Science Service System

Summary of Proposal MTH1847

TitleXSARWat. Spaceborne remote sensing of precipitation effects and flooded areas from X-band synthetic aperture radars: models, methods and applications
Investigator Mori, Saverio - Sapienza University of Rome, DIET - Dep. of Information Eng., Elec. and Telecom.
Team MemberNo team members defined
SummaryThe present proposal seeks to develop techniques to detect, analyze and retrieve atmospheric attenuation and precipitation intensity by means of spaceborne X-band Synthetic Aperture Radars(X-SAR). The use of satellite X-SAR is generally not devoted to the atmospheric observation, but there is relevant theoretical and experimental evidence that X-band radar may be significantly affected by precipitation occurrence within the synthetically scanned area. As a matter of fact, the Precipitation Radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite was designed at Ku band. Previous analyses have, indeed, already shown that both ice and liquid precipitating hydrometeors can give a detectable signature on X-SAR images, both in amplitude and phase. These analyses used X-SAR data available from theX-SAR/SIR-C campaign in 1994 sponsored by NASA, ASI and DLR, and more recently TerraSAR-X and COSMO-SkyMed data. TerraSAR-X (TSX) satellite can thus offer a unique opportunityto quantify these effects and to develop techniques to: 1) retrieve precipitation rate in both liquid and ice phase at very high spatial resolution; 2) correct X-SAR images affected by atmospheric effects. These aims would have several benefits as: i) on one hand, it would open a completely new application of X-SAR instruments devoted to the estimation of highly-resolved precipitation fields of interest for hydrological purposes and civil protection measurements, especially in areas where ground based radar are not available; ii) on the other hand, it would contribute to improve the quality check of X-SAR data processing chain by detecting and possibly compensating for atmospheric attenuation and scattering effects. The retrieval methodology proposed will be based on the development of inversion algorithms able to exploit the physically-based information derived from microwave polarimetric models applied to simulated rainy cloud structures. The latter will constructed by using both simplified two-dimensional precipitation models and three-dimensional outputs of high-resolution mesoscale cloud-resolving numerical models. Several inversion methodologies will be investigated and developed in order to compare their performances.Precipitation estimation by means of spaceborne X-Band SARs could be improved by means of a pre-processing step in which precipitating areas are distinguished by floods and permanent water surfaces. On the other end, although quite rare, artifacts due to heavy rain or wet snow cover might cause an overestimation of flooded areas detected by flood mapping algorithms that use X-Band SAR data as inputs. In fact, the X-Band radar signature of water surfaces can be confused with that produced by intense precipitation cells, as well as with the microwave signature of wet snow. To tackle this problem, which was generally disregarded in the literature, an automatic method to distinguish, in a X-band SAR image, water surfaces (either flooded, or permanent water bodies) from artifacts due to heavy precipitation and from wet snow has been proposed in previous work and will be investigated within this project. The polarimetric information content will be also analyzed in order to exploit the polarimetric capability of TSX X-SAR. The X-SAR data analysis will benefit from the synergy of co-located data from geosynchronous- Earth-orbit (GEO) mid and thermal infrared radiometers, low-Earth-orbit (LEO) C-band SARs, microwave radiometers and spectrometers.The TSX-based rainfall retrieval performances will be basically validated against ground-based weather radar and rain gauge network data as measurement opportunities will occur over instrumented ground area. Funds for theproposed project will be provided by the Sapienza University of Rome.

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DLR 2004-2016