KIT | KIT-Bibliothek | Impressum
Open Access Logo
URN: urn:nbn:de:swb:90-520712

Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations

Alshawaf, F.; Fersch, B.; Hinz, S.; Kunstmann, H.; Mayer, M.; Meyer, F.J.

Data fusion aims at integrating multiple data sources that can be redundant or complementary to produce complete, accurate information of the parameter of interest. In this work, data fusion of precipitable water vapor (PWV) estimated from remote sensing observations and data from the Weather Research and Forecasting (WRF) modeling system are applied to provide complete grids of PWV with high quality. Our goal is to correctly infer PWV at spatially continuous, highly resolved grids from heterogeneous data sets. This is done by a geostatistical data fusion approach based on the method of fixed-rank kriging. The first data set contains absolute maps of atmospheric PWV produced by combining observations from the Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). These PWV maps have a high spatial density and a millimeter accuracy; however, the data are missing in regions of low coherence (e.g., forests and vegetated areas). The PWV maps simulated by the WRF model represent the second data set. The model maps are available for wide areas, but they have a coarse spatial resolution and a still ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU)
Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Jahr 2015
Sprache Englisch
Identifikator ISSN: 1027-5606
KITopen ID: 1000052071
HGF-Programm 12.02.03; LK 01
Erschienen in Hydrology and Earth System Sciences
Band 19
Heft 12
Seiten 4747-4764
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft KITopen Landing Page