Publications

Zhang, WJ; Zhao, JR; Zhu, WB; Kong, YB; Wan, BC; Liao, YL (2025). Comprehensive Validation of MODIS-Derived Instantaneous Air Temperature and Daily Minimum Temperature at Nighttime. REMOTE SENSING, 17(10), 1732.

Abstract
Nighttime near-surface air temperature is a critical input for ecological, hydrological, and meteorological models and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived instantaneous nighttime near-surface air temperature (Ta) and daily minimum temperatures (Tmin) can provide spatially continuous monitoring. The MOD07 Level-2 and MYD07 Level-2 atmospheric profile product provides air temperature at various altitude levels, facilitating a more direct estimation of Ta and Tmin. However, previous validations mainly focused on daytime, with a lack of validation for nighttime. Therefore, this study comprehensively evaluated the MOD07 Level-2 and MYD07 Level-2 derived Ta by 2168 hourly meteorological measurements over 5000 m altitude spanning in China. Furthermore, a detailed evaluation of their capability to estimate Tmin was also compared with MOD11 Level-2 and MYD11 Level-2 land surface temperature. Our results show that the highest available pressure method (HAP) estimated that, in instantaneous nighttime Ta, there was severe underestimation especially in high-altitude areas for both MOD07 (r = 0.95, Bias = -0.27 degrees C, and RMSE = 4.53 degrees C) and MYD07 data (r = 0.96, Bias = -0.17 degrees C, and RMSE = 3.73 degrees C). The adiabatic lapse rate (ALR) correction effectively reduced these errors, achieving optimal accuracy with MYD07 data (r = 0.97, Bias = -0.05 degrees C, and RMSE = 3.29 degrees C). However, the underestimation by the HAP method was still insufficient compared to Tmin estimation by land surface temperature (LST). The LST method offers improved accuracy (r = 0.98, Bias = -0.16 degrees C, RMSE = 2.89 degrees C). In general, MYD-based estimations consistently outperformed MOD-based estimations. However, seasonal and elevational variability was observed in all methods, with errors increasing notably in mountainous areas (RMSE rapidly increases to 5 degrees C and above when the altitude exceeds 2000 m). These findings can provide practical guidance for selecting appropriate inversion methods according to terrain and season and support the development of more accurate air temperature products for a range of climate- and environmental-related applications.

DOI:
10.3390/rs17101732

ISSN:
2072-4292