Evaluation of Real-Time Satellite Precipitation Data for Global Drought Monitoring

Abstract

he Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) near-real-time (RT) data are considered less accurate than the TMPA research quality (RP) data because of the simplified data processing algorithm and the lack of gauge adjustments. However, for near-real-time hydrological applications, such as drought nowcasting, the RT data must play a key role given latency considerations and consistency is essential with products like RP, which have a long-term climatology. The authors used a bivariate test to examine the consistency between the monthly RT and RP precipitation estimates for 12 yr (2000?12) and found that, for over 75% of land cells globally, RT and RP were statistically consistent at 0.05 significance level. The inconsistent grid cells are spatially clustered in western North America, northern South America, central Africa, and most of Australia. The authors also show that RT generally increases with time relative to RP in northern South America and western Australia, while in western North America and eastern Australia, RT decreases relative to RP. In other areas such as the eastern part of North America, Eurasia, and southern part of the South America, the RT data are statistically consistent with the RP data and are appropriate for global- or macroscale hydrological applications.