Articles | Volume 12, issue 7
https://doi.org/10.5194/gmd-12-2875-2019
© Author(s) 2019. 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-12-2875-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
12 Jul 2019
Development and technical paper |
| 12 Jul 2019
| 12 Jul 2019
Significant improvement of cloud representation in the global climate model MRI-ESM2
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Seiji Yukimoto
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Tsuyoshi Koshiro
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Naga Oshima
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Taichu Tanaka
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Hiromasa Yoshimura
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Ryoji Nagasawa
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052, Japan
Related authors
No articles found.
Victoria A. Flood, Kimberly Strong, Cynthia H. Whaley, Kaley A. Walker, Thomas Blumenstock, James W. Hannigan, Johan Mellqvist, Justus Notholt, Mathias Palm, Amelie N. Röhling, Stephen Arnold, Stephen Beagley, Rong-You Chien, Jesper Christensen, Makoto Deushi, Srdjan Dobricic, Xinyi Dong, Joshua S. Fu, Michael Gauss, Wanmin Gong, Joakim Langner, Kathy S. Law, Louis Marelle, Tatsuo Onishi, Naga Oshima, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Manu A. Thomas, Svetlana Tsyro, and Steven Turnock
Atmos. Chem. Phys., 24, 1079–1118, https://doi.org/10.5194/acp-24-1079-2024, https://doi.org/10.5194/acp-24-1079-2024, 2024
Short summary
Short summary
It is important to understand the composition of the Arctic atmosphere and how it is changing. Atmospheric models provide simulations that can inform policy. This study examines simulations of CH4, CO, and O3 by 11 models. Model performance is assessed by comparing results matched in space and time to measurements from five high-latitude ground-based infrared spectrometers. This work finds that models generally underpredict the concentrations of these gases in the Arctic troposphere.
Alkiviadis Kalisoras, Aristeidis K. Georgoulias, Dimitris Akritidis, Robert J. Allen, Vaishali Naik, Chaincy Kuo, Sophie Szopa, Pierre Nabat, Dirk Olivié, Twan van Noije, Philippe Le Sager, David Neubauer, Naga Oshima, Jane Mulcahy, Larry W. Horowitz, and Prodromos Zanis
EGUsphere, https://doi.org/10.5194/egusphere-2023-2571, https://doi.org/10.5194/egusphere-2023-2571, 2023
Short summary
Short summary
Effective Radiative Forcing (ERF) is a metric for estimating how human activities and natural agents change the energy flow into and out of the Earth’s climate system. We investigate the anthropogenic aerosol ERF and we estimate the contribution of individual processes to the total ERF using simulations from Earth System Models within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our findings highlight that aerosol-cloud interactions drive ERF variability during the last 150 years.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie Hammer, Larry Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
EGUsphere, https://doi.org/10.5194/egusphere-2023-2370, https://doi.org/10.5194/egusphere-2023-2370, 2023
Short summary
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its five components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce well the observed spatial pattern for OC, sulfate, nitrate and ammonium, yet the agreement is poorer for BC.
Cynthia H. Whaley, Kathy S. Law, Jens Liengaard Hjorth, Henrik Skov, Stephen R. Arnold, Joakim Langner, Jakob Boyd Pernov, Garance Bergeron, Ilann Bourgeois, Jesper H. Christensen, Rong-You Chien, Makoto Deushi, Xinyi Dong, Peter Effertz, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Greg Huey, Ulas Im, Rigel Kivi, Louis Marelle, Tatsuo Onishi, Naga Oshima, Irina Petropavlovskikh, Jeff Peischl, David A. Plummer, Luca Pozzoli, Jean-Christophe Raut, Tom Ryerson, Ragnhild Skeie, Sverre Solberg, Manu A. Thomas, Chelsea Thompson, Kostas Tsigaridis, Svetlana Tsyro, Steven T. Turnock, Knut von Salzen, and David W. Tarasick
Atmos. Chem. Phys., 23, 637–661, https://doi.org/10.5194/acp-23-637-2023, https://doi.org/10.5194/acp-23-637-2023, 2023
Short summary
Short summary
This study summarizes recent research on ozone in the Arctic, a sensitive and rapidly warming region. We find that the seasonal cycles of near-surface atmospheric ozone are variable depending on whether they are near the coast, inland, or at high altitude. Several global model simulations were evaluated, and we found that because models lack some of the ozone chemistry that is important for the coastal Arctic locations, they do not accurately simulate ozone there.
Flossie Brown, Gerd A. Folberth, Stephen Sitch, Susanne Bauer, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Makoto Deushi, Inês Dos Santos Vieira, Corinne Galy-Lacaux, James Haywood, James Keeble, Lina M. Mercado, Fiona M. O'Connor, Naga Oshima, Kostas Tsigaridis, and Hans Verbeeck
Atmos. Chem. Phys., 22, 12331–12352, https://doi.org/10.5194/acp-22-12331-2022, https://doi.org/10.5194/acp-22-12331-2022, 2022
Short summary
Short summary
Surface ozone can decrease plant productivity and impair human health. In this study, we evaluate the change in surface ozone due to climate change over South America and Africa using Earth system models. We find that if the climate were to change according to the worst-case scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of ozone exposure, but other areas will experience a climate benefit.
Hitoshi Matsui, Tatsuhiro Mori, Sho Ohata, Nobuhiro Moteki, Naga Oshima, Kumiko Goto-Azuma, Makoto Koike, and Yutaka Kondo
Atmos. Chem. Phys., 22, 8989–9009, https://doi.org/10.5194/acp-22-8989-2022, https://doi.org/10.5194/acp-22-8989-2022, 2022
Short summary
Short summary
Using a global aerosol model, we find that the source contributions to radiative effects of black carbon (BC) in the Arctic are quite different from those to mass concentrations and deposition flux of BC in the Arctic. This is because microphysical properties (e.g., mixing state), altitudes, and seasonal variations of BC in the atmosphere differ among emissions sources. These differences need to be considered for accurate simulations of Arctic BC and its source contributions and climate impacts.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
Short summary
Short summary
Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Hiromasa Yoshimura
Geosci. Model Dev., 15, 2561–2597, https://doi.org/10.5194/gmd-15-2561-2022, https://doi.org/10.5194/gmd-15-2561-2022, 2022
Short summary
Short summary
This paper proposes a new double Fourier series (DFS) method on a sphere that improves the numerical stability of a model compared with conventional DFS methods. The shallow-water model and the advection model using the new DFS method give stable results without the appearance of high-wavenumber noise near the poles. The model using the new DFS method is faster than the model using spherical harmonics (especially at high resolutions) and gives almost the same results.
Henry Bowman, Steven Turnock, Susanne E. Bauer, Kostas Tsigaridis, Makoto Deushi, Naga Oshima, Fiona M. O'Connor, Larry Horowitz, Tongwen Wu, Jie Zhang, Dagmar Kubistin, and David D. Parrish
Atmos. Chem. Phys., 22, 3507–3524, https://doi.org/10.5194/acp-22-3507-2022, https://doi.org/10.5194/acp-22-3507-2022, 2022
Short summary
Short summary
A full understanding of ozone in the troposphere requires investigation of its temporal variability over all timescales. Model simulations show that the northern midlatitude ozone seasonal cycle shifted with industrial development (1850–2014), with an increasing magnitude and a later summer peak. That shift reached a maximum in the mid-1980s, followed by a reversal toward the preindustrial cycle. The few available observations, beginning in the 1970s, are consistent with the model simulations.
Sho Ohata, Makoto Koike, Atsushi Yoshida, Nobuhiro Moteki, Kouji Adachi, Naga Oshima, Hitoshi Matsui, Oliver Eppers, Heiko Bozem, Marco Zanatta, and Andreas B. Herber
Atmos. Chem. Phys., 21, 15861–15881, https://doi.org/10.5194/acp-21-15861-2021, https://doi.org/10.5194/acp-21-15861-2021, 2021
Short summary
Short summary
Vertical profiles of black carbon (BC) in the Arctic were measured during the PAMARCMiP aircraft-based experiment in spring 2018 and compared with those observed during previous aircraft campaigns in 2008, 2010, and 2015. Their differences were explained primarily by the year-to-year variation of biomass burning activities in northern midlatitudes over Eurasia. Our observations provide a bases to evaluate numerical model simulations that assess the BC radiative effects in the Arctic spring.
Sho Ohata, Tatsuhiro Mori, Yutaka Kondo, Sangeeta Sharma, Antti Hyvärinen, Elisabeth Andrews, Peter Tunved, Eija Asmi, John Backman, Henri Servomaa, Daniel Veber, Konstantinos Eleftheriadis, Stergios Vratolis, Radovan Krejci, Paul Zieger, Makoto Koike, Yugo Kanaya, Atsushi Yoshida, Nobuhiro Moteki, Yongjing Zhao, Yutaka Tobo, Junji Matsushita, and Naga Oshima
Atmos. Meas. Tech., 14, 6723–6748, https://doi.org/10.5194/amt-14-6723-2021, https://doi.org/10.5194/amt-14-6723-2021, 2021
Short summary
Short summary
Reliable values of mass absorption cross sections (MACs) of black carbon (BC) are required to determine mass concentrations of BC at Arctic sites using different types of filter-based absorption photometers. We successfully estimated MAC values for these instruments through comparison with independent measurements of BC by a continuous soot monitoring system called COSMOS. These MAC values are consistent with each other and applicable to study spatial and temporal variation in BC in the Arctic.
David D. Parrish, Richard G. Derwent, Steven T. Turnock, Fiona M. O'Connor, Johannes Staehelin, Susanne E. Bauer, Makoto Deushi, Naga Oshima, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 21, 9669–9679, https://doi.org/10.5194/acp-21-9669-2021, https://doi.org/10.5194/acp-21-9669-2021, 2021
Short summary
Short summary
The few ozone measurements made before the 1980s indicate that industrial development increased ozone concentrations by a factor of ~ 2 at northern midlatitudes, which are now larger than at southern midlatitudes. This difference was much smaller, and likely reversed, in the pre-industrial atmosphere. Earth system models find similar increases, but not higher pre-industrial ozone in the south. This disagreement may indicate that modeled natural ozone sources and/or deposition loss are inadequate.
Rei Kudo, Henri Diémoz, Victor Estellés, Monica Campanelli, Masahiro Momoi, Franco Marenco, Claire L. Ryder, Osamu Ijima, Akihiro Uchiyama, Kouichi Nakashima, Akihiro Yamazaki, Ryoji Nagasawa, Nozomu Ohkawara, and Haruma Ishida
Atmos. Meas. Tech., 14, 3395–3426, https://doi.org/10.5194/amt-14-3395-2021, https://doi.org/10.5194/amt-14-3395-2021, 2021
Short summary
Short summary
A new method, Skyrad pack MRI version 2, was developed to retrieve aerosol physical and optical properties, water vapor, and ozone column concentrations from the sky radiometer, a filter radiometer deployed in the SKYNET international network. Our method showed good performance in a radiative closure study using surface solar irradiances from the Baseline Surface Radiation Network and a comparison using aircraft in situ measurements of Saharan dust events during the SAVEX-D 2015 campaign.
Mizuo Kajino, Makoto Deushi, Tsuyoshi Thomas Sekiyama, Naga Oshima, Keiya Yumimoto, Taichu Yasumichi Tanaka, Joseph Ching, Akihiro Hashimoto, Tetsuya Yamamoto, Masaaki Ikegami, Akane Kamada, Makoto Miyashita, Yayoi Inomata, Shin-ichiro Shima, Pradeep Khatri, Atsushi Shimizu, Hitoshi Irie, Kouji Adachi, Yuji Zaizen, Yasuhito Igarashi, Hiromasa Ueda, Takashi Maki, and Masao Mikami
Geosci. Model Dev., 14, 2235–2264, https://doi.org/10.5194/gmd-14-2235-2021, https://doi.org/10.5194/gmd-14-2235-2021, 2021
Short summary
Short summary
This study compares performance of aerosol representation methods of the Japan Meteorological Agency's regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). It indicates separate treatment of sea salt and dust in coarse mode and that of light-absorptive and non-absorptive particles in fine mode could provide accurate assessments on aerosol feedback processes.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
Short summary
Short summary
We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Kouji Adachi, Naga Oshima, Sho Ohata, Atsushi Yoshida, Nobuhiro Moteki, and Makoto Koike
Atmos. Chem. Phys., 21, 3607–3626, https://doi.org/10.5194/acp-21-3607-2021, https://doi.org/10.5194/acp-21-3607-2021, 2021
Short summary
Short summary
Aerosol particles influence the Arctic climate by interacting with solar radiation, forming clouds, and melting surface snow and ice. Individual-particle analyses using transmission electron microscopy (TEM) and model simulations provide evidence of biomass burning and anthropogenic contributions to the Arctic aerosols by showing a wide range of compositions and mixing states depending on sampling altitude. Our results reveal the aerosol aging processes and climate influences in the Arctic.
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.
Mayumi Yoshida, Keiya Yumimoto, Takashi M. Nagao, Taichu Y. Tanaka, Maki Kikuchi, and Hiroshi Murakami
Atmos. Chem. Phys., 21, 1797–1813, https://doi.org/10.5194/acp-21-1797-2021, https://doi.org/10.5194/acp-21-1797-2021, 2021
Short summary
Short summary
We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol forecast. This is the first study that utilizes the assimilated model forecast of aerosol as an a priori estimate of the retrieval. Aerosol retrievals were improved by effectively incorporating both model and satellite information. By using the assimilated forecast as an a priori estimate, information from previous observations can be propagated to future retrievals, thus leading to better retrieval accuracy.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
Short summary
Short summary
This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Kine Onsum Moseid, Michael Schulz, Trude Storelvmo, Ingeborg Rian Julsrud, Dirk Olivié, Pierre Nabat, Martin Wild, Jason N. S. Cole, Toshihiko Takemura, Naga Oshima, Susanne E. Bauer, and Guillaume Gastineau
Atmos. Chem. Phys., 20, 16023–16040, https://doi.org/10.5194/acp-20-16023-2020, https://doi.org/10.5194/acp-20-16023-2020, 2020
Short summary
Short summary
In this study we compare solar radiation at the surface from observations and Earth system models from 1961 to 2014. We find that the models do not reproduce the so-called
global dimmingas found in observations. Only model experiments with anthropogenic aerosol emissions display any dimming at all. The discrepancies between observations and models are largest in China, which we suggest is in part due to erroneous aerosol precursor emission inventories in the emission dataset used for CMIP6.
Sho Ohata, Tatsuhiro Mori, Yutaka Kondo, Sangeeta Sharma, Antti Hyvärinen, Elisabeth Andrews, Peter Tunved, Eija Asmi, John Backman, Henri Servomaa, Daniel Veber, Makoto Koike, Yugo Kanaya, Atsushi Yoshida, Nobuhiro Moteki, Yongjing Zhao, Junji Matsushita, and Naga Oshima
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1190, https://doi.org/10.5194/acp-2020-1190, 2020
Preprint withdrawn
Short summary
Short summary
Reliable values of mass absorption cross sections (MAC) of black carbon (BC) are required to determine mass concentrations of BC at Arctic sites using different types of filter-based absorption photometers. We successfully estimated MAC values for these instruments through comparison with independent measurements of BC by continuous soot monitoring system called COSMOS. These MAC values are consistent with each other and applicable to study spatial and temporal variation of BC in the Arctic.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
Short summary
Short summary
A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Kouji Adachi, Naga Oshima, Zhaoheng Gong, Suzane de Sá, Adam P. Bateman, Scot T. Martin, Joel F. de Brito, Paulo Artaxo, Glauber G. Cirino, Arthur J. Sedlacek III, and Peter R. Buseck
Atmos. Chem. Phys., 20, 11923–11939, https://doi.org/10.5194/acp-20-11923-2020, https://doi.org/10.5194/acp-20-11923-2020, 2020
Short summary
Short summary
Occurrences, size distributions, and number fractions of individual aerosol particles from the Amazon basin during the GoAmazon2014/5 campaign were analyzed using transmission electron microscopy. Aerosol particles from natural sources (e.g., mineral dust, primary biological aerosols, and sea salts) during the wet season originated from the Amazon forest and long-range transports (the Saharan desert and the Atlantic Ocean). They commonly mix at an individual particle scale during transport.
Robert J. Allen, Steven Turnock, Pierre Nabat, David Neubauer, Ulrike Lohmann, Dirk Olivié, Naga Oshima, Martine Michou, Tongwen Wu, Jie Zhang, Toshihiko Takemura, Michael Schulz, Kostas Tsigaridis, Susanne E. Bauer, Louisa Emmons, Larry Horowitz, Vaishali Naik, Twan van Noije, Tommi Bergman, Jean-Francois Lamarque, Prodromos Zanis, Ina Tegen, Daniel M. Westervelt, Philippe Le Sager, Peter Good, Sungbo Shim, Fiona O'Connor, Dimitris Akritidis, Aristeidis K. Georgoulias, Makoto Deushi, Lori T. Sentman, Jasmin G. John, Shinichiro Fujimori, and William J. Collins
Atmos. Chem. Phys., 20, 9641–9663, https://doi.org/10.5194/acp-20-9641-2020, https://doi.org/10.5194/acp-20-9641-2020, 2020
Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, Kari Alterskjær, William Collins, Adriana Sima, Olivier Boucher, Jean-Louis Dufresne, Pierre Nabat, Martine Michou, Seiji Yukimoto, Jason Cole, David Paynter, Hideo Shiogama, Fiona M. O'Connor, Eddy Robertson, Andy Wiltshire, Timothy Andrews, Cécile Hannay, Ron Miller, Larissa Nazarenko, Alf Kirkevåg, Dirk Olivié, Stephanie Fiedler, Anna Lewinschal, Chloe Mackallah, Martin Dix, Robert Pincus, and Piers M. Forster
Atmos. Chem. Phys., 20, 9591–9618, https://doi.org/10.5194/acp-20-9591-2020, https://doi.org/10.5194/acp-20-9591-2020, 2020
Short summary
Short summary
The spread in effective radiative forcing for both CO2 and aerosols is narrower in the latest CMIP6 (Coupled Model Intercomparison Project) generation than in CMIP5. For the case of CO2 it is likely that model radiation parameterisations have improved. Tropospheric and stratospheric radiative adjustments to the forcing behave differently for different forcing agents, and there is still significant diversity in how clouds respond to forcings, particularly for total anthropogenic forcing.
Prodromos Zanis, Dimitris Akritidis, Aristeidis K. Georgoulias, Robert J. Allen, Susanne E. Bauer, Olivier Boucher, Jason Cole, Ben Johnson, Makoto Deushi, Martine Michou, Jane Mulcahy, Pierre Nabat, Dirk Olivié, Naga Oshima, Adriana Sima, Michael Schulz, Toshihiko Takemura, and Konstantinos Tsigaridis
Atmos. Chem. Phys., 20, 8381–8404, https://doi.org/10.5194/acp-20-8381-2020, https://doi.org/10.5194/acp-20-8381-2020, 2020
Short summary
Short summary
In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014.
Daniele Visioni, Giovanni Pitari, Vincenzo Rizi, Marco Iarlori, Irene Cionni, Ilaria Quaglia, Hideharu Akiyoshi, Slimane Bekki, Neal Butchart, Martin Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando Garcia, Patrick Joeckel, Douglas Kinnison, Jean-François Lamarque, Marion Marchand, Martine Michou, Olaf Morgenstern, Tatsuya Nagashima, Fiona M. O'Connor, Luke D. Oman, David Plummer, Eugene Rozanov, David Saint-Martin, Robyn Schofield, John Scinocca, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Holger Tost, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-525, https://doi.org/10.5194/acp-2020-525, 2020
Preprint withdrawn
Short summary
Short summary
In this work we analyse the trend in ozone profiles taken at L'Aquila (Italy, 42.4° N) for seventeen years, between 2000 and 2016 and compare them against already available measured ozone trends. We try to understand and explain the observed trends at various heights in light of the simulations from seventeen different model, highlighting the contribution of changes in circulation and chemical ozone loss during this time period.
Andreas Chrysanthou, Amanda C. Maycock, Martyn P. Chipperfield, Sandip Dhomse, Hella Garny, Douglas Kinnison, Hideharu Akiyoshi, Makoto Deushi, Rolando R. Garcia, Patrick Jöckel, Oliver Kirner, Giovanni Pitari, David A. Plummer, Laura Revell, Eugene Rozanov, Andrea Stenke, Taichu Y. Tanaka, Daniele Visioni, and Yousuke Yamashita
Atmos. Chem. Phys., 19, 11559–11586, https://doi.org/10.5194/acp-19-11559-2019, https://doi.org/10.5194/acp-19-11559-2019, 2019
Short summary
Short summary
We perform the first multi-model comparison of the impact of nudged meteorology on the stratospheric residual circulation (RC) in chemistry–climate models. Nudging meteorology does not constrain the mean strength of RC compared to free-running simulations, and despite the lack of agreement in the mean circulation, nudging tightly constrains the inter-annual variability in the tropical upward mass flux in the lower stratosphere. In summary, nudging strongly affects the representation of RC.
Kévin Lamy, Thierry Portafaix, Béatrice Josse, Colette Brogniez, Sophie Godin-Beekmann, Hassan Bencherif, Laura Revell, Hideharu Akiyoshi, Slimane Bekki, Michaela I. Hegglin, Patrick Jöckel, Oliver Kirner, Ben Liley, Virginie Marecal, Olaf Morgenstern, Andrea Stenke, Guang Zeng, N. Luke Abraham, Alexander T. Archibald, Neil Butchart, Martyn P. Chipperfield, Glauco Di Genova, Makoto Deushi, Sandip S. Dhomse, Rong-Ming Hu, Douglas Kinnison, Michael Kotkamp, Richard McKenzie, Martine Michou, Fiona M. O'Connor, Luke D. Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Eugene Rozanov, David Saint-Martin, Kengo Sudo, Taichu Y. Tanaka, Daniele Visioni, and Kohei Yoshida
Atmos. Chem. Phys., 19, 10087–10110, https://doi.org/10.5194/acp-19-10087-2019, https://doi.org/10.5194/acp-19-10087-2019, 2019
Short summary
Short summary
In this study, we simulate the ultraviolet radiation evolution during the 21st century on Earth's surface using the output from several numerical models which participated in the Chemistry-Climate Model Initiative. We present four possible futures which depend on greenhouse gases emissions. The role of ozone-depleting substances, greenhouse gases and aerosols are investigated. Our results emphasize the important role of aerosols for future ultraviolet radiation in the Northern Hemisphere.
Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
Short summary
Short summary
Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation authorities, solar energy plant managers, climate service providers, and health professionals. This paper describes the advances in the field and sets out requirements for observations for the sustainability of these activities.
Mizuo Kajino, Makoto Deushi, Tsuyoshi Thomas Sekiyama, Naga Oshima, Keiya Yumimoto, Taichu Yasumichi Tanaka, Joseph Ching, Akihiro Hashimoto, Tetsuya Yamamoto, Masaaki Ikegami, Akane Kamada, Makoto Miyashita, Yayoi Inomata, Shin-ichiro Shima, Kouji Adachi, Yuji Zaizen, Yasuhito Igarashi, Hiromasa Ueda, Takashi Maki, and Masao Mikami
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-128, https://doi.org/10.5194/gmd-2018-128, 2018
Revised manuscript not accepted
Clara Orbe, Huang Yang, Darryn W. Waugh, Guang Zeng, Olaf Morgenstern, Douglas E. Kinnison, Jean-Francois Lamarque, Simone Tilmes, David A. Plummer, John F. Scinocca, Beatrice Josse, Virginie Marecal, Patrick Jöckel, Luke D. Oman, Susan E. Strahan, Makoto Deushi, Taichu Y. Tanaka, Kohei Yoshida, Hideharu Akiyoshi, Yousuke Yamashita, Andreas Stenke, Laura Revell, Timofei Sukhodolov, Eugene Rozanov, Giovanni Pitari, Daniele Visioni, Kane A. Stone, Robyn Schofield, and Antara Banerjee
Atmos. Chem. Phys., 18, 7217–7235, https://doi.org/10.5194/acp-18-7217-2018, https://doi.org/10.5194/acp-18-7217-2018, 2018
Short summary
Short summary
In this study we compare a few atmospheric transport properties among several numerical models that are used to study the influence of atmospheric chemistry on climate. We show that there are large differences among models in terms of the timescales that connect the Northern Hemisphere midlatitudes, where greenhouse gases and ozone-depleting substances are emitted, to the Southern Hemisphere. Our results may have important implications for how models represent atmospheric composition.
Neal Butchart, James A. Anstey, Kevin Hamilton, Scott Osprey, Charles McLandress, Andrew C. Bushell, Yoshio Kawatani, Young-Ha Kim, Francois Lott, John Scinocca, Timothy N. Stockdale, Martin Andrews, Omar Bellprat, Peter Braesicke, Chiara Cagnazzo, Chih-Chieh Chen, Hye-Yeong Chun, Mikhail Dobrynin, Rolando R. Garcia, Javier Garcia-Serrano, Lesley J. Gray, Laura Holt, Tobias Kerzenmacher, Hiroaki Naoe, Holger Pohlmann, Jadwiga H. Richter, Adam A. Scaife, Verena Schenzinger, Federico Serva, Stefan Versick, Shingo Watanabe, Kohei Yoshida, and Seiji Yukimoto
Geosci. Model Dev., 11, 1009–1032, https://doi.org/10.5194/gmd-11-1009-2018, https://doi.org/10.5194/gmd-11-1009-2018, 2018
Short summary
Short summary
This paper documents the numerical experiments to be used in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi), which was set up to improve the representation of the QBO and tropical stratospheric variability in global climate models.
Keiya Yumimoto, Taichu Y. Tanaka, Naga Oshima, and Takashi Maki
Geosci. Model Dev., 10, 3225–3253, https://doi.org/10.5194/gmd-10-3225-2017, https://doi.org/10.5194/gmd-10-3225-2017, 2017
Short summary
Short summary
A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a two-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard the Terra and Aqua satellites every 6 h and has a TL159 horizontal resolution (approximately 1.1° × 1.1°).
Takuma Miyakawa, Naga Oshima, Fumikazu Taketani, Yuichi Komazaki, Ayako Yoshino, Akinori Takami, Yutaka Kondo, and Yugo Kanaya
Atmos. Chem. Phys., 17, 5851–5864, https://doi.org/10.5194/acp-17-5851-2017, https://doi.org/10.5194/acp-17-5851-2017, 2017
Short summary
Short summary
We have deployed a single particle soot photometer (SP2) to characterize black carbon (BC) aerosols near industrial sources in Japan in the early summer of 2014 and at a remote island in the spring of 2015. The observed changes in the SP2-derived size distributions and mixing state of BC-containing particles with air mass transport are connected to meteorological variability (transport pathways and air mass histories) in spring in east Asia.
Masuo Nakano, Akiyoshi Wada, Masahiro Sawada, Hiromasa Yoshimura, Ryo Onishi, Shintaro Kawahara, Wataru Sasaki, Tomoe Nasuno, Munehiko Yamaguchi, Takeshi Iriguchi, Masato Sugi, and Yoshiaki Takeuchi
Geosci. Model Dev., 10, 1363–1381, https://doi.org/10.5194/gmd-10-1363-2017, https://doi.org/10.5194/gmd-10-1363-2017, 2017
Short summary
Short summary
Three 7 km mesh next-generation global models and a 20 km mesh conventional global model were run to improve tropical cyclone (TC) prediction. The 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. However, the simulated TC structures and their intensities in each case are very different for each model. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improvement.
Olaf Morgenstern, Michaela I. Hegglin, Eugene Rozanov, Fiona M. O'Connor, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Slimane Bekki, Neal Butchart, Martyn P. Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando R. Garcia, Steven C. Hardiman, Larry W. Horowitz, Patrick Jöckel, Beatrice Josse, Douglas Kinnison, Meiyun Lin, Eva Mancini, Michael E. Manyin, Marion Marchand, Virginie Marécal, Martine Michou, Luke D. Oman, Giovanni Pitari, David A. Plummer, Laura E. Revell, David Saint-Martin, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Geosci. Model Dev., 10, 639–671, https://doi.org/10.5194/gmd-10-639-2017, https://doi.org/10.5194/gmd-10-639-2017, 2017
Short summary
Short summary
We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.
Osamu Uchino, Tetsu Sakai, Toshiharu Izumi, Tomohiro Nagai, Isamu Morino, Akihiro Yamazaki, Makoto Deushi, Keiya Yumimoto, Takashi Maki, Taichu Y. Tanaka, Taiga Akaho, Hiroshi Okumura, Kohei Arai, Takahiro Nakatsuru, Tsuneo Matsunaga, and Tatsuya Yokota
Atmos. Chem. Phys., 17, 1865–1879, https://doi.org/10.5194/acp-17-1865-2017, https://doi.org/10.5194/acp-17-1865-2017, 2017
Short summary
Short summary
To validate products of GOSAT, we observed vertical profiles of aerosols, thin cirrus clouds, and tropospheric ozone with a mobile lidar system that consisted of a two-wavelength (532 and 1064 nm) polarization lidar and tropospheric ozone differential absorption lidar (DIAL). We used these lidars to make continuous measurements over Saga (33.24° N, 130.29° E) during 20–31 March 2015. High ozone and high aerosol concentrations were observed almost simultaneously and impacted surface air quality.
Kunihiko Kodera, Rémi Thiéblemont, Seiji Yukimoto, and Katja Matthes
Atmos. Chem. Phys., 16, 12925–12944, https://doi.org/10.5194/acp-16-12925-2016, https://doi.org/10.5194/acp-16-12925-2016, 2016
Short summary
Short summary
The spatial structure of the solar cycle signals on the Earth's surface is analysed to identify the mechanisms. Both tropical and extratropical solar surface signals can result from circulation changes in the upper stratosphere through (i) a downward migration of wave zonal mean flow interactions and (ii) changes in the stratospheric mean meridional circulation. Amplification of the solar signal also occurs through interaction with the ocean.
W. R. Sessions, J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. E. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. C. Jorba, H.-M. H. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal
Atmos. Chem. Phys., 15, 335–362, https://doi.org/10.5194/acp-15-335-2015, https://doi.org/10.5194/acp-15-335-2015, 2015
Short summary
B. H. Samset, G. Myhre, A. Herber, Y. Kondo, S.-M. Li, N. Moteki, M. Koike, N. Oshima, J. P. Schwarz, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, M. Chin, T. Diehl, R. C. Easter, S. J. Ghan, T. Iversen, A. Kirkevåg, J.-F. Lamarque, G. Lin, X. Liu, J. E. Penner, M. Schulz, Ø. Seland, R. B. Skeie, P. Stier, T. Takemura, K. Tsigaridis, and K. Zhang
Atmos. Chem. Phys., 14, 12465–12477, https://doi.org/10.5194/acp-14-12465-2014, https://doi.org/10.5194/acp-14-12465-2014, 2014
Short summary
Short summary
Far from black carbon (BC) emission sources, present climate models are unable to reproduce flight measurements. By comparing recent models with data, we find that the atmospheric lifetime of BC may be overestimated in models. By adjusting modeled BC concentrations to measurements in remote regions - over oceans and at high altitudes - we arrive at a reduced estimate for BC radiative forcing over the industrial era.
K. Osada, S. Ura, M. Kagawa, M. Mikami, T. Y. Tanaka, S. Matoba, K. Aoki, M. Shinoda, Y. Kurosaki, M. Hayashi, A. Shimizu, and M. Uematsu
Atmos. Chem. Phys., 14, 1107–1121, https://doi.org/10.5194/acp-14-1107-2014, https://doi.org/10.5194/acp-14-1107-2014, 2014
N. Oshima and M. Koike
Geosci. Model Dev., 6, 263–282, https://doi.org/10.5194/gmd-6-263-2013, https://doi.org/10.5194/gmd-6-263-2013, 2013
Related subject area
Climate and Earth system modeling
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach
Towards the definition of a solar forcing dataset for CMIP7
ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
The Regional Climate-Chemistry-Ecology Coupling Model RegCM-Chem (v4.6)-YIBs (v1.0): Development and Application
Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections
An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields
An emulation-based approach for interrogating reactive transport models
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
A sub-grid parameterization scheme for topographic vertical motion in CAM5-SE
Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
Short summary
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
Short summary
This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Short summary
Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
Short summary
Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
Short summary
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
Short summary
Short summary
A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
Short summary
Short summary
Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
Short summary
Short summary
The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
Short summary
Short summary
We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
Short summary
Short summary
This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
Short summary
Short summary
By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
Short summary
Short summary
We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
Short summary
Short summary
Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
Short summary
Short summary
We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
Short summary
Short summary
We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
Short summary
Short summary
Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
Short summary
Short summary
This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
Short summary
Short summary
This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
Short summary
Short summary
The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
Short summary
Short summary
The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
Short summary
Short summary
Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
Short summary
Short summary
Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
Short summary
Short summary
This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
Short summary
Short summary
We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
Short summary
Short summary
The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
Short summary
Short summary
We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
Short summary
Short summary
For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
Short summary
Short summary
Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
Short summary
Short summary
This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
Short summary
Short summary
Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
Short summary
Short summary
Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
Short summary
Short summary
Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Baiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1733, https://doi.org/10.5194/egusphere-2023-1733, 2023
Short summary
Short summary
For the first time, we coupled a regional climate chemistry model RegCM-Chem with a dynamic vegetation model YIBs to create a regional climate-chemistry-ecology model RegCM-Chem-YIBs. We applied it to simulate climatic, chemical and ecological parameters in East Asia and fully validated it on a variety of observational data. The research results show that RegCM-Chem-YIBs model is a valuable tool for studying terrestrial carbon cycle, atmospheric chemistry, and climate change in regional scale.
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, https://doi.org/10.5194/gmd-16-7171-2023, 2023
Short summary
Short summary
We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.
Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm
Geosci. Model Dev., 16, 7143–7170, https://doi.org/10.5194/gmd-16-7143-2023, https://doi.org/10.5194/gmd-16-7143-2023, 2023
Short summary
Short summary
This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.
Angus Fotherby, Harold J. Bradbury, Jennifer L. Druhan, and Alexandra V. Turchyn
Geosci. Model Dev., 16, 7059–7074, https://doi.org/10.5194/gmd-16-7059-2023, https://doi.org/10.5194/gmd-16-7059-2023, 2023
Short summary
Short summary
We demonstrate how, given a simulation of fluid and rock interacting, we can emulate the system using machine learning. This means that, for a given initial condition, we can predict the final state, avoiding the simulation step once the model has been trained. We present a workflow for applying this approach to any fluid–rock simulation and showcase two applications to different fluid–rock simulations. This approach has applications for improving model development and sensitivity analyses.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-223, https://doi.org/10.5194/gmd-2023-223, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion by either uniform erosion processes where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea level history, material properties, and the relative influence of different erosional processes.
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
Short summary
Short summary
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
EGUsphere, https://doi.org/10.5194/egusphere-2023-2720, https://doi.org/10.5194/egusphere-2023-2720, 2023
Short summary
Short summary
We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth System Models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation:
2. Multiple aerosol types, J. Geophys. Res., 105, 6837,
https://doi.org/10.1029/1999JD901161, 2000.
Abdul-Razzak, H., Ghan, S. J., and Rivera-Carpio, C.: A parameterization of
aerosol activation: 1. Single aerosol type, J. Geophys. Res., 103, 6123,
https://doi.org/10.1029/97JD03735, 1998.
Abel, S. J., Walters, D. N., and Allen, G.: Evaluation of stratocumulus cloud
prediction in the Met Office forecast model during VOCALS-REx, Atmos.
Chem. Phys.,
10, 10541–10559, https://doi.org/10.5194/acp-10-10541-2010, 2010.
Betts, A. K.: Diurnal variation of California coastal stratocumulus from two
days of boundary layer soundings, Tellus A, 42, 302–304,
https://doi.org/10.1034/j.1600-0870.1990.t01-1-00007.x, 1990.
Betts, A. K. and Boers, R.: A Cloudiness Transition in a Marine Boundary
Layer, J. Atmos. Sci., 47, 1480–1497,
https://doi.org/10.1175/1520-0469(1990)047<1480:ACTIAM>2.0.CO;2,
1990.
Bigg, E. K.: The supercooling of water, Proc. Phys. Soc. B, 66, 688–694, 1953.
Bodas-Salcedo, A., Williams, K. D., Ringer, M. A., Beau, I., Cole, J. N. S.,
Dufresne, J. L., Koshiro, T., Stevens, B., Wang, Z., and Yokohata, T.:
Origins of the solar radiation biases over the Southern Ocean in CFMIP2
models, J. Climate, 27, 41–56, https://doi.org/10.1175/JCLI-D-13-00169.1, 2014.
Bodas-Salcedo, A., Hill, P. G., Furtado, K., Williams, K. D., Field, P. R.,
Manners, J. C., Hyder, P., and Kato, S.: Large contribution of supercooled
liquid clouds to the solar radiation budget of the Southern Ocean, J. Climate,
29, 4213–4228, https://doi.org/10.1175/JCLI-D-15-0564.1, 2016.
Bony, S., Webb, M., Bretherton, C., Klein, S., Siebesma, P., Tselioudis, G.,
and Zhang, M.: CFMIP: Towards a better evaluation and understanding of
clouds and cloud feedbacks in CMIP5 models, Clivar Exch., 56, 20–24, 2011.
Bretherton, C. S., Wood, R., George, R. C., Leon, D., Allen, G., and Zheng, X.:
Southeast Pacific stratocumulus clouds, precipitation and boundary layer
structure sampled along 20∘ S during VOCALS-REx, Atmos. Chem. Phys., 10,
10639–10654, https://doi.org/10.5194/acp-10-10639-2010, 2010.
Brooks, M. E., Hogan, R. J., and Illingworth, A. J.: Parameterizing the
Difference in Cloud Fraction Defined by Area and by Volume as Observed with
Radar and Lidar, J. Atmos. Sci., 62, 2248–2260, https://doi.org/10.1175/JAS3467.1,
2005.
Bushell, A. C. and Martin, G. M.: The impact of vertical resolution upon GCM
simulations of marine stratocumulus, Clim. Dynam., 15, 293–318,
https://doi.org/10.1007/s003820050283, 1999.
Caldwell, P. and Bretherton, C. S.: Response of a Subtropical
Stratocumulus-Capped Mixed Layer to Climate and Aerosol Changes, J. Climate,
22, 20–38, https://doi.org/10.1175/2008JCLI1967.1, 2009.
Caldwell, P. M., Zhang, Y., and Klein, S. A.: CMIP3 subtropical stratocumulus
cloud feedback interpreted through a mixed-layer model, J. Climate, 26,
1607–1625, https://doi.org/10.1175/JCLI-D-12-00188.1, 2013.
Cesana, G. and Chepfer, H.: Evaluation of the cloud thermodynamic phase in a
climate model using CALIPSO-GOCCP, J. Geophys. Res.-Atmos., 118,
7922–7937, https://doi.org/10.1002/jgrd.50376, 2013.
Cesana, G., Waliser, D. E., Jiang, X., and Li, J. L. F.: Multimodel
evaluation of cloud phase transition using satellite and reanalysis data, J.
Geophys. Res.-Atmos., 120, 7871–7892, https://doi.org/10.1002/2014JD022932, 2015.
Cesana, G., Chepfer, H., Winker, D., Getzewich, B., Cai, X., Jourdan, O.,
Mioche, G., Okamoto, H., Hagihara, Y., Noel, V., and Reverdy, M.: Using in
situ airborne measurements to evaluate three cloud phase products derived
from CALIPSO, J. Geophys. Res.-Atmos., 121, 5788–5808,
https://doi.org/10.1002/2015JD024334, 2016.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B. N., Duncan, B. N.,
Martin, R. V., Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric
Aerosol Optical Thickness from the GOCART Model and Comparisons with
Satellite and Sun Photometer Measurements, J. Atmos. Sci., 59, 461–483,
https://doi.org/10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2,
2002.
Clarke, A. D., Owens, S. R., and Zhou, J.: An ultrafine sea-salt flux from
breaking waves: Implications for cloud condensation nuclei in the remote
marine atmosphere, J. Geophys. Res., 111, D06202,
https://doi.org/10.1029/2005JD006565, 2006.
Collins, W. D.: Parameterization of Generalized Cloud Overlap for Radiative
Calculations in General Circulation Models, J. Atmos. Sci., 58,
3224–3242, https://doi.org/10.1175/1520-0469(2001)058<3224:POGCOF>2.0.CO;2, 2001.
Cotton, W. R., Tripoli, G. J., Rauber, R. M., and Mulvihill, E. A.: Numerical
Simulation of the Effects of Varying Ice Crystal Nucleation Rates and
Aggregation Processes on Orographic Snowfall, J. Clim. Appl. Meteorol.,
25, 1658–1680, https://doi.org/10.1175/1520-0450(1986)025<1658:NSOTEO>2.0.CO;2, 1986.
Covert, D. S., Kapustin, V. N., Bates, T. S., and Quinn, P. K.: Physical
properties of marine boundary layer aerosol particles of the mid-Pacific in
relation to sources and meteorological transport, J. Geophys. Res.,
101, 6919–6930, https://doi.org/10.1029/95JD03068, 1996.
Deardorff, J. W.: Cloud Top Entrainment Instability, J. Atmos. Sci., 37,
131–147, https://doi.org/10.1175/1520-0469(1980)037<0131:CTEI>2.0.CO;2, 1980.
Duynkerke, P. G. and Teixeira, J.: Comparison of the ECMWF Reanalysis with
FIRE I Observations: Diurnal Variation of Marine Stratocumulus, J. Climate,
14, 1466–1478, https://doi.org/10.1175/1520-0442(2001)014<1466:COTERW>2.0.CO;2, 2001.
ECMWF: Clouds and large-scale precipitation, IFS Documentation, European
Centre for Medium-Range Weather Forecasts, CY25r1, Part IV, Chapter 6, 2002.
ECMWF: Clouds and large-scale precipitation, IFS Documentation, European
Centre for Medium-Range Weather Forecasts, CY43r3, Part IV, Chapter 7, 2017.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B.,
Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model
Intercomparison Project Phase 6 (CMIP6) experimental design and organization,
Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Forbes, R. M. and Ahlgrimm, M.: On the Representation of High-Latitude
Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model, Mon. Weather
Rev., 142, 3425–3445, https://doi.org/10.1175/MWR-D-13-00325.1, 2014.
Forbes, R. M., Geer, A., Lonitz, K., and Ahlgrimm, M.: Reducing systematic
errors in cold-air outbreaks, European Centre for
Medium-Range Weather Forecasts, ECMWF Newsletter, No. 146, 17–22, https://doi.org/10.21957/s 41h7q7l,
2016.
Frey, W. R. and Kay, J. E.: The influence of extratropical cloud phase and
amount feedbacks on climate sensitivity, Clim. Dynam., 50, 3097–3116,
https://doi.org/10.1007/s00382-017-3796-5, 2018.
Geleyn, J.-F. and Hollingsworth, A.: An economical analytical method for
the computation of the interaction between scattering and line absorption of
radiation, Beitr. Phys. Atmos., 52, 1–16, 1979.
Guo, Z., Wang, M., Qian, Y., Larson, V. E., Ghan, S., Ovchinnikov, M.,
Bogenschutz, P. A., Zhao, C., Lin, G., and Zhou, T.: A sensitivity analysis
of cloud properties to CLUBB parameters in the single-column Community
Atmosphere Model (SCAM5), J. Adv. Model. Earth Syst., 6, 829–858,
https://doi.org/10.1002/2014MS000315, 2015.
Hahn, C. J. and Warren, S. G.: Extended edited synoptic cloud reports from
ships and land stations over the globe, 1952–1996 (2009 update). NDP-026C,
Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory,
Oak Ridge, TN, 2009.
Heymsfield, A. J.: Precipitation Development in Stratiform Ice Clouds: A
Microphysical and Dynamical Study, J. Atmos. Sci., 34, 367–381,
https://doi.org/10.1175/1520-0469(1977)034<0367:PDISIC>2.0.CO;2, 1977.
Heymsfield, A. J. and Donner, L. J.: A Scheme for Parameterizing Ice-Cloud
Water Content in General Circulation Models, J. Atmos. Sci., 47,
1865–1877, https://doi.org/10.1175/1520-0469(1990)047<1865:ASFPIC>2.0.CO;2, 1990.
Heymsfield, A. J. and Iaquinta, J.: Cirrus Crystal Terminal Velocities, J.
Atmos. Sci., 57, 916–938, https://doi.org/10.1175/1520-0469(2000)057<0916:CCTV>2.0.CO;2, 2000.
Hoose, C., Kristjánsson, J. E., Iversen, T., Kirkevåg, A., Seland,
Ø., and Gettelman, A.: Constraining cloud droplet number concentration in
GCMs suppresses the aerosol indirect effect, Geophys. Res. Lett., 36,
L12807, https://doi.org/10.1029/2009GL038568, 2009.
Hu, Y., Rodier, S., Xu, K. M., Sun, W., Huang, J., Lin, B., Zhai, P., and
Josset, D.: Occurrence, liquid water content, and fraction of supercooled
water clouds from combined CALIOP/IIR/MODIS measurements, J. Geophys. Res., 115,
D00H34, https://doi.org/10.1029/2009JD012384, 2010.
Jakob, C.: The representation of cloud cover in Atmospheric General
Circulation Models, thesis, Fakultat fur Physik der
Ludwig-Maximilians-Universitat, European Centre for Medium-Range Weather
Forecasts, submitted, 2000.
Jiang, J. H., Su, H., Zhai, C., Perun, V. S., Del Genio, A., Nazarenko, L.
S., Donner, L. J., Horowitz, L., Seman, C., Cole, J., Gettelman, A., Ringer,
M. A., Rotstayn, L., Jeffrey, S., Wu, T., Brient, F., Dufresne, J. L.,
Kawai, H., Koshiro, T., Watanabe, M., Lécuyer, T. S., Volodin, E. M.,
Iversen, T., Drange, H., Mesquita, M. D. S., Read, W. G., Waters, J. W.,
Tian, B., Teixeira, J., and Stephens, G. L.: Evaluation of cloud and water
vapor simulations in CMIP5 climate models Using NASA “A-Train” satellite
observations, J. Geophys. Res., 117, D14105, https://doi.org/10.1029/2011JD017237,
2012.
Jones, A., Roberts, D. L., Woodage, M. J., and Johnson, C. E.: Indirect
sulphate aerosol forcing in a climate model with an interactive sulphur
cycle, J. Geophys. Res., 106, 20293–20310,
https://doi.org/10.1029/2000JD000089, 2001.
Kärcher, B. and Lohmann, U.: A Parameterization of cirrus cloud
formation: Homogeneous freezing including effects of aerosol size, J.
Geophys. Res., 107, 4698, https://doi.org/10.1029/2001JD001429,
2002.
Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud
formation: Heterogeneous freezing, J. Geophys. Res., 108, 4402,
https://doi.org/10.1029/2002JD003220, 2003.
Kärcher, B., Hendricks, J., and Lohmann, U.: Physically based
parameterization of cirrus cloud formation for use in global atmospheric
models, J. Geophys. Res., 111, D01205, https://doi.org/10.1029/2005JD006219, 2006.
Kawai, H.: Improvement of a Cloud Ice Fall Scheme in GCM, CAS/JSC WGNE
Research Activities in Atmospheric and Oceanic Modelling/WMO, 35, 4.11–4.12,
2005.
Kawai, H.: Improvement of a Stratocumulus Scheme for Mid-latitude Marine Low
Clouds, CAS/JSC WGNE Research Activities in Atmospheric and Oceanic
Modelling/WMO, 43, 4.03–4.04, 2013.
Kawai, H. and Inoue, T.: A simple parameterization scheme for subtropical
marine stratocumulus, SOLA, 2, 17–20,
https://doi.org/10.2151/sola.2006-005, 2006.
Kawai, H., Yabu, S., Hagihara, Y., Koshiro, T., and Okamoto, H.:
Characteristics of the cloud top heights of marine boundary layer clouds and
the frequency of marine fog over mid-latitudes, J. Meteorol. Soc. Jpn.,
93, 613–628, https://doi.org/10.2151/jmsj.2015-045, 2015a.
Kawai, H., Koshiro, T., Webb, M., Yukimoto, S., and Tanaka, T.: Cloud
feedbacks in MRI-CGCM3, CAS/JSC WGNE Research Activities in Atmospheric and
Oceanic Modelling/WMO, 45, 7.11–7.12, 2015b.
Kawai, H., Koshiro, T., and Webb, M. J.: Interpretation of factors
controlling low cloud cover and low cloud feedback using a unified
predictive index, J. Climate, 30, 9119–9131, https://doi.org/10.1175/JCLI-D-16-0825.1,
2017.
Kawai, H., Koshiro, T., Endo, H., and Arakawa, O.: Changes in marine fog over
the North Pacific under different climates in CMIP5 multimodel simulations,
J. Geophys. Res.-Atmos., 123, 10911–10924, https://doi.org/10.1029/2018JD028899,
2018.
Kay, J. E., Wall, C., Yettella, V., Medeiros, B., Hannay, C., Caldwell, P.,
and Bitz, C.: Global climate impacts of fixing the Southern Ocean shortwave
radiation bias in the Community Earth System Model (CESM), J. Climate, 29,
4617–4636, https://doi.org/10.1175/JCLI-D-15-0358.1, 2016.
Klein, S. A. and Hartmann, D. L.: The seasonal cycle of low stratiform
clouds, J. Climate, 6, 1587–1606, https://doi.org/10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2,
1993.
Koshiro, T., Shiotani, M., Kawai, H., and Yukimoto, S.: Evaluation of
Relationships between Subtropical Marine Low Stratiform Cloudiness and
Estimated Inversion Strength in CMIP5 Models Using the Satellite Simulator
Package COSP, SOLA, 14, 25–32, https://doi.org/10.2151/sola.2018-005, 2018.
Kuo, H.-C. and Schubert, W. H.: Stability of cloud-topped boundary layers,
Q. J. Roy. Meteor. Soc., 114, 887–916, https://doi.org/10.1002/qj.49711448204,
1988.
Larson, K., Hartmann, D. L., and Klein, S. A.: The Role of Clouds, Water
Vapor, Circulation, and Boundary Layer Structure in the Sensitivity of the
Tropical Climate, J. Climate, 12), 2359–2374,
https://doi.org/10.1175/1520-0442(1999)012<2359:TROCWV>2.0.CO;2,
1999.
Lauer, A. and Hamilton, K.: Simulating Clouds with Global Climate Models: A
Comparison of CMIP5 Results with CMIP3 and Satellite Data, J. Climate, 26,
3823–3845, https://doi.org/10.1175/JCLI-D-12-00451.1, 2013.
Lauer, A., Hamilton, K., Wang, Y., Phillips, V. T. J., and Bennartz, R.: The
Impact of Global Warming on Marine Boundary Layer Clouds over the Eastern
Pacific – A Regional Model Study, J. Climate, 23, 5844–5863,
https://doi.org/10.1175/2010JCLI3666.1, 2010.
Levkov, L., Rockel, B., Kapitza, H., and Raschke, E.: 3D mesoscale numerical
studies of cirrus and stratus clouds by their time and space evolution,
Beitr. Phys. Atmos., 65, 35–58, 1992.
Li, J. L. F., Waliser, D. E., Stephens, G., Lee, S., L'Ecuyer, T., Kato, S.,
Loeb, N., and Ma, H. Y.: Characterizing and understanding radiation budget
biases in CMIP3/CMIP5 GCMs, contemporary GCM, and reanalysis, J. Geophys.
Res.-Atmos., 118, 8166–8184, https://doi.org/10.1002/jgrd.50378, 2013.
Liu, X., Easter, R. C., Ghan, S. J., Zaveri, R., Rasch, P., Shi, X., Lamarque, J.-F.,
Gettelman, A., Morrison, H., Vitt, F., Conley, A., Park, S., Neale, R., Hannay, C.,
Ekman, A. M. L., Hess, P., Mahowald, N., Collins, W., Iacono, M. J., Bretherton, C. S.,
Flanner, M. G., and Mitchell, D.: Toward a minimal representation of aerosols in climate models: description and evaluation in the Community
Atmosphere Model CAM5, Geosci. Model Dev., 5, 709–739, https://doi.org/10.5194/gmd-5-709-2012, 2012.
Lock, A. P.: Factors influencing cloud area at the capping inversion for
shallow cumulus clouds, Q. J. Roy. Meteor. Soc., 135, 941–952,
https://doi.org/10.1002/qj.424, 2009.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward Optimal Closure of the
Earth's Top-of-Atmosphere Radiation Budget, J. Climate, 22, 748–766,
https://doi.org/10.1175/2008JCLI2637.1, 2009.
Lohmann, U.: Possible Aerosol Effects on Ice Clouds via Contact Nucleation,
J. Atmos. Sci., 59, 647–656, https://doi.org/10.1175/1520-0469(2001)059<0647:PAEOIC>2.0.CO;2, 2002.
Lohmann, U. and Diehl, K.: Sensitivity Studies of the Importance of Dust Ice
Nuclei for the Indirect Aerosol Effect on Stratiform Mixed-Phase Clouds, J.
Atmos. Sci., 63, 968–982, https://doi.org/10.1175/JAS3662.1, 2006.
Lohmann, U., Stier, P., Hoose, C., Ferrachat, S., Kloster, S., Roeckner, E., and
Zhang, J.: Cloud microphysics and aerosol indirect effects in the global
climate model ECHAM5-HAM, Atmos. Chem. Phys., 7, 3425–3446, https://doi.org/10.5194/acp-7-3425-2007, 2007.
MacVean, M. K.: A Numerical Investigation of the Criterion for Cloud-Top
Entrainment Instability, J. Atmos. Sci., 50, 2481–2495,
https://doi.org/10.1175/1520-0469(1993)050<2481:ANIOTC>2.0.CO;2,
1993.
MacVean, M. K. and Mason, P. J.: Cloud-Top Entrainment Instability through
Small-Scale Mixing and Its Parameterization in Numerical Models, J. Atmos.
Sci., 47, 1012–1030, https://doi.org/10.1175/1520-0469(1990)047<1012:CTEITS>2.0.CO;2, 1990.
Manton, M. J. and Cotton, W. R.: Formulation of approximate equations for
modeling moist deep convection on the mesoscale, Atmospheric Science Paper,
No. 266, Colorado State University, 1977.
Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta,
M., Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz,
D., Pincus, R., Schmidt, H., and Tomassini, L.: Tuning the climate of a
global model, J. Adv. Model. Earth Syst., 4, M00A01, https://doi.org/10.1029/2012MS000154, 2012.
McCoy, D. T., Hartmann, D. L., Zelinka, M. D., Ceppi, P., and Grosvenor, D.
P.: Mixed-phase cloud physics and Southern Ocean cloud feedback in climate
models, J. Geophys. Res.-Atmos., 120, 9539–9554,
https://doi.org/10.1002/2015JD023603, 2015.
McFarquhar, G. M. and Heymsfield, A. J.: Parameterization of Tropical Cirrus
Ice Crystal Size Distributions and Implications for Radiative Transfer:
Results from CEPEX, J. Atmos. Sci., 54, 2187–2200,
https://doi.org/10.1175/1520-0469(1997)054<2187:POTCIC>2.0.CO;2,
1997.
Medeiros, B., Stevens, B., Held, I. M., Zhao, M., Williamson, D. L., Olson,
J. G., and Bretherton, C. S.: Aquaplanets, Climate Sensitivity, and Low
Clouds, J. Climate, 21, 4974–4991, https://doi.org/10.1175/2008JCLI1995.1, 2008.
Meyers, M. P., DeMott, P. J., and Cotton, W. R.: New Primary Ice-Nucleation
Parameterizations in an Explicit Cloud Model, J. Appl. Meteorol., 31,
708–721, https://doi.org/10.1175/1520-0450(1992)031<0708:NPINPI>2.0.CO;2, 1992.
Miller, R. L.: Tropical Thermostats and Low Cloud Cover, J. Climate, 10,
409–440, https://doi.org/10.1175/1520-0442(1997)010<0409:TTALCC>2.0.CO;2, 1997.
Morrison, H. and Gettelman, A.: A New Two-Moment Bulk Stratiform Cloud
Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3).
Part I: Description and Numerical Tests, J. Climate, 21, 3642–3659,
https://doi.org/10.1175/2008JCLI2105.1, 2008.
Murakami, M.: Numerical Modeling of Dynamical and Microphysical Evolution of
an Isolated Convective Cloud – The 19 July 1981 CCOPE cloud, J. Meteor. Soc.
Jpn., 68, 107–128, https://doi.org/10.2151/jmsj1965.68.2_107,
1990.
Nagasawa, R.: The Problem of Cloud Overlap in the Radiation Process of JMA's
Global NWP Model, CAS/JSC WGNE Research Activities in Atmospheric and
Oceanic Modelling/WMO, 42, 0415-0416, 2012.
Nam, C., Bony, S., Dufresne, J. L., and Chepfer, H.: The 'too few, too bright'
tropical low-cloud problem in CMIP5 models, Geophys. Res. Lett., 39,
L21801, https://doi.org/10.1029/2012GL053421, 2012.
Neubauer, D., Lohmann, U., Hoose, C., and Frontoso, M. G.: Impact of the
representation of marine
stratocumulus clouds on the anthropogenic aerosol effect,
Atmos. Chem. Phys., 14, 11997–12022,
https://doi.org/10.5194/acp-14-11997-2014, 2014.
Nuijens, L., Medeiros, B., Sandu, I., and Ahlgrimm, M.: The behavior of
trade-wind cloudiness in observations and models: The major cloud components
and their variability, J. Adv. Model. Earth Syst., 7, 600–616,
https://doi.org/10.1002/2014MS000390, 2015.
Pincus, R., Platnick, S., Ackerman, S. A., Hemler, R. S., and Patrick
Hofmann, R. J.: Reconciling simulated and observed views of clouds: MODIS,
ISCCP, and the limits of instrument simulators, J. Climate, 25,
4699–4720, https://doi.org/10.1175/JCLI-D-11-00267.1, 2012.
Qu, X., Hall, A., Klein, S. A., and Caldwell, P. M.: On the spread of changes
in marine low cloud cover in climate model simulations of the 21st century,
Clim. Dynam., 42, 2603–2626, https://doi.org/10.1007/s00382-013-1945-z, 2014.
Rahn, D. A. and Garreaud, R.: Marine boundary layer over the subtropical southeast
Pacific during VOCALS-REx -– Part 1: Mean structure and diurnal cycle,
Atmos. Chem. Phys., 10, 4491–4506, https://doi.org/10.5194/acp-10-4491-2010, 2010.
Randall, D. A.: Conditional Instability of the First Kind Upside-Down, J.
Atmos. Sci., 37, 125–130, https://doi.org/10.1175/1520-0469(1980)037<0125:CIOTFK>2.0.CO;2, 1980.
Rossow, W. B. and Schiffer, R. A.: Advances in Understandig Clouds from
ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287,
https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2,
1999.
Rotstayn, L. D.: A physically based scheme for the treatment of stratiform
clouds and precipitation in large-scale models. I: Description and
evaluation of the microphysical processes, Q. J. Roy. Meteor. Soc.,
123, 1227–1282, https://doi.org/10.1002/qj.49712354106, 1997.
Rotstayn, L. D.: On the “tuning” of autoconversion parameterizations in
climate models, J. Geophys. Res., 105, 15495–15507,
https://doi.org/10.1029/2000JD900129, 2000.
Rutledge, S. A. and Hobbs, P.: The Mesoscale and Microscale Structure and
Organization of Clouds and Precipitation in Midlatitude Cyclones. VIII: A
Model for the “Seeder-Feeder” Process in Warm-Frontal Rainbands, J. Atmos.
Sci., 40, 1185–1206, https://doi.org/10.1175/1520-0469(1983)040<1185:TMAMSA>2.0.CO;2, 1983.
Seinfeld, J. H., and Pandis, S. N.: Atmospheric Chemistry and Physics: From
Air Pollution to Climate Change 2nd ed, John Wiley & Sons, New York, USA,
1203, 2006.
Siebesma, A. P., Jakob, C., Lenderink, G., Neggers, R. A. J., Teixeira, J.,
van Meijgaard, E., Calvo, J., Chlond, A., Grenier, H., Jones, C.,
Köhler, M., Kitagawa, H., Marquet, P., Lock, A. P., Müller, F.,
Olmeda, D. C., and Severijns, C.: Cloud representation in general-circulation
models over the northern Pacific Ocean: A EUROCS intercomparison study, Q.
J. Roy. Meteor. Soc., 130, 3245–3267, https://doi.org/10.1256/qj.03.146, 2004.
Slingo, J. M.: A cloud parametrization scheme derived from GATE data for use
with a numerical model, Q. J. Roy. Meteor. Soc., 106, 747–770,
https://doi.org/10.1002/qj.49710645008, 1980.
Slingo, J. M.: The Development and Verification of A Cloud Prediction Scheme
For the Ecmwf Model, Q. J. Roy. Meteor. Soc., 113, 899–927,
https://doi.org/10.1002/qj.49711347710, 1987.
Smith, R. N. B.: A scheme for predicting layer clouds and their water
content in a general circulation model, Q. J. Roy. Meteor. Soc., 116,
435–460, https://doi.org/10.1002/qj.49711649210, 1990.
Soden, B. J. and Held, I. M.: An Assessment of Climate Feedbacks in Coupled
Ocean – Atmosphere Models, J. Climate, 19, 3354–3360,
https://doi.org/10.1175/JCLI9028.1, 2006.
Soden, B. J., Held, I. M., Colman, R. C., Shell, K. M., Kiehl, J. T., and
Shields, C. A.: Quantifying climate feedbacks using radiative kernels, J.
Climate, 21, 3504–3520, https://doi.org/10.1175/2007JCLI2110.1, 2008.
Su, H., Jiang, J. H., Zhai, C., Perun, V. S., Shen, J. T., Del Genio, A.,
Nazarenko, L. S., Donner, L. J., Horowitz, L., Seman, C., Morcrette, C.,
Petch, J., Ringer, M., Cole, J., Von Salzen, K., Mesquita, M. D. S.,
Iversen, T., Kristjansson, J. E., Gettelman, A., Rotstayn, L., Jeffrey, S.,
Dufresne, J. L., Watanabe, M., Kawai, H., Koshiro, T., Wu, T., Volodin, E.
M., L'Ecuyer, T., Teixeira, J., and Stephens, G. L.: Diagnosis of
regime-dependent cloud simulation errors in CMIP5 models using “a-Train”
satellite observations and reanalysis data, J. Geophys. Res.-Atmos., 118,
2762–2780, https://doi.org/10.1029/2012JD018575, 2013.
Suzuki, K., Stephens, G., Bodas-Salcedo, A., Wang, M., Golaz, J.-C.,
Yokohata, T., and Koshiro, T.: Evaluation of the Warm Rain Formation Process
in Global Models with Satellite Observations, J. Atmos. Sci., 72,
3996–4014, https://doi.org/10.1175/JAS-D-14-0265.1, 2015.
Takemura, T., Nozawa, T., Emori, S., Nakajima, T. Y., and Nakajima, T.:
Simulation of climate response to aerosol direct and indirect effects with
aerosol transport-radiation model, J. Geophys. Res., 110, D02202,
https://doi.org/10.1029/2004JD005029, 2005.
Tan, I. and Storelvmo, T.: Sensitivity Study on the Influence of Cloud
Microphysical Parameters on Mixed-Phase Cloud Thermodynamic Phase
Partitioning in CAM5, J. Atmos. Sci., 73, 709–728,
https://doi.org/10.1175/JAS-D-15-0152.1, 2016.
Tan, I., Storelvmo, T., and Zelinka, M. D.: Observational constraints on
mixed-phase clouds imply higher climate sensitivity, Science,
352, 224–227, https://doi.org/10.1126/science.aad5300, 2016.
Tanaka, T. Y., Orito, K., Sekiyama, T. T., Shibata, K., Chiba, M., and
Tanaka, H.: MASINGAR, a global tropospheric aerosol chemical transport model
coupled with MRI/JMA98 GCM: Model description, Pap. Meteorol. Geophys.,
53, 119–138, https://doi.org/10.2467/mripapers.53.119, 2003.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res., 106, 7183–7192,
https://doi.org/10.1029/2000JD900719, 2001.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498,
https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Teixeira, J.: The impact of increased boundary layer vertical resolution on
the ECMWF forecast system, European Centre for
Medium-Range Weather Forecasts, ECMWF technical memorandum, 268, 1–55, 1999.
Tiedtke, M.: Representation of Clouds in Large-Scale Models, Mon. Weather Rev.,
121, 3040–3061, 1993.
Trenberth, K. E. and Fasullo, J. T.: Simulation of present-day and
twenty-first-century energy budgets of the southern oceans, J. Climate., 23,
440–454, https://doi.org/10.1175/2009JCLI3152.1, 2010.
Tsushima, Y., Emori, S., Ogura, T., Kimoto, M., Webb, M. J., Williams, K.
D., Ringer, M. A., Soden, B. J., Li, B., and Andronova, N.: Importance of the
mixed-phase cloud distribution in the control climate for assessing the
response of clouds to carbon dioxide increase: a multi-model study, Clim.
Dynam., 27, 113–126, https://doi.org/10.1007/s00382-006-0127-7, 2006.
Tsushima, Y., Ringer, M. A., Webb, M. J., and Williams, K. D.: Quantitative
evaluation of the seasonal variations in climate model cloud regimes, Clim.
Dynam., 41, 2679–2696, https://doi.org/10.1007/s00382-012-1609-4, 2013.
Tsushima, Y., Ringer, M. A., Koshiro, T., Kawai, H., Roehrig, R., Cole, J.,
Watanabe, M., Yokohata, T., Bodas-Salcedo, A., Williams, K. D., and Webb, M.
J.: Robustness, uncertainties, and emergent constraints in the radiative
responses of stratocumulus cloud regimes to future warming, Clim. Dynam.,
46, https://doi.org/10.1007/s00382-015-2750-7, 2016.
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D.
C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A.,
Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E.,
Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. Van De, Bidlot, J.,
Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher,
M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L.,
Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette,
J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K.
E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40
re-analysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012,
https://doi.org/10.1256/qj.04.176, 2005.
Wang, Y., Xu, H. and Xie, S.-P.: Regional Model Simulations of Marine
Boundary Layer Clouds over the Southeast Pacific off South America. Part II:
Sensitivity Experiments, Mon. Weather Rev., 132, 2650–2668,
https://doi.org/10.1175/MWR2812.1, 2004.
Webb, M. J., Lambert, F. H., and Gregory, J. M.: Origins of differences in
climate sensitivity, forcing and feedback in climate models, Clim. Dynam.,
40, 677–707, https://doi.org/10.1007/s00382-012-1336-x, 2013.
Webb, M. J., Andrews, T., Bodas-Salcedo, A., Bony, S., Bretherton, C. S., Chadwick, R.,
Chepfer, H., Douville, H., Good, P., Kay, J. E., Klein, S. A., Marchand, R., Medeiros, B.,
Siebesma, A. P., Skinner, C. B., Stevens, B., Tselioudis, G., Tsushima, Y., and Watanabe, M.:
The Cloud Feedback Model Intercomparison Project (CFMIP)
contribution to CMIP6, Geosci. Model Dev., 10, 359–384,
https://doi.org/10.5194/gmd-10-359-2017, 2017.
Williams, K. D., Ringer, M. A., Senior, C. A., Webb, M. J., McAvaney, B. J.,
Andronova, N., Bony, S., Dufresne, J. L., Emori, S., Gudgel, R., Knutson,
T., Li, B., Lo, K., Musat, I., Wegner, J., Slingo, A., and Mitchell, J. F.
B.: Evaluation of a component of the cloud response to climate change in an
intercomparison of climate models, Clim. Dynam., 26, 145–165,
https://doi.org/10.1007/s00382-005-0067-7, 2006.
Wilson, D. R., Smith, R. N. B., Gregory, D., Wilson, C. A., Bushell, A. C.,
and Cusack, S.: The large-scale cloud scheme and saturated specific
humidity, Unified Model documentation paper, 29, Met Office, Exeter, UK,
2007.
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., Morcrette,
C. J., and Bodas-Salcedo, A.: PC2: A prognostic cloud fraction and
condensation scheme. II: Climate model simulations, Q. J. Roy. Meteor. Soc.,
134, 2109–2125, https://doi.org/10.1002/qj.332, 2008.
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z.,
Hunt, W. H., and Young, S. A.: Overview of the CALIPSO Mission and CALIOP
Data Processing Algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323,
https://doi.org/10.1175/2009JTECHA1281.1, 2009.
Wood, R.: Stratocumulus Clouds, Mon. Weather Rev., 140, 2373–2423,
https://doi.org/10.1175/MWR-D-11-00121.1, 2012.
Wood, R. and Bretherton, C. S.: On the relationship between stratiform low
cloud cover and lower-tropospheric stability, J. Climate, 19, 6425–6432,
https://doi.org/10.1175/JCLI3988.1, 2006.
Yamaguchi, T. and Randall, D. A.: Large-Eddy Simulation of Evaporatively
Driven Entrainment in Cloud-Topped Mixed Layers, J. Atmos. Sci., 65,
1481–1504, https://doi.org/10.1175/2007JAS2438.1, 2008.
Yukimoto, S., Yoshimura, H., Hosaka, M., Sakami, T., Tsujino, H., Hirabara,
M., Tanaka, T. Y., Deushi, M., Obata, A., Nakano, H., Adachi, Y., Shindo,
E., Yabu, S., Ose, T., and Kitoh, A.: Meteorological Research Institute
Earth System Model Version 1 (MRI-ESM1) – Model Description, Tech. Rep.
of MRI, 64, 83 pp., available at:
http://www.mri-jma.go.jp/Publish/Technical/index_en.html (last access: 4 July 2019),
2011.
Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara,
M., Tanaka, T. Y., Shindo, E., Tsujino, H., Deushi, M., Mizuta, R., Yabu,
S., Obata, A., Nakano, H., Koshiro, T., Ose, T., and Kitoh, A.: A new global
climate model of the Meteorological Research Institute: MRI-CGCM3 –Model
Description and Basic Performance, J. Meteorol. Soc. Jpn., 90A, 23–64,
https://doi.org/10.2151/jmsj.2012-A02, 2012.
Yukimoto, S., Kawai, H., Koshiro, T., Oshima, N., Yoshida, K., Urakawa, S.,
Tsujino, H., Deushi, M., Tanaka, T., Hosaka, M., Yabu, S., Yoshimura, H.,
Shindo, E., Mizuta, R., Obata, A., Adachi, Y. and Ishii, M.: The
Meteorological Research Institute Earth System Model version 2.0,
MRI-ESM2.0: Description and basic evaluation of the physical component, J.
Meteor. Soc. Jpn., 97, https://doi.org/10.2151/jmsj.2019-051, in press,
2019.
Zhang, Y., Xie, S., Covey, C., Lucas, D. D., Gleckler, P., Klein, S. A.,
Tannahill, J., Doutriaux, C., and Klein, R.: Regional assessment of the
parameter-dependent performance of CAM4 in simulating tropical clouds,
Geophys. Res. Lett., 39, L14708, https://doi.org/10.1029/2012GL052184, 2012.
Zurovac-Jevtić, D. and Zhang, G. J.: Development and Test of a Cirrus
Parameterization Scheme Using NCAR CCM3, J. Atmos. Sci., 60, 1325–1344,
https://doi.org/10.1175/1520-0469(2003)060<1325:DATOAC>2.0.CO;2,
2003.
Short summary
The representation of clouds was significantly improved in the climate model MRI-ESM2. The model is planned for use in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) simulations. In particular, a notorious lack of reflection of solar radiation over the Southern Ocean was drastically improved in the model. The score of the spatial pattern of radiative fluxes for MRI-ESM2 is better than for any CMIP5 model. We present modifications implemented in the various physics schemes.
The representation of clouds was significantly improved in the climate model MRI-ESM2. The model...
