Abstract
The sampling error variances of the 5° × 5° Global Historical Climatological Network (GHCN) monthly surface air temperature data are estimated from January 1851 to December 2001. For each GHCN grid box and for each month in the above time interval, an error variance is computed. The authors’ error estimation is determined by two parameters: the spatial variance and a correlation factor determined by using a regression. The error estimation procedures have the following steps. First, for a given month for each grid box with at least four station anomalies, the spatial variance of the grid box’s temperature anomaly, σ̂2s, is calculated by using a 5-yr moving time window (MTW). Second, for each grid box with at least four stations, a regression is applied to find a correlation factor, αs, in the same 5-yr MTW. Third, spatial interpolation is used to fill the spatial variance and the correlation factor in grid boxes with less than four stations. Fourth, the sampling error variance is calculated by using the formula E2 = αsσ̂2s/N, where N is the total number of observations for the grid box in the given month. The two parameters of the authors’ error estimation are compared with those of the University of East Anglia’s Climatic Research Unit for the decadal data. The comparison shows a close agreement of the parameters’ values for decadal data. An advantage of this new method is the generation of monthly error estimates. The authors’ error product will be available at the U.S. National Climatic Data Center.
<i>Brief communication</i> "A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method"
