DocumentCode
2205304
Title
Analysis of atmospheric signals in spaceborne InSAR - toward water vapor mapping based on multiple sources
Author
Alshawaf, Fadwa ; Fersch, Benjamin ; Hinz, Stefan ; Kunstmann, Harald ; Mayer, Michael ; Thiele, Antje ; Westerhaus, Malte ; Meyer, Franz
Author_Institution
Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany
fYear
2012
fDate
22-27 July 2012
Firstpage
1960
Lastpage
1963
Abstract
The dominant error source for short wavelength spaceborne radar signals is due to water vapor present in the neutral atmosphere (neutrosphere). This distortion signal is characterized by high variations in time and space, and can be exploited as a valuable source for quantifying the water vapor content of the Earth´s atmosphere. Available water vapor measurements provided by Envisat Medium Resolution Imaging Spectrometer (MERIS) and simulations from numerical weather prediction models are still limited in observing rapid fluctuations of water vapor. Therefore, we are investigating Interferometric Synthetic Aperture Radar (InSAR) for water vapor mapping. In this paper, water vapor maps derived from Persistent Scatterer InSAR (PSI), MERIS, and the Weather Research and Forecasting (WRF) model are presented with comparative analyses.
Keywords
atmospheric humidity; remote sensing by radar; synthetic aperture radar; weather forecasting; Earth atmosphere; Envisat MERIS; Interferometric Synthetic Aperture Radar; Medium Resolution Imaging Spectrometer; WRF model; atmospheric signal analysis; distortion signal; dominant error source; multiple sources; neutral atmosphere; numerical weather prediction models; persistent scatterer InSAR; short wavelength spaceborne radar signals; spaceborne INSAR; water vapor content; water vapor mapping; water vapor rapid fluctuations; weather forecasting; weather research; Atmospheric modeling; Clouds; Delay; Meteorology; Numerical models; Predictive models; InSAR; MERIS; Neutrospheric water vapor; PSI WRF;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6351118
Filename
6351118
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