An improved temporal correction method for mobile measurement of outdoor thermal climates

Accurate temporal corrections for the spatial meteorological parameters obtained through mobile measurements are essential in the synchronous analysis of local urban climates. This paper discusses current temporal correction models and proposes an improved model by considering correlation coefficients that are influenced by the underlying surface conditions, and the distance between the stationary weather stations and the mobile location points during a mobile measurement. Together with four adjacent, simultaneously recording stationary weather stations, long-term mobile temperature and humidity measurements were taken along a 17-km transect covering 18 mobile location points through the University Town of Shenzhen. Using the multiple air temperature and relative humidity values of the mobile location points and stationary weather stations, the function equations for determining the correlation coefficients were obtained for application in the proposed temporal correction model. Further, three kinds of validation methods were applied to compare temporal correction models. Validation results showed that the temporal correction model proposed in this study was significantly more accurate and reliable compared to the other models.