A Drought Monitoring Method Based on Precipitable Water Vapor and Precipitation

Abstract

Precipitable water vapor (PWV) with high precision and high temporal resolution can be obtained based on the global navigation and positioning system (GNSS) technique, which is important for GNSS in disaster prevention and mitigation. However, the related studies on drought monitoring using PWV are rarely performed before, which becomes the focus of this paper. This paper proposes a novel drought monitoring method using GNSS-derived PWV and precipitation, and a multi-time-scale standardized precipitation conversion index (SPCI) is established. This index is different from the traditional index in terms of expression, standardization and time scale. The proposed SPCI is then compared with SPI/SPEI/scPDSI (Standardized Precipitation Index/Standardized Precipitation Evapotranspiration Index/ self-calibrating Palmer Drought Severity Index) and applied to local and global drought monitoring. Validated results show that multi-time-scale SPCI has good consistency with the corresponding SPI/SPEI/scPDSI. The correlation between SPCI and SPEI is the strongest (more than 0.96) in 12-month scale, which indicates the application potential of SPCI in drought monitoring. In addition, applications for regional (Queensland, Australia) and global drought/wet monitoring further verify the capability of the proposed SPCI. The average percentage deviations of drought/wet monitoring between SPCI and SPEI are 2.77% and 3.75%, respectively on a global scale. The above results show that the SPCI developed in this study is efficiently applied to global flood/wet studies.

A Rainfall Forecast Model Based on GNSS Tropospheric Parameters and BP-NN Algorithm

“…In addition, there has been some progress in the application of GNSS to meteorology. Many scholars have applied GNSS PWV to typhoon monitoring [13], drought index improvement [14], drought monitoring [15,16], air quality monitoring [17][18][19], and short-term rainfall early warning [3,[20][21][22][23].…”

An Improved Model for Detecting Heavy Precipitation Using GNSS-Derived Zenith Total Delay Measurements

“…Consequently, a more reliable model for prediction of extreme heavy precipitation is of urgent need. The rapid developments of the Global Navigation Satellite Systems (GNSS) in the past decades have extended the use of this emerging system to the monitoring and early detection of short-term severe weather events [3]− [6] and long-term climate research [7]− [9]. This is due to its all-weather operability, high accuracy, high spatiotemporal resolution and low cost [10]− [14].…”

A Global Assessment of Precipitable Water Vapor Derived From GNSS Zenith Tropospheric Delays With ERA5, NCEP FNL, and NCEP GFS Products

“…The subtraction of the zenith hydrostatic delay (ZHD) from ZTD yields the zenith wet delay (ZWD) from which PWV can be inferred (Bevis et al., 1992; Davis et al., 1985). GNSS‐derived PWV has been presently applied in broad fields, including the following: monitoring climate change (Chen & Liu, 2016b; Parracho et al., 2018; Zhao et al., 2020a), improving the numerical weather prediction (NWP) model (Gendt et al., 2004; Smith et al., 2007), detecting extreme weather (Bordi et al., 2016; Chen et al., 2017; Means, 2013; K. Zhang et al., 2015; Zhao et al., 2020b), and validating satellite and reanalysis products (Bock et al., 2005; Chen, Dai, Liu, Wu, & Xia, 2018; Jiang et al., 2020; Roman et al., 2016).…”