David Kneis, C. Chatterjee, R. Singh

• The paper examines the quality of satellite-abased precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-aadjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-astep procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the subbasin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-arunoff simulation. At sub-abasin level (4000 to 16 000 km(2)) the satellite-abased areal precipitation estimates were found to be moderately correlated with the gauge-abased counterparts (R-2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM dataThe paper examines the quality of satellite-abased precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-aadjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-astep procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the subbasin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-arunoff simulation. At sub-abasin level (4000 to 16 000 km(2)) the satellite-abased areal precipitation estimates were found to be moderately correlated with the gauge-abased counterparts (R-2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-aintensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate < 0.6 for ground-abased intensities > 80 mm day(-1)). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-abased equivalents (false alarm ratios of 0.2-0.6). In addition, the real-atime product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-arunoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by reservoir operation). This compares to the values of 0.71-0.78 for the gauge-djusted TRMM 3B42 data and 0.65-0.77 for the 3B42-RT real-atime data. Whether the 3B42-RT data are useful in the context of operational runoff prediction in spite of the identified problems remains a question for further research.…