Our goal was to develop a methodology that could ultimately be used to produce several datasets for the region, and which was sufficiently flexible that we could apply it to various timescales in both the instrumental and paleoclimatic records.
It was important for us to account for the large topographic variations across the Southwest. Thus we developed a technique, which uses topographic data, including elevation, slope and aspect, to estimate winter (December–March) temperature and precipitation throughout Arizona and New Mexico at 1 x 1 km (0.6 x 0.6 mi.) resolution. Data from 662 temperature stations and 572 precipitation stations were used to create the interpolated data. Exploratory analyses showed that a single regression model was sufficient for creating gridded temperature datasets at 1 x 1 km resolution. For precipitation, a series of sub-regional models was used rather than a region-wide model (Brown and Comrie, 2002).
The final temperature (Figure 1) and precipitation (Figure 2) models explain 98 percent and 63 percent of the variance in the station data, respectively. Climate anomalies were calculated by examining the differences between each temperature and precipitation station and its respective modeled values. These anomaly data were used to produce winter temperature and precipitation maps at 1 x 1 km resolution for the period 1961 to 1999.
The final portion of the study is an investigation of the connections between winter climate in Arizona and New Mexico and large-scale climate patterns in the Pacific Ocean.
We have compared the 1 x 1 km resolution winter climate data with well-documented climatic indices representing patterns of atmospheric and oceanic variability in the North and East Pacific Ocean for the period 1961 to 1999. We calculated linear statistics to quantify the relationships between our fine-scale winter climate and the climate indices.