Print Email Facebook Twitter Evaluation of three satellite precipitation products TRMM 3B42, CMORPH, and PERSIANN over a subtropical watershed in China Title Evaluation of three satellite precipitation products TRMM 3B42, CMORPH, and PERSIANN over a subtropical watershed in China Author Liu, J. Duan, Z. Jiang, J. Zhu, A.X. Faculty Civil Engineering and Geosciences Department Water Management Date 2015-12-31 Abstract This study conducted a comprehensive evaluation of three satellite precipitation products (TRMM (Tropical Rainfall Measuring Mission) 3B42, CMORPH (the Climate Prediction Center (CPC)Morphing algorithm), and PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks)) using data from 52 rain gauge stations over the Meichuan watershed, which is a representative watershed of the Poyang Lake Basin in China. All the three products were compared and evaluated during a 9-year period at different spatial (grid and watershed) and temporal (daily, monthly, and annual) scales. The results showed that at daily scale, CMORPH had the best performance with coefficients of determination (?2) of 0.61 at grid scale and 0.74 atwatershed scale. For precipitation intensities larger than or equal to 25 mm,RMSE%ofCMORPHandTRMM3B42were less than 50%, indicating CMORPH and TRMM 3B42 might be useful for hydrological applications at daily scale. At monthly and annual temporal scales,TRMM3B42 had the best performances, with high ? 2 ranging from0.93 to 0.99, and thus was deemed to be reliable and had good potential for hydrological applications at monthly and annual scales. PERSIANN had the worst performance among the three products at all cases. To reference this document use: http://resolver.tudelft.nl/uuid:1c2b1202-8533-4434-8383-1ae2472ea278 Publisher Hindawi Publishing Corporation ISSN 1687-9309 Source Advances in Meteorology, 2015 (Article ID 151239) Part of collection Institutional Repository Document type journal article Rights (c) 2015 Junzhi Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Files PDF 317519.pdf 17.09 MB Close viewer /islandora/object/uuid:1c2b1202-8533-4434-8383-1ae2472ea278/datastream/OBJ/view