Articles | Volume 17, issue 2
https://doi.org/10.5194/gmd-17-497-2024
© Author(s) 2024. 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-17-497-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy of Sciences, Beijing 101408, China
Department of Land, Air, and Water Resources, University of California, Davis, Davis, California 95616, USA
Paul Ullrich
Department of Land, Air, and Water Resources, University of California, Davis, Davis, California 95616, USA
Xianhong Meng
CORRESPONDING AUTHOR
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy of Sciences, Beijing 101408, China
Christopher Duffy
Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA
Hao Chen
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy of Sciences, Beijing 101408, China
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
Zhaoguo Li
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy of Sciences, Beijing 101408, China
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Manuscript not accepted for further review
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The under-ice water temperature of Ngoring Lake has been rising based on in situ observations. We obtained results showing that strong downward shortwave radiation is the main meteorological factor, and precipitation, wind speed, downward longwave radiation, air temperature, ice albedo, and ice extinction coefficient have an impact on the range and rate of lake temperature rise. Once the ice breaks, the lake body releases more energy than other lakes, whose water temperature remains horizontal.
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Yunshuai Zhang, Qian Huang, Yaoming Ma, Jiali Luo, Chan Wang, Zhaoguo Li, and Yan Chou
Atmos. Chem. Phys., 21, 15949–15968, https://doi.org/10.5194/acp-21-15949-2021, https://doi.org/10.5194/acp-21-15949-2021, 2021
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The source region of the Yellow River has an important role in issues related to water resources, ecological environment, and climate changes in China. We utilized large eddy simulation to understand whether the surface heterogeneity promotes or inhibits the boundary-layer turbulence, the great contribution of the thermal circulations induced by surface heterogeneity to the water and heat exchange between land/lake and air. Moreover, the turbulence in key locations is characterized.
Paul A. Ullrich, Colin M. Zarzycki, Elizabeth E. McClenny, Marielle C. Pinheiro, Alyssa M. Stansfield, and Kevin A. Reed
Geosci. Model Dev., 14, 5023–5048, https://doi.org/10.5194/gmd-14-5023-2021, https://doi.org/10.5194/gmd-14-5023-2021, 2021
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TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets. Version 2.1 of TE now provides extensive support for nodal and areal features. This paper describes the algorithms that have been added to the TE framework since version 1.0 and gives several examples of how these can be combined to produce composite algorithms for evaluating and understanding atmospheric features.
Robert Ladwig, Paul C. Hanson, Hilary A. Dugan, Cayelan C. Carey, Yu Zhang, Lele Shu, Christopher J. Duffy, and Kelly M. Cobourn
Hydrol. Earth Syst. Sci., 25, 1009–1032, https://doi.org/10.5194/hess-25-1009-2021, https://doi.org/10.5194/hess-25-1009-2021, 2021
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Short summary
Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating...