Search

Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China. [ABSTRACT FROM AUTHOR]

Temperature seasonality, the difference between summer and winter temperatures in mid–high latitudes, is an important component of the climate. Whether humans have had detectable influences on changing surface temperature seasonality at scales smaller than the subcontinental scale, where humans are directly impacted, is not clear. In this study, the first detection and attribution analysis of changes in temperature seasonality in China has been carried out. Detection and attribution of both summer and winter temperatures were also conducted, with careful consideration of observational uncertainty and the inconsistency between observation and model simulations induced by the long coastline and country border in China. The results show that the response to external forcings is robustly detectable in the spatiotemporal pattern of weakening seasonality and in that of warming winter temperature, although models may have underestimated the observed changes. The response to external forcings is detectable and consistent with the observed change in summer temperature averaged over China. Human influences are detectable in changes in seasonality and summer and winter temperatures, most robustly in winter, and these influences can be separated from those of natural forcing when averaged over China. The recent increase in summer temperature was found to be due to external forcings, and the warming hiatus in winter temperature from 1998 to 2013 was due to a statistically significant cooling trend induced by internal variability. These results will give insights into the understanding of the warming hiatus in China, as well as the hot summers and cold winters in recent years. [ABSTRACT FROM AUTHOR]