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Keywords:

  • temperature change;
  • Alaska;
  • reference dates;
  • running mean;
  • Hamming filter;
  • linear best fit

[1] Quantifying temperature trends across multiple decades in Alaska is an essential component for informing policy on climate change in the region. However, Alaska’s climate is governed by a complex set of drivers operating at various spatial and temporal scales, which we posit should result in a sensitivity of trend estimates to the selection of reference start and end dates as well as the choice of statistical methods employed for quantifying temperature change. As such, this study attempts to address three questions: (1) How sensitive are temperature trend estimates in Alaska to reference start dates? (2) To what degree do methods vary with respect to estimating temperature change in Alaska? and (3) How do different reference start dates and statistical methods respond to climatic events that impact Alaska’s temperature? To answer these questions, we examine the use of five methods for quantifying temperature trends at 10 weather stations in Alaska and compare multiple reference start dates from 1958 to 1993 while using a single reference end date of 2003. The results from this analysis demonstrate that, with some methods, the discrepancy in temperature trend estimates between consecutive start dates can be larger than the overall temperature change reported for the second half of the 20th century. Second, different methods capture different climatic patterns, thus influencing temperature trend estimates. Third, temperature trend estimation varies more significantly when a reference start date is defined by an extreme temperature. These findings emphasize that sensitivity analyses should be an essential component in estimating multidecadal temperature trends and that comparing estimates derived from different methods should be performed with caution. Furthermore, the ability to describe temperature change using current methods may be compromised given the increase in temperature extremes in contemporary climate change.