Monitoring and prediction of hurricane tracks using GPS tropospheric products

被引:0
作者
Yohannes Getachew Ejigu
Felix Norman Teferle
Anna Klos
Janusz Bogusz
Addisu Hunegnaw
机构
[1] Ethiopian Space Science and Technology Institute (ESSTI),Department of Space Science and Application Research Development
[2] Department of Physics,Institute of Civil and Environmental Engineering
[3] Wolkite University,Faculty of Civil Engineering and Geodesy
[4] University of Luxembourg,undefined
[5] Military University of Technology,undefined
来源
GPS Solutions | 2021年 / 25卷
关键词
GPS; Integrated water vapor; Hurricane Harvey; Hurricane Irma; Spaghetti plot; Tropical cyclone;
D O I
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学科分类号
摘要
We have reconstructed integrated water vapor (IWV) using the zenith wet delays to track the properties of hurricanes and explore their spatial and temporal distributions estimated from 922 GPS stations. Our results show that a surge in GPS-derived IWV occurred at least six hours prior to the landfall of two major hurricanes (Harvey and Irma) that struck the Gulf and East Coasts of the USA in 2017. We observed enhanced IWV, in particular, for the two hurricanes landfall locations. The observed variations exhibit a correlation with the precipitation value constructed from GPM/IMERG satellite mission coinciding with hurricane storm front passage. We used GPS-IWV data as inputs for spaghetti line plots for our path predictions, helping us predict the paths of Hurricanes Harvey and Irma. Hence, a directly estimable zenith wet delay sourced from GPS that has not been previously reported can serve as an additional resource for improving the monitoring of hurricane paths.
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[1]  
Ackerman SA(2019)Satellites see the world’s atmosphere Meteorol aphs 59 1-4
[2]  
Platnick S(2013)GNSS observations of deep convective time scales in the Amazon Geophys Res Lett 40 2818-2823
[3]  
Bhartia PK(2012)Operational assimilation of GPS Zenith total delay observations into the met office numerical weather prediction models Mon Weather Rev 140 2706-2719
[4]  
Duncan B(1992)GPS meteorology: remote sensing of atmospheric water vapor using the global positioning system J Geophys Res Atmos 97 15787-15801
[5]  
L’ecuyer T(2019)Recent increases in tropical cyclone intensification rates Nat Commun 142 56-71
[6]  
Heidinger A(2018)Harnessing the GPS data explosion for interdisciplinary science Eos 88 651-668
[7]  
Skofronick-Jackson G(2016)A high-quality reprocessed ground-based GPS dataset for atmospheric process studies, radiosonde and model evaluation, and reanalysis of HyMeX S pecial Observing Period Q J R Meteorol Soc 20 1593-1607
[8]  
Loeb N(2006)Global Mapping Function (GMF): a new empirical mapping function based on numerical weather model data Geophys Res Lett 44 153-166
[9]  
Schmit T(2007)Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season Bull Am Meteor Soc 23 659-680
[10]  
Smith N(1985)Geodesy by radio interferometry: effects of atmospheric modeling errors on estimates of baseline length Radio Sci 50 3-16