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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 1 | Copyright

Special issue: Advances in Mediterranean meteorology

Nat. Hazards Earth Syst. Sci., 10, 121-132, 2010
https://doi.org/10.5194/nhess-10-121-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  22 Jan 2010

22 Jan 2010

Water vapour distribution at urban scale using high-resolution numerical weather model and spaceborne SAR interferometric data

E. Pichelli1, R. Ferretti1, D. Cimini1, D. Perissin2, M. Montopoli4,1, F. S. Marzano3,1, and N. Pierdicca3 E. Pichelli et al.
  • 1Department Physics, University of L'Aquila/CETEMPS, L'Aquila, Italy
  • 2Institute of Space and Earth Information Science, Chinese University of Hong Kong, Hong Kong, China
  • 3Department Electronic Engineering, Sapienza University of Rome, Rome, Italy
  • 4Department of Electrical and Information Engineering, University of L'Aquila, L'Aquila, Italy

Abstract. The local distribution of water vapour in the urban area of Rome has been studied using both a high resolution mesoscale model (MM5) and Earth Remote Sensing-1 (ERS-1) satellite radar data. Interferometric Synthetic Aperture Radar (InSAR) techniques, after the removal of all other geometric effects, estimate excess path length variation between two different SAR acquisitions (Atmospheric Phase Screen: APS). APS are strictly related to the variations of the water vapour content along the radar line of sight. To the aim of assessing the MM5 ability to reproduce the gross features of the Integrated Water Vapour (IWV) spatial distribution, as a first step ECMWF IWV has been used as benchmark against which the high resolution MM5 model and InSAR APS maps have been compared. As a following step, the high resolution IWV MM5 maps have been compared with both InSAR and surface meteorological data. The results show that the high resolution IWV model maps compare well with the InSAR ones. Support to this finding is obtained by semivariogram analysis that clearly shows good agreement beside from a model bias.

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