We assess the correspondence between precipitation products from atmospheric reanalyses (ERA‐40, NCEP‐1, and NCEP‐2), the Climate Prediction Center (CPC) Merged Analyses of Precipitation (CMAP‐1 and CMAP‐2), and the Global Precipitation Climatology Project Version 2 (GPCP‐2) with adjusted observational precipitation (AOP) from China for 1979–2001 and also for ERA‐40 and NCEP‐1 over 1958–1978. In general, we conclude that CMAP‐1 and GPCP‐2 agree more closely with AOP than the reanalysis products do, although ERA‐40 data agree more closely with AOP than NCEP data. The percentages of precipitation differences (PPDs) across China between annual ERA‐40, NCEP‐1, NCEP‐2, CMAP‐1, CMAP‐2, and GPCP‐2 data and AOP are −12, 22, 14, −8, −7, and −15%, respectively, for 1979–2001. Although relatively small biases are evident for China as a whole, maximum PPDs, usually occurring around the Qinghai‐Tibetan Plateau, can exceed 1000%, indicating a strong terrain dependence of gridded precipitation data. GPCP‐2, although characterized by greater underestimation for most of China compared with CMAP‐1, exhibits a smaller biases range and hence may be better than CMAP‐1. Compared with the NCEP‐1 system, NCEP‐2 represents an improvement as NCEP‐2 precipitation agrees more closely with AOP than NCEP‐1 data. However, the coherence of NCEP‐2 precipitation needs further improvement. In addition, we find worse consistency and accuracy and larger positive biases in some parts of China for CMAP‐2 versus CMAP‐1, illustrating an advantage of including reanalysis data in CMAP, as CMAP‐1 does. CMAP‐1 could be further improved if they used the more skillful ERA‐40 precipitation instead of the NCEP/NCAR data.
No takes yet. Share an insight, caveat, or question.
Ma et al. (2009) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: