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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]

Abstract Climate classifications of climate models' outputs have been used to assess environmental changes but systematic analyses of the differences between models, scenarios and classification methods are scarce. Here, the results of applying the most commonly used climate classifications to the outputs of 47 Global Climate Models (GCM) of different physical parameterizations and varied grid size are presented. The extent and intensity of changes for present climate, three different Representative Pathways Scenarios (RCP26, RCP45 and RCP85) and three increasingly-fine classification methods show that there is a consensus between models, and that climate classifications are indeed useful tools to translate physical climatology variables into environmental changes. The main conclusions are that climate classifications can indeed be used to gauge model performance at several grid sizes and that the classification method does not decisively affects the potential global changes in future climates under increasing greenhouse gas emissions. The analyses also reveal that there are several uncertainties that are not attributable to model grid size or to limitations in the reference datasets but more likely to deficiencies in the physics of the models. Highlights • This paper provides a systematic analysis of climate classifications for present and future climates. • Several classifications methods are used to illustrate the consensus between models and observations. • Overall, global models show consistent changes but uncertainties persist with large differences in individual model skill. [ABSTRACT FROM AUTHOR]

Abstract Most estimates of Chinese regional Surface Air Temperatures since the late-19th century have identified two relatively warm periods – 1920s–40s and 1990s–present. However, there is considerable debate over how the two periods compare to each other. Some argue the current warm period is much warmer than the earlier warm period. Others argue the earlier warm period was comparable to the present. In this collaborative paper, including authors from both camps, the reasons for this ongoing debate are discussed. Several different estimates of Chinese temperature trends, both new and previously published, are considered. A study of the effects of urbanization bias on Chinese temperature trends was carried out using the new updated version of the Global Historical Climatology Network (GHCN) – version 4 (currently in beta production). It is shown that there are relatively few rural stations with long records, but urbanization bias artificially makes the early warm period seem colder and the recent warm period seem warmer. However, current homogenization approaches (which attempt to reduce non-climatic biases) also tend to have similar effects, making it unclear whether reducing or increasing the relative warmth of each period is most appropriate. A sample of 17 Chinese temperature proxy series (12 regional and 5 national) is compared and contrasted specifically for the period since the 19th century. Most proxy series imply a warm early-20th century period and a warm recent period, but the relative warmth of these two periods differs between proxies. Also, with some proxies, one or other of the warm periods is absent. [ABSTRACT FROM AUTHOR]