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.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael J. Prather, Alexander T. Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Christopher J. Smith, Steven T. Turnock, Duncan Watson-Parris, and Paul J. Young
EGUsphere, https://doi.org/10.5194/egusphere-2024-2528, https://doi.org/10.5194/egusphere-2024-2528, 2024
Short summary
Short summary
The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. In this paper, we review its contribution to AR6, and the wider understanding of the role of these species in climate and climate change. We identify remaining challenges concluding with recommendations aimed to improve the utility and uptake of climate model data to address the role of short-lived climate forcers in the Earth system.
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
Atmos. Chem. Phys., 24, 7837–7872, https://doi.org/10.5194/acp-24-7837-2024, https://doi.org/10.5194/acp-24-7837-2024, 2024
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 S. Hammer, Larry W. 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
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
Short summary
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 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 the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
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.
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
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Architectural Insights and Training Methodology Optimization of Pangu-Weather
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Robust handling of extremes in quantile mapping – "Murder your darlings"
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
Evaluation of global fire simulations in CMIP6 Earth system models
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Design, evaluation and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Introducing the MESMER-M-TPv0.1.0 module: Spatially Explicit Earth System Model Emulation for Monthly Precipitation and Temperature
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
A computationally light-weight model for ensemble forecasting of environmental hazard: General TAMSAT-ALERT v1.2.1
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
Short summary
Short summary
We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
Short summary
Short summary
In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
Short summary
Short summary
This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
Short summary
Short summary
Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
Short summary
Short summary
In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
Short summary
Short summary
Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
Short summary
Short summary
This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
Short summary
Short summary
We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
Short summary
Short summary
This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
Short summary
Short summary
The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
Short summary
Short summary
A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
Short summary
Short summary
We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
Short summary
Short summary
A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
Short summary
Short summary
Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
Short summary
Short summary
Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
Short summary
Short summary
We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
Short summary
Short summary
Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
Short summary
Short summary
Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
Short summary
Short summary
The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
Short summary
Short summary
We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
Short summary
Short summary
Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
Short summary
Short summary
Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
Short summary
Short summary
Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20–30%. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases accessibility of training and working with the model.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
Short summary
Short summary
Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
Short summary
Short summary
The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Short summary
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. 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
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
Short summary
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 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 the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
Short summary
Short summary
The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
Short summary
Short summary
This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
Short summary
Short summary
We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
Short summary
Short summary
The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
Short summary
Short summary
We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
Short summary
Short summary
Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
Short summary
Short summary
To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
Short summary
Short summary
This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
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
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
Short summary
Short summary
Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-85, https://doi.org/10.5194/gmd-2024-85, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study provides the first comprehensive assessment of historical fire simulations from 19 CMIP6 ESMs. Most models reproduce global total, spatial pattern, seasonality, and regional historical changes well, but fail to simulate the recent decline in global burned area and underestimate the fire sensitivity to wet-dry conditions. They addressed three critical issues in CMIP5. We present targeted guidance for fire scheme development and methodologies to generate reliable fire projections.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
Short summary
Short summary
All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Giovanni Di Virgilio, Jason Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew Riley, and Jyothi Lingala
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-87, https://doi.org/10.5194/gmd-2024-87, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models, and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows to generate monthly means of local precipitation and temperature at low computational costs.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
Short summary
Short summary
We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
Short summary
Short summary
In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Emily Black, John Ellis, and Ross Maidment
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-75, https://doi.org/10.5194/gmd-2024-75, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present General TAMSAT-ALERT: a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and forecasting data into probabilistic hazard assessments. As such, it complements existing systems and enhances their utility for actionable hazard assessment.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
Short summary
Short summary
Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
Short summary
Short summary
Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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 driven by either uniform erosion 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.
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...
