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DOI10.1029/2018JD029610
Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau
Huang, Anning1; Lazhu2; Wang, Junbo2; Dai, Yongjiu3; Yang, Kun4; Wei, Nan3; Wen, Lijuan5; Wu, Yang6,7; Zhu, Xueyan1; Zhang, Xindan1; Cai, Shuxin1
2019-03-27
发表期刊JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
ISSN2169-897X
EISSN2169-8996
出版年2019
卷号124期号:6页码:3143-3167
文章类型Article
语种英语
国家Peoples R China
英文摘要

The ability of FLake, WRF-Lake, and CoLM-Lake models in simulating the thermal features of Lake Nam Co in Central Tibetan Plateau has been evaluated in this study. All the three models with default settings exhibited distinct errors in the simulated vertical temperature profile. Then model calibration was conducted by adjusting three (four) key parameters within FLake and CoLM-Lake (WRF-Lake) in a series of sensitive experiments. Results showed that each model's performance is sensitive to the key parameters and becomes much better when adjusting all the key parameters relative to tuning single parameter. Overall, setting the temperature of maximum water density to 1.1 degrees C instead of 4 degrees C in the three models consistently leads to improved vertical thermal structure simulation during cold seasons; reducing the light extinction coefficient in FLake results in much deeper mixed layer and warmer thermocline during warm seasons in better agreement with the observation. The vertical thermal structure can be clearly improved by decreasing the light extinction coefficient and increasing the turbulent mixing in WRF-Lake and CoLM-Lake during warm seasons. Meanwhile, the modeled water temperature profile in warm seasons can be significantly improved by further replacing the constant surface roughness lengths by a parameterized scheme in WRF-Lake. Further intercomparison indicates that among the three calibrated models, FLake (WRF-Lake) performs the best to simulate the temporal evolution and intensity of temperature in the layers shallower (deeper) than 10m, while WRF-Lake is the best at simulating the amplitude and pattern of the temperature variability at all depths.


英文关键词lake model evaluation Lake Nam Co Tibetan Plateau thermal structure
领域气候变化
收录类别SCI-E
WOS记录号WOS:000464653500018
WOS关键词REGIONAL CLIMATE MODEL ; LAURENTIAN GREAT-LAKES ; NAM CO BASIN ; SHALLOW LAKE ; FLAKE MODEL ; POTENTIAL TEMPERATURE ; SUMMER PRECIPITATION ; WATER TEMPERATURE ; PHYSICAL CONTROLS ; DIFFUSE FRACTION
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/181718
专题气候变化
作者单位1.Nanjing Univ, Sch Atmospher Sci, CMA NJU Joint Lab Climate Predict Studies, Nanjing, Jiangsu, Peoples R China;
2.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing, Peoples R China;
3.Sun Yat Sen Univ, Sch Atmospher Sci, Guangdong Prov Key Lab Climate Change & Nat Disas, Guangzhou, Guangdong, Peoples R China;
4.Tsinghua Univ, Dept Earth Syst Sci, Beijing, Peoples R China;
5.Chinese Acad Sci, Key Lab Land Surface Proc & Climate Change Cold &, Lanzhou, Gansu, Peoples R China;
6.Nanjing Univ, Sch Atmospher Sci, State Key Lab State Severe Weather, Nanjing, Jiangsu, Peoples R China;
7.Nanjing Univ, Sch Atmospher Sci, Joint Ctr Atmospher Radar Res CMA NJU, Nanjing, Jiangsu, Peoples R China
推荐引用方式
GB/T 7714
Huang, Anning,Lazhu,Wang, Junbo,et al. Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(6):3143-3167.
APA Huang, Anning.,Lazhu.,Wang, Junbo.,Dai, Yongjiu.,Yang, Kun.,...&Cai, Shuxin.(2019).Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(6),3143-3167.
MLA Huang, Anning,et al."Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.6(2019):3143-3167.
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