Estimating Instantaneous Air Temperature Based On Remote Sensing Surface Temperature Products Over SanDianHe River Basin

Near-surface air temperature(Ta),which defines the air temperature above 2 m above the surface,is the most important variable in climate and ecology,due to the junction of the critical surface weather environment and the atmosphere,direct time influence,and scale monitoring of hydrometeorology.The overestimated monitoring scale is the research and significance of the subscale.However,due to the limited number of actual climate change scenarios and complex regional distributions under climatic conditions,the resulting climate change scenarios are quite low.Real-time monitoring of body temperature possible.In this thesis,the fifth-generation reanalysis Ta is based on the moderate-resolution imaging spectroradiometer(MODIS)land surface temperature(LST)and the European Centre for Medium-Range Weather Forecasts(ECMWF).Products are the data source.First,the spatiotemporal continuous MODIS LST was reconstructed by using the Data Interpolating Empirical Orthogonal Function(DINEOF)method.Second,a simple multi-variable linear regression equation(Simple multi-variable linear regression)for instantaneous temperature estimation was established based on the ERA5 reanalysis data.regression,SML),and finally use the MODIS data to estimate the near-surface instantaneous temperature.At the same time,the study uses the observation data of the radiation-meteorological parameter comprehensive observation instrument installed in Zhenglan Banner,Inner Mongolia from April to July 2021 to verify the instantaneous temperature estimation.accuracy.The following conclusions are drawn:(1)Through the analysis,summary and repeated tests of the existing remote sensing temperature inversion theories,technologies and methods at home and abroad,the research shows that the surface temperature,atmospheric downlink long-wave radiation,atmospheric water vapor and terrain are most closely related to the near-surface temperature.The study selected typical parameters for air temperature estimation.Spatially continuous remote sensing surface temperature was reconstructed using data interpolating empirical orthogonal function.In order to verify the accuracy of the reconstructed surface temperature,the method of artificially generating clouds was used.The verification results of the reconstructed surface temperature show that the root mean square error(Root Mean Square Error,RMSE)of day and night are 2.7411 K and 1.9331 K,respectively.Reconstructed surface temperature data are suitable for use in air temperature estimation models.(2)Using the empirical orthogonal function interpolation method to reconstruct the spatially continuous remote sensing surface temperature has a good effect.In order to verify the accuracy of the reconstructed surface temperature,the study uses the method of artificially generating clouds to test,and the results show that the root mean square error(Root Mean Square Error,RMSE)day and night are 2.7411 K and 1.9331 K,respectively.(3)The temperature estimation model proposed in this paper has good accuracy.The verification results show that the coefficient of determination of the instantaneous air temperature is 0.8599,and the RMSE is 3.5K.At the same time,it is tested in daytime and nighttime.The RMSEs of the two are 3.98 K and 2.95 K,respectively,and the accuracy at night is higher than that in daytime.The research results can provide a scientific basis for the study of climate change and climate change adaptation in the Lightning River Basin,and have important theoretical reference significance for the rational allocation of water resources in the basin in the future.(4)In the thesis,most of the remote sensing temperature inversions were based on the daily average temperature.In this paper,based on the surface temperature data obtained from the MODIS data in one day,the instantaneous temperature of the Lightning River Basin was estimated.To a certain extent,the applicability of using remote sensing data products to invert air temperature is improved,and new ideas are provided for obtaining air temperature data with higher temporal resolution and higher precision.