Many rainfall estimation techniques and algorithms are developed for a particular region and for very different time-space scales. Instantaneous rain rates may vary from fractions of mm to over 100mm per hr. and the rainfall intensity with duration varies from region to region. We need to understand the errors structure for a variety of instruments and algorithms that are in use today or will be in use tomorrow over different regions. Bangladesh is the country that suffers from flooding in most of the year because of highly intensive rainfall within and outside of the country. The performance of satellite rainfall is an important issue for hydro-meteorological application in Bangladesh. In this study, the first space-borne Precipitation Radar (PR) launched by Tropical Rainfall Measuring Mission (TRMM) satellite data is used, which produces rain/no rain flag, vertical rain rate profile, near surface rain etc. However, only those gauge stations are considered in this study that falls inside the instantaneous field of view of particular TRMM observations. The preliminary result shows that Bangladesh is distinct from the other region in USA. Passive Microwave calibrated IR (3B41RT) performs better than TMI-2A12 rain product over Bangladesh. The main reason could be summer rain in Bangladesh that comes mainly from extensive mid-level stratiform clouds. We could also observe from PR reflectivity profile using contoured frequency by altitude display (CFAD), higher detection error are those areas where stratiform rain is dominant, or constitute a significant proportion.
As part of a wider study of carbon cycling in boreal peatlands, radar remote sensing was used with the objective of obtaining diverse environmental information related to these environments. An analysis of multi-temporal Fine beam mode RADARSAT-1 images was carried out, with the support of collected field data, to verify if water table height and volumetric water content influenced radar backscatter coefficient. A maximum likelihood classification (MLC) on speckle filtered and textural images was also carried out, evaluated and compared with a similar classification procedure on Standard beam mode images. Significant changes in water table position and soil moisture have been observed but these were not reflected in radar backscatter coefficient. C-band wavelength, shallow incidence angle and high volumetric water content of peat are some factors that would limit hydrological conditions monitoring with Fine beam mode images. Further analyses have to be done in order to confirm these conclusions. MLC classification using textural images generated from multi-temporal Fine beam mode images brought poorer results than a similar classification using multi-temporal Standard beam mode textural images. This can be explained by the lower radiometric resolution of Fine beam mode images. If only radar imageries are available for boreal peatland mapping, Standard beam mode images should be used, even if they have a lower geometric resolution.