Evaluation of Seven Atmospheric Profiles from Reanalysis and Satellite-Derived Products: Implication for Single-Channel Land Surface Temperature Retrieval

Jingjing Yang,Maofang Gao,Si-Bo Duan,Xiaoyu Zhang,Cheng Huang,Pei Leng,Penghai Wu

doi:10.3390/rs12050791

Abstract

Land surface temperature (LST) is vital for studies of hydrology, ecology, climatology, and environmental monitoring. The radiative-transfer-equation-based single-channel algorithm, in conjunction with the atmospheric profile, is regarded as the most suitable one with which to produce long-term time series LST products from Landsat thermal infrared (TIR) data. In this study, the performances of seven atmospheric profiles from different sources (the MODerate-resolution Imaging Spectroradiomete atmospheric profile product (MYD07), the Atmospheric Infrared Sounder atmospheric profile product (AIRS), the European Centre for Medium-range Weather Forecasts (ECMWF), the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), the National Centers for Environmental Prediction (NCEP)/Global Forecasting System (GFS), NCEP/Final Operational Global Analysis (FNL), and NCEP/Department of Energy (DOE)) were comprehensively evaluated in the single-channel algorithm for LST retrieval from Landsat 8 TIR data. Results showed that when compared with the radio sounding profile downloaded from the University of Wyoming (UWYO), the worst accuracies of atmospheric parameters were obtained for the MYD07 profile. Furthermore, the root-mean-square error (RMSE) values (approximately 0.5 K) of the retrieved LST when using the ECMWF, MERRA2, NCEP/GFS, and NCEP/FNL profiles were smaller than those but greater than 0.8 K when the MYD07, AIRS, and NCEP/DOE profiles were used. Compared with the in situ LST measurements that were collected at the Hailar, Urad Front Banner, and Wuhai sites, the RMSE values of the LST that were retrieved by using the ECMWF, MERRA2, NCEP/GFS, and NCEP/FNL profiles were approximately 1.0 K. The largest discrepancy between the retrieved and in situ LST was obtained for the NCEP/DOE profile, with an RMSE value of approximately 1.5 K. The results reveal that the ECMWF, MERRA2, NCEP/GFS, and NCEP/FNL profiles have great potential to perform accurate atmospheric correction and generate long-term time series LST products from Landsat TIR data by using a single-channel algorithm.

Highlights

Land surface temperature (LST) is a key parameter that reflects the physical processes of land at local and global scales, and it plays an important role in the interaction between the surface and the atmosphere, as well as the process of water cycle and energy exchange [1,2,3,4]
Eight atmospheric profiles that were obtained from multiple sources were used in this study, including one radio sounding profile downloaded from the University of Wyoming (UWYO), two satellite-derived profiles (MxD07 and AIRS), and five reanalysis profiles (the European Centre for Medium-range Weather Forecasts (ECMWF), the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), the National Centers for Environmental Prediction (NCEP)/Global Forecasting System (GFS ), NCEP/Final Operational Global Analysis (FNL), and NCEP/Department of Energy (DOE))
The vertical distributions of air temperature and dew point temperature that were extracted from the reanalysis profiles were more similar than those from the satellite-derived profiles (i.e., MYD07 and AIRS) when using the UWYO profile as reference data

Summary

Introduction

Land surface temperature (LST) is a key parameter that reflects the physical processes of land at local and global scales, and it plays an important role in the interaction between the surface and the atmosphere, as well as the process of water cycle and energy exchange [1,2,3,4]. Satellites carrying thermal infrared (TIR) sensors can effectively measure LST at the local and global scales [8,9,10,11]. Landsat satellites carrying TIR sensors have been launched since the 1980s. Except for the Thermal Infrared Sensor (TIRS), which is aboard the Landsat 8 satellite, other sensors (e.g., the Thematic Mapper (TM) and the Enhanced Thematic Mapper (ETM+)) have only one TIR band [12]. A single-channel algorithm is usually used to estimate LST from TIRS band 10 data [12,15,16,17]. The RTE-based single-channel algorithm in conjunction with atmospheric profiles has been proven to have high LST retrieval accuracy [25,26]

Methods

Findings

Discussion

Conclusion