Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4171-2023
© 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-16-4171-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
25 Jul 2023
Development and technical paper |
| 25 Jul 2023
| 25 Jul 2023
Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions
Siting Li
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
Zhaodong Liu
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
Wenjie Zhang
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
Hongli Liu
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
Yaqiang Wang
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
Huizheng Che
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
Xiaoye Zhang
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing, China
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Sunling Gong, Hongli Liu, Bihui Zhang, Jianjun He, Hengde Zhang, Yaqiang Wang, Shuxiao Wang, Lei Zhang, and Jie Wang
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Lei Zhang, Sunling Gong, Tianliang Zhao, Chunhong Zhou, Yuesi Wang, Jiawei Li, Dongsheng Ji, Jianjun He, Hongli Liu, Ke Gui, Xiaomei Guo, Jinhui Gao, Yunpeng Shan, Hong Wang, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
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Xiaoning Xie, Anmin Duan, Zhengguo Shi, Xinzhou Li, Hui Sun, Xiaodong Liu, Xugeng Cheng, Tianliang Zhao, Huizheng Che, and Yangang Liu
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Teruyuki Nakajima, Monica Campanelli, Huizheng Che, Victor Estellés, Hitoshi Irie, Sang-Woo Kim, Jhoon Kim, Dong Liu, Tomoaki Nishizawa, Govindan Pandithurai, Vijay Kumar Soni, Boossarasiri Thana, Nas-Urt Tugjsurn, Kazuma Aoki, Sujung Go, Makiko Hashimoto, Akiko Higurashi, Stelios Kazadzis, Pradeep Khatri, Natalia Kouremeti, Rei Kudo, Franco Marenco, Masahiro Momoi, Shantikumar S. Ningombam, Claire L. Ryder, Akihiro Uchiyama, and Akihiro Yamazaki
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By combining long-term observational data analyses, synoptic classifications, and meteorology–chemistry coupled simulations, the complicated impacts of large-scale synoptic forcing and local boundary layer processes on the aerosol pollution in the Beijing–Tianjin–Hebei region have been investigated. The influences of the aerosol radiative effect on boundary layer structure and pollution were also examined. This study has important implications for better understanding pollution in China.
Zhe Jiang, Minzheng Duan, Huizheng Che, Wenxing Zhang, Teruyuki Nakajima, Makiko Hashimoto, Bin Chen, and Akihiro Yamazaki
Atmos. Meas. Tech., 13, 1195–1212, https://doi.org/10.5194/amt-13-1195-2020, https://doi.org/10.5194/amt-13-1195-2020, 2020
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This study analyzed the aerosol optical properties derived by SKYRAD.pack versions 5.0 and 4.2 using the radiometer measurements over Qionghai and Yucheng in China, which are two new sites of SKYNET. The seasonal variability of the aerosol properties over the two sites were investigated based on SKYRAD.pack V5.0. The validation results provide valuable references for continued improvement of the retrieval algorithms of SKYNET and other aerosol observational networks.
Linlin Liang, Guenter Engling, Chang Liu, Wanyun Xu, Xuyan Liu, Yuan Cheng, Zhenyu Du, Gen Zhang, Junying Sun, and Xiaoye Zhang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-19, https://doi.org/10.5194/acp-2020-19, 2020
Revised manuscript not accepted
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Our study captured an episode with extreme biomass burning tracer level at an agricultural site in North China, with concentrations of levoglucosan as high as 4.37 μg m−3. Based on comparison of the chemical composition between different biomass burning periods, it appeared that biomass burning can obviously elevate the levels of organic components, but seems to have no significant effect on the production of secondary inorganic ions, although their precursors increased during the episode.
Jun Zhu, Xiangao Xia, Huizheng Che, Jun Wang, Zhiyuan Cong, Tianliang Zhao, Shichang Kang, Xuelei Zhang, Xingna Yu, and Yanlin Zhang
Atmos. Chem. Phys., 19, 14637–14656, https://doi.org/10.5194/acp-19-14637-2019, https://doi.org/10.5194/acp-19-14637-2019, 2019
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The long-term temporal–spatial variations of the aerosol optical properties over the Tibetan Plateau (TP) based on the multiple ground-based sun photometer sites and the MODIS product are presented. Besides, the aerosol pollution and aerosol transport processes over the TP are also analyzed by the observations and models. The results in this region could help reduce the assessment uncertainties of aerosol radiative forcing and provide more information on aerosol transportation.
Lei Li, Oleg Dubovik, Yevgeny Derimian, Gregory L. Schuster, Tatyana Lapyonok, Pavel Litvinov, Fabrice Ducos, David Fuertes, Cheng Chen, Zhengqiang Li, Anton Lopatin, Benjamin Torres, and Huizheng Che
Atmos. Chem. Phys., 19, 13409–13443, https://doi.org/10.5194/acp-19-13409-2019, https://doi.org/10.5194/acp-19-13409-2019, 2019
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A novel methodology to monitor atmospheric aerosol components using remote sensing is presented. The concept is realized within the GRASP (Generalized Retrieval of Aerosol and Surface Properties) project. Application to POLDER/PARASOL and AERONET observations yielded the spatial and temporal variability of absorbing and non-absorbing insoluble and soluble aerosol species in the fine and coarse size fractions. This presents the global-scale aerosol component derived from satellite measurements.
Renmin Yuan, Xiaoye Zhang, Hao Liu, Yu Gui, Bohao Shao, Xiaoping Tao, Yaqiang Wang, Junting Zhong, Yubin Li, and Zhiqiu Gao
Atmos. Chem. Phys., 19, 12857–12874, https://doi.org/10.5194/acp-19-12857-2019, https://doi.org/10.5194/acp-19-12857-2019, 2019
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To understand the contribution of ground emission during heavy pollution in Beijing, Tianjin and Hebei, aerosol fluxes were estimated in Beijing and Gucheng areas. The results show that in the three stages of a heavy pollution process (transport, accumulative and removal stages: TS, AS and RS), the ground emissions in the TS and RS stages are stronger, while the ground discharge in the AS stage is weak. The weakened mass flux indicates that the already weak turbulence would be further weakened.
Huizheng Che, Xiangao Xia, Hujia Zhao, Oleg Dubovik, Brent N. Holben, Philippe Goloub, Emilio Cuevas-Agulló, Victor Estelles, Yaqiang Wang, Jun Zhu, Bing Qi, Wei Gong, Honglong Yang, Renjian Zhang, Leiku Yang, Jing Chen, Hong Wang, Yu Zheng, Ke Gui, Xiaochun Zhang, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 11843–11864, https://doi.org/10.5194/acp-19-11843-2019, https://doi.org/10.5194/acp-19-11843-2019, 2019
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A full-scale description of ground-based aerosol microphysical and optical properties over China is presented. Moreover, the results have also provided significant information about optical and radiative aerosol properties for different types of sites covering a broad expanse of China. The results have considerable value for ground-truthing satellite observations and validating aerosol models.
Xianyi Yang, Huizheng Che, Hitoshi Irie, Quanliang Chen, Ke Gui, Ying Cai, Yu Zheng, Linchang An, Hujia Zhao, Lei Li, Yuanxin Liang, Yaqiang Wang, Hong Wang, and Xiaoye Zhang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-339, https://doi.org/10.5194/amt-2019-339, 2019
Preprint withdrawn
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This study assesses the performance of SKYNET in comparison to AERONET (Aerosol Robotic Network) for retrieving aerosol optical properties (AOPs) in Beijing, China. SKYNET data retrieved by SR-CEReS analysis package are used to analyze a serious pollution event in winter over Beijing. The AOPs under three weather conditions (clean, dusty, haze) in Beijing are discussed. Measurements from the SKYNET skyradiometer can be used to analyze the AOPs over Beijing reasonably.
Huizheng Che, Ke Gui, Xiangao Xia, Yaqiang Wang, Brent N. Holben, Philippe Goloub, Emilio Cuevas-Agulló, Hong Wang, Yu Zheng, Hujia Zhao, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 10497–10523, https://doi.org/10.5194/acp-19-10497-2019, https://doi.org/10.5194/acp-19-10497-2019, 2019
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A comprehensive assessment of the global and regional AOD trends over the past 37 years (1980–2016) is presented. AOD observations from both AERONET and CARSNET were used for the first time to assess the performance of the MERRA-2 AOD dataset on a global scale. Based on statistical models, we found the meteorological parameters explained a larger proportion of the regional AOD variability (20.4 %–2.8 %) when compared with emission factors (0 %%–56 %).
Hua Yu, Weijun Li, Yangmei Zhang, Peter Tunved, Manuel Dall'Osto, Xiaojing Shen, Junying Sun, Xiaoye Zhang, Jianchao Zhang, and Zongbo Shi
Atmos. Chem. Phys., 19, 10433–10446, https://doi.org/10.5194/acp-19-10433-2019, https://doi.org/10.5194/acp-19-10433-2019, 2019
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Interaction of anthropogenic particles with radiation and clouds plays an important role in Arctic climate change. The mixing state of different aerosols is a key parameter influencing such interactions. However, little is known of this parameter, preventing an accurate representation of this information in global models. Multi-microscopic techniques were used to find one general core–shell structure in which secondary sulfate particles were covered by organic coating in the Arctic atmosphere.
Yahui Che, Jie Guang, Gerrit de Leeuw, Yong Xue, Ling Sun, and Huizheng Che
Atmos. Meas. Tech., 12, 4091–4112, https://doi.org/10.5194/amt-12-4091-2019, https://doi.org/10.5194/amt-12-4091-2019, 2019
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The use of AOD data retrieved from ATSR-2, AATSR and AVHRR to produce a very long time series is investigated. The study is made over a small area in northern China with a large variation of AOD values. Sun photometer data from AERONET and CARSNET and radiance-derived AOD are used as reference. The results show that all data sets compare well. However, AVHRR underestimates high AOD (mainly occurring in summer) but performs better than (A)ATSR in winter.
Weijun Li, Lei Liu, Qi Yuan, Liang Xu, Yanhong Zhu, Bingbing Wang, Hua Yu, Xiaokun Ding, Jian Zhang, Dao Huang, Dantong Liu, Wei Hu, Daizhou Zhang, Pingqing Fu, Maosheng Yao, Min Hu, Xiaoye Zhang, and Zongbo Shi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-539, https://doi.org/10.5194/acp-2019-539, 2019
Preprint withdrawn
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The real state of individual primary biological aerosol particles (PBAPs) derived from natural sources is under mystery, although many studies well evaluate the morphology, mixing state, and elemental composition of anthropogenic particles. It induces that some studies mislead some anthropogenic particles into biological particles through electron microscopy. Here we firstly estimate the full database of individual PBAPs through two microscopic instruments. The database is good for research.
Linlin Wang, Junkai Liu, Zhiqiu Gao, Yubin Li, Meng Huang, Sihui Fan, Xiaoye Zhang, Yuanjian Yang, Shiguang Miao, Han Zou, Yele Sun, Yong Chen, and Ting Yang
Atmos. Chem. Phys., 19, 6949–6967, https://doi.org/10.5194/acp-19-6949-2019, https://doi.org/10.5194/acp-19-6949-2019, 2019
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Urban boundary layer (UBL) affects the physical and chemical processes of the pollutants, and UBL structure can also be altered by pollutants. This paper presents the interactions between air pollution and the UBL structure by using the field data mainly collected from a 325 m meteorology tower, as well as from a Doppler wind lidar, during a severe heavy pollution event that occurred during 1–4 December 2016 in Beijing.
Junting Zhong, Xiaoye Zhang, Yaqiang Wang, Jizhi Wang, Xiaojing Shen, Hongsheng Zhang, Tijian Wang, Zhouqing Xie, Cheng Liu, Hengde Zhang, Tianliang Zhao, Junying Sun, Shaojia Fan, Zhiqiu Gao, Yubin Li, and Linlin Wang
Atmos. Chem. Phys., 19, 3287–3306, https://doi.org/10.5194/acp-19-3287-2019, https://doi.org/10.5194/acp-19-3287-2019, 2019
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In various haze regions in China, including the Guanzhong Plain, the middle and lower reaches of the Yangtze River, the Pearl River Delta, the Sichuan Basin, and the Northeast China Plain, heavy aerosol pollution episodes include inter-/trans-regional transport stages and cumulative stages (CSs). During CSs a two-way feedback mechanism exists between unfavorable meteorological conditions and cumulative aerosol pollution. This two-way feedback is further quantified and its magnitude is compared.
Angela Benedetti, Francesca Di Giuseppe, Luke Jones, Vincent-Henri Peuch, Samuel Rémy, and Xiaoye Zhang
Atmos. Chem. Phys., 19, 987–998, https://doi.org/10.5194/acp-19-987-2019, https://doi.org/10.5194/acp-19-987-2019, 2019
Hong Wang, Yue Peng, Xiaoye Zhang, Hongli Liu, Meng Zhang, Huizheng Che, Yanli Cheng, and Yu Zheng
Atmos. Chem. Phys., 18, 17717–17733, https://doi.org/10.5194/acp-18-17717-2018, https://doi.org/10.5194/acp-18-17717-2018, 2018
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The explosive growth (EG) of PM2.5 resulted in a PM2.5 maximum, which was generally underestimated by atmospheric chemical models due to the deficient description of the local
turbulence intermittent. The aerosol–radiation feedback (AF) and decrease in turbulence diffusion (DTD) may reduce the underestimation of PM2.5 EG by 20–25% and 14–20%, respectively. The modeled EG stage PM2.5 error was decreased from −40 to −51% to −11 to 2% by the combined effects of AF and DTD in Jing–Jin–Ji.
Yue Peng, Hong Wang, Yubin Li, Changwei Liu, Tianliang Zhao, Xiaoye Zhang, Zhiqiu Gao, Tong Jiang, Huizheng Che, and Meng Zhang
Atmos. Chem. Phys., 18, 17421–17435, https://doi.org/10.5194/acp-18-17421-2018, https://doi.org/10.5194/acp-18-17421-2018, 2018
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Two surface layer schemes are evaluated in eastern China based on observational flux data. The results indicate that the Li scheme better describes regional atmosphere stratification compared with the MM5 scheme, especially for the transition stage from unstable to stable atmosphere conditions, corresponding to PM2.5 accumulation. Our research suggests the potential improved possibilities for severe haze prediction in eastern China by coupling Li online into atmosphere chemical models.
Xiaoning Xie, Xiaodong Liu, Huizheng Che, Xiaoxun Xie, Xinzhou Li, Zhengguo Shi, Hongli Wang, Tianliang Zhao, and Yangang Liu
Atmos. Chem. Phys., 18, 12683–12698, https://doi.org/10.5194/acp-18-12683-2018, https://doi.org/10.5194/acp-18-12683-2018, 2018
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This study extends our previous investigation in dust–radiation interactions to investigate SRF and its feedbacks on the regional climate and the dust cycle over east Asia by use of the CAM4-BAM. Our results show that SRF increases the east Asian dust emissions significantly by 13.7 % in the spring, in contrast to −7.6 % of decreased dust emissions by DRF. Hence, a significant feature of SRF on the Tibetan Plateau can create a positive feedback loop to enhance the dust cycle over east Asia.
Xiaoye Zhang, Junting Zhong, Jizhi Wang, Yaqiang Wang, and Yanju Liu
Atmos. Chem. Phys., 18, 5991–5999, https://doi.org/10.5194/acp-18-5991-2018, https://doi.org/10.5194/acp-18-5991-2018, 2018
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The relation between interdecadal changes in weather conditions and climate warming is uncertain. Here, the decadal worsening of meteorological conditions since the 1960s in the Beijing area was found to be partly attributed to climate warming, which is defined by more warming in the higher layers of the boundary layer (BL) than the lower layers. This worsening may also partly be related to the impact on the increasing aerosol pollution (particularly after 2010).
Tianze Sun, Huizheng Che, Bing Qi, Yaqiang Wang, Yunsheng Dong, Xiangao Xia, Hong Wang, Ke Gui, Yu Zheng, Hujia Zhao, Qianli Ma, Rongguang Du, and Xiaoye Zhang
Atmos. Chem. Phys., 18, 2949–2971, https://doi.org/10.5194/acp-18-2949-2018, https://doi.org/10.5194/acp-18-2949-2018, 2018
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The Yangtze River Delta (YRD) region is a key hub in China with air pollution problems. We applied various data from observations and satellites, finding particles in summer prefer hygroscopic growth leading to high scatter. Transported scatter particles lead to a cooling effect which lowers the boundary layer, creating positive feedback. Transported pollutants over YRD are from the North China Plain, northwestern deserts, and southern biomass burning. This finding helps air quality control.
Bingliang Zhuang, Tijian Wang, Jane Liu, Huizheng Che, Yong Han, Yu Fu, Shu Li, Min Xie, Mengmeng Li, Pulong Chen, Huimin Chen, Xiu-qun Yang, and Jianning Sun
Atmos. Chem. Phys., 18, 1419–1436, https://doi.org/10.5194/acp-18-1419-2018, https://doi.org/10.5194/acp-18-1419-2018, 2018
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Aerosols have a significant influence on climate changes. Their uncertainties could be substantially reduced if observation data were used. The properties and the DRF of fractionated aerosols in the western Yangtze River Delta are investigated based on measurements. Results reveal the characteristics of the optical properties and DRFs of different types of fractionated aerosols, which can be further used to improve aerosol modelling performance in the eastern regions of China.
Xiaojing Shen, Junying Sun, Niku Kivekäs, Adam Kristensson, Xiaoye Zhang, Yangmei Zhang, Lu Zhang, Ruxia Fan, Xuefei Qi, Qianli Ma, and Huaigang Zhou
Atmos. Chem. Phys., 18, 587–599, https://doi.org/10.5194/acp-18-587-2018, https://doi.org/10.5194/acp-18-587-2018, 2018
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In this study we used the NanoMap method by applying back trajectories and particle number size distribution in different rural sites in China to evaluate the spatial distribution of NPF events and their occurrence probability. We found difference in the horizontal spatial distribution of new particle source areas was connected to typical meteorological conditions. The horizontal extent of NPF reached to larger than 500 km at two sites, favoured by the fast transport of northwesterly air masses.
Huizheng Che, Bing Qi, Hujia Zhao, Xiangao Xia, Thomas F. Eck, Philippe Goloub, Oleg Dubovik, Victor Estelles, Emilio Cuevas-Agulló, Luc Blarel, Yunfei Wu, Jun Zhu, Rongguang Du, Yaqiang Wang, Hong Wang, Ke Gui, Jie Yu, Yu Zheng, Tianze Sun, Quanliang Chen, Guangyu Shi, and Xiaoye Zhang
Atmos. Chem. Phys., 18, 405–425, https://doi.org/10.5194/acp-18-405-2018, https://doi.org/10.5194/acp-18-405-2018, 2018
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Sun photometer measurements from seven sites in the Yangtze River Delta (YRD) from 2011 to 2015 were used to characterize the climatology of aerosol microphysical and optical properties, calculate direct aerosol radiative forcing (DARF) and classify aerosols based on size and absorption. This study contributes to our understanding of aerosols and regional climate/air quality, and the results will be useful for validating satellite retrievals and for improving climate models and remote sensing.
Junting Zhong, Xiaoye Zhang, Yunsheng Dong, Yaqiang Wang, Cheng Liu, Jizhi Wang, Yangmei Zhang, and Haochi Che
Atmos. Chem. Phys., 18, 247–258, https://doi.org/10.5194/acp-18-247-2018, https://doi.org/10.5194/acp-18-247-2018, 2018
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Beijing heavy pollution episodes are characterized by the transport stage (TS) and the cumulative stage (CS). PM2.5 pollution formation in the TS is primarily caused by pollutants transported from the south of Beijing. PM2.5 cumulative explosive growth in the CS is dominated by stable atmospheric stratification due to the interaction of particulate matter (PM) and meteorological factors. The positive meteorological feedback on PM2.5 mass noted explains over 70% of cumulative explosive growth.
Ying Zhang, Zhengqiang Li, Yuhuan Zhang, Donghui Li, Lili Qie, Huizheng Che, and Hua Xu
Atmos. Meas. Tech., 10, 3203–3213, https://doi.org/10.5194/amt-10-3203-2017, https://doi.org/10.5194/amt-10-3203-2017, 2017
Shurui Chen, Liang Xu, Yinxiao Zhang, Bing Chen, Xinfeng Wang, Xiaoye Zhang, Mei Zheng, Jianmin Chen, Wenxing Wang, Yele Sun, Pingqing Fu, Zifa Wang, and Weijun Li
Atmos. Chem. Phys., 17, 1259–1270, https://doi.org/10.5194/acp-17-1259-2017, https://doi.org/10.5194/acp-17-1259-2017, 2017
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Many studies have focused on the unusually severe hazes instead of the more frequent light and moderate hazes (22–63 %) in winter in the North China Plain (NCP). The morphology, mixing state, and size of organic aerosols in the L & M hazes were characterized. We conclude that the direct emissions from residential coal stoves without any pollution controls in rural and urban outskirts contribute large amounts of primary OM particles to the regional L & M hazes in winter in the NCP.
Y. Q. Yang, J. Z. Wang, S. L. Gong, X. Y. Zhang, H. Wang, Y. Q. Wang, J. Wang, D. Li, and J. P. Guo
Atmos. Chem. Phys., 16, 1353–1364, https://doi.org/10.5194/acp-16-1353-2016, https://doi.org/10.5194/acp-16-1353-2016, 2016
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A new model, PLAM/h, has been developed and used in near-real-time air quality forecasts by considering both meteorology and pollutant emissions, based on the two-dimensional probability density function diagnosis model for emissions. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the forecasting ability for fog-haze weather in North China.
P. Wang, H. Wang, Y. Q. Wang, X. Y. Zhang, S. L. Gong, M. Xue, C. H. Zhou, H. L. Liu, X. Q. An, T. Niu, and Y. L. Cheng
Atmos. Chem. Phys., 16, 989–1002, https://doi.org/10.5194/acp-16-989-2016, https://doi.org/10.5194/acp-16-989-2016, 2016
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An ensemble optimal interpolation (EnOI) data assimilation technique is used to investigate the possibility of optimally recovering the spatially resolved emissions bias of BC. The inversed emission over China in January is 240.1 Gg, and annual emission is about 2539 Gg. Even though only monthly mean BC measurements are employed to inverse the emissions, the accuracy of the daily model simulation improves. We finds that EnOI is a useful and computation-free method to make top-down estimation.
C. Zhou, X. Zhang, S. Gong, Y. Wang, and M. Xue
Atmos. Chem. Phys., 16, 145–160, https://doi.org/10.5194/acp-16-145-2016, https://doi.org/10.5194/acp-16-145-2016, 2016
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A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme from emissions to precipitation has been developed under the CMA chemical weather modeling system GRAPES/CUACE. The ACI for January 2013 has been studied using this model. The interactive microphysical properties of clouds improve the precipitation, showing 24 to 48 % enhancements of threat score for 6 h precipitation in all regions and reduction of the regional mean bias of temperature by 3 °C in certain precipitation events.
Y. Q. Wang, X. Y. Zhang, J. Y. Sun, X. C. Zhang, H. Z. Che, and Y. Li
Atmos. Chem. Phys., 15, 13585–13598, https://doi.org/10.5194/acp-15-13585-2015, https://doi.org/10.5194/acp-15-13585-2015, 2015
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Concentrations of PM10, PM2.5 and PM1 were monitored at 24 stations of CAWNET from 2006 to 2014. The average levels of particulate matter (PM) concentrations and relationships were investigated. Seasonal, interannual and diurnal variations of the PM were revealed. The effects of meteorological factors on the PM were discussed. The highest PM concentrations were observed at the stations of Xian, Zhengzhou and Gucheng, in Guanzhong and the Huabei Plain.
J.-W. Xu, R. V. Martin, A. van Donkelaar, J. Kim, M. Choi, Q. Zhang, G. Geng, Y. Liu, Z. Ma, L. Huang, Y. Wang, H. Chen, H. Che, P. Lin, and N. Lin
Atmos. Chem. Phys., 15, 13133–13144, https://doi.org/10.5194/acp-15-13133-2015, https://doi.org/10.5194/acp-15-13133-2015, 2015
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1. GOCI (Geostationary Ocean Color Imager) retrieval of AOD is consistent with AERONET AOD (RMSE=0.08-0.1)
2. GOCI-derived PM2.5 is in significant agreement with in situ observations (r2=0.66, rRMSE=18.3%)
3. Population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg/m3, threatening the health of its more than 400 million residents
4. Secondary inorganics (SO42-, NO3-, NH4+) & organic matter are the most significant components of GOCI-derived PM2.5.
X. Y. Zhang, J. Z. Wang, Y. Q. Wang, H. L. Liu, J. Y. Sun, and Y. M. Zhang
Atmos. Chem. Phys., 15, 12935–12952, https://doi.org/10.5194/acp-15-12935-2015, https://doi.org/10.5194/acp-15-12935-2015, 2015
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No obvious changes were found in annual mean concentrations of major chemical components and PM10 in 2013, relative to 2012. But wintertime mass were quite different; approximately 60% of the winter mass increase from 2012 to 2013 can be attributed to severe meteorological conditions in the HBP area, and mass of chemical components exhibited a decline during 2006 to 2010, and then a rise till 2013. Coal-combustion was still the largest anthropogenic source of aerosol pollution in 2013 in China.
J. W. Chi, W. J. Li, D. Z. Zhang, J. C. Zhang, Y. T. Lin, X. J. Shen, J. Y. Sun, J. M. Chen, X. Y. Zhang, Y. M. Zhang, and W. X. Wang
Atmos. Chem. Phys., 15, 11341–11353, https://doi.org/10.5194/acp-15-11341-2015, https://doi.org/10.5194/acp-15-11341-2015, 2015
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Sea salt aerosols (SSA) are dominant particles in the Arctic atmosphere. Our result suggests that the hydrophilic MgCl2 coating in fresh SSA likely intrigued the heterogeneous reactions at the beginning of SSA and acidic gases in the Arctic. The content of organic matter increased in the aged SSA compared with the fresh SSA, which suggests organic acids (beside inorganic acids) participate in the ageing of SSA in the Arctic.
L. Zhang, J. Y. Sun, X. J. Shen, Y. M. Zhang, H. Che, Q. L. Ma, Y. W. Zhang, X. Y. Zhang, and J. A. Ogren
Atmos. Chem. Phys., 15, 8439–8454, https://doi.org/10.5194/acp-15-8439-2015, https://doi.org/10.5194/acp-15-8439-2015, 2015
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The aerosol hygroscopic properties at a rural background site in the Yangtze River delta of China was discussed. The results show the scattering coefficient and backscattering coefficient increased by 58 and 25% as relative humidity (RH) increased from 40 to 85%, while the hemispheric backscatter fraction decreased by 21%. Aerosol hygroscopic growth caused a 47% increase in calculated aerosol direct radiative forcing at 85% RH compared to the forcing at 40% RH. Nitrate played a vital role.
H. Che, X.-Y. Zhang, X. Xia, P. Goloub, B. Holben, H. Zhao, Y. Wang, X.-C. Zhang, H. Wang, L. Blarel, B. Damiri, R. Zhang, X. Deng, Y. Ma, T. Wang, F. Geng, B. Qi, J. Zhu, J. Yu, Q. Chen, and G. Shi
Atmos. Chem. Phys., 15, 7619–7652, https://doi.org/10.5194/acp-15-7619-2015, https://doi.org/10.5194/acp-15-7619-2015, 2015
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This work studied more than 10 years of measurements of aerosol optical depths (AODs) made for 50 sites of CARSNET compiled into a climatology of aerosol optical properties for China. It lets us see a detailed full-scale description of AOD observations over China. The results would benefit us a lot in comprehending the temporal and special distribution aerosol optical property over China. Also the data would be valuable to communities of aerosol satellite retrieval, modelling, etc.
C. Jiang, H. Wang, T. Zhao, T. Li, and H. Che
Atmos. Chem. Phys., 15, 5803–5814, https://doi.org/10.5194/acp-15-5803-2015, https://doi.org/10.5194/acp-15-5803-2015, 2015
Z. L. Wang, H. Zhang, and X. Y. Zhang
Atmos. Chem. Phys., 15, 3671–3685, https://doi.org/10.5194/acp-15-3671-2015, https://doi.org/10.5194/acp-15-3671-2015, 2015
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This study highlights that there are no effective ways to remove the black carbon exclusively without influencing the other co-emitted components, our results therefore indicate that a reduction in BC emission can lead to an unexpected warming on the Earth’s climate system in the future.
H. Wang, M. Xue, X. Y. Zhang, H. L. Liu, C. H. Zhou, S. C. Tan, H. Z. Che, B. Chen, and T. Li
Atmos. Chem. Phys., 15, 3257–3275, https://doi.org/10.5194/acp-15-3257-2015, https://doi.org/10.5194/acp-15-3257-2015, 2015
H. Wang, G. Y. Shi, X. Y. Zhang, S. L. Gong, S. C. Tan, B. Chen, H. Z. Che, and T. Li
Atmos. Chem. Phys., 15, 3277–3287, https://doi.org/10.5194/acp-15-3277-2015, https://doi.org/10.5194/acp-15-3277-2015, 2015
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Solar radiation reaching the ground decreases about 15% in Chinese 3JNS region and by 20 to 25% in the region with the highest AOD. Aerosol cools the PBL atmosphere but warms the atmosphere above it, leading to a more stable atmosphere that causes a decrease in turbulence diffusion of about 52% and in PBL height of about 33%; this results in a positive feedback on the PM2.5 concentration within the PBL and the surface as well as the haze formation.
Y. M. Zhang, X. Y. Zhang, J. Y. Sun, G. Y. Hu, X. J. Shen, Y. Q. Wang, T. T. Wang, D. Z. Wang, and Y. Zhao
Atmos. Chem. Phys., 14, 12237–12249, https://doi.org/10.5194/acp-14-12237-2014, https://doi.org/10.5194/acp-14-12237-2014, 2014
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An AMS was employed to measure the mass and size distributions of PM1 at an elevated site. Features of PM1 at four seasons, during different kinds of episodes including NPF, polluted, PBL, LFT and in-cloud, were discussed. The characterizations of PM1 at seven clusters of air masses were also analyzed. BBOA, CCOA and oxidized organic aerosols were resolved by AMS-PMF (positive matrix function). Almost half of OA were oxidized, and BBOA is 34% of OA in summer; CCOA is 22% of OA in winter as well.
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
J. Tao, J. Gao, L. Zhang, R. Zhang, H. Che, Z. Zhang, Z. Lin, J. Jing, J. Cao, and S.-C. Hsu
Atmos. Chem. Phys., 14, 8679–8699, https://doi.org/10.5194/acp-14-8679-2014, https://doi.org/10.5194/acp-14-8679-2014, 2014
H. Che, X. Xia, J. Zhu, Z. Li, O. Dubovik, B. Holben, P. Goloub, H. Chen, V. Estelles, E. Cuevas-Agulló, L. Blarel, H. Wang, H. Zhao, X. Zhang, Y. Wang, J. Sun, R. Tao, X. Zhang, and G. Shi
Atmos. Chem. Phys., 14, 2125–2138, https://doi.org/10.5194/acp-14-2125-2014, https://doi.org/10.5194/acp-14-2125-2014, 2014
A. Petzold, J. A. Ogren, M. Fiebig, P. Laj, S.-M. Li, U. Baltensperger, T. Holzer-Popp, S. Kinne, G. Pappalardo, N. Sugimoto, C. Wehrli, A. Wiedensohler, and X.-Y. Zhang
Atmos. Chem. Phys., 13, 8365–8379, https://doi.org/10.5194/acp-13-8365-2013, https://doi.org/10.5194/acp-13-8365-2013, 2013
H. Jiang, H. Liao, H. O. T. Pye, S. Wu, L. J. Mickley, J. H. Seinfeld, and X. Y. Zhang
Atmos. Chem. Phys., 13, 7937–7960, https://doi.org/10.5194/acp-13-7937-2013, https://doi.org/10.5194/acp-13-7937-2013, 2013
Related subject area
Numerical methods
Hydro-geomorphological modelling of leaky wooden dam efficacy from reach to catchment scale with CAESAR-Lisflood 1.9j
Enhancing single precision with quasi-double precision: achieving double-precision accuracy in the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 8.2.1
Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand
Subgrid corrections for the linear inertial equations of a compound flood model – a case study using SFINCS 2.1.1 Dollerup release
Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study
Development of a high-order global dynamical core using the discontinuous Galerkin method for an atmospheric large-eddy simulation (LES) and proposal of test cases: SCALE-DG v0.8.0
A joint reconstruction and model selection approach for large-scale linear inverse modeling (msHyBR v2)
Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter
The Paleochrono-1.1 probabilistic model to derive a common age model for several paleoclimatic sites using absolute and relative dating constraints
asQ: parallel-in-time finite element simulations using ParaDiag for geoscientific models and beyond
Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)
Potential based Thermodynamics with Consistent Conservative Cascade Transport for Implicit Large Eddy Simulation: PTerodaC3TILES version 1.0
The Measurement Error Proxy System Model: MEPSM v0.2
Numerical stabilization methods for level-set-based ice front migration
Modelling chemical advection during magma ascent
Consistent point data assimilation in Firedrake and Icepack
A computationally efficient parameterization of aerosol, cloud and precipitation pH for application at global and regional scale (EQSAM4Clim-v12)
Assessing the benefits of approximately exact step sizes for Picard and Newton solver in simulating ice flow (FEniCS-full-Stokes v.1.3.2)
Assessing effects of climate and technology uncertainties in large natural resource allocation problems
VISIR-2: ship weather routing in Python
Incremental analysis update (IAU) in the Model for Prediction Across Scales coupled with the Joint Effort for Data assimilation Integration (MPAS–JEDI 2.0.0)
Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0
CLAQC v1.0 – Country Level Air Quality Calculator. An Empirical Modeling Approach
Developing meshing workflows in Gmsh v4.11 for the geologic uncertainty assessment of high-temperature aquifer thermal energy storage
Development and preliminary validation of a land surface image assimilation system based on the Common Land Model
NorSand4AI: a comprehensive triaxial test simulation database for NorSand constitutive model materials
ParticleDA.jl v.1.0: a distributed particle-filtering data assimilation package
HETerogeneous vectorized or Parallel (HETPv1.0): an updated inorganic heterogeneous chemistry solver for the metastable-state NH4+–Na+–Ca2+–K+–Mg2+–SO42−–NO3−–Cl−–H2O system based on ISORROPIA II
Three-dimensional geological modelling of igneous intrusions in LoopStructural v1.5.10
Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17)
Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding
An automatic mesh generator for coupled 1D–2D hydrodynamic models
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 2: A semi-discrete error analysis framework for assessing coupling schemes
jsmetrics v0.2.0: a Python package for metrics and algorithms used to identify or characterise atmospheric jet streams
P3D-BRNS v1.0.0: a three-dimensional, multiphase, multicomponent, pore-scale reactive transport modelling package for simulating biogeochemical processes in subsurface environments
MinVoellmy v1: a lightweight model for simulating rapid mass movements based on a modified Voellmy rheology
Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets
Sweep interpolation: a cost-effective semi-Lagrangian scheme in the Global Environmental Multiscale model
CHONK 1.0: landscape evolution framework: cellular automata meets graph theory
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations
Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods
GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
Parameterization and tuning of the Bay of Biscay Atlantis model v1
A comparison of Eulerian and Lagrangian methods for vertical particle transport in the water column
AutoQS v1: automatic parametrization of QuickSampling based on training images analysis
A dynamical core based on a discontinuous Galerkin method for higher-order finite-element sea ice modeling
GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation
Leveraging Google's Tensor Processing Units for tsunami-risk mitigation planning in the Pacific Northwest and beyond
An improved subgrid channel model with upwind-form artificial diffusion for river hydrodynamics and floodplain inundation simulation
Joshua M. Wolstenholme, Christopher J. Skinner, David Milan, Robert E. Thomas, and Daniel R. Parsons
Geosci. Model Dev., 18, 1395–1411, https://doi.org/10.5194/gmd-18-1395-2025, https://doi.org/10.5194/gmd-18-1395-2025, 2025
Short summary
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Leaky wooden dams are a type of natural flood management intervention that aims to reduce flood risk downstream by temporarily holding back water during a storm event and releasing it afterwards. These structures alter the river hydrology, and therefore the geomorphology, yet often this is excluded from numerical models. Here we show that by not simulating geomorphology, we are currently underestimating the efficacy of these structures to reduce the flood peak and store water.
Jiayi Lai, Lanning Wang, Qizhong Wu, Yizhou Yang, and Fang Wang
Geosci. Model Dev., 18, 1089–1102, https://doi.org/10.5194/gmd-18-1089-2025, https://doi.org/10.5194/gmd-18-1089-2025, 2025
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High-performance computing limitations often hinder numerical model development. Traditional models use double precision for accuracy, which is computationally expensive. Lower precision reduces costs but can introduce errors. The quasi-double-precision (QDP) algorithm helps mitigate these errors. This study applies the QDP algorithm to the Model for Prediction Across Scales – Atmosphere, showing reduced errors and computational time, making it an efficient solution for large-scale simulations.
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Bödecker, Carsten F. Dormann, Florian Pappenberger, and Gianpaolo Balsamo
Geosci. Model Dev., 18, 921–937, https://doi.org/10.5194/gmd-18-921-2025, https://doi.org/10.5194/gmd-18-921-2025, 2025
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We compared spatiotemporal forecasts of three machine learning models that learned water and energy
states on the land surface from a physical model scheme. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the globe. We found that all approaches deliver highly accurate approximations of the physical dynamic at long time horizons, implying their usefulness to advance land surface forecasting with synthetic data.
states on the land surface from a physical model scheme. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the globe. We found that all approaches deliver highly accurate approximations of the physical dynamic at long time horizons, implying their usefulness to advance land surface forecasting with synthetic data.
Maarten van Ormondt, Tim Leijnse, Roel de Goede, Kees Nederhoff, and Ap van Dongeren
Geosci. Model Dev., 18, 843–861, https://doi.org/10.5194/gmd-18-843-2025, https://doi.org/10.5194/gmd-18-843-2025, 2025
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Accurate flood risk assessments are crucial for storm protection. To achieve efficiency, computational costs must be minimized. This paper introduces a novel subgrid approach for linear inertial equations (LIEs) with bed level and friction variations, implemented in the Super-Fast INundation of CoastS (SFINCS) model. Pre-processed lookup tables enhance simulation precision with lower costs. Validations show significant accuracy improvement even at coarser resolutions.
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
Geosci. Model Dev., 18, 803–818, https://doi.org/10.5194/gmd-18-803-2025, https://doi.org/10.5194/gmd-18-803-2025, 2025
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In geosciences, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. We introduce a generalizable framework for calibrating numerical models, with a case study of the geomorphological model CAESAR-Lisflood. This approach efficiently identifies the optimal set of parameters for a given numerical model, enabling retrospective and prospective analyses at various temporal resolutions.
Yuta Kawai and Hirofumi Tomita
Geosci. Model Dev., 18, 725–762, https://doi.org/10.5194/gmd-18-725-2025, https://doi.org/10.5194/gmd-18-725-2025, 2025
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When considering future high-resolution atmospheric simulations with O(10–100 m) grid spacing, such as global large-eddy simulations, numerical errors with the conventional low-order dynamical cores can contaminate the effects of turbulent parameterization. To achieve high-order discretization, we developed a global atmospheric dynamical core using the discontinuous Galerkin method (DGM). By conducting several validation tests, we discussed the impact of a high-order DGM on atmospheric flows.
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 17, 8853–8872, https://doi.org/10.5194/gmd-17-8853-2024, https://doi.org/10.5194/gmd-17-8853-2024, 2024
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Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee
Geosci. Model Dev., 17, 8799–8816, https://doi.org/10.5194/gmd-17-8799-2024, https://doi.org/10.5194/gmd-17-8799-2024, 2024
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We developed an advanced snow water equivalent (SWE) data assimilation framework using satellite data based on a land surface model. The results of this study highlight the beneficial impact of data assimilation by effectively combining land surface model and satellite-derived data according to their relative uncertainty, thereby controlling not only transitional regions but also the regions with heavy snow accumulation that are difficult to detect by satellite.
Frédéric Parrenin, Marie Bouchet, Christo Buizert, Emilie Capron, Ellen Corrick, Russell Drysdale, Kenji Kawamura, Amaëlle Landais, Robert Mulvaney, Ikumi Oyabu, and Sune Olander Rasmussen
Geosci. Model Dev., 17, 8735–8750, https://doi.org/10.5194/gmd-17-8735-2024, https://doi.org/10.5194/gmd-17-8735-2024, 2024
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The Paleochrono-1.1 probabilistic dating model allows users to derive a common and optimized chronology for several paleoclimatic sites from various archives (ice cores, speleothems, marine cores, lake cores, etc.). It combines prior sedimentation scenarios with chronological information such as dated horizons, dated intervals, stratigraphic links and (for ice cores) Δdepth observations. Paleochrono-1.1 is available under an open-source license.
Joshua Hope-Collins, Abdalaziz Hamdan, Werner Bauer, Lawrence Mitchell, and Colin Cotter
EGUsphere, https://doi.org/https://doi.org/10.48550/arXiv.2409.18792, https://doi.org/https://doi.org/10.48550/arXiv.2409.18792, 2024
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Effectively using modern supercomputers requires massively parallel algorithms. Time-parallel algorithms calculate the system state (e.g. the atmosphere) at multiple times simultaneously and have exciting potential, but are tricky to implement and still require development. We have developed software to simplify implementing and testing the ParaDiag algorithm on supercomputers. We show that for some atmospheric problems it can enable faster or more accurate solutions than traditional techniques.
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024, https://doi.org/10.5194/gmd-17-8399-2024, 2024
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This paper introduces a numerical method for simulating particle-based aerosol transport in atmospheric models. We detail the various numerical properties of the advection order method and demonstrate its implementation in a 3D weather prediction model (WRF) for the first time. Particle-based techniques improve the accuracy of aerosol size and composition predictions, which are key for aerosol–cloud and aerosol–radiation interactions.
John Thuburn
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-153, https://doi.org/10.5194/gmd-2024-153, 2024
Revised manuscript accepted for GMD
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A new computational fluid dynamics code for simulating the atmospheric boundary layer and convection is presented. Moist thermodynamics is formulated via thermodynamic potentials, avoiding inconsistencies that can be introduced with conventional approaches. Numerical methods typical of weather and climate models are used, with no explicit subgrid scheme. Results highlight some advantages (e.g., large time steps) and disadvantages (e.g., weak vertical fluxes near the surface) of this approach.
Matt J. Fischer
Geosci. Model Dev., 17, 6745–6760, https://doi.org/10.5194/gmd-17-6745-2024, https://doi.org/10.5194/gmd-17-6745-2024, 2024
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In paleoclimate research, proxy system models (PSMs) model chemical or biological systems which receive environmental input and output (e.g., geochemical signals). The environmental inputs are rarely noiseless, which causes problems when calibrating multi-input PSMs. Here a PSM is developed which includes generalized noise in both model inputs and outputs and prior information. A quasi-Bayesian method enhances the stability of the solution of the Measurement Error Proxy System Model.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, https://doi.org/10.5194/gmd-17-6227-2024, 2024
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We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev., 17, 6105–6122, https://doi.org/10.5194/gmd-17-6105-2024, https://doi.org/10.5194/gmd-17-6105-2024, 2024
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Predicting the behaviour of magmatic systems is important for understanding Earth's matter and heat transport. Numerical modelling is a technique that can predict complex systems at different scales of space and time by solving equations using various techniques. This study tests four algorithms to find the best way to transport the melt composition. The "weighted essentially non-oscillatory" algorithm emerges as the best choice, minimising errors and preserving system mass well.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
Geosci. Model Dev., 17, 5369–5386, https://doi.org/10.5194/gmd-17-5369-2024, https://doi.org/10.5194/gmd-17-5369-2024, 2024
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Scientists often use models to study complex processes, like the movement of ice sheets, and compare them to measurements for estimating quantities that are hard to measure. We highlight an approach that ensures accurate results from point data sources (e.g. height measurements) by evaluating the numerical solution at true point locations. This method improves accuracy, aids communication between scientists, and is well-suited for integration with specialised software that automates processes.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
Geosci. Model Dev., 17, 5009–5021, https://doi.org/10.5194/gmd-17-5009-2024, https://doi.org/10.5194/gmd-17-5009-2024, 2024
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EQSAM4Clim has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. It is based on an analytical concept that is sufficiently fast and free of numerical noise, which makes it attractive for air quality forecasting. Version 12 allows the calculation of aerosol composition based on the gas–liquid–solid and the reduced gas–liquid partitioning with the associated water uptake for both cases, including the acidity of the aerosols.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
Geosci. Model Dev., 17, 4943–4959, https://doi.org/10.5194/gmd-17-4943-2024, https://doi.org/10.5194/gmd-17-4943-2024, 2024
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Future sea-level rise is of big significance for coastal regions. The melting and acceleration of glaciers plays a major role in sea-level change. Computer simulation of glaciers costs a lot of computational resources. In this publication, we test a new way of simulating glaciers. This approach produces the same results but has the advantage that it needs much less computation time. As simulations can be obtained with fewer computation resources, higher resolution and physics become affordable.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
Geosci. Model Dev., 17, 4791–4819, https://doi.org/10.5194/gmd-17-4791-2024, https://doi.org/10.5194/gmd-17-4791-2024, 2024
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This paper applies a cutting-edge numerical method, SCEQ, to show how uncertain climate change and technological progress affect the future utilization of the world's scarce land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The study finds the range of outcomes for land use change to be smaller when using this novel method compared to existing deterministic models.
Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović
Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, https://doi.org/10.5194/gmd-17-4355-2024, 2024
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Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, https://doi.org/10.5194/gmd-17-4199-2024, 2024
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To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs
Geosci. Model Dev., 17, 4031–4052, https://doi.org/10.5194/gmd-17-4031-2024, https://doi.org/10.5194/gmd-17-4031-2024, 2024
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We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions for optimal aircraft trajectories, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel and uses weather conditions simulated by the EMAC atmospheric model. This paper focuses on the ability of SolFinder to identify eco-efficient trajectories, reducing a flight's climate impact at limited cost penalties.
Stefania Renna, Francesco Granella, Lara Aleluia Reis, and Paulina Estela Schulz-Antipa
EGUsphere, https://doi.org/10.2139/ssrn.4591252, https://doi.org/10.2139/ssrn.4591252, 2024
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The Country Level Air Quality Calculator (CLAQC) is a new fast modeling tool that predicts globally country-level monthly and annual concentrations of two major air pollutants, fine particulate matter (PM2.5) and tropospheric ozone (O3). It was designed to inform national and regional climate and pollution mitigation policies. It is easy to use and computationally efficient, allowing the simulation of a large number of policy scenarios for policy assessments and optimization frameworks.
Ali Dashti, Jens C. Grimmer, Christophe Geuzaine, Florian Bauer, and Thomas Kohl
Geosci. Model Dev., 17, 3467–3485, https://doi.org/10.5194/gmd-17-3467-2024, https://doi.org/10.5194/gmd-17-3467-2024, 2024
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This study developed new meshing workflows to enable the automatic generation of meshes that follow geological models. The workflow allows for importing several geological models as input for Gmsh and later exporting the same number of high-quality meshes. This way, geological uncertainty is directly included in the numerical simulations. This study evaluates the impact of the geological uncertainty on thermohydraulic performance of two reservoirs for high-temperature heat storage applications.
Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
Geosci. Model Dev., 17, 3447–3465, https://doi.org/10.5194/gmd-17-3447-2024, https://doi.org/10.5194/gmd-17-3447-2024, 2024
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In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The findings demonstrate that the assimilation of surface soil moisture observation images effectively and reasonably enhances the spatial structure of soil moisture analysis field.
Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante
Geosci. Model Dev., 17, 3175–3197, https://doi.org/10.5194/gmd-17-3175-2024, https://doi.org/10.5194/gmd-17-3175-2024, 2024
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The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils, providing two datasets: one with 2000 soil types, 40 test conditions each (160 000 triaxial tests), and a second with 2048 soil types, 42 test conditions each (172 032 triaxial tests). Each dataset is a 4000×10 matrix applicable for multivariate forecasting and geotechnical simulations. In addition, a new Python code is introduced, empowering researchers to leverage Python packages for NorSand analyses.
Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas
Geosci. Model Dev., 17, 2427–2445, https://doi.org/10.5194/gmd-17-2427-2024, https://doi.org/10.5194/gmd-17-2427-2024, 2024
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Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. A key challenge is the optimal use of high-performance computing environments. The work presented here focuses on a developed open-source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency, and scalability.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev., 17, 2197–2219, https://doi.org/10.5194/gmd-17-2197-2024, https://doi.org/10.5194/gmd-17-2197-2024, 2024
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This work outlines a new solver written in Fortran to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the forward algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev., 17, 1975–1993, https://doi.org/10.5194/gmd-17-1975-2024, https://doi.org/10.5194/gmd-17-1975-2024, 2024
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Previous work has demonstrated that adding geological knowledge to modelling methods creates more accurate and reliable models. Following this reasoning, we added constraints from magma emplacement mechanisms into existing modelling frameworks to improve the 3D characterisation of igneous intrusions. We tested the method on synthetic and real-world case studies, and the results show that our method can reproduce intrusion morphologies with no manual processing and using realistic datasets.
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024, https://doi.org/10.5194/gmd-17-1957-2024, 2024
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It is vital to know the extent and concentration of volcanic ash in the atmosphere during a volcanic eruption. Whilst satellite imagery may give an estimate of the ash right now (assuming no cloud coverage), we also need to know where it will be in the coming hours. This paper presents a method for estimating parameters for a volcanic eruption based on satellite observations of ash in the atmosphere. The software package is open source and applicable to similar inversion scenarios.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
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Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Younghun Kang and Ethan J. Kubatko
Geosci. Model Dev., 17, 1603–1625, https://doi.org/10.5194/gmd-17-1603-2024, https://doi.org/10.5194/gmd-17-1603-2024, 2024
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Models used to simulate the flow of coastal and riverine waters, including flooding, require a geometric representation (or mesh) of geographic features that exhibit a range of disparate spatial scales from large, open waters to small, narrow channels. Representing these features in an accurate way without excessive computational overhead presents a challenge. Here, we develop an automatic mesh generation tool to help address this challenge. Our results demonstrate the efficacy of our approach.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
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Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
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Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
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Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
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Coupled reaction transport modelling is an established and beneficial method for studying natural and synthetic porous material, with applications ranging from industrial processes to natural decompositions in terrestrial environments. Up to now, a framework that explicitly considers the porous structure (e.g. from µ-CT images) for modelling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
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The Voellmy rheology has been widely used for simulating snow and rock avalanches. Recently, a modified version of this rheology was proposed, which turned out to be able to predict the observed long runout of large rock avalanches theoretically. The software MinVoellmy presented here is the first numerical implementation of the modified rheology. It consists of MATLAB and Python classes, where simplicity and parsimony were the design goals.
Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
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This study introduces a new computational framework called Scalable Feature Extraction and Tracking (SCAFET), designed to extract and track features in climate data. SCAFET stands out by using innovative shape-based metrics to identify features without relying on preconceived assumptions about the climate model or mean state. This approach allows more accurate comparisons between different models and scenarios.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
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The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
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This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
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This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Ane Lopez de Gamiz-Zearra, Cecilie Hansen, Xavier Corrales, Iñaki Quincoces, Izaskun Preciado, and Eider Andonegi
EGUsphere, https://doi.org/10.5194/egusphere-2023-1368, https://doi.org/10.5194/egusphere-2023-1368, 2023
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This paper describes the development of the first calibrated end-to-end Atlantis model for the Bay of Biscay that will help us improve the comprehension of the spatial functioning of the Bay of Biscay ecosystem and help establishing management measures of human activities. Our results highlighted the importance of lower trophic levels to the pelagic system and demonstrate the importance of having accurate and precise data for biological processes.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
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Short summary
Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Optimizing the initial state of atmospheric chemistry model input is one of the most essential...
