Suppose you are a city planner, regional water manager, or wildlife conservation specialist who is asked to include the potential impacts of climate variability and change in your risk management and planning efforts. What climate information would you use? The choice is often regional or local climate projections downscaled from global climate models (GCMs; also known as general circulation models) to include detail at spatial and temporal scales that align with those of the decision problem. A few years ago this information was hard to come by. Now there is Web‐based access to a proliferation of high‐resolution climate projections derived with differing downscaling methods.
[1] Numerous studies have evaluated precipitation trends in Alaska and come to different conclusions. These studies differ in analysis period and methodology and do not address the issue of temporal homogeneity. To reconcile these conflicting results, we selected 29 stations with largely complete monthly records, screened them for homogeneity, and then evaluated trend over two analysis periods (1950-2010 and 1980-2010) using three methods: least absolute deviation regression, ordinary least squares regression (with and without transformation), and Mann-Kendall trend testing following removal of first-order autocorrelation. We found that differences in analytical period had a significant impact on trends and that the presence of inhomogeneities or step changes also posed a substantial challenge in detecting reliable long-term trends in precipitation over Alaska, particularly in the southern part of the state. Although some of these inhomogeneities occur in the mid-1970s and could be associated with well-documented changes in the Pacific Ocean and the Aleutian Low at that time, many of the inhomogeneities co-occur with changes in station location, instrumentation, or operation. These operationally induced changes make it difficult to accurately detect the impact of decadal to multidecadal climate variability on precipitation amounts and to assess historical precipitation trends in Alaska.
There is a great deal of interest in whether and how Alaska's precipitation is changing but little agreement in the existing peer-reviewed literature. To provide insight on this question, we have selected three commonly used 0.5°resolution gridded precipitation products that have long-term monthly data coverage (Climatic Research Unit TS3.10.1, Global Precipitation Climatology Centre Full Data Reanalysis version 5, and University of Delaware version 2.01) and evaluated their homogeneity and trends with multiple methods over two periods, 1950-2008 and 1980-2008. All three data sets displayed common broadscale features of Alaska's precipitation climatology, but there were substantial differences between them in terms of average precipitation amount and interannual variability. Temporal inhomogeneity was a significant concern over Alaska in gridded precipitation products, as it was in the state's coastal weather stations. Although underlying station inhomogeneities were inherited to some extent by all of the gridded data sets, differences in data set construction contributed to dissimilarities in inhomogeneity, as well. There were contrasts in trends between the two time periods, and some minor discrepancies occurred as a function of the trend detection method, but the main disparities stemmed from choice of data set. Indeed, there were large areas where these data sets disagreed on both the sign and significance of precipitation trends. Until further analysis can resolve these differences, researchers using gridded precipitation data or evaluating studies based on such data should interpret results with extreme caution.
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