Abstract
Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38°NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40°NS using data obtained from numerous weather stations in 1998–2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research.
Highlights
Precipitation is a key variable for the Earth’s water cycle and energy balance, plays a major role in monitoring water-related natural hazards and water resource management
This study focuses on the evaluation of Tropical Multisatellite Precipitation Analysis (TMPA), a quasi-global precipitation product
A moderate correlation was observed between TMPA V7 and rain gauge with a CC of 0.63, indicating that these two datasets are in good agreement to some degree
Summary
Precipitation is a key variable for the Earth’s water cycle and energy balance, plays a major role in monitoring water-related natural hazards and water resource management. Precipitation exerts major effects on the earth’s ecosystem [4] and hydrological cycle. Accurate measurement of precipitation is essential to investigate spatial pattern of rainfall at regional scale. Having accurate rainfall data will improve our understanding of the effect of precipitation on hydrology and climate change. The limitations of rain gauge measurement restrict our understanding of precipitation: one is the insufficient spatial representation [5], which means that direct measurements of rainfall at an single station were generally not very useful in making estimates of areal rain and spatial distribution of rainfall over large areas; the other is sparse distribution over mountainous areas and unavailability over the oceans [6, 7]. A long history of the development in the estimation of precipitation data based on satellite data has culminated in sophisticated satellite instruments and techniques that can be used to combine information from multiple satellites to produce long time series products that are useful for climate monitoring [8]
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