The University of Arizona

Temperature | CLIMAS

 SW Climate Outlook


(data through July 17, 2013)
Data Source(s): High Plains Regional Climate Center

Temperatures since the water year began on October 1 have been warmest in the southern deserts and coolest in higher elevations, and temperatures have been within a few degrees Fahrenheit of average for most of the Southwest (Figures 1a–b). The coldest region has been in the Sangre de Cristo Mountains in northern New Mexico. While temperatures during January and February were below average, conditions in the last three months were the opposite. The April–June period ranked as the 11th and 16th warmest (out of 119) in Arizona and New Mexico, respectively.

The last 30 days were particularly warm as a result of a strong ridge of high pressure that brought an extreme heat wave to the Southwest and caused record-high temperatures across the region. Maximum temperatures along the lower Colorado River valley reached the low 120s and Phoenix hit 119 degrees F. Tucson also experienced its warmest June on record; the high temperature each day eclipsed 99 degrees F. Between June 18 and July 17, temperatures were 2–4 degrees F warmer than average in western Arizona and New Mexico and across eastern New Mexico (Figures 1c–d). The high temperatures increased water demand, especially in west-central New Mexico where drought became exceptional.


The water year begins on October 1 and ends on September 30 of the following year. We are in the 2013 water year as of October 1, 2012. Water year is more commonly used in association with precipitation; water year temperature can be used to measure the temperatures associated with the hydrological activity during the water year.

Average refers to the arithmetic mean of annual data from 1981–2010. Departure from average temperature is calculated by subtracting current data from the average. The result can be positive or negative.

The continuous color maps (Figures 1a, 1b, 1c) are derived by taking measurements at individual meteorological stations and mathematically interpolating (estimating) values between known data points. The dots in Figure 1d show data values for individual stations. Interpolation procedures can cause aberrant values in data-sparse regions.

These are experimental products from the High Plains Regional Climate Center.