Modeling Near-Surface Air Temperature From Solar Radiation and Lapse Rate: New Development on Short-Term Monthly and Daily Approach

Abstract

Short-term monthly mean temperature (T_m ) and short-term daily mean temperature (T_d ) rather than long-term monthly and daily mean temperature (T_m and T_d ) are preferred for some ecosystem studies such as carbon source and sink, pine beetle mortality, and snow melting. The recent progress of modeling T_m and T_d (based on the previous work on T_m ) supported by climatologically aided interpolation (CAI) is reported over the mountainous Yellowstone National Park. With the spatial scale of a 30 m digital elevation model (DEM), the slope, aspect, and shadows cast by surrounding topography, which could not be well captured by very coarse DEM, could be taken into account. Data from 12 months (Jan-Dec 2008) and 12 dates (25 Jan-Dec 2008) were used to demonstrate the approach. Inverse distance weighting (IDW) interpolations of limited temperature anomalies were adopted to represent the deviations from normality. T_m , as a preexisting climatology surface, was added to deviations in order to model T_m . Linear temporal interpolation of adjacent T_m was used to create a climatology surface, which was then added to deviations in order to model T_d . Results show the mean absolute errors (MAEs) for T_m ranged from 0.75° C to 1.78° C, while the MAEs for T_d ranged from 1.14° C to 2.02° C. The four factors of elevation, seasonal change of lapse rate, temperature difference caused by variation in solar radiation, and preexisting climatology surface for the CAI approach were comprehensively considered in this approach.

Keywords:

• montane ecosystem
• surface temperature
• temperature anomalies
• inverse distance weighting
• Yellowstone National Park