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Climate classifications based on temperature and precipitation measurements are increasingly being used for environmental and climate change studies. Using three classification methods (Köppen, Extended Köppen, and Holdridge) and one observational dataset for present climate (CRU, Climate Research Unit), we show that GCMs have bridged the gap that led to the emergence of RCMs thirty years ago, as GCMs can now provide global climate classifications whose accuracy and precision are comparable to those of regional outputs of the RCMs. Projections of high-resolution GCMs for future climates under the assumptions of three Representative Concentration Pathways (RCP26, RCP45 and RCP85) can therefore be used as a primary source for climate change and global warming studies at high resolution. This paper provides comprehensive, model-derived climate classifications for the entire planet, using RCMs and two GCMs for present and future climate-change scenarios, and discusses how well the models actually represent the climates of the world when compared with reference, ground validation data. It turns out that both GCMs and RCMs appear still limited to provide practical estimates of the world climates even for present climate conditions. The modeling of precipitation remains the Achilles' heel of models and thus of multidimensional indices, which are very sensitive to this variable. The conclusion is that model outputs at regional scale need to be taken with extreme caution without venturing into informing policies presenting potentially large societal impacts. Nonetheless, the role of models as privileged tools to advance our scientific knowledge of the Earth's system remains undisputed. • A systematic analysis of climate classifications with RCMs and two high resolution GCMs is presented. • Three classification methods are used to illustrate the differences between models and observations. • Current high-resolution GCMs can provide climate classifications with the same accuracy as those from RCMs. • Uncertainties in modeling precipitation persist for large parts of the world. [ABSTRACT FROM AUTHOR]

In recent years, climate extreme events have caused increasing direct economic and social losses in the arid region of northwestern China. Based on daily temperature and precipitation data from 1960 to 2010, this paper discussed the linear trend and abrupt changes of climate indices. The general evolution was obtained by the empirical orthogonal function (EOF), the Mann-Kendall test, and the distribution-free cumulative sum chart (CUSUM) test. The results are as follows: (1) climate showed a warming trend at annual and seasonal scale, with all temperature indices exhibiting statistically significant changes. The warm indices have increased, with 1.37%days/decade of warm days (TX90p), 0.17 °C/decade of warmest days (TXx) and 1.97 days/decade of warm spell duration indicator (WSDI), respectively. The cold indices have decreased, with − 1.89%days/decade, 0.65 °C/decade and − 0.66 days/decade for cold nights (TN10p), coldest nights (TNn) and cold spell duration indicator (CSDI), respectively. The precipitation indices have also increased significantly, coupled with the changes of magnitude (max 1-day precipitation amount (RX1day)), frequency (rain day (R0.1)), and duration (consecutive dry days (CDD)). (2) Abrupt changes of the annual regional precipitation indices and the minimum temperature indices were observed around 1986, and that of the maximum temperature indices were observed in 1996. (3) The EOF1 indicated the overall coherent distribution for the whole study area, and its principal component (PC1) was also observed, showing a significant linear trend with an abrupt change, which were in accordance with the regional observation results. EOF2 and EOF3 show contrasts between the southern and northern study areas, and between the eastern and western study areas, respectively, whereas no significant tendency was observed for their PCs. Hence, the climate indices have changed significantly, with linear trends and abrupt changes noted for all climate indices, which will have serious impacts on water resources and ecological environment in the arid region of China. [ABSTRACT FROM AUTHOR]