delaying sea-level rise by pumping ocean water onto Antarctica. Due to wave propagation ice is discharged much faster back into the ocean than expected from pure advection. A millennium-scale storage of > 80 % of the additional ice requires a distance of > 700 km from the coastline. The pumping energy required to elevate ocean water to mitigate a sea-level rise of 3 mm yr−1 exceeds 7 % of current global primary energy supply.
K. Frieler, A. Levermann, J. Elliott, J. Heinke, A. Arneth, M. F. P. Bierkens, P. Ciais, D. B. Clark, D. Deryng, P. Döll, P. Falloon, B. Fekete, C. Folberth, A. D. Friend, C. Gellhorn, S. N. Gosling, I. Haddeland, N. Khabarov, M. Lomas, Y. Masaki, K. Nishina, K. Neumann, T. Oki, R. Pavlick, A. C. Ruane, E. Schmid, C. Schmitz, T. Stacke, E. Stehfest, Q. Tang, D. Wisser, V. Huber, F. Piontek, L. Warszawski, J. Schewe, H. Lotze-Campen, and H. J. Schellnhuber
Earth Syst. Dynam., 6, 447–460, https://doi.org/10.5194/esd-6-447-2015, https://doi.org/10.5194/esd-6-447-2015, 2015
A. Levermann, R. Winkelmann, S. Nowicki, J. L. Fastook, K. Frieler, R. Greve, H. H. Hellmer, M. A. Martin, M. Meinshausen, M. Mengel, A. J. Payne, D. Pollard, T. Sato, R. Timmermann, W. L. Wang, and R. A. Bindschadler
Earth Syst. Dynam., 5, 271–293, https://doi.org/10.5194/esd-5-271-2014, https://doi.org/10.5194/esd-5-271-2014, 2014
J. Heinke, S. Ostberg, S. Schaphoff, K. Frieler, C. Müller, D. Gerten, M. Meinshausen, and W. Lucht
Geosci. Model Dev., 6, 1689–1703, https://doi.org/10.5194/gmd-6-1689-2013, https://doi.org/10.5194/gmd-6-1689-2013, 2013
S. Hempel, K. Frieler, L. Warszawski, J. Schewe, and F. Piontek
Earth Syst. Dynam., 4, 219–236, https://doi.org/10.5194/esd-4-219-2013, https://doi.org/10.5194/esd-4-219-2013, 2013
M. Perrette, F. Landerer, R. Riva, K. Frieler, and M. Meinshausen
Earth Syst. Dynam., 4, 11–29, https://doi.org/10.5194/esd-4-11-2013, https://doi.org/10.5194/esd-4-11-2013, 2013
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Geosci. Model Dev., 14, 5183–5204, https://doi.org/10.5194/gmd-14-5183-2021, https://doi.org/10.5194/gmd-14-5183-2021, 2021
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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
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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.
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Tobias Peter Bauer, Peter Holtermann, Bernd Heinold, Hagen Radtke, Oswald Knoth, and Knut Klingbeil
Geosci. Model Dev., 14, 4843–4863, https://doi.org/10.5194/gmd-14-4843-2021, https://doi.org/10.5194/gmd-14-4843-2021, 2021
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We present the coupled atmosphere–ocean model system ICONGETM. The added value and potential of using the latest coupling technologies are discussed in detail. An exchange grid handles the different coastlines from the unstructured atmosphere and the structured ocean grids. Due to a high level of automated processing, ICONGETM requires only minimal user input. The application to a coastal upwelling scenario demonstrates significantly improved model results compared to uncoupled simulations.
Dawn L. Woodard, Alexey N. Shiklomanov, Ben Kravitz, Corinne Hartin, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 4751–4767, https://doi.org/10.5194/gmd-14-4751-2021, https://doi.org/10.5194/gmd-14-4751-2021, 2021
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We have added a representation of the permafrost carbon feedback to the simple, open-source global carbon–climate model Hector and calibrated the results to be consistent with historical data and Earth system model projections. Our results closely match previous work, estimating around 0.2 °C of warming from permafrost this century. This capability will be useful to explore uncertainties in this feedback and for coupling with integrated assessment models for policy and economic analysis.
Klaus Wyser, Torben Koenigk, Uwe Fladrich, Ramon Fuentes-Franco, Mehdi Pasha Karami, and Tim Kruschke
Geosci. Model Dev., 14, 4781–4796, https://doi.org/10.5194/gmd-14-4781-2021, https://doi.org/10.5194/gmd-14-4781-2021, 2021
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This paper describes the large ensemble done by SMHI with the EC-Earth3 climate model. The ensemble comprises 50 realizations for each of the historical experiments after 1970 and four different future projections for CMIP6. We describe the creation of the initial states for the ensemble and the reduced set of output variables. A first look at the results illustrates the changes in the climate during this century and puts them in relation to the uncertainty from the model's internal variability.
Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, and Peng Gong
Geosci. Model Dev., 14, 4573–4592, https://doi.org/10.5194/gmd-14-4573-2021, https://doi.org/10.5194/gmd-14-4573-2021, 2021
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In this study, we implemented the specific morphology, phenology and harvest process of oil palm in the global land surface model ORCHIDEE-MICT. The improved model generally reproduces the same leaf area index, biomass density and life cycle fruit yield as observations. This explicit representation of oil palm in a global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.
Benjamin A. Toms, Karthik Kashinath, Prabhat, and Da Yang
Geosci. Model Dev., 14, 4495–4508, https://doi.org/10.5194/gmd-14-4495-2021, https://doi.org/10.5194/gmd-14-4495-2021, 2021
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We test whether a type of machine learning called neural networks can be used trustfully within the geosciences. We do so by challenging the networks to understand the spatial patterns of a commonly studied geoscientific phenomenon. The neural networks can correctly identify the spatial patterns, which lends confidence that similar networks can be used for more uncertain problems. The results of this study may give geoscientists confidence when using neural networks in their research.
Klaus Klingmüller and Jos Lelieveld
Geosci. Model Dev., 14, 4429–4441, https://doi.org/10.5194/gmd-14-4429-2021, https://doi.org/10.5194/gmd-14-4429-2021, 2021
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Soil moisture is of great importance for weather and climate. We present a machine learning model that produces accurate predictions of satellite-observed surface soil moisture, based on meteorological data from a climate model. It can be used as soil moisture parametrisation in climate models and to produce comprehensive global soil moisture datasets. Moreover, it may motivate similar applications of machine learning in climate science.
Jeremy McGibbon, Noah D. Brenowitz, Mark Cheeseman, Spencer K. Clark, Johann P. S. Dahm, Eddie C. Davis, Oliver D. Elbert, Rhea C. George, Lucas M. Harris, Brian Henn, Anna Kwa, W. Andre Perkins, Oliver Watt-Meyer, Tobias F. Wicky, Christopher S. Bretherton, and Oliver Fuhrer
Geosci. Model Dev., 14, 4401–4409, https://doi.org/10.5194/gmd-14-4401-2021, https://doi.org/10.5194/gmd-14-4401-2021, 2021
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FV3GFS is a weather and climate model written in Fortran. It uses Fortran so that it can run fast, but this makes it hard to add features if you do not (or even if you do) know Fortran. We have written a Python interface to FV3GFS that lets you import the Fortran model as a Python package. We show examples of how this is used to write
modelscripts, which reproduce or build on what the Fortran model can do. You could do this same wrapping for any compiled model, not just FV3GFS.
Alexander Pasternack, Jens Grieger, Henning W. Rust, and Uwe Ulbrich
Geosci. Model Dev., 14, 4335–4355, https://doi.org/10.5194/gmd-14-4335-2021, https://doi.org/10.5194/gmd-14-4335-2021, 2021
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Decadal climate ensemble forecasts are increasingly being used to guide adaptation measures. To ensure the applicability of these probabilistic predictions, inherent systematic errors of the prediction system must be adjusted. Since it is not clear which statistical model is optimal for this purpose, we propose a recalibration strategy with a systematic model selection based on non-homogeneous boosting for identifying the most relevant features for both ensemble mean and ensemble spread.
Daniel J. Lunt, Deepak Chandan, Alan M. Haywood, George M. Lunt, Jonathan C. Rougier, Ulrich Salzmann, Gavin A. Schmidt, and Paul J. Valdes
Geosci. Model Dev., 14, 4307–4317, https://doi.org/10.5194/gmd-14-4307-2021, https://doi.org/10.5194/gmd-14-4307-2021, 2021
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Often in science we carry out experiments with computers in which several factors are explored, for example, in the field of climate science, how the factors of greenhouse gases, ice, and vegetation affect temperature. We can explore the relative importance of these factors by
swapping in and outdifferent values of these factors, and can also carry out experiments with many different combinations of these factors. This paper discusses how best to analyse the results from such experiments.
Markus Adloff, Andy Ridgwell, Fanny M. Monteiro, Ian J. Parkinson, Alexander J. Dickson, Philip A. E. Pogge von Strandmann, Matthew S. Fantle, and Sarah E. Greene
Geosci. Model Dev., 14, 4187–4223, https://doi.org/10.5194/gmd-14-4187-2021, https://doi.org/10.5194/gmd-14-4187-2021, 2021
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We present the first representation of the trace metals Sr, Os, Li and Ca in a 3D Earth system model (cGENIE). The simulation of marine metal sources (weathering, hydrothermal input) and sinks (deposition) reproduces the observed concentrations and isotopic homogeneity of these metals in the modern ocean. With these new tracers, cGENIE can be used to test hypotheses linking these metal cycles and the cycling of other elements like O and C and simulate their dynamic response to external forcing.
Alessandro Anav, Adriana Carillo, Massimiliano Palma, Maria Vittoria Struglia, Ufuk Utku Turuncoglu, and Gianmaria Sannino
Geosci. Model Dev., 14, 4159–4185, https://doi.org/10.5194/gmd-14-4159-2021, https://doi.org/10.5194/gmd-14-4159-2021, 2021
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The Mediterranean Basin is a complex region, characterized by the presence of pronounced topography and a complex land–sea distribution including a considerable number of islands and straits; these features generate strong local atmosphere–sea interactions.
Regional Earth system models have been developed and used to study both present and future Mediterranean climate systems. The main aims of this paper are to present and evaluate the newly developed regional Earth system model ENEA-REG.
Markus Drüke, Werner von Bloh, Stefan Petri, Boris Sakschewski, Sibyll Schaphoff, Matthias Forkel, Willem Huiskamp, Georg Feulner, and Kirsten Thonicke
Geosci. Model Dev., 14, 4117–4141, https://doi.org/10.5194/gmd-14-4117-2021, https://doi.org/10.5194/gmd-14-4117-2021, 2021
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In this study, we couple the well-established and comprehensively validated state-of-the-art dynamic LPJmL5 global vegetation model to the CM2Mc coupled climate model (CM2Mc-LPJmL v.1.0). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. The new climate model is able to capture important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the the impacts of managed land (crop growth and irrigation).
Dirk Barbi, Nadine Wieters, Paul Gierz, Miguel Andrés-Martínez, Deniz Ural, Fatemeh Chegini, Sara Khosravi, and Luisa Cristini
Geosci. Model Dev., 14, 4051–4067, https://doi.org/10.5194/gmd-14-4051-2021, https://doi.org/10.5194/gmd-14-4051-2021, 2021
Cléa Denamiel, Petra Pranić, Damir Ivanković, Iva Tojčić, and Ivica Vilibić
Geosci. Model Dev., 14, 3995–4017, https://doi.org/10.5194/gmd-14-3995-2021, https://doi.org/10.5194/gmd-14-3995-2021, 2021
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The atmospheric results of the Adriatic Sea and Coast (AdriSC) climate simulation (1987–2017) are evaluated against available observational datasets in the Adriatic region. Generally, the AdriSC model performs better than regional climate models that have resolutions that are 4 times more coarse, except concerning summer temperatures, which are systematically underestimated. High-resolution climate models may thus provide new insights about the local impacts of global warming in the Adriatic.
Guy Munhoven
Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, https://doi.org/10.5194/gmd-14-3603-2021, 2021
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Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Max Kulinich, Yanan Fan, Spiridon Penev, Jason P. Evans, and Roman Olson
Geosci. Model Dev., 14, 3539–3551, https://doi.org/10.5194/gmd-14-3539-2021, https://doi.org/10.5194/gmd-14-3539-2021, 2021
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We present a novel stochastic approach based on Markov chains to estimate climate model weights of multi-model ensemble means. This approach showed improved performance (better correlation with observations) over existing alternatives during cross-validation and model-as-truth tests. The results of this comparative analysis should serve to motivate further studies in applications of Markov chain and other nonlinear methods to find optimal model weights for constructing ensemble means.
Jens Pfafferott, Sascha Rißmann, Matthias Sühring, Farah Kanani-Sühring, and Björn Maronga
Geosci. Model Dev., 14, 3511–3519, https://doi.org/10.5194/gmd-14-3511-2021, https://doi.org/10.5194/gmd-14-3511-2021, 2021
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The building model is integrated via an urban surface model into the urban climate model.
There is a strong interaction between the built environment and the urban climate.
According to the building energy concept, the energy demand results in a waste heat; this is directly transferred to the urban environment.
The impact of buildings on the urban climate is defined by different physical building parameters with different technical facilities for ventilation, heating and cooling.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Jun'ya Takakura, Shinichiro Fujimori, Kiyoshi Takahashi, Naota Hanasaki, Tomoko Hasegawa, Yukiko Hirabayashi, Yasushi Honda, Toshichika Iizumi, Chan Park, Makoto Tamura, and Yasuaki Hijioka
Geosci. Model Dev., 14, 3121–3140, https://doi.org/10.5194/gmd-14-3121-2021, https://doi.org/10.5194/gmd-14-3121-2021, 2021
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To simplify calculating economic impacts of climate change, statistical methods called emulators are developed and evaluated. There are trade-offs between model complexity and emulation performance. Aggregated economic impacts can be approximated by relatively simple emulators, but complex emulators are necessary to accommodate finer-scale economic impacts.
Meng-Zhuo Zhang, Zhongfeng Xu, Ying Han, and Weidong Guo
Geosci. Model Dev., 14, 3079–3094, https://doi.org/10.5194/gmd-14-3079-2021, https://doi.org/10.5194/gmd-14-3079-2021, 2021
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The Multivariable Integrated Evaluation Tool (MVIETool) is a simple-to-use and straightforward tool designed for evaluation and intercomparison of climate models in terms of vector fields or multiple fields. The tool incorporates some new improvements in vector field evaluation (VFE) and multivariable integrated evaluation (MVIE) methods, which are introduced in this paper.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077, https://doi.org/10.5194/gmd-14-3067-2021, https://doi.org/10.5194/gmd-14-3067-2021, 2021
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev., 14, 3007–3036, https://doi.org/10.5194/gmd-14-3007-2021, https://doi.org/10.5194/gmd-14-3007-2021, 2021
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This paper presents an update of the FaIR simple climate model, which can estimate the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used widely in academia, corporate research, and education.
Tongwen Wu, Rucong Yu, Yixiong Lu, Weihua Jie, Yongjie Fang, Jie Zhang, Li Zhang, Xiaoge Xin, Laurent Li, Zaizhi Wang, Yiming Liu, Fang Zhang, Fanghua Wu, Min Chu, Jianglong Li, Weiping Li, Yanwu Zhang, Xueli Shi, Wenyan Zhou, Junchen Yao, Xiangwen Liu, He Zhao, Jinghui Yan, Min Wei, Wei Xue, Anning Huang, Yaocun Zhang, Yu Zhang, Qi Shu, and Aixue Hu
Geosci. Model Dev., 14, 2977–3006, https://doi.org/10.5194/gmd-14-2977-2021, https://doi.org/10.5194/gmd-14-2977-2021, 2021
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This paper presents the high-resolution version of the Beijing Climate Center (BCC) Climate System Model, BCC-CSM2-HR, and describes its climate simulation performance including the atmospheric temperature and wind; precipitation; and the tropical climate phenomena such as TC, MJO, QBO, and ENSO. BCC-CSM2-HR is our model version contributing to the HighResMIP. We focused on its updates and differential characteristics from its predecessor, the medium-resolution version BCC-CSM2-MR.
Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo
Geosci. Model Dev., 14, 2959–2975, https://doi.org/10.5194/gmd-14-2959-2021, https://doi.org/10.5194/gmd-14-2959-2021, 2021
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State-of-the-art Earth system models, like the ones used in CMIP6, suffer from temporal inconsistencies at the ocean–atmosphere interface. In this study, a mathematically consistent iterative Schwarz method is used as a reference. Its tremendous computational cost makes it unusable for production runs, but it allows us to evaluate the error made when using legacy coupling schemes. The impact on the climate at longer timescales of days to decades is not evaluated.
Steven R. Brus, Phillip J. Wolfram, Luke P. Van Roekel, and Jessica D. Meixner
Geosci. Model Dev., 14, 2917–2938, https://doi.org/10.5194/gmd-14-2917-2021, https://doi.org/10.5194/gmd-14-2917-2021, 2021
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Wind-generated waves are an important process in the global climate system. They mediate many interactions between the ocean, atmosphere, and sea ice. Models which describe these waves are computationally expensive and have often been excluded from coupled Earth system models. To address this, we have developed a capability for the WAVEWATCH III model which allows model resolution to be varied globally across the coastal open ocean. This allows for improved accuracy at reduced computing time.
Elisa Ziegler and Kira Rehfeld
Geosci. Model Dev., 14, 2843–2866, https://doi.org/10.5194/gmd-14-2843-2021, https://doi.org/10.5194/gmd-14-2843-2021, 2021
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Past climate changes are the only record of how the climate responds to changes in conditions on Earth, but simulations with complex climate models are challenging. We extended a simple climate model such that it simulates the development of temperatures over time. In the model, changes in carbon dioxide and ice distribution affect the simulated temperatures the most. The model is very efficient and can therefore be used to examine past climate changes happening over long periods of time.
Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev., 14, 2801–2826, https://doi.org/10.5194/gmd-14-2801-2021, https://doi.org/10.5194/gmd-14-2801-2021, 2021
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Clouds play an vital role in Earth's energy budget, and even a small change in cloud fields can have a large impact on the climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties and thus provide a useful tool to explore unsolved problems relating to clouds.
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
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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.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev., 14, 2781–2799, https://doi.org/10.5194/gmd-14-2781-2021, https://doi.org/10.5194/gmd-14-2781-2021, 2021
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Global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve simulations of the models, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Chao Sun, Li Liu, Ruizhe Li, Xinzhu Yu, Hao Yu, Biao Zhao, Guansuo Wang, Juanjuan Liu, Fangli Qiao, and Bin Wang
Geosci. Model Dev., 14, 2635–2657, https://doi.org/10.5194/gmd-14-2635-2021, https://doi.org/10.5194/gmd-14-2635-2021, 2021
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Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
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Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Pirkka Ollinaho, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom, and Heikki Järvinen
Geosci. Model Dev., 14, 2143–2160, https://doi.org/10.5194/gmd-14-2143-2021, https://doi.org/10.5194/gmd-14-2143-2021, 2021
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OpenEnsemble 1.0 is a novel dataset that aims to open ensemble or probabilistic weather forecasting research up to the academic community. The dataset contains atmospheric states that are required for running model forecasts of atmospheric evolution. Our capacity to observe the atmosphere is limited; thus, a single reconstruction of the atmospheric state contains some errors. Our dataset provides sets of 50 slightly different atmospheric states so that these errors can be taken into account.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
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We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Hui Wan, Shixuan Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, and Huiping Yan
Geosci. Model Dev., 14, 1921–1948, https://doi.org/10.5194/gmd-14-1921-2021, https://doi.org/10.5194/gmd-14-1921-2021, 2021
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Numerical models used in weather and climate research and prediction unavoidably contain numerical errors resulting from temporal discretization, and the impact of such errors can be substantial. Complex process interactions often make it difficult to pinpoint the exact sources of such errors. This study uses a series of sensitivity experiments to identify components in a global atmosphere model that are responsible for time step sensitivities in various cloud regimes.
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680, https://doi.org/10.5194/gmd-14-1657-2021, https://doi.org/10.5194/gmd-14-1657-2021, 2021
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This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593, https://doi.org/10.5194/gmd-14-1575-2021, https://doi.org/10.5194/gmd-14-1575-2021, 2021
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A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Sonia Jerez, Laura Palacios-Peña, Claudia Gutiérrez, Pedro Jiménez-Guerrero, Jose María López-Romero, Enrique Pravia-Sarabia, and Juan Pedro Montávez
Geosci. Model Dev., 14, 1533–1551, https://doi.org/10.5194/gmd-14-1533-2021, https://doi.org/10.5194/gmd-14-1533-2021, 2021
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This research explores the role of aerosols when modeling surface solar radiation at regional scales (over Europe). A set of model experiments was performed with and without dynamical modeling of atmospheric aerosols and their direct and indirect effects on radiation. Results showed significant differences in the simulated solar radiation, mainly driven by the aerosol impact on cloudiness, which calls for caution when interpreting model experiments that do not include aerosols.
Sara Top, Lola Kotova, Lesley De Cruz, Svetlana Aniskevich, Leonid Bobylev, Rozemien De Troch, Natalia Gnatiuk, Anne Gobin, Rafiq Hamdi, Arne Kriegsmann, Armelle Reca Remedio, Abdulla Sakalli, Hans Van De Vyver, Bert Van Schaeybroeck, Viesturs Zandersons, Philippe De Maeyer, Piet Termonia, and Steven Caluwaerts
Geosci. Model Dev., 14, 1267–1293, https://doi.org/10.5194/gmd-14-1267-2021, https://doi.org/10.5194/gmd-14-1267-2021, 2021
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Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.
Yaqiong Lu and Xianyu Yang
Geosci. Model Dev., 14, 1253–1265, https://doi.org/10.5194/gmd-14-1253-2021, https://doi.org/10.5194/gmd-14-1253-2021, 2021
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Crop growth in land surface models normally requires high-temporal-resolution climate data, but such high-temporal-resolution climate data are not provided by many climate model simulations due to expensive storage, which limits modeling choices if there is an interest in a particular climate simulation that only saved monthly outputs. Our work provides an alternative way to use the monthly climate for crop yield projections. Such an approach could be easily adopted by other crop models.
John G. Virgin, Christopher G. Fletcher, Jason N. S. Cole, Knut von Salzen, and Toni Mitovski
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-11, https://doi.org/10.5194/gmd-2021-11, 2021
Revised manuscript accepted for GMD
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Equilibrium climate sensitivity, or the amount of warming the Earth would exhibit a result of a doubling of atmospheric CO2, is a common metric used in assessments of climate models. Here, we compare climate sensitivity between two versions of the Canadian Earth System Model. We find the newest iteration of the model (version 5) to have higher climate sensitivity due to reductions in low level clouds, which reflect radiation and cool the planet, as the surface warms.
Rumi Ohgaito, Akitomo Yamamoto, Tomohiro Hajima, Ryouta O'ishi, Manabu Abe, Hiroaki Tatebe, Ayako Abe-Ouchi, and Michio Kawamiya
Geosci. Model Dev., 14, 1195–1217, https://doi.org/10.5194/gmd-14-1195-2021, https://doi.org/10.5194/gmd-14-1195-2021, 2021
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Using the MIROC-ES2L Earth system model, selected time periods of the past were simulated. The ability to simulate the past is also an evaluation of the performance of the model in projecting global warming. Simulations for 21 000, 6000, and 127 000 years ago, and a simulation for 1000 years starting in 850 CE were simulated. The results showed that the model can generally describe past climate change.
Qiong Zhang, Ellen Berntell, Josefine Axelsson, Jie Chen, Zixuan Han, Wesley de Nooijer, Zhengyao Lu, Qiang Li, Qiang Zhang, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 1147–1169, https://doi.org/10.5194/gmd-14-1147-2021, https://doi.org/10.5194/gmd-14-1147-2021, 2021
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Paleoclimate modelling has long been regarded as a strong out-of-sample test bed of the climate models that are used for the projection of future climate changes. Here, we document the model experimental setups for the three past warm periods with EC-Earth3-LR and present the results on the large-scale features. The simulations demonstrate good performance of the model in capturing the climate response under different climate forcings.
Gill M. Martin, Richard C. Levine, José M. Rodriguez, and Michael Vellinga
Geosci. Model Dev., 14, 1007–1035, https://doi.org/10.5194/gmd-14-1007-2021, https://doi.org/10.5194/gmd-14-1007-2021, 2021
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Our study highlights a number of different techniques that can be employed to investigate the sources of model error. We demonstrate how this methodology can be used to identify the regions and model components responsible for the development of long-standing errors in the Asian summer monsoon. Once these are known, further work can be done to explore the local processes contributing to this behaviour and their sensitivity to changes in physical parameterisations and/or model resolution.
Trang Van Pham, Christian Steger, Burkhardt Rockel, Klaus Keuler, Ingo Kirchner, Mariano Mertens, Daniel Rieger, Günther Zängl, and Barbara Früh
Geosci. Model Dev., 14, 985–1005, https://doi.org/10.5194/gmd-14-985-2021, https://doi.org/10.5194/gmd-14-985-2021, 2021
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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.
Michael Steiner, Beiping Luo, Thomas Peter, Michael C. Pitts, and Andrea Stenke
Geosci. Model Dev., 14, 935–959, https://doi.org/10.5194/gmd-14-935-2021, https://doi.org/10.5194/gmd-14-935-2021, 2021
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We evaluate polar stratospheric clouds (PSCs) as simulated by the chemistry–climate model (CCM) SOCOLv3.1 in comparison with measurements by the CALIPSO satellite. A cold bias results in an overestimated PSC area and mountain-wave ice is underestimated, but we find overall good temporal and spatial agreement of PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes may also achieve good approximations of the fundamental properties of PSCs.
Zhaoyuan Yu, Dongshuang Li, Zhengfang Zhang, Wen Luo, Yuan Liu, Zengjie Wang, and Linwang Yuan
Geosci. Model Dev., 14, 875–887, https://doi.org/10.5194/gmd-14-875-2021, https://doi.org/10.5194/gmd-14-875-2021, 2021
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Few lossy compression methods consider both the global and local multidimensional coupling correlations, which could lead to information loss in data compression. Here we develop an adaptive lossy compression method, Adaptive-HGFDR, to capture both the global and local variation of multidimensional coupling correlations and improve approximation accuracy. The method can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity.
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Short summary
To identify the impacts of historical climate change it is necessary to separate the effect of the different impact drivers. To address this, one needs to compare historical impacts to a counterfactual world with impacts that would have been without climate change. We here present an approach that produces counterfactual climate data and can be used in climate impact models to simulate counterfactual impacts. We make these data available through the ISIMIP project.
To identify the impacts of historical climate change it is necessary to separate the effect of...
