DOI: 10.5194/hess-19-4747-2015
Scopus记录号: 2-s2.0-84949057761
论文题名: Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations
作者: Alshawaf F ; , Fersch B ; , Hinz S ; , Kunstmann H ; , Mayer M ; , Meyer F ; J
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 12 起始页码: 4747
结束页码: 4764
语种: 英语
Scopus关键词: Data fusion
; Global positioning system
; Image resolution
; Interpolation
; Synthetic aperture radar
; Water vapor
; Weather forecasting
; Atmospheric simulations
; Computational burden
; Global Navigation Satellite Systems
; High spatial density
; Interferometric synthetic aperture radars
; Multiple data sources
; Precipitable water vapor
; Weather research and forecasting models
; Remote sensing
; accuracy assessment
; atmospheric modeling
; data set
; geostatistics
; GNSS
; kriging
; mapping method
; radar
; spatial resolution
; water vapor
英文摘要: 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 limited accuracy. The PWV maps inferred by the data fusion at any spatial resolution show better qualities than those inferred from single data sets. In addition, by using the fixed-rank kriging method, the computational burden is significantly lower than that for ordinary kriging. © 2015 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78373
Appears in Collections: 气候变化事实与影响
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作者单位: Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Karlsruhe, Germany; Institute of Meteorology and Climate Research, Campus Alpin, KIT, Garmisch-Partenkirchen, Germany; Geodetic Institute, KIT, Karlsruhe, Germany; Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, United States
Recommended Citation:
Alshawaf F,, Fersch B,, Hinz S,et al. Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations[J]. Hydrology and Earth System Sciences,2015-01-01,19(12)