Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology

TLDR

The study constructs a 0.5° latitude by 0.5° longitude surface climatology of global land areas, excluding Antarctica, for the 1961–1990 period. Using 19,800–3,615 station climatological normals, the authors interpolate nine surface variables—precipitation, wet‑day frequency, mean temperature, diurnal temperature range, vapor pressure, sunshine, cloud cover, ground frost frequency, and wind speed—via thin‑plate splines that incorporate latitude, longitude, and elevation, and validate the results with cross‑validation and comparisons to other climatologies. The resulting climatology improves upon earlier global terrestrial products by providing a strictly 1961–1990 dataset, an expanded variable suite, explicit elevation dependence, and regional error estimates, and it is already employed in ecosystem modeling, climate model evaluation, and climate‑change impact studies, with data and monthly field images available from the Climatic Research Unit and the web.

Abstract

The construction of a 0.5° lat × 0.5° long surface climatology of global land areas, excluding Antarctica, is described. The climatology represents the period 1961–90 and comprises a suite of nine variables: precipitation, wet-day frequency, mean temperature, diurnal temperature range, vapor pressure, sunshine, cloud cover, ground frost frequency, and wind speed. The climate surfaces have been constructed from a new dataset of station 1961–90 climatological normals, numbering between 19 800 (precipitation) and 3615 (wind speed). The station data were interpolated as a function of latitude, longitude, and elevation using thin-plate splines. The accuracy of the interpolations are assessed using cross validation and by comparison with other climatologies. This new climatology represents an advance over earlier published global terrestrial climatologies in that it is strictly constrained to the period 1961–90, describes an extended suite of surface climate variables, explicitly incorporates elevation as a predictor variable, and contains an evaluation of regional errors associated with this and other commonly used climatologies. The climatology is already being used by researchers in the areas of ecosystem modelling, climate model evaluation, and climate change impact assessment. The data are available from the Climatic Research Unit and images of all the monthly fields can be accessed via the World Wide Web.