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A geostatistical approach to multisensor rain field reconstruction and downscaling
1University of Genova, Dept. of Communication, Computer and System Science, Opera Pia 13, 16145 Genova, Italy
2University of Genova, Dept. of Environmental Engineering, 1Montallegro, 16145 Genova, Italy
Email for corresponding author: luca@diam.unige.it
Abstract. A rain field reconstruction and downscaling methodology is presented, which allows suitable integration of large scale rainfall information and rain-gauge measurements at the ground. The former data set is assumed to provide probabilistic indicators that are used to infer the parameters of the probability density function of the stochastic rain process at each pixel site. Rain-gauge measurements are assumed as the ground truth and used to constrain the reconstructed rain field to the associated point values. Downscaling is performed by assuming the a posteriori estimates of the rain figures at each grid cell as the a priori large-scale conditioning values for reconstruction of the rain field at finer scale. The case study of an intense rain event recently observed in northern Italy is presented and results are discussed with reference to the modelling capabilities of the proposed methodology.
Keywords: Reconstruction, downscaling, remote sensing, geostatistics, Meteosat
Final Revised Paper (PDF, 407 KB)
Citation: Fiorucci, P., La Barbera, P., Lanza, L.G., and Minciardi, R.: A geostatistical approach to multisensor rain field reconstruction and downscaling, Hydrol. Earth Syst. Sci., 5, 201-213, 2001. Bibtex EndNote Reference Manager
