The Effects of Gridding Algorithms on the Statistical Moments and Their Trends of Daily Surface Air Temperature
作者： Nicholas R. Cavanaugh , Samuel S. P. Shen
DOI: 10.1175/JCLI-D-14-00668.1
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摘要: AbstractThis paper explores the effects from averaging weather station data onto a grid on first four statistical moments of daily minimum and maximum surface air temperature (SAT) anomalies over entire globe. The Global Historical Climatology Network–Daily (GHCND) Met Office Hadley Centre GHCND (HadGHCND) datasets 1950 to 2010 are examined. exhibit large spatial patterns for each moment statistically significant trends 2010, indicating that SAT probability density functions non-Gaussian have undergone characteristic changes in shape due decadal variability and/or climate change. Comparisons with show gridded averages always underestimate observed variability, particularly extremes, altered some cases opposite sign geographic areas. A closure approach based quasi-normal approximation is taken explore SAT’s higher-order po...
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