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Passive Microwave Monitoring of Rainfall over Iran

Congress: 2008
Author(s):

Keyword(s): Rainfall SSM/I- Grody and Basist mask - Fine-tuned algorithm - D5K algorithm
AbstractSatellite passive microwave data have been analyzed to establish and demonstrate the utility of a remote sensing application related to the retrieval of rainfall over Iran. In order to achieve this objective, a new fine- tuned algorithm from F11-SSM/I data was developed. To minimize errors cased by spatial and temporal variations in surface temperature, emissivity and atmospheric effects - which are particularly significant in Iran given its geographical position and climatic conditions - the algorithm uses the non-raining brightness temperatures within 1/10 latitude by 1/10 longitude pixels, supported by 136 rain gauges. In order to remove the effect of scattering signatures, the Grody and Basist mask was used to identify snow surfaces, desert sands and frozen ground. The coastal areas were eliminated by using the coast mask for 50 km distance in width along 657 km in the north and 2133 km in the south. Precipitation events over the regions which are covered by snow (mainly mountainous and high elevation areas) have been deleted because their brightness temperatures are very similar to those caused by snow. The new algorithm is based on the modification of the basic adjusted frequency difference between V37 GHz and V85 GHz channels, and applied only over land. This technique objectively adjusts rain rate estimated by the SSM/I sensor. The adjustment is based on spatially and temporally variable coefficients of rain-free conditions Results derived from this algorithm were validated against the ground truth data for a number of synoptic stations, and then compared with the results of the D5K algorithm from WetNet PIP-3 (NASA 1996). In this way, the correlation coefficent is increased from 0.38 to 0.61, and the rms error reduced from 262.8 to 149.3 mm. The main conclusion of this paper is that passive microwave satellite data can provide useful information on rainfall over Iran at least on climatological-scales, and should be exploited further, together with other data types, to improve the collection and practical application of environmental data in this climatically and geographically very varied country.
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