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Nonlinear Dynamical Structure of precipitation in China and its Regional Climatic Characters

机译:中国降水非线性动力结构及其区域气候特征

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Since a long period of time, studies on precipitation forecasts are limited in using traditional linear statistical methods, and especially when analyzing the regional characters of precipitation, the ocular estimate and Empirical Orthogonal Function (EOF) decomposition methods etc. are generally used.. However, precipitation series is a typical nonlinear or chaotic observational series, the typical statistical analysis means is not able to fully mine the dynamical signal of the time series. In the light of the recent research achievements of nonlinear science and in the context of the daily precipitation data from 1951 to 2000 at 740 stations compiled by the National Climate center, the dynamic space of precipitation at each station is first reconstructed using the time-lag method, and the regional climatic characters of summer precipitation in the monsoon area of China are then analyzed using dynamical correlation factor exponent Q, yielding the five dynamic climate characteristic regions whose property differs from the traditional “precipitation pattern”, i.e. 1. Jianghuai pattern covering 65 stations; 2. South China pattern covering 49 stations; 3. North China pattern covering 59 stations; 4. Northeast China pattern covering 27 stations; and 5.) Tibetan plateau pattern covering 53 stations. The statistical data show that weather (precipitation) in the five dynamic climate characteristic regions simultaneously becomes dry, wet and normal, that is to say, each region possesses a common spatial-temporal characteristic structure. Further analysis of physical mechanisms suggests that the Jianghuai pattern and South China pattern are close related with ENSO, which may results from the effect of the India-East Asia (IEA) teleconnection pattern; among the other three patterns North and Northeast China patterns are positively related with the ridge line position of subtropical high, but the ENSO shows no obvious influence on the three patterns, which may be associated with that the regions are mainly out of the weak impact area of ENSO; furthermore the influence of the ridge line of subtropical high on precipitation in North China is most remarkable. This has instructive significance for the development of regional climate models, and the analysis of precipitation characters and precipitation forecast.
机译:由于长期以来,对降水预报的研究仅限于使用传统的线性统计方法,尤其是在分析降水的区域特征时,通常使用目视估计和经验正交函数(EOF)分解方法等。降水序列是典型的非线性或混沌观测序列,典型的统计分析手段无法充分挖掘时间序列的动态信号。根据非线性科学的最新研究成果,结合国家气候中心编制的1951年至2000年740个站点​​的日降水量数据,首先利用时滞重建每个站点的降水动态空间方法,然后运用动态相关因子指数Q分析了中国季风区夏季降水的区域气候特征,得出了五个与传统“降水模式”不同的动态气候特征区域。1.江淮模式覆盖65个站; 2.华南模式覆盖49个站; 3.华北模式覆盖59个站点; 4.东北格局,覆盖27个站; 5)青藏高原模式覆盖53个站。统计数据表明,五个动态气候特征区域的天气(降水)同时变得干燥,潮湿和正常,也就是说,每个区域都具有共同的时空特征结构。对物理机制的进一步分析表明,江淮模式和华南模式与ENSO密切相关,这可能是由于印度—东亚(IEA)遥距模式的影响所致。在其他三种模式中,华北和东北模式与副热带高压的脊线位置成正相关,但ENSO对这三种模式没有明显的影响,这可能与该地区主要在弱势影响区之外有关ENSO;此外,华北地区副高脊线对降水的影响最为显着。这对区域气候模式的发展,降水特征的分析和降水预报具有指导意义。

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