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Evaluation and characteristic research in diurnal surface temperature cycle in China using FY-2F data

  • role： First author第一作者
  • Email：xiangchenmeng@yeah.net
  • Introduction：孟翔晨，1990年生，男，博士研究生，研究方向为热红外地表温度反演的理论和应用。E-mail：xiangchenmeng@yeah.net
MENG Xiangchen,  
  • No information about the author is available
LIU Hao,  
  • role： Corresponding author通信作者
  • Email：Jie_Cheng@bnu.edu.cn
  • Introduction：程洁，1981年生，男，副教授，研究方向为热红外定量遥感。E-mail：Jie_Cheng@bnu.edu.cn
CHENG Jie*

résumé

Diurnal Surface Temperature Cycle (DSTC) model is an important input parameter in the field of meteorology, hydrology, and ecology. In the past 20 years, various DSTC models under clear-sky conditions have been developed on the basis of Spinning Enhanced Visible and Infrared Imager (SEVIRI) and Geostationary Operational Environment Satellite (GOES) satellites. However, only a few related studies have focused on China due to its complex topography, geomorphology, and climatic conditions. This situation restricts the application and development of DSTC models in the region. Although the DSTC model is mature, its evaluation is often based on the data of a certain point or day, which lacks verification at a large range of time and spatial scales. Moreover, the free variable setting of the DSTC model cannot meet the need at large time and spatial scales. Thus, the variable setting of the DSTC model must be expanded. In this study, six DSTC models were evaluated on the basis of FY-2F land surface temperature product at the monthly average and large space scales for China. In addition, JNG06 model was used to analyze the diurnal variation characteristics of Land Surface Temperature (LST) with the changes in seasonality, latitude and longitude, and land cover types. Semi-empirical model is simple and convenient and has a wide range of applications. Physical model is close to the actual physical condition of the surface. Therefore, five semi-empirical models, namely, GOT01, VAN06, JNG06, INA08, and GOT09, and the GEM-V physical model were used for DSTC simulation and analysis. On the basis of the geographical location of 194 meteorological stations, the corresponding FY-2F LST data were extracted, and the average monthly and hourly LST data after quality control were set as the model initial value. To evaluate the fitting accuracy of DSTC model in China, the model evaluation was divided into two parts: 1) the fitting of DSTC model was divided into five time periods, and the precision of DSTC model was analyzed; and 2) the fitting accuracy of each model under different land cover types was statistically explored on the basis of the land cover types of 194 stations. JNG06 model was also used to analyze the diurnal variation characteristics of LST with the changes in seasonality, latitude and longitude, and land cover types. Analysis of the average root mean square error (RMSE) of five time windows showed that GOT09 model obtained the global optimal fitting accuracy with an RMSE of 0.89 K, followed by JNG06 and GEM_V models with RMSEs of 0.92 and 0.94 K, respectively. GOT01, INA08, and VAN06 models obtained the worst accuracy. Each model had the best fitting precision in urban and built-up, cropland/natural vegetation mosaic, and evergreen broadleaf forest with an RMSE between 0.89 and 0.92 K. The fitting precision in mixed forest and cropland followed with an RMSE of around 1.0 K. Each model had the worst fitting precision in barren or sparse vegetation and savannas with an RMSE of above 1.3 K. From the results, we can conclude that the accuracies of GOT01, VAN06, and INA08 are poor in all land cover types and time windows, and the remaining models are relatively robust with close accuracy. The land surface temperature simulated by JNG06 model in four land cover types vary with the changes in latitude and longitude. The rule of LST varies with the change in latitude and but is unaffected by the change in longitude. The DSTC model can be used as the input parameter of climate and hydrological models. The model can also be used as reference for future studies on the DSTC model and its applications.

mots-clés

remote sensing;FY-2F;MCD12C1;LST (Land Surface Temperature);diurnal surface temperature cycle;meteorology stations

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