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Dai Y, Wang T, Sheng Y, Wang L, Chen H, Zhang X, Li X, Wang W, Wu J, Chen W, Yao T. Westerly-triggered lake-effect snowfall enhanced with climate warming over the Tibetan Plateau. Sci Bull (Beijing) 2024; 69:968-977. [PMID: 38331705 DOI: 10.1016/j.scib.2024.01.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 02/10/2024]
Abstract
Lake-effect snowfall (LES) occurs when cold air moves across open lakes. LES is expected to occur more frequently over the TP, due to the intensified lake expansion caused by intensified global warming. Thus, there is an urgent need to comprehensively assess the LES over the TP. Here, we revealed that the LES is triggered by westerly southward shift leading to the drop in air temperature and is positively correlated with lake area, wind speed and longitude across 12 large lakes (>300 km2) based on satellite observations and reanalysis data. Using a sensitivity model simulation, we determined that large lakes in the southern TP contributed to more than 50% of the snowfall in the downwind area in 2013. Projections indicate that the westerly-triggered LES will increase under the future RCP4.5 climate warming scenario, highlighting the importance of developing adaptive policies to address the growing risks associated with future LES.
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Affiliation(s)
- Yufeng Dai
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Tao Wang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yongwei Sheng
- Department of Geography, University of California, Los Angeles CA 90095, USA
| | - Lei Wang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Hongbin Chen
- College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China
| | - Xiaowen Zhang
- Department of Resource Management, Tangshan Normal University, Tangshan 063000, China
| | - Xiangyu Li
- Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Weicai Wang
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Junfei Wu
- Center for Pan-third Pole Environment, Lanzhou University, Lanzhou 730000, China
| | - Wenfeng Chen
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Tandong Yao
- State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
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Huang A, Lazhu, Wang J, Dai Y, Yang K, Wei N, Wen L, Wu Y, Zhu X, Zhang X, Cai S. 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 : JGR 2019; 124:3143-3167. [PMID: 31218151 PMCID: PMC6559290 DOI: 10.1029/2018jd029610] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 01/20/2019] [Accepted: 01/26/2019] [Indexed: 10/13/2023]
Abstract
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 °C instead of 4 °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 10 m, while WRF-Lake is the best at simulating the amplitude and pattern of the temperature variability at all depths.
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Affiliation(s)
- Anning Huang
- CMA‐NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric SciencesNanjing UniversityNanjingChina
| | - Lazhu
- Key Laboratory of Tibetan Environment Changes and Land Surface ProcessesInstitute of Tibetan Plateau Research, Chinese Academy of SciencesBejingChina
| | - Junbo Wang
- Key Laboratory of Tibetan Environment Changes and Land Surface ProcessesInstitute of Tibetan Plateau Research, Chinese Academy of SciencesBejingChina
| | - Yongjiu Dai
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric SciencesSun Yat‐sen UniversityGuangzhouChina
| | - Kun Yang
- Department of Earth System ScienceTsinghua UniversityBeijingChina
| | - Nan Wei
- Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, School of Atmospheric SciencesSun Yat‐sen UniversityGuangzhouChina
| | - Lijuan Wen
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid RegionsChinese Academy of SciencesLanzhouChina
| | - Yang Wu
- State Key Laboratory State of Severe Weather and Joint Center for Atmospheric Radar Research of CMA/NJU, School of Atmospheric SciencesNanjing UniversityNanjingChina
| | - Xueyan Zhu
- CMA‐NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric SciencesNanjing UniversityNanjingChina
| | - Xindan Zhang
- CMA‐NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric SciencesNanjing UniversityNanjingChina
| | - Shuxin Cai
- CMA‐NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric SciencesNanjing UniversityNanjingChina
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Evaluation of the Multi-Scale Ultra-High Resolution (MUR) Analysis of Lake Surface Temperature. REMOTE SENSING 2017. [DOI: 10.3390/rs9070723] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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