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This paper presents an assessment of the 3B42 research version rainfall product from NASA's Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA). The study provides new results of TMPA data accuracy in urban areas and highlights trends associated with the climatological indicators of temperature and relative humidity in cities. Ten years (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) of TMPA data were analyzed for three case study cities in the United States (Houston, Atlanta, and Las Vegas) and one in Korea (Cheongju), representing semi-arid to humid climates. At each location, an urbanized river basin and non-urbanized river basin were selected and comparisons between TMPA and rain gage observations were made for recorded storm events in the study period, the largest storm events by total depth, and selected hurricanes and topical storms. The results indicate TMPA data match well with rain gage observations at all locations. TMPA is slightly underestimated for semi-arid regions and overestimated for humid regions. The relative magnitude of TMPA rain event accumulation compared to rain gage accumulation is noted to be smaller for urbanized watersheds and high intensity events. The correlation of TMPA accuracy with temperature and relative humidity and the analysis of accuracy by season indicate TMPA is more accurate for convective rainfall events. This suggests a possible linkage between the observed urban-modified temperatures, hypothesized enhanced convection, and improved TMPA accuracy in urban areas.

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In this research, the analysis method of future flooding discharge considering climate change and land-use change is proposed. In order to reduce uncertainty of climate change data, RCP 8.5 climate change scenario data is compared with long-term observed rainfall data in case study area and calibrated by regional parameters which can reflect regional weather characteristics and is required parameters for daily weather generation for future climate change data. Using calibrated RCP 8.5 data, the probability rainfall of 1 day and 5 days rainfall duration is calculated by 3 different time zone(Future 1 : 2011~2040, Future 2 : 2041~2070, Future 3 : 2071~2100). The algorithm of sub-module in Dyna-CLUE model is used to calculate the future land-use change by 3 different landuse scenarios and 3 different time zone. The S-RAT which is distributed hydrology model is used to simulate the future discharge by different time zone, 1 and 5 days rainfall duration and land-use change scenarios. As a result, the peak discharge is increased as far future and more urbanized. However, climate change is more effect to increase of peak discharge than the land-use change. Although to simulate future data such as climate and land-use change has a lot of uncertainty, those kinds of research must be required to reduce future natural disaster damage. It is expected that the analysis method in this research would be contribute to more correctly quantify the future flooding risk.