Articles | Volume 16, issue 22
https://doi.org/10.5194/gmd-16-6857-2023
© Author(s) 2023. 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-16-6857-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A sub-grid parameterization scheme for topographic vertical motion in CAM5-SE
Yaqi Wang
China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, Beijing 100081, China
College of Global Change and Earth System Science (GCESS), Beijing Normal University, Beijing 100875, China
Lanning Wang
CORRESPONDING AUTHOR
College of Global Change and Earth System Science (GCESS), Beijing Normal University, Beijing 100875, China
Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China
Juan Feng
College of Global Change and Earth System Science (GCESS), Beijing Normal University, Beijing 100875, China
Zhenya Song
Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
Qizhong Wu
College of Global Change and Earth System Science (GCESS), Beijing Normal University, Beijing 100875, China
Huaqiong Cheng
College of Global Change and Earth System Science (GCESS), Beijing Normal University, Beijing 100875, China
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Jiayi Lai, Lanning Wang, Qizhong Wu, Yizhou Yang, and Fang Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2986, https://doi.org/10.5194/egusphere-2024-2986, 2024
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In this study, we applied the quasi double-precision algorithm to MPAS-A. Found that, the algorithm can effectively reduce the errors introduced by using low precision through the iterative process of time integration. The error of surface pressure of 4 cases are reduced by 68%, 75%, 97%, 96%. When applied the quasi double-precision algorithm in MPAS-A, we achieved to reduce all double precision to single precision, memory has been reduced by almost half, while the computation increases only 2%.
Lei Kong, Xiao Tang, Zifa Wang, Jiang Zhu, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Jie Li, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 16, 4351–4387, https://doi.org/10.5194/essd-16-4351-2024, https://doi.org/10.5194/essd-16-4351-2024, 2024
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A new long-term inversed emission inventory for Chinese air quality (CAQIEI) is developed in this study, which contains constrained monthly emissions of NOx, SO2, CO, PM2.5, PM10, and NMVOCs in China from 2013 to 2020 with a horizontal resolution of 15 km. Emissions of different air pollutants and their changes during 2013–2020 were investigated and compared with previous emission inventories, which sheds new light on the complex variations of air pollutant emissions in China.
Falei Xu, Shuang Wang, Yan Li, and Juan Feng
Atmos. Chem. Phys., 24, 10689–10705, https://doi.org/10.5194/acp-24-10689-2024, https://doi.org/10.5194/acp-24-10689-2024, 2024
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This study examines how the winter North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) affect dust activities in North China during the following spring. The results show that the NAO and ENSO, particularly in their negative phases, greatly influence dust activities. When both are negative, their combined effect on dust activities is even greater. This research highlights the importance of these climate patterns in predicting spring dust activities in North China.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1437, https://doi.org/10.5194/egusphere-2024-1437, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can well reproduce the distribution of PAHs. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change of BaP is less than PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although "the Action Plan" has been implemented.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
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.
Xianwei Wu, Liang Hu, Lanning Wang, Haitian Lu, and Juepeng Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-164, https://doi.org/10.5194/gmd-2023-164, 2023
Revised manuscript not accepted
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In order to build an effective surrogate model for the community atmospheric model (CAM). We present a surrogate model-based parameter tuning framework for the CAM and apply it to improve the CAM5 precipitation performance and propose a multilevel surrogate model-based optimization method. We design a nonuniform parameter parameterization scheme and integrate the parameters using a parameter smoothing scheme, and the experimental results improve in four regions.
Kai Cao, Qizhong Wu, Lingling Wang, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongqing Li, and Lanning Wang
Geosci. Model Dev., 16, 4367–4383, https://doi.org/10.5194/gmd-16-4367-2023, https://doi.org/10.5194/gmd-16-4367-2023, 2023
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Offline performance experiment results show that the GPU-HADVPPM on a V100 GPU can achieve up to 1113.6 × speedups to its original version on an E5-2682 v4 CPU. A series of optimization measures are taken, and the CAMx-CUDA model improves the computing efficiency by 128.4 × on a single V100 GPU card. A parallel architecture with an MPI plus CUDA hybrid paradigm is presented, and it can achieve up to 4.5 × speedup when launching eight CPU cores and eight GPU cards.
Jinming Feng, Meng Luo, Jun Wang, Yuan Qiu, Qizhong Wu, and Ke Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-867, https://doi.org/10.5194/egusphere-2023-867, 2023
Preprint withdrawn
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We modified the code of the Weather Research and Forecasting Model (WRF) v3.8.1 to include the forcing components more than the Greenhouse Gases and evaluate the impact of forcing configurations on the climate simulation results in China. It showed that different external forcing configurations in WRF could result in considerable impact on the annual temperature and precipitation trend, which was stronger than parameterization schemes but was weaker than spectral nudging.
Yan Li, Falei Xu, Juan Feng, Mengying Du, Wenjun Song, Chao Li, and Wenjing Zhao
Atmos. Chem. Phys., 23, 6021–6042, https://doi.org/10.5194/acp-23-6021-2023, https://doi.org/10.5194/acp-23-6021-2023, 2023
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There is a significantly negative relationship between boreal winter North Atlantic Oscillation (NAO) and dust aerosols (DAs) in the eastern part of China (30–40°N, 105–120°E), which is not a DA source area but is severely affected by the dust events (DEs). Under the effect of the NAO negative phase, main atmospheric circulation during the DEs is characterized by variation of the transient eddy flux. The work is of reference value to the prediction of DEs and the understanding of their causes.
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.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
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We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
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.
Qian Ma, Kaicun Wang, Yanyi He, Liangyuan Su, Qizhong Wu, Han Liu, and Youren Zhang
Earth Syst. Sci. Data, 14, 463–477, https://doi.org/10.5194/essd-14-463-2022, https://doi.org/10.5194/essd-14-463-2022, 2022
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Surface incident solar radiation plays a key role in atmospheric circulation, the water cycle, and ecological equilibrium on Earth. A homogenized century-long surface incident solar radiation dataset was obtained over Japan.
Ying Wei, Xueshun Chen, Huansheng Chen, Yele Sun, Wenyi Yang, Huiyun Du, Qizhong Wu, Dan Chen, Xiujuan Zhao, Jie Li, and Zifa Wang
Geosci. Model Dev., 14, 4411–4428, https://doi.org/10.5194/gmd-14-4411-2021, https://doi.org/10.5194/gmd-14-4411-2021, 2021
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The sub-grid particle formation (SGPF) in plumes plays an important role in air pollution and climate. We coupled an SGPF scheme to a chemical transport model with an aerosol microphysics module and applied it to investigate the SGPF impact over China. The scheme clearly improved the model performance in simulating aerosol components and particle number at typical sites influenced by point sources. The results indicate the significant effects of SGPF on aerosol particles in industrial areas.
Xueshun Chen, Fangqun Yu, Wenyi Yang, Yele Sun, Huansheng Chen, Wei Du, Jian Zhao, Ying Wei, Lianfang Wei, Huiyun Du, Zhe Wang, Qizhong Wu, Jie Li, Junling An, and Zifa Wang
Atmos. Chem. Phys., 21, 9343–9366, https://doi.org/10.5194/acp-21-9343-2021, https://doi.org/10.5194/acp-21-9343-2021, 2021
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Atmospheric aerosol particles have significant climate and health effects that depend on aerosol size, composition, and mixing state. A new global-regional nested aerosol model with an advanced particle microphysics module and a volatility basis set organic aerosol module was developed to simulate aerosol microphysical processes. Simulations strongly suggest the important role of anthropogenic organic species in particle formation over the areas influenced by anthropogenic sources.
Hui Wang, Qizhong Wu, Alex B. Guenther, Xiaochun Yang, Lanning Wang, Tang Xiao, Jie Li, Jinming Feng, Qi Xu, and Huaqiong Cheng
Atmos. Chem. Phys., 21, 4825–4848, https://doi.org/10.5194/acp-21-4825-2021, https://doi.org/10.5194/acp-21-4825-2021, 2021
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We assessed the influence of the greening trend on BVOC emission in China. The comparison among different scenarios showed that vegetation changes resulting from land cover management are the main driver of BVOC emission change in China. Climate variability contributed significantly to interannual variations but not much to the long-term trend during the study period.
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.
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Tao Song, Fei Li, Haitao Zheng, Guanglin Jia, Miaomiao Lu, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 13, 529–570, https://doi.org/10.5194/essd-13-529-2021, https://doi.org/10.5194/essd-13-529-2021, 2021
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China's air pollution has changed substantially since 2013. Here we have developed a 6-year-long high-resolution air quality reanalysis dataset over China from 2013 to 2018 to illustrate such changes and to provide a basic dataset for relevant studies. Surface fields of PM2.5, PM10, SO2, NO2, CO, and O3 concentrations are provided, and the evaluation results indicate that the reanalysis dataset has excellent performance in reproducing the magnitude and variation of air pollution in China.
Han Xiao, Qizhong Wu, Xiaochun Yang, Lanning Wang, and Huaqiong Cheng
Geosci. Model Dev., 14, 223–238, https://doi.org/10.5194/gmd-14-223-2021, https://doi.org/10.5194/gmd-14-223-2021, 2021
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Few studies have investigated the effects of initial conditions on the simulation or prediction of PM2.5 concentrations. Here, sensitivity experiments are used to explore the effects of three initial mechanisms (clean, restart, and continuous) and emissions in Xi’an in December 2016. According to this work, if the restart mechanism cannot be used due to computing resource and storage space limitations when forecasting PM2.5 concentrations, a spin-up time of at least 27 h is needed.
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.
Baozhu Ge, Syuichi Itahashi, Keiichi Sato, Danhui Xu, Junhua Wang, Fan Fan, Qixin Tan, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Hong Liao, Meigen Zhang, Zhe Wang, Meng Li, Jung-Hun Woo, Junichi Kurokawa, Yuepeng Pan, Qizhong Wu, Xuejun Liu, and Zifa Wang
Atmos. Chem. Phys., 20, 10587–10610, https://doi.org/10.5194/acp-20-10587-2020, https://doi.org/10.5194/acp-20-10587-2020, 2020
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Performances of the simulated deposition for different reduced N (Nr) species in China were conducted with the Model Inter-Comparison Study for Asia. Results showed that simulated wet deposition of oxidized N was overestimated in northeastern China and underestimated in south China, but Nr was underpredicted in all regions by all models. Oxidized N has larger uncertainties than Nr, indicating that the chemical reaction process is one of the most importance factors affecting model performance.
Juan Feng, Jianlei Zhu, Jianping Li, and Hong Liao
Atmos. Chem. Phys., 20, 9883–9893, https://doi.org/10.5194/acp-20-9883-2020, https://doi.org/10.5194/acp-20-9883-2020, 2020
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This paper explores the month-to-month variability of aerosol concentrations (ACs) over China. The AC variability is dominated by the monopole mode and the meridional dipole mode. The associated dynamic and thermal impacts of the climate systems are examined to explain their contributions to the formation of the two modes. The result suggests the variations are originating from the tropical Pacific, and extratropical atmospheric systems contribute to the dominant variabilities of ACs over China.
Meng Gao, Zhiwei Han, Zhining Tao, Jiawei Li, Jeong-Eon Kang, Kan Huang, Xinyi Dong, Bingliang Zhuang, Shu Li, Baozhu Ge, Qizhong Wu, Hyo-Jung Lee, Cheol-Hee Kim, Joshua S. Fu, Tijian Wang, Mian Chin, Meng Li, Jung-Hun Woo, Qiang Zhang, Yafang Cheng, Zifa Wang, and Gregory R. Carmichael
Atmos. Chem. Phys., 20, 1147–1161, https://doi.org/10.5194/acp-20-1147-2020, https://doi.org/10.5194/acp-20-1147-2020, 2020
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Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the models.
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Joshua S. Fu, Xuemei Wang, Syuichi Itahashi, Kazuyo Yamaji, Tatsuya Nagashima, Hyo-Jung Lee, Cheol-Hee Kim, Chuan-Yao Lin, Lei Chen, Meigen Zhang, Zhining Tao, Jie Li, Mizuo Kajino, Hong Liao, Zhe Wang, Kengo Sudo, Yuesi Wang, Yuepeng Pan, Guiqian Tang, Meng Li, Qizhong Wu, Baozhu Ge, and Gregory R. Carmichael
Atmos. Chem. Phys., 20, 181–202, https://doi.org/10.5194/acp-20-181-2020, https://doi.org/10.5194/acp-20-181-2020, 2020
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Evaluation and uncertainty investigation of NO2, CO and NH3 modeling over China were conducted in this study using 14 chemical transport model results from MICS-Asia III. All models largely underestimated CO concentrations and showed very poor performance in reproducing the observed monthly variations of NH3 concentrations. Potential factors related to such deficiencies are investigated and discussed in this paper.
Xiaomeng Huang, Xing Huang, Dong Wang, Qi Wu, Yi Li, Shixun Zhang, Yuwen Chen, Mingqing Wang, Yuan Gao, Qiang Tang, Yue Chen, Zheng Fang, Zhenya Song, and Guangwen Yang
Geosci. Model Dev., 12, 4729–4749, https://doi.org/10.5194/gmd-12-4729-2019, https://doi.org/10.5194/gmd-12-4729-2019, 2019
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We designed a simple computing library (OpenArray) to decouple ocean modelling and parallel computing. OpenArray provides 12 basic operators featuring user-friendly interfaces and an implicit parallelization ability. Based on OpenArray, we implement a practical ocean model with an enhanced readability and an excellent scalable performance. OpenArray may signal the beginning of a new frontier in future ocean modelling through ingesting basic operators and cutting-edge computing techniques.
Jie Li, Tatsuya Nagashima, Lei Kong, Baozhu Ge, Kazuyo Yamaji, Joshua S. Fu, Xuemei Wang, Qi Fan, Syuichi Itahashi, Hyo-Jung Lee, Cheol-Hee Kim, Chuan-Yao Lin, Meigen Zhang, Zhining Tao, Mizuo Kajino, Hong Liao, Meng Li, Jung-Hun Woo, Jun-ichi Kurokawa, Zhe Wang, Qizhong Wu, Hajime Akimoto, Gregory R. Carmichael, and Zifa Wang
Atmos. Chem. Phys., 19, 12993–13015, https://doi.org/10.5194/acp-19-12993-2019, https://doi.org/10.5194/acp-19-12993-2019, 2019
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This study evaluated and intercompared 14 CTMs with ozone observations in East Asia, within the framework of the Model Inter-Comparison Study for ASIA Phase III (MICS-Asia III). Potential causes of the discrepancies between model results and observation were investigated by assessing the planetary boundary layer heights, emission fluxes, dry deposition, chemistry and vertical transport among models. Finally, a multi-model estimate of pollution distributions was provided.
Juan Feng, Jianping Li, Hong Liao, and Jianlei Zhu
Atmos. Chem. Phys., 19, 10787–10800, https://doi.org/10.5194/acp-19-10787-2019, https://doi.org/10.5194/acp-19-10787-2019, 2019
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Background climate can affect the aerosol concentration (AC). It is found that when negative NAO overlaps El Niño, the anomalous circulations are not favorable for the transportation of aerosol, resulting in enhanced AC over eastern China. By contrast, a sole negative NAO event is linked with increased AC over central China. The results suggest that both the extratropical and tropical climate systems play an important role in impacting the AC over China.
Hui Wang, Junmin Lin, Qizhong Wu, Huansheng Chen, Xiao Tang, Zifa Wang, Xueshun Chen, Huaqiong Cheng, and Lanning Wang
Geosci. Model Dev., 12, 749–764, https://doi.org/10.5194/gmd-12-749-2019, https://doi.org/10.5194/gmd-12-749-2019, 2019
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A new framework was designed for the widely used Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the single-instruction, multiple-data (SIMD) technology in next-generation processors like Knights Landing (KNL) to improve their calculation performance. The optimization is aimed at implementing the fine-grain level parallelization of CBM-Z. The test results showed significant acceleration with our optimization on both CPU and KNL platforms.
Hui Wang, Qizhong Wu, Hongjun Liu, Yuanlin Wang, Huaqiong Cheng, Rongrong Wang, Lanning Wang, Han Xiao, and Xiaochun Yang
Atmos. Chem. Phys., 18, 9583–9596, https://doi.org/10.5194/acp-18-9583-2018, https://doi.org/10.5194/acp-18-9583-2018, 2018
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The Beijing area has suffered from severe air quality pollution in recent years, including ozone pollution in summer. BVOC emissions play a non-negligible role in air quality and climate. Since the forest cover rate increased from 20.6 % to 35.8 % during 1998–2013 in Beijing, we presented a new estimation of local BVOC emissions in a current scenario based on the latest emission model MEGAN v2.1 and also adopted diverse input datasets for the sensitivities of the model and results.
Meng Gao, Zhiwei Han, Zirui Liu, Meng Li, Jinyuan Xin, Zhining Tao, Jiawei Li, Jeong-Eon Kang, Kan Huang, Xinyi Dong, Bingliang Zhuang, Shu Li, Baozhu Ge, Qizhong Wu, Yafang Cheng, Yuesi Wang, Hyo-Jung Lee, Cheol-Hee Kim, Joshua S. Fu, Tijian Wang, Mian Chin, Jung-Hun Woo, Qiang Zhang, Zifa Wang, and Gregory R. Carmichael
Atmos. Chem. Phys., 18, 4859–4884, https://doi.org/10.5194/acp-18-4859-2018, https://doi.org/10.5194/acp-18-4859-2018, 2018
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Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-ASIA III Topic 3 study design is presented.
Hui Wang, Huansheng Chen, Qizhong Wu, Junmin Lin, Xueshun Chen, Xinwei Xie, Rongrong Wang, Xiao Tang, and Zifa Wang
Geosci. Model Dev., 10, 2891–2904, https://doi.org/10.5194/gmd-10-2891-2017, https://doi.org/10.5194/gmd-10-2891-2017, 2017
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We introduced some methods to port our Global Nested Air Quality Prediction Modeling System (GNAQPMS) model on Intel Knight Landing (KNL). In this paper, we introduced both common and specific methods to accelerate out model better. With the guidance of the resources material on Intel Websites (http://www.intel.com/content/www/us/en/products/processors/xeon-phi.html) and relative books, this paper could be an example for the model developers to take advantage of KNL for their model.
Q. Shu, Z. Song, and F. Qiao
The Cryosphere, 9, 399–409, https://doi.org/10.5194/tc-9-399-2015, https://doi.org/10.5194/tc-9-399-2015, 2015
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We evaluated all CMIP5 sea-ice simulations with more metrics in both the Antarctic and the Arctic, in an attempt to provide the community a useful reference. Generally speaking, our study shows that the performance of an Arctic sea-ice simulation is better than that of an Antarctic sea-ice simulation, that sea-ice extent simulation is better than sea-ice volume simulation, and that mean-state simulation is better than long-term trend simulation.
Z. Y. Song, H. L. Liu, C. Z. Wang, L. P. Zhang, and F. L. Qiao
Ocean Sci., 10, 837–843, https://doi.org/10.5194/os-10-837-2014, https://doi.org/10.5194/os-10-837-2014, 2014
L. Liu, G. Yang, B. Wang, C. Zhang, R. Li, Z. Zhang, Y. Ji, and L. Wang
Geosci. Model Dev., 7, 2281–2302, https://doi.org/10.5194/gmd-7-2281-2014, https://doi.org/10.5194/gmd-7-2281-2014, 2014
Q. Z. Wu, W. S. Xu, A. J. Shi, Y. T. Li, X. J. Zhao, Z. F. Wang, J. X. Li, and L. N. Wang
Geosci. Model Dev., 7, 2243–2259, https://doi.org/10.5194/gmd-7-2243-2014, https://doi.org/10.5194/gmd-7-2243-2014, 2014
D. Ji, L. Wang, J. Feng, Q. Wu, H. Cheng, Q. Zhang, J. Yang, W. Dong, Y. Dai, D. Gong, R.-H. Zhang, X. Wang, J. Liu, J. C. Moore, D. Chen, and M. Zhou
Geosci. Model Dev., 7, 2039–2064, https://doi.org/10.5194/gmd-7-2039-2014, https://doi.org/10.5194/gmd-7-2039-2014, 2014
Related subject area
Climate and Earth system modeling
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
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
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator
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
Short-term effects of hurricanes on nitrate-nitrogen runoff loading: a case study of Hurricane Ida using E3SM land model (v2.1)
CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
GOSI9: UK Global Ocean and Sea Ice configurations
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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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 meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future 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 us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
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., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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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 data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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.
Maria Rosa Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-73, https://doi.org/10.5194/gmd-2024-73, 2024
Revised manuscript accepted for GMD
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Observational data and modelling capabilities are expanding in recent years, but there are still barriers preventing these two data sources to be used in synergy. Proper comparison requires generating, storing and handling a large amount of data. This manuscript describes the first step in the development of a new set of software tools, the ‘VISION toolkit’, which can enable the easy and efficient integration of observational and model data required for model evaluation.
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
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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
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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
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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
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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
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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.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 2000–2020 and improves significant errors in a low resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon river are well captured and the mean flows across the multiple passages in the Caribbean Sea agree with observations.
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
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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.
Catherine Guiavarc'h, Dave Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene T. Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
EGUsphere, https://doi.org/10.5194/egusphere-2024-805, https://doi.org/10.5194/egusphere-2024-805, 2024
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GOSI9 is the new UK’s hierarchy of global ocean and sea ice models. Developed as part of a collaboration between several UK research institutes it will be used for various applications such as weather forecast and climate prediction. The models, based on NEMO, are available at three resolutions 1°, ¼° and 1/12°. GOSI9 improves upon previous version by reducing global temperature and salinity biases and enhancing the representation of the Arctic sea ice and of the Antarctic Circumpolar Current.
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Short summary
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a...