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The projected changes of precipitation and temperature in the Yangtze River Basin in the 20th Century from 20 models of the CMIP3 (phase 3 of the Coupled Model Inter-comparison Project) dataset are analyzed based on the observed precipitation and temperature data of 147 meteorological stations in the Yangtze River Basin. The results show that all models tend to underestimate the annual mean temperature over the Yangtze River Basin, and to overestimate the annual mean precipitation. The temporal changes of simulated annual mean precipitation and temperature are broadly comparable with the observations, but with large variability among the results of the models. Most of the models can reproduce maximum precipitation during the monsoon season, while all models tend to underestimate the mean temperature of each month over the Yangtze River Basin. The Taylor diagram shows that the differences between modeled and observed temperature are relatively smaller as compared to differences in precipitation. For a detailed investigation of regional characteristics of climate change in the Yangtze River Basin during 2011-2050, the multi-model ensembles produced by an upgraded REA method are carried out for more reliable projections. The projected precipitation and temperature show large spatial variability in the Yangtze River Basin. Mean precipitation will increase under the A1B and B1 scenarios and decrease under the A2 scenario, with linear trends ranging from −21 to 28.5 mm/decade. Increasing mean temperature can be found in all scenarios with linear trends ranging from 0.15 to 0.48°C/decade. Grids in the head region of the Jingshajiang catchment show distinct increasing trends for all scenarios. Some physical processes associated with precipitation are not well represented in the models. [ABSTRACT FROM AUTHOR]

In this paper, change-points in time series of annual extremes in temperature and precipitation in the Zhujiang River Basin are analyzed with the CUSUM test. The data cover the period 1961-2007 for 192 meteorological stations. Annual indicators are analyzed: mean temperature, maximum temperature, warm days, total precipitation, 5-day maximum precipitation, and dry days. Significant change-points (1986/87, 1997/98, 1968/69, and 2003/04) are detected in the time series of most of the indicators. The change-point in 1986/87 is investigated in more detail. Most stations with this change-point in temperature indicators are located in the eastern and coastal areas of the basin. Stations with this change-point in dry days are located in the western area. The means and trends of the temperature indicators increase in the entire basin after 1986/87. The highest magnitudes can be found at the coast and delta. Decreasing (increasing) tendencies in total and 5-day maximum precipitation (dry days) are mostly observed in the western and central regions. The detected change-points can be explained by changes in the indices of the Western Pacific subtropical high and the East Asian summer monsoon as well as by change-points in wind directions. In years when the indices simultaneously increase and decrease (indices taking reverse directions to negative and positive) higher annual temperatures and lower annual precipitation occur in the Zhujiang River Basin. The high station density and data quality are very useful for spatially assessing change-points of climatic extreme events. The relation of the change points to large-scale oscillation can provide valuable data for planning adaptation measures against climate risks, e.g. for flood control, disaster preparedness, and water resource management. [ABSTRACT FROM AUTHOR]

Climate projections for the Huaihe River Basin, China, for the years 2001–2100 are derived from the ECHAM5/MPI-OM model based on observed precipitation and temperature data covering 1964–2007. Streamflow for the Huaihe River under three emission scenarios (SRES-A2, A1B, B1) from 2010 to 2100 is then projected by applying artificial neural networks (ANN). The results show that annual streamflow will change significantly under the three scenarios from 2010 to 2100. The interannual fluctuations cover a significant increasing streamflow trend under the SRES-A2 scenario (2051–2085). The streamflow trend declines gradually under the SRES-A1B scenario (2024–2037), and shows no obvious trend under the SRES-B1 scenario. From 2010 to 2100, the correlation coefficient between the observed and modeled streamflow in SRES-A2 scenario is the best of the three scenarios. Combining SRES-A2 scenario of the ECHAM5 model and ANN might therefore be the best approach for assessing and projecting future water resources in the Huaihe basin and other catchments. Compared to the observed period of streamflows, the projected periodicity of streamflows shows significant changes under different emission scenarios. Under A2 scenario and A1B scenario, the period would delay to about 32–33a and 27–28a, respectively, but under B1 scenario, the period would not change, as it is about 5–6a and the observed period is about 7–8a. All this might affect drought/flood management, water supply and irrigation projects in the Huaihe River basin. [ABSTRACT FROM AUTHOR]

Precipitation trends in the Yangtze River catchment (PR China) have been analyzed for the past 50 years by applying the Mann-Kendall trend test and geospatial analyses. Monthly precipitation trends of 36 stations have been calculated. Significant positive trends at many stations can be observed for the summer months, which naturally show precipitation maxima. They were preceded and/or followed by negative trends. This observation points towards a concentration of summer precipitation within a shorter period of time. The analysis of a second data set on a gridded basis with 0.5° resolution reveals trends with distinct spatial patterns. The combination of classic trend tests and spatially interpolated precipitation data sets allows the spatiotemporal visualization of detected trends. Months with positive trends emphasize the aggravation of severe situation in a region, which is particularly prone to flood disasters during summer. Reasons for the observed trends were found in variations in the meridional wind pattern at the 850 hPa level, which account for an increased transport of warm moist air to the Yangtze River catchment during the summer months. [ABSTRACT FROM AUTHOR]

In this paper, precipitation concentrations across the Pearl River basin and the associated spatial patterns are analyzed based on daily precipitation data of 42 rain gauging stations during the period 1960–2005. Regions characterized by the different changing properties of precipitation concentration index (CI) are identified. The southwest and northeast parts of the Pearl River basin are characterized by lower and decreasing precipitation CI; the northwest and south parts of the study river basin show higher and increasing precipitation CI. Higher but decreasing precipitations CI are found in the West and East River basin. Comparison of precipitation CI trends before and after 1990 shows that most parts of the Pearl River basin are characterized by increasing precipitation CI after 1990. Decreasing precipitation CI after 1990 (compared to precipitation CI changes before 1990) is observed only in a few stations located in the lower Gui River and the lower Yu River. Significant increasing precipitation CI after 1990 is detected in the West River, lower North River and upper Beipan River. These changes of precipitation CI in the Pearl River basin are likely to be associated with the consequences of the well-evidenced global warming. These findings can contribute to basin-scale water resource management and conservation of ecological environment in the Pearl River basin. [ABSTRACT FROM AUTHOR]

Finer climate change information on spatial scale is required for impact studies than that presently provided by global or regional climate models. It is especially true for regions like South Asia with complex topography, coastal or island locations, and the areas of highly heterogeneous land-cover. To deal with the situation, an inexpensive method (statistical downscaling) has been adopted. Statistical DownScaling Model (SDSM) employed for downscaling of daily minimum and maximum temperature data of 44 national stations for base time (1961-1990) and then the future scenarios generated up to 2099. Observed as well as Predictors (product of National Oceanic and Atmospheric Administration) data were calibrated and tested on individual/multiple basis through linear regression. Future scenario was generated based on HadCM3 daily data for A2 and B2 story lines. The downscaled data has been tested, and it has shown a relatively strong relationship with the observed in comparison to ECHAM5 data. Generally, the southern half of the country is considered vulnerable in terms of increasing temperatures, but the results of this study projects that in future, the northern belt in particular would have a possible threat of increasing tendency in air temperature. Especially, the northern areas (hosting the third largest ice reserves after the Polar Regions), an important feeding source for Indus River, are projected to be vulnerable in terms of increasing temperatures. Consequently, not only the hydro-agricultural sector but also the environmental conditions in the area may be at risk, in future. [ABSTRACT FROM AUTHOR]