Multi-dataset comparison of gridded observed temperature and precipitation extremes over China

Abstract

Five gridded datasets containing measures of temperature and precipitation extremes over the past five decades over China are compared. Time series, spatial averages and trends in China's coldest and warmest days and nights and wettest days are estimated from these datasets that vary in their station network density, interpolation procedures and the order in which extremes are calculated. We find that country-wide trends in temperature extremes are coherent irrespective of dataset choice although actual values are generally smaller in the dataset in which indices are calculated from daily interpolated grids rather than from station points. There are also some regional differences in trends especially over regions with sparse data networks, e.g. the Tibetan Plateau. Averaged across China, trends calculated over the period 1961-2009 vary from a minimum of 0.13°Cdecade-1 (hottest day) to 0.65°Cdecade-1 (coldest night). The coldest day and night have tended to warm faster than the warmest day and night. Trends in precipitation extremes are much less coherent spatially and can be positive or negative depending on the choice of dataset. The length of station record chosen is also vital to eliminate spurious trends. The results have important implications for detection and attribution and model evaluation studies.