Development of Global Hourly 0.5° Land Surface Air Temperature Datasets

Abstract

Abstract Land surface air temperature (SAT) is one of the most important variables in weather and climate studies, and its diurnal cycle is also needed for a variety of applications. Global long-term hourly SAT observational data, however, do not exist. While such hourly products could be obtained from global reanalyses, they are found to be unrealistic in representing the SAT diurnal cycle. Global hourly 0.5° SAT datasets are developed here based on four reanalysis products [Modern-Era Retrospective Analysis for Research and Applications (MERRA for 1979–2009), 40-yr ECMWF Re-Analysis (ERA-40 for 1958–2001), ECMWF Interim Re-Analysis (ERA-Interim for 1979–2009), and NCEP–NCAR reanalysis for 1948–2009)] and the Climate Research Unit Time Series version 3.10 (CRU TS3.10) for 1948–2009. The three-step adjustments include the spatial downscaling to 0.5° grid cells, the temporal interpolation from 6-hourly (in ERA-40 and NCEP–NCAR reanalysis) to hourly using the MERRA hourly SAT climatology for each day (and the linear interpolation from 3-hourly in ERA-Interim to hourly), and the bias correction in both monthly-mean maximum (Tmax) and minimum (Tmin) SAT using the CRU data. The final products have exactly the same monthly Tmax and Tmin as the CRU data, and perform well in comparison with in situ hourly measurements over six sites and with a regional daily SAT dataset over Europe. They agree with each other much better than the original reanalyses, and the spurious SAT jumps of reanalyses over some regions are also substantially eliminated. One of the uncertainties in the final products can be quantified by their differences in the true monthly mean (using 24-hourly values) and the monthly averaged diurnal cycle.