Calculating Global Temperature Anomalies Using Three New Methods

Deriving global temperatures anomalies involves the surface averaging of normalized ocean and station temperature data in homogeneously distributed in both space and time. Different groups have adopted different averaging schemes to deal with this problem. For example GISS use approximately 8000 equal area cells and interpolate near neighbor stations. Berkeley Earth fit a temperature distribution to a 1 degree grid, while HadCRUT4 use regular binning on to a 5 degree grid. Cowtan and Way then attempt to correct HadCRUT4 for spatial bias by kriging results into sparse regions, guided by satellite data. In this paper we look at alternative methods based on averaging over the 3D spheroidal surface of the earth. It is shown that this approach alone removes any spatial bias, thereby avoiding direct interpolation. A spherical triangulation method is described which additionally has the benefit of avoiding binning completely by using each data point individually. Longer term 3D averaging is investigated by using an Icosahedral binning. New monthly and annual temperature series are presented for each method based on a) merging CRUTEM4 with HadCRUT3 (HadCRUT4.5), and b) merging GHCN V3C with HadSST3.