[en] Tropical cyclones are one of the most powerful
severe weather events that produce devastating socioeconomic
and environmental impacts in the areas they strike. Therefore,
monitoring and tracking of the arrival times and path
of the tropical cyclones are extremely valuable in providing
early warning to the public and governments. Hurricane
Florence struck the East cost of USA in 2018 and offers
an outstanding case study. We employed Global Positioning
System (GPS) derived precipitable water vapor (PWV)
data to track and investigate the characteristics of storm occurrences
in their spatial and temporal distribution using a
dense ground network of permanent GPS stations. Our findings
indicate that a rise in GPS-derived PWV occurred several
hours before Florence’s manifestation. Also, we compared
the temporal distribution of the GPS-derived PWV
content with the precipitation value for days when the storm
appeared in the area under influence. The study will contribute
to quantitative assessment of the complementary GPS
tropospheric products in hurricane monitoring and tracking
using GPS-derived water vapor evolution from a dense network
of permanent GPS stations
Disciplines :
Earth sciences & physical geography
Author, co-author :
Ejigu, Yohannes Getachew; Ethiopian Space Science and Technology Institute, Addis Ababa, Ethiopia
TEFERLE, Felix Norman ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
klos, Anna; Military University of Technology, Warsaw, Poland
Bogusz, Janusz; Military University of Technology, Warsaw, Poland
HUNEGNAW, Addisu ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
External co-authors :
yes
Language :
English
Title :
Tracking Hurricanes using GPS atmospheric precipitable water vapor field
Publication date :
2020
Event name :
IUGG symposium
Event date :
8-07-2019 - 18-07-2019
Audience :
International
Main work title :
Beyond 100: The Next Century in Geodesy
Publisher :
Springer, Heidelberg, Germany
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
FnR Project :
FNR12909050 - Advanced Asymmetry Tropospheric Products For Meteorology From Gnss And Sar Observations, 2018 (01/02/2019-31/07/2022) - Norman Teferle