With EOF,REOF and trend analysis method the spatial distribution feature and the time evolution rule of the total amount cover over the Northwest China for the last 40 years are analyzed based on the monthly mean total cloud amountdata between 1961 and 2000 collected from 174 observational stations.

利用中国西北地区174个测站1961~2000年1~12月总云量资料,采用EOF、REOF、趋势分析等方法,分析了40年来西北地区总云量的时空分布特征及其变化规律。

With EOF and trend analysis method adopted,the spatio-temporal variation of total cloud amountis analyzed for 75 stations over the Plateau during the period of 1971-2004.

利用青藏高原及其周边地区75个地面气象台站的云量日均值资料,采用正交经验函数(EOF)和线性倾向估计等方法,分析了高原地区1971-2004年总云量的时空变化特征。

By using the data of total cloud amountat 22 stations over Tibet in 1971-2008,the change trends of total cloud amountwere analyzed.

利用1971—2008年西藏地区22个台站观测的总云量资料,初步分析研究了西藏地区总云量的变化趋势。

The spatial characteristics and yearly,seasonally and daily variation properties of total cloud coveris analyzed in this paper based on every-three-hour mean monthly data of ISCCP from July,1983 to December,1993 over the Tibetan Plateau which is divided into 39 grids.

利用 ISCCP提供的 1 983年 7月— 1 993年 1 2月 3 h一次的月平均卫星总云量资料 ,将整个高原分为 3 9个网格点 ,分析了高原总云量的年、季节、日变化规律及其空间分布特征 ,并根据高原水汽条件和地形动力影响以及环流特征作出一定的科学解释。

The strongest correlation was found between the total cloud coverand tree-ring δ18O covering the whole wet season (June to October).

主要与季风期(8-10月)的降水和相对湿度、6-10月总云量、5-6月平均温度显著相关,尤其和总云量相关性最高(r=-0。

In order to forecast total cloud coverfor Beijing single station,we use the nonlinear method-BP(Back Propagation) neural net.

为了对北京单站总云量进行预报,利用人工神经网络的BP模型,针对不同时次进行关键因子的选取,尝试用多种预报因子的组合,建立了总云量预报模型。