Articles | Volume 14, issue 5
https://doi.org/10.5194/gmd-14-2977-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-2977-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
26 May 2021
Model description paper |
| 26 May 2021
| 26 May 2021
BCC-CSM2-HR: a high-resolution version of the Beijing Climate Center Climate System Model
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Rucong Yu
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Yixiong Lu
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Weihua Jie
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Yongjie Fang
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Jie Zhang
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Li Zhang
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Xiaoge Xin
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Laurent Li
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Laboratoire de Météorologie Dynamique, IPSL, CNRS, Sorbonne Université, Ecole Normale Supérieure, Ecole Polytechnique, Paris 75005, France
Zaizhi Wang
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Yiming Liu
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Fang Zhang
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Fanghua Wu
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Min Chu
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Jianglong Li
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Weiping Li
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Yanwu Zhang
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Xueli Shi
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Wenyan Zhou
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Junchen Yao
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Xiangwen Liu
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
He Zhao
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Jinghui Yan
Beijing Climate Center, China Meteorological Administration, Beijing 100081, China
Min Wei
National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China
Wei Xue
Tsinghua University, Beijing 100084, China
Anning Huang
Nanjing University, Nanjing 210023, China
Yaocun Zhang
Nanjing University, Nanjing 210023, China
Yu Zhang
Chengdu University of Information Technology, Chengdu 610225, China
The First Institute of Oceanography of the Ministry of Natural Resources, Qingdao 266061, China
National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado 80307-3000, USA
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Lilong Zhou and Wei Xue
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Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
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Di Wang, Camille Risi, Lide Tian, Di Yang, Gabriel Bowen, Siteng Fan, Yang Su, Hongxi Pang, and Laurent Li
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-151, https://doi.org/10.5194/amt-2024-151, 2024
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Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
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
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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.
Junli Yang, Weijun Quan, Li Zhang, Jianglin Hu, Qiying Chen, and Martin Wild
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-74, https://doi.org/10.5194/gmd-2024-74, 2024
Revised manuscript not accepted
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Due to the difficulties involved in the measurements of the Downward long-wave irradiance (DnLWI), the numerical weather prediction (NWP) models have been developed to obtain the DnLWI indirectly. In this study, a long-term high time-resolution (1 min) observational dataset of the DnLWI in China was used to evaluate the radiation scheme in the CMA-MESO model over various underlying surfaces and climate zones.
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
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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.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
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
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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.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev., 16, 1975–1995, https://doi.org/10.5194/gmd-16-1975-2023, https://doi.org/10.5194/gmd-16-1975-2023, 2023
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The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult; however, it is unclear whether TPs exist in global climate models. Here, we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP).
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
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A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Di Wang, Lide Tian, Camille Risi, Xuejie Wang, Jiangpeng Cui, Gabriel J. Bowen, Kei Yoshimura, Zhongwang Wei, and Laurent Z. X. Li
Atmos. Chem. Phys., 23, 3409–3433, https://doi.org/10.5194/acp-23-3409-2023, https://doi.org/10.5194/acp-23-3409-2023, 2023
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To better understand the spatial and temporal distribution of vapor isotopes, we present two vehicle-based spatially continuous snapshots of the near-surface vapor isotopes in China during the pre-monsoon and monsoon periods. These observations are explained well by different moisture sources and processes along the air mass trajectories. Our results suggest that proxy records need to be interpreted in the context of regional systems and sources of moisture.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, https://doi.org/10.5194/acp-22-13753-2022, 2022
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We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Yuejin Ye, Zhenya Song, Shengchang Zhou, Yao Liu, Qi Shu, Bingzhuo Wang, Weiguo Liu, Fangli Qiao, and Lanning Wang
Geosci. Model Dev., 15, 5739–5756, https://doi.org/10.5194/gmd-15-5739-2022, https://doi.org/10.5194/gmd-15-5739-2022, 2022
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The swNEMO_v4.0 is developed with ultrahigh scalability through the concepts of hardware–software co-design based on the characteristics of the new Sunway supercomputer and NEMO4. Three breakthroughs, including an adaptive four-level parallelization design, many-core optimization and mixed-precision optimization, are designed. The simulations achieve 71.48 %, 83.40 % and 99.29 % parallel efficiency with resolutions of 2 km, 1 km and 500 m using 27 988 480 cores, respectively.
Peter Hitchcock, Amy Butler, Andrew Charlton-Perez, Chaim I. Garfinkel, Tim Stockdale, James Anstey, Dann Mitchell, Daniela I. V. Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, Bill Merryfield, Michael Sigmond, Baoqiang Xiang, Liwei Jia, Yu-Kyung Hyun, Jiyoung Oh, Damien Specq, Isla R. Simpson, Jadwiga H. Richter, Cory Barton, Jeff Knight, Eun-Pa Lim, and Harry Hendon
Geosci. Model Dev., 15, 5073–5092, https://doi.org/10.5194/gmd-15-5073-2022, https://doi.org/10.5194/gmd-15-5073-2022, 2022
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This paper describes an experimental protocol focused on sudden stratospheric warmings to be carried out by subseasonal forecast modeling centers. These will allow for inter-model comparisons of these major disruptions to the stratospheric polar vortex and their impacts on the near-surface flow. The protocol will lead to new insights into the contribution of the stratosphere to subseasonal forecast skill and new approaches to the dynamical attribution of extreme events.
Xin Wang, Yilun Han, Wei Xue, Guangwen Yang, and Guang J. Zhang
Geosci. Model Dev., 15, 3923–3940, https://doi.org/10.5194/gmd-15-3923-2022, https://doi.org/10.5194/gmd-15-3923-2022, 2022
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This study uses a set of deep neural networks to learn a parameterization scheme from a superparameterized general circulation model (GCM). After being embedded in a realistically configurated GCM, the parameterization scheme performs stably in long-term climate simulations and reproduces reasonable climatology and climate variability. This success is the first for long-term stable climate simulations using machine learning parameterization under real geographical boundary conditions.
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
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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.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-52, https://doi.org/10.5194/gmd-2022-52, 2022
Revised manuscript not accepted
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A new global surface wave-tide-circulation coupled ocean model FIO-COM32 with resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are proved to be important contributors to the significant improvements of FIO-COM32 simulations. It should be the time to merge these separated model components (surface wave, tidal current and ocean circulation) for new generation ocean model development.
Tingfeng Wu, Boqiang Qin, Anning Huang, Yongwei Sheng, Shunxin Feng, and Céline Casenave
Geosci. Model Dev., 15, 745–769, https://doi.org/10.5194/gmd-15-745-2022, https://doi.org/10.5194/gmd-15-745-2022, 2022
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Most hydrodynamic models were initially developed based in marine environments. They cannot be directly applied to large lakes. Based on field observations and numerical experiments of a large shallow lake, we developed a hydrodynamic model by adopting new schemes of wind stress, wind waves, and turbulence for large lakes. Our model can greatly improve the simulation of lake currents. This study will be a reminder to limnologists to prudently use ocean models to study lake hydrodynamics.
Jie Zhang, Kalli Furtado, Steven T. Turnock, Jane P. Mulcahy, Laura J. Wilcox, Ben B. Booth, David Sexton, Tongwen Wu, Fang Zhang, and Qianxia Liu
Atmos. Chem. Phys., 21, 18609–18627, https://doi.org/10.5194/acp-21-18609-2021, https://doi.org/10.5194/acp-21-18609-2021, 2021
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The CMIP6 ESMs systematically underestimate TAS anomalies in the NH midlatitudes, especially from 1960 to 1990. The anomalous cooling is concurrent in time and space with anthropogenic SO2 emissions. The spurious drop in TAS is attributed to the overestimated aerosol concentrations. The aerosol forcing sensitivity cannot well explain the inter-model spread of PHC biases. And the cloud-amount term accounts for most of the inter-model spread in aerosol forcing sensitivity.
Yixiong Lu, Tongwen Wu, Yubin Li, and Ben Yang
Geosci. Model Dev., 14, 5183–5204, https://doi.org/10.5194/gmd-14-5183-2021, https://doi.org/10.5194/gmd-14-5183-2021, 2021
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The spurious precipitation in the tropical southeastern Pacific and southern Atlantic is one of the most prominent systematic biases in coupled atmosphere–ocean general circulation models. This study significantly promotes the marine stratus simulation and largely alleviates the excessive precipitation biases through improving parameterizations of boundary-layer turbulence and shallow convection, providing an effective solution to the long-standing bias in the tropical precipitation simulation.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
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
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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.
Yuan Zhang, Olivier Boucher, Philippe Ciais, Laurent Li, and Nicolas Bellouin
Geosci. Model Dev., 14, 2029–2039, https://doi.org/10.5194/gmd-14-2029-2021, https://doi.org/10.5194/gmd-14-2029-2021, 2021
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We investigated different methods to reconstruct spatiotemporal distribution of the fraction of diffuse radiation (Fdf) to qualify the aerosol impacts on GPP using the ORCHIDEE_DF land surface model. We find that climatological-averaging methods which dampen the variability of Fdf can cause significant bias in the modeled diffuse radiation impacts on GPP. Better methods to reconstruct Fdf are recommended.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
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Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Zun Yin, Catherine Ottlé, Philippe Ciais, Feng Zhou, Xuhui Wang, Polcher Jan, Patrice Dumas, Shushi Peng, Laurent Li, Xudong Zhou, Yan Bo, Yi Xi, and Shilong Piao
Hydrol. Earth Syst. Sci., 25, 1133–1150, https://doi.org/10.5194/hess-25-1133-2021, https://doi.org/10.5194/hess-25-1133-2021, 2021
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We improved the irrigation module in a land surface model ORCHIDEE and developed a dam operation model with the aim to investigate how irrigation and dams affect the streamflow fluctuations of the Yellow River. Results show that irrigation mainly reduces the annual river flow. The dam operation, however, mainly affects streamflow variation. By considering two generic operation rules, flood control and base flow guarantee, our dam model can sustainably improve the simulation accuracy.
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
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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.
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
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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.
Yihui Zhou, Yi Zhang, Jian Li, Rucong Yu, and Zhuang Liu
Geosci. Model Dev., 13, 6325–6348, https://doi.org/10.5194/gmd-13-6325-2020, https://doi.org/10.5194/gmd-13-6325-2020, 2020
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This paper explores the configuration of a global atmospheric model (global-to-regional integrated forecast system-atmosphere; GRIST-A) with various multiresolution grids. The model performance is evaluated from dry dynamics to simple physics and full physics. The model is able to resolve the fine-scale structures in the grid-refinement region, and the adverse impact due to the mesh transition and the coarse-resolution area can be controlled well.
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
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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.
Lena R. Boysen, Victor Brovkin, Julia Pongratz, David M. Lawrence, Peter Lawrence, Nicolas Vuichard, Philippe Peylin, Spencer Liddicoat, Tomohiro Hajima, Yanwu Zhang, Matthias Rocher, Christine Delire, Roland Séférian, Vivek K. Arora, Lars Nieradzik, Peter Anthoni, Wim Thiery, Marysa M. Laguë, Deborah Lawrence, and Min-Hui Lo
Biogeosciences, 17, 5615–5638, https://doi.org/10.5194/bg-17-5615-2020, https://doi.org/10.5194/bg-17-5615-2020, 2020
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We find a biogeophysically induced global cooling with strong carbon losses in a 20 million square kilometre idealized deforestation experiment performed by nine CMIP6 Earth system models. It takes many decades for the temperature signal to emerge, with non-local effects playing an important role. Despite a consistent experimental setup, models diverge substantially in their climate responses. This study offers unprecedented insights for understanding land use change effects in CMIP6 models.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
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Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
Xiao Lu, Lin Zhang, Tongwen Wu, Michael S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, and Min Wei
Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, https://doi.org/10.5194/gmd-13-3817-2020, 2020
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This study presents the development and evaluation of a new climate chemistry model, BCC-GEOS-Chem v1.0, which couples the GEOS-Chem chemical transport model as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model. A 3-year (2012–2014) simulation of BCC-GEOS-Chem v1.0 shows that the model captures well the spatiotemporal distributions of tropospheric ozone, other gaseous pollutants, and aerosols.
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Short summary
This paper presents the high-resolution version of the Beijing Climate Center (BCC) Climate System Model, BCC-CSM2-HR, and describes its climate simulation performance including the atmospheric temperature and wind; precipitation; and the tropical climate phenomena such as TC, MJO, QBO, and ENSO. BCC-CSM2-HR is our model version contributing to the HighResMIP. We focused on its updates and differential characteristics from its predecessor, the medium-resolution version BCC-CSM2-MR.
This paper presents the high-resolution version of the Beijing Climate Center (BCC) Climate...
