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| Abstract |
Maps were produced for anomalies, and for absolute temperature and precipitation in each year between 1958 and 1988. Along with maps indicating variability at the stations, others have been completed based on the interpolated time series. Due to surface smoothing of the interpolation the variability of the interpolated time series is usually lower than the one based upon station observations.
Temperature variability is quite low during the summer half. Anomalies are mostly less than 2 C in nearly all of China. During the winter months the anomaly increases up to 6 C with the highest variability in modern China and on the plateau. the pattern of monthly anomalies is stable in that relatively large areas show the same trend of deviation.
Variability of rainfall shows large differences in spatial and temporal terms. Rainfall variability is highest during winter when rainfall is low. Especially the monthly data offer a comprehensive insight into seasonal differences in regional rainfall variability. In northern China's agricultural productive areas variability is high during the spring months, decreases in summer and increases as of September. In the middle and lower reaches of the Changjiang river basin variability is high in July and August amounting to as much as over 50%. Variability is relatively low in Southwest China, which includes the fertile Sichuan basin. Also in China's northeastern agricultural areas variability is relatively low during the growing season. From a policy point of view it is also of interest to aggregate the data for certain geographic regions. Results for provinces and major watersheds are presented.
The interpolated surfaces are validated by comparing them with the station observations available in this study. Anomaly surfaces validation is determined by the interpolation error. There is a good fit for temperature anomaly surfaces compared to observed station anomalies. Because of the high spatial variability of rainfall anomalies including the possibility of extreme events in selected stations, interpolated anomalies are usually reduced during the interpolation. The temperature and rainfall time series validation is, in addition by the interpolation error, influenced by the differences in the 31-year average observed at the stations and the average presented in the long-term average grids to which the anomaly surfaces are linked.
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This page was last updated on 2008-8-11.