The remote sensing technology is used to analyze the periodic changes of precipitation in the semi-arid areas of northern China and provide a reference basis for precipitation prediction. Authors were based on GPS observation data and corresponding ground meteorological parameters to obtain the study area’s comprehensive water vapor content value and use precipitation and time to establish a linear regression equation based on the content value to express the precipitation trend change. The periodic structure and abnormal changes of the periodic precipitation series on different time scales were obtained through wavelet analysis, combined with anomaly calculations to analyze the increase and decrease precipitation characteristics. The Morlet continuous wavelet transform map was also used to reflect the periodic oscillations of precipitation on different time scales. The wavelet variance map was used to reflect the distribution of regional precipitation with scale years. The authors analyzed the cycle change characteristics of the comprehensive precipitation series in Harbin, Changchun, Shenyang, and Dalian. They concluded that the annual precipitation in the four regions showed a decreasing trend in 50 years. And through the wavelet cycle frequency-domain relationship change law, the change characteristics of precipitation in the northern semi-arid area in the entire time domain were obtained.
Estimation of the dynamics and yields of cereals in a semi-arid area using remote sensing and the SAFY growth model
