Estimating daily maximum air temperature with MODIS data and a daytime temperature variation model in Beijing urban area

ABSTRACT

An algorithm to estimate daily maximum T_a (T_a^max) is presented in this study based on moderate resolution imaging spectroradiometer (MODIS) products and a daytime T_a variation model. The algorithm first estimates daytime T_a at the times of Terra and Aqua satellites overpass. Subsequently, the T_a^max is inferred from the daytime T_a estimations using the daytime T_a variation model. This algorithm was applied to the area within the sixth ring road of Beijing from 2009 to 2010. A comprehensive validation experiment including a leave-one-out cross validation, a temporal validation, an overall comparison and a sensitivity analysis was conducted to evaluate the new algorithm. Results indicate that the spatial distribution of T_a^max can be accurately generated using the algorithm with a root mean square error (RMSE) varying from 1.62 to 2.33 K and a coefficient of determination varying from 0.95 to 0.98. Sensitivity analysis shows that the algorithm is more sensitive to T_s at daytime of Aqua MODIS overpass (T_s^Aqua_day) than to T_s at other times. A 2 K increase in T_s^Aqua_day would result in a 1.9 K increase in T_a^max estimates.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant 41501457 and 41471348], the joint fund of the National Natural Science and Civil Aviation research foundation of China [No. U1533114] and the State Key Laboratory of Coal Resources and Safe Mining Open Research Project [Grant SKLCRSM14KFB04].