Journal
JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY
Volume 52, Issue 8, Pages 1677-1687Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/JAMC-D-13-026.1
Keywords
Climate change; Changepoint analysis; Regression analysis; Time series; Hindcasts; Seasonal forecasting
Categories
Funding
- National Science Foundation [AGS-1112200]
- Div Atmospheric & Geospace Sciences
- Directorate For Geosciences [1112200] Funding Source: National Science Foundation
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Eleven alternatives to the annually updated 30-yr average for specifying climate normals are considered for the purpose of projecting nonstationarity in the mean U.S. temperature climate during 2006-12. Comparisons are made for homogenized U.S. Historical Climatology Network station data, corresponding nonhomogenized station data, and spatially aggregated (megadivision) data. The use of homogenized station data shows clear improvement over nonhomogenized station data and spatially aggregated data in terms of mean-squared specification errors on independent data. The best single method overall was the most recent 15-yr average as implemented by the Climate Prediction Center (CPC15), consistent with previous work using nonhomogenized and spatially aggregated data, although hinge functions with the change point fixed at 1975 performed well for the spring and summer seasons. A hybrid normals-specification method, using one of these piecewise continuous functions when the regressions are sufficiently strong and the CPC15 otherwise, exhibits a favorable trade-off between squared error and bias that may make it an optimal choice for some users.
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