Improving temperature interpolation using MODIS LST and local topography: a comparison of methods in south east Australia

Abstract

Available climate data for south east Australia is reliant upon elevational lapse rates, which do not account for mesoscale processes that can affect temperatures, such as cold air drainage. Additional predictor variables are available for generating new climate datasets such as topographic indices and Moderate Resolution Imaging Spectroradiometer land surface temperature (MODIS LST); however, these have not been thoroughly tested to date. In this study, the relative benefits of including a localized topographic index and standardized MODIS LST values for temperature interpolation were assessed using partial bivariate splines, full and partial trivariate splines, and regression kriging. Triv..