Spatio-Temporal Variability in Topoclimate Inferred from Land Surface Temperature Data and its Relevance for Mapping Climatic Refugia

Monday, 14 December 2015: 13:55
3005 (Moscone West)
Solomon Dobrowski, Jared Oyler and Brady Allred, University of Montana, Missoula, MT, United States
Topoclimatic diversity is considered an important trait of climatic refugia as it should allow for short distance dispersal of organisms to ameliorate climatic shifts. Nevertheless, topoclimatic diversity can be a challenge to quantify in the absence of distributed sensors or extensive instrumentation. In practice, topographic complexity is used as a proxy for topoclimatic diversity with the assumption that complex terrain will necessarily lead to diverse climates. However, this ignores spatio-temporal variability in soil moisture, snow cover, land cover, and vegetation which mediates the influence terrain has on climate. To better quantify topoclimatic diversity, we examine ten year climatological means for each month for daytime and nighttime MODIS Aqua satellite land surface temperature (LST) observations over the pacific northwest of the U.S. LST is well suited for this application because it is sensitive to variability in regional climate, hydrology, and land cover all of which can dramatically alter the energy balance and temperature of a site. We decompose the spatio-temporal variability in LST into its drivers including geographic position (x,y,z), biophysical factors (e.g. snow cover, vegetation cover, land surface type), and topoclimatic factors (e.g. cold air drainage, aspect). We find that nighttime LST data can be readily used to identify topoclimatic diversity driven by cold air pooling and thermal stratification of minimum temperatures whereas daytime LST data primarily characterizes the influence of vegetation cover on maximum temperatures. For both daytime and nighttime LST, the relative influence of topoclimatic drivers varies seasonally and is also sensitive to maritime influences or continentality of the site. Our approach allows for the decomposition of thermal variability into spatial and temporal components and allows for directly mapping regions of high topoclimatic diversity, an initial step for identifying potential climate refugia.