基于小波变换的GPS水汽与气象要素相关性分析

利用北京市GPS连续观测资料结合气象资料开展GPS水汽与气象要素的相关性分析。首先使用GAMIT软件解算2009-06-01~2012-04-30的北京GPS连续观测网观测数据并结合气压数据获得测站水汽序列；然后用小波变换方法对GPS水汽、温度和气压数据进行分解与重构，并对重构后的数据进行相关性分析。GPS水汽序列的变化趋势与温度呈显著正相关，与气压呈显著负相关。水汽和气压存在年周期和半年周期变化，两者存在显著负相关特性；温度有年周期变化，水汽和温度在d13重构结果的相关性最好，存在显著正相关特性。

Correlation Analysis of GPS PWV and Meteorological Elements Based on Wavelet Transform

Precipitable water vapor is one of the key factors influencing weather and climate change; change in water vapor is closely related to temperature and atmospheric pressure. In this paper, we conduct a correlation analysis of GPS water vapor and meteorological factors by using GAMIT software solver the value of PWV for Beijing combined with meteorological data. Firstly,we used GAMIT software solver on the value of PWV for Beijing continuous observation network data from June 1,2009 to April 30,2012, in conjunction with atmospheric pressure data, to acquire station PWV sequence. Then we used wavelet transform method to break down and reconstruct the data for GPS PWV, temperature and atmospheric pressure and analyzed the correlation of new data. There is a positive correlation between the trend of GPS PWV sequence and temperature, and a significantly negatively correlation with atmospheric pressure. The PWV and atmospheric pressure have half-cycle and annual change; both appear in an obvious negative correlation. Temperature cycling for years, the best correlation of water vapor and temperature is in d13 reconstruction. There are significant positive correlation properties.