Combining Meteosat-10 satellite image data with GPS tropospheric path delays to estimate regional integrated water vapor (IWV) distribution
Using GPS satellites signals, we can study different processes and coupling mechanisms that can help us understand the physical conditions in the lower atmosphere, which might lead or act as proxies for severe weather events such as extreme storms and flooding. GPS signals received by ground station...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-02-01
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Series: | Atmospheric Measurement Techniques |
Online Access: | http://www.atmos-meas-tech.net/10/537/2017/amt-10-537-2017.pdf |
Summary: | Using GPS satellites signals, we can study different processes and coupling
mechanisms that can help us understand the physical conditions in the lower
atmosphere, which might lead or act as proxies for severe weather events
such as extreme storms and flooding. GPS signals received by ground stations
are multi-purpose and can also provide estimates of tropospheric zenith
delays, which can be converted into accurate integrated water vapor (IWV)
observations using collocated pressure and temperature measurements on the
ground. Here, we present for the first time the use of Israel's dense
regional GPS network for extracting tropospheric zenith path delays combined
with near-real-time Meteosat-10 water vapor (WV) and surface temperature
pixel intensity values (7.3 and 10.8 µm channels, respectively)
in order to assess whether it is possible to obtain absolute IWV (kg m<sup>−2</sup>) distribution. The results show good agreement between the absolute values obtained from our triangulation strategy based solely on GPS zenith total delays (ZTD) and Meteosat-10 surface temperature data compared with
available radiosonde IWV absolute values. The presented strategy can provide
high temporal and special IWV resolution, which is needed as part of the
accurate and comprehensive observation data integrated in modern data
assimilation systems and is required for increasing the accuracy of
regional numerical weather prediction systems forecast. |
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ISSN: | 1867-1381 1867-8548 |