Landscape and temporal patterns of temperature were observed for local (13 station) and regional (35 station) networks in the southern Appalachian Mountains of North America. Temperatures decreased with altitude at mean rates of 7°C/km (maximum temperature) and 3°C/kin (minimum temperature). Daily lapse rates depended on the method and stations used in the calculations. Average daily temperature ranges decreased as elevation increased, from 14°C at 700 m to 7°C at 1440 m, and daily temperature ranges were typically higher in spring and fall at any given station. Daily maximum temperatures above the forest canopy averaged 1.4°C higher at a south-facing station relative to a comparable northwest-facing station, and above-canopy daily minimum temperatures were depressed at a valley-bottom station. Regional regression models provided a more accurate estimates of station temperature than either kriging or local lapse models when tested using 35 National Climatic Data Center (NCDC) stations in the southern Appalachians. Data-splitting tests yielded mean absolute errors (MAE) from 1.39 to 2.30°C for predictions of daily temperatures. Ten-year biases for an independent data set collected at four stations in the Coweeta Basin ranged from -2.87 to 2.91°C for daily temperatures, with regional regression performing best, on average. However tests against another independent data set indicate regional regression and local lapse models were not significantly different, with mean biases averaged from -2.78 to 2.91°C for daily predicted temperatures.
Copyright 2009 Elsevier B.V., All rights reserved.