Climate and Dynamics
Evaluation of precipitation from the ERA-40, NCEP-1, and NCEP-2 Reanalyses and CMAP-1, CMAP-2, and GPCP-2 with ground-based measurements in China
Article first published online: 8 MAY 2009
Copyright 2009 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 114, Issue D9, 16 May 2009
How to Cite
2009), Evaluation of precipitation from the ERA-40, NCEP-1, and NCEP-2 Reanalyses and CMAP-1, CMAP-2, and GPCP-2 with ground-based measurements in China, J. Geophys. Res., 114, D09105, doi:10.1029/2008JD011178., , , , , and (
- Issue published online: 8 MAY 2009
- Article first published online: 8 MAY 2009
- Manuscript Accepted: 27 FEB 2009
- Manuscript Revised: 18 FEB 2009
- Manuscript Received: 20 SEP 2008
 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.