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Abstract: Significant quasi-cycles in precipitation time series of 132 climate stations spread over China from 1951 to 2002 have been detected by applying Autocorrelation Spectral Analysis (ASA). By the same method, significant quasi-cycles have also been identified in time series of the potential influencing factors: Southern Oscillation Index (SOI), Sea Surface Temperature (SST) and Sea Level Pressure (SLP). Similarities between some precipitation time series spectra and the spectrum of a potential driving force have been detected; e.g. several series from the Yangtze River''s middle reaches show 3–4-year cycles which are similar to the SOI and several SST signals. These time series have been further investigated by low-pass filtering with the Savitzky–Golay filter and by means of correlation analysis. It is proved that the SOI and the SSTs of the Bay of Bengal are in relatively stable anti-phase. However, no stable link between these signals and the precipitation series in the Yangtze River basin can be detected. Subsequent analyses of 850hPa winds lead to the outcome that certain wind patterns could either suppress or force the SST and SOI teleconnection signals. [Copyright &y& Elsevier]

The article discusses how summer rainfall in the Yangtze River basin in China is forecasted using neural network techniques with input and output variables. Input variables for neural networks include Southern Oscillation Index (SOI), the East Atlantic/Western Russia (EA/WR) pattern, the Scandinavia (SCA), the Polar/Eurasia (POL) pattern and several indices from sea surface temperatures (SST), and sea level pressures (SLP). Rainfall is considered to be the output variable. The winter SST and SLP indices are distinguished to be the most important forecasters of summer rainfall in the Yangtze River basin.

Snow is an important component of a climate system, and very sensitive to climate change, and it can be an indicator of checking and monitoring global change. This paper is concerned with identifying changes in the time series of snowfall in Qinghai, located in western China. We used the Mann-Kendall test to evaluate the annual and monthly trends in snowfall in Qinghai during the periods 1957/58–2006/07 based on data obtained from 25 stations. Significant positive and negative trends at the 90, 95, and 99 percent confidence levels were detected for numerous stations. In order to understand the regional pattern of snowfall in Qinghai, the detected trends are spatially interpolated using the inverse distance weighted interpolation method in a GIS environment. The results indicate that in January snowfall in the most area of Qinghai shows a significant upward trend, especially in the Delingha and Nomhon area in northern Qaidam Basin, as well as southeastern Qinghai, however, there is no significant downward trend area. The trend analysis indicates that annual snowfall has a significant upward trend in Delingha and Nomhon area in northern Qaidam Basin, and the downward trends occurred in the Qilian mountain area and Gonghe Basin. This is especially the case for highlighting the spatial structure of snowfall trends. The research results help in further understanding the regional pattern of snowfall in Qinghai and its response to global climatic warming. [ABSTRACT FROM AUTHOR]

Here we present the first systematic measurements of European mountain permafrost temperatures from a latitudinal transect of six boreholes extending from the Alps, through Scandinavia to Svalbard. Boreholes were drilled in bedrock to depths of at least 100 m between May 1998 and September 2000. Geothermal profiles provide evidence for regional-scale secular warming, since all are nonlinear, with near-surface warm-side temperature deviations from the deeper thermal gradient. Topographic effects lead to variability between Alpine sites. First approximation estimates, based on curvature within the borehole thermal profiles, indicate a maximum ground surface warming of +1 °C in Svalbard, considered to relate to thermal changes in the last 100 years. In addition, a 15-year time series of thermal data from the 58-m-deep Murte`l–Corvatsch permafrost borehole in Switzerland, drilled in creeping frozen ice-rich rock debris, shows an overall warming trend, but with high-amplitude interannual fluctuations that reflect early winter snow cover more strongly than air temperatures. Thus interpretation of the deeper borehole thermal histories must clearly take account of the potential effects of changing snow cover in addition to atmospheric temperatures. [Copyright &y& Elsevier]