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Abstract
AbstarctGlobal Navigation Satellite System (GNSS) can effectively retrieve precipitable water vapor (PWV) with high precision and high-temporal resolution. GNSS-derived PWV can be used to reflect water vapor variation in the process of strong convection weather. By studying the relationship between time-varying PWV and rainfall, it can be found that PWV contents increase sharply before raining. Therefore, a short-term rainfall forecasting method is proposed based on GNSS-derived PWV. Then the method is validated using hourly GNSS-PWV data from Zhejiang Continuously Operating Reference Station (CORS) network of the period 1 September 2014 to 31 August 2015 and its corresponding hourly rainfall information. The results show that the forecasted correct rate can reach about 80%, while the false alarm rate is about 66%. Compared with results of the previous studies, the correct rate is improved by about 7%, and the false alarm rate is comparable. The method is also applied to other three actual rainfall events of different regions, different durations, and different types. The results show that the method has good applicability and high accuracy, which can be used for rainfall forecasting, and in the future study, it can be assimilated with traditional weather forecasting techniques to improve the forecasted accuracy.
Highlights
Water vapor is an important component of the atmosphere, which affects the radiation balance, energy transportation, and the formation of cloud and precipitation[1]
Different types of rainfall process, especially extreme rainfall events have different great impacts on all aspects of living and property[12]. It brings serious destruction and enormous economic loses13.in this paper, we study the relationship between Global Navigation Satellite System (GNSS)-derived precipitable water vapor (PWV) and rainfall, and establish a short-term rainfall forecasting method
For PWV, the threshold is selected monthly because of its seasonal characteristics, and should ensure that the correct rate is much higher than the false alarm rate; for PWV variations, it should be determined under the selection of the rate of change of PWV, to improve the forecasted results
Summary
Analysis of the relationship between GNSS-PWV and rainfall Preliminary analysis of the relationship between GNSS-PWV and rainfall. To explore the relationship between GNSS-derived PWV and rainfall, station LJSL is taken as an example to analyze the time-varying characteristic of PWV during several rainfall events (Fig. 2). Because when threshold is small, there will be contained more events which includes correct events and false events Experiments and Benevides’s forecasted experiments in Portugal[21] indicate that the rate of change of PWV can afford better forecasted results than other two factors (PWV, and PWV variation)
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