Determining the precipitable water vapor with ground-based GPS and comparing its yearly variation to rainfall over Taiwan

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• 作者：Ta-Kang Yeh^a ; ^{bigsteel@mail.ntpu.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; Jing-Shan Hong^b ; Chuan-Sheng Wang^d ; Chieh-Hung Chen^c ; Kwo-Hwa Chen^a ; Chin-Tzu Fong^b
• 关键词：GPS ; Precipitable water vapor ; Rainfall ; Yearly variation ; Taiwan
• 刊名：Advances in Space Research
• 出版年：2016
• 出版时间：15 June 2016
• 年：2016
• 卷：57
• 期：12
• 页码：2496-2507
• 全文大小：1944 K

文摘

Water vapor plays an important role in weather prediction. Thus, it would be helpful to use precipitable water vapor (PWV) data from Global Positioning System (GPS) signals to understand weather phenomena. Approximately 100 ground GPS stations that cooperate with approximately 500 ground weather stations were used in this study. The relationship between the PWV and rainfall was investigated by analyzing the amplitude and phase that resulted from harmonic analyses. The results indicated that the maximum PWV amplitudes were between 10.98 and 13.10 mm and always occurred at the end of July. The magnitudes of the PWV growth rate were between 0.65 and 0.81 mm/yr. These rates increased from 9.2% to 13.0% between 2006 and 2011. The largest peak PWV amplitude occurred in the Western region. However, the largest rainfall amplitude occurred in the Southern region. The presented peak rainfall time agreed with the peak PWV time in the Western, Southern, and Central Mountain regions. Although rainfall decreased with time in Taiwan, this decrease was not large. The greatest rainfall consistently occurred during the months in which typhoons occurred, and the greatest PWV values occurred at the end of July. Although the end of July had the greatest monthly average PWV values, the rainfall magnitude during this period was smaller than that during the typhoons, which only occurred for a few days; the PWV also increased during typhoons. Because this effect was short-term, it did not significantly contribute to the PWV monthly average.