4B.2 Effects of MMTS on Long-Term Extreme Temperature Trends

Tuesday, 24 January 2017: 8:45 AM
609 (Washington State Convention Center )
Kenneth E. Kunkel, CICS-NC, Asheville, NC; and N. J. Doesken, D. A. Robinson, M. R. Gerbush, and W. A. Ryan

In the 1980s, the National Weather Service’s Cooperative Observer Network (COOP) began to change the daily maximum (Tmax) and minimum temperature (Tmin) instrumentation from liquid-in-glass thermometers in a Cotton Region Shelter (CRS/LIG) to an electronic Maximum-Minimum Temperature System (MMTS) in a smaller radiation shield. Since the changeover, simultaneous side-by-side observations from the CRS/LIG and MMTS systems have been made at the Colorado State University (Fort Collins) and Rutgers University (New Brunswick) COOP stations. These simultaneous observations, now exceeding 20 years in length, were analyzed to estimate the impact of this changeover on trends in extreme temperatures.

The CRS/LIG Tmax observations are about 0.4°Cwarmer than MMTS both for mean Tmax and extreme (lowest and highest 5 percentile) high Tmax. However, for extreme low Tmax, the CRS/LIG excess over MMTS ranged from 0.5 to 0.8°C. Observations of snow depth indicate that snow cover is on average highest on days with the lowest Tmax values, indicating that snow cover is likely one of the causes for the larger differences. For extreme values of Tmin, the differences between CRS/LIG and MMTS are small (around 0.1°C or less) for both extreme high Tmin and extreme low Tmin.

A sensitivity study using various daily temperature adjustment values applied to daily observations for a set of long-term COOP stations indicates some potential noticeable quantitative effects on extreme temperature metrics. Most important, the differences between variations in metrics separately calculated with Tmax and Tmin are substantially diminished and conclusions about different behavior of extreme nighttime vs daytime extremes may need to be re-examined. However, based on the comparison at these two stations, the potential changes in extreme metrics do not appear to be large enough to negate broad conclusions concerning national trends and variations.

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