Anomaly analysis of GNSS water vapor before rainstorms based on wavelet transform
In order to explore the abnormal changes in atmospheric water vapor before rainstorms, this paper is based on the ground-based global navigation satellite system (GNSS) data and hourly precipitation observation data of adjacent meteorological stations at Suzhou in 2022, the GNSS atmospheric precipitable water vapor (PWV) was decomposed and reconstructed using wavelet transform to analyze the abnormal change characteristics of GNSS PWV time series before and after rainstorms.The research results show that there is generally a significant increase in 1-3 days before the occurrence of rainstorms in 2022.The maximum peak value of PWV for summer rainstorm can reach 72.4 mm, the maximum peak value of PWV for autumn rainstorms can reach 68.3 mm, and the maximum peak value of PWV for spring rainstorms can reach 46.3 mm.The relationship between sudden extreme rainstorms and PWV amplification is related, and the faster the amplification, the greater the precipitation of rainstorms.The peak or valley value of the fourth layer high-frequency coefficient (d4) of PWV after wavelet decomposition and reconstruction is earlier than that of rainstorms occurrence by 1-3 days, and the faster the amplification, the greater amplitude of high-frequency coefficient of PWV d4 after wavelet transform.This method can detect the abnormal changes in the PWV time series before rainstorms and provide a certain reference basis for a short-term forecast of rainstorms.
global navigation satellite system (GNSS)rainstormsprecipitable water vaporwavelet transform
万方数据
维普
