Assessment of satellite-based rainfall estimates in urban areas in different geographic and climatic regions

Abstract

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.

Accuracy Evaluation of Two High-Resolution Satellite-Based Rainfall Products: TRMM 3B42V7 and CMORPH in Shanghai

“…However, in this study, the error distribution characteristics of satellite-based rainfall products are not discussed further. Han et al [9] also evaluated the accuracy of TRMM data in urban areas in different climatic regions (Houston, Atlanta, Las Vegas in the United States and one in Korea, Cheongju), as a function of climatic variables, and for different storm types. The results show that the relative magnitude of TRMM rain accumulation compared to rain gauge accumulation is smaller for higher rainfall intensity events.…”

“…Different rainfall trends have been observed from many discrete ground meteorological stations [7]. However, those studies are limited in terms of both their sparse spatial scope and data accuracy [9,10].…”

“…These products provide an important input for some hydrological models and natural hazard researches [18][19][20], and are used for simulating the rainfall spatio-temporal distribution at global and regional scales [21,22]. Previous research indicates that the spatial and temporal accuracies of both the 3B42V7 and CMORPH products are obviously higher in China [23,24], and the three-hourly 0.25 • TRMM 3B42V7 and CMORPH data have a higher correlation with rain gauge data and can simulate precipitation spatio-temporal processes in urban areas [9]. Zhang et al used the TRMM 3B42V6 products to simulate the rainfall spatio-temporal distribution in the Beijing metropolitan region and found that there were fewer rain days and a higher rainfall intensity in urban areas than in other surrounding regions under the impact of urbanization [25].…”

The use of remotely sensed environmental data in the study of malaria

“…The cold cloud duration (CCD) can be derived from Meteosat thermal IR imaging (Dugdale et al, 1991) and provides rainfall estimates based on the length of time a cloud top is below a threshold temperature. The Tropical Rainfall Measuring Mission (TRMM; http://trmm.gsfc.nasa.gov/) satellite provides near-real-time direct measurement of rainfall in tropical areas based on passive microwave and active radar sensors, which closely matches ground rain gage observations (Sharma et al, 2007;Han et al, 2010), even in urban areas (Hand and Shepherd, 2009). Nevertheless, the influence of location, climate, topography, time period, cloud types and rainfall types can affect accuracy (Barros et al, 2000).…”

Analysis of precipitation extremes based on satellite (CHIRPS) and in situ dataset over Cyprus

“…They also referred to taking into consideration limitations regarding both the accuracy of the TRMM and the interpolation process of the E-OBS datasets. Han et al (2011) studied the assessment of the accuracy of satellite-based rainfall data in urban areas in different climatic regions, as a function of climatic variables, and for different storm types. They found that satellite-based rainfall data matched well with rain gauge observations at all locations, while a possible linkage between the observed urbanmodified temperatures, hypothesized enhanced convection and improved satellite-based rainfall data accuracy existed in urban areas.…”