Journal of Hydrometeorology | Cui et al. 
Atmospheric reanalyses have been used in many studies to investigate the variabilities and trends of precipitation because of their global coverage and long record; however, their results must be properly analyzed and their uncertainties must be understood. In this study, precipitation estimates from five global reanalyses [ERA-Interim; MERRA, version 2 (MERRA2); JRA-55; CFSR; and 20CR, version 2c (20CRv2c)] and one regional reanalysis (NARR) are compared against the CPC Unified Gauge-Based Analysis (CPCUGA) and GPCP over the contiguous United States (CONUS) during the period 1980–2013. Reanalyses capture the variability of the precipitation distribution over the CONUS as observed in CPCUGA and GPCP, but large regional and seasonal differences exist. Compared with CPCUGA, global reanalyses generally overestimate the precipitation over the western part of the country throughout the year and over the northeastern CONUS during the fall and winter seasons. These issues may be associated with the difficulties models have in accurately simulating precipitation over complex terrain and during snowfall events. Furthermore, systematic errors found in five global reanalyses suggest that their physical processes in modeling precipitation need to be improved. Even though negative biases exist in NARR, its spatial variability is similar to both CPCUGA and GPCP; this is anticipated because it assimilates observed precipitation, unlike the global reanalyses. Based on CPCUGA, there is an average decreasing trend of −1.38 mm yr−1 over the CONUS, which varies depending on the region with only the north-central to northeastern parts of the country having positive trends. Although all reanalyses exhibit similar interannual variation as observed in CPCUGA, their estimated precipitation trends, both linear and spatial trends, are distinct from CPCUGA.
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