Ground‐Validation and Error Attribution of Near‐Surface Air Temperature From AIRS in North America

Abstract

Abstract Accurate estimation of near‐surface air temperature (TsurfAir) at fine spatiotemporal resolution is crucial for environmental applications, data assimilation into land surface models, and climate change studies. The Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite measures TsurfAir twice a day at the global scale. In this study, the AIRS TsurfAir is validated using ground‐based weather stations in North America. Owing to the high density of weather stations, spatial heterogeneity (<1°) of TsurfAir is modeled using semi‐variograms and further used to calculate the validation reference via ordinary kriging at AIRS retrieval footprints. This analysis intends to reveal error characteristics in cold and hot seasons by selecting six months of data in January and July of three years, along with a case study on two extreme events. Furthermore, MODIS‐enabled land surface temperature and land cover are used to attribute the observed error in TsurfAir. Results show an overall warm bias of 0.11 K from AIRS TsurfAir and conditional bias over‐ and underestimating cold and hot temperatures, respectively. Spatial heterogeneity of TsurfAir is found to influence the variance of AIRS TsurfAir error. As a possible source of TsurfAir error, land surface temperatures (Tskin) from AIRS and MODIS are compared. Close match between the two Tskin products indicates a lesser influence of the Tskin difference on TsurfAir error. Overall, the ground validation of AIRS TsurfAir along with the error attribution can facilitate post‐processing of AIRS products and uncertainty analysis for the wide range of applications of AIRS TsurfAir.

Keywords

• AIRS
• ground‐validation
• error attribution
• MODIS
• near‐surface air temperature