We use the high resolution North American Regional Analysis
(NARR) dataset to build for the United States a Temperature
Change Index (TCI) based on four contributing variables derived
from the layer-averaged temperature and lapse rate of the 1000mb
- 700mb layer (near-surface to 3000 meters) for the 1979-2008
period. The analysis uses Geographic Information Systems (GIS)
methods to identify distinct regional patterns based on
aggregate temperature trends and variability scores. The
resulting index allows us to identify and compare regions that
experience high (low) temperature trends and variability that
are referred to as hot spots (cold spots). The upper Midwest
emerges as the region that experiences the largest increases and
variability, due to the large magnitude of variability and
trends of all variables. In contrast, the lowest TCI scores are
observed over southeastern regions and the Rocky Mountains.
Regarding landscape characteristics, high TCI scores occur
mostly over agricultural lands (thus implyin