首页|Parameterization,sensitivity,and uncertainty of 1-D thermo-dynamic thin-ice thickness retrieval

Parameterization,sensitivity,and uncertainty of 1-D thermo-dynamic thin-ice thickness retrieval

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Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article examines the deviation of the classical model's TIT output when using different parameterization schemes and the sensitivity of the output to the ice thickness.Moreover,it estimates the uncertainty of the output in response to the uncertainties of the input variables.The parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow conductivity.Measured input parameters include air temperature,ice surface temperature,and wind speed.Among the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice conductivity.The sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and depth.The retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved data.From in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be high.The resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement error.The results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and −0.005 m,respectively.

Arctic sea ice1-D thermodynamic ice modelthin-ice thicknesssea ice parameterization

Tianyu Zhang、Mohammed Shokr、Zhida Zhang、Fengming Hui、Xiao Cheng、Zhilun Zhang、Jiechen Zhao、Chunlei Mi

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School of Geospatial Engineering and Science,Sun Yat-Sen University/Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China

Key Laboratory of Comprehensive Observation of Polar Environment(Sun Yat-Sen University),Ministry of Education,Zhuhai 519082,China

State Key Laboratory of Remote Sensing Science,College of Global Change and Earth System Science,Beijing Normal University,Beijing 100875,China

Science and Technology Branch,Environment and Climate Change Canada,Toronto M3H5T4,Canada

Qingdao Innovation and Development Base(Centre),Harbin Engineering University,Qingdao 266500,China

State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

University of Chinese Academy of Sciences, Beijing 100049, China

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2024

10.1007/s13131-023-2210-x

海洋学报(英文版)
中国海洋学会

海洋学报(英文版)

CSTPCD
影响因子：0.323
ISSN：0253-505X
年,卷(期)：2024.43(7)
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