The atmospheric moisture budget from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) is evaluated in polar regions for the period 1979-2005 and compared with previous estimates, accumulation syntheses over polar ice sheets, and in situ Arctic precipitation observations. The system is based on a nonspectral background model and utilizes the incremental analysis update scheme. The annual moisture convergence from MERRA for the north polar cap is comparable to previous estimates using 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) and earlier reanalyses but it is more than 50% larger than MERRA precipitation minus evaporation (P-E) computed from physics output fields. This imbalance is comparable to earlier reanalyses for the Arctic. For the south polar cap, the imbalance is 20%. The MERRA physics output fields are also found to be overly sensitive to changes in the satellite observing system, particularly over data-sparse regions of the Southern Ocean. Comparisons between MERRA and prognostic fields from two contemporary reanalyses yield a spread of values from 6% of the mean over the Antarctic Ice Sheet to 61% over a domain of the Arctic Ocean. These issues highlight continued problems associated with the representation of cold-climate physical processes in global data assimilation models. The distribution of MERRA surface fluxes over the major polar ice sheets emphasizes larger values along the coastal escarpments, which agrees more closely with recent assessments of ice sheet accumulation using regional models. Differences between these results and earlier assessments illustrate a continued ambiguity in the surface moisture flux distribution over Greenland and Antarctica. The higher spatial and temporal resolution as well as the availability of all budget components, including analysis increments in MERRA, offer prospects for an improved representation of the high-latitude water cycle in reanalyses.
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Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
Li, Jiandong
Sun, Zhian
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Australian Bur Meteorol, Sci & Innovat Grp, Sci Serv, Melbourne, Vic, AustraliaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
Sun, Zhian
Liu, Yimin
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Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
Liu, Yimin
You, Qinglong
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Fudan Univ, Dept Atmospher & Ocean Sci, Shanghai, Peoples R China
Fudan Univ, Inst Atmospher Sci, Shanghai, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
You, Qinglong
Chen, Guoxing
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Fudan Univ, Dept Atmospher & Ocean Sci, Shanghai, Peoples R China
Fudan Univ, Inst Atmospher Sci, Shanghai, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China
Chen, Guoxing
Bao, Qing
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Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing, Peoples R China