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Viviane B. S. Silva, Vernon E. Kousky, and R. Wayne Higgins

Abstract

In this study, the authors document the extent to which the precipitation statistics of the new CFS reanalysis (CFSR) represent an improvement over the earlier reanalyses: the NCEP–NCAR reanalysis (R1) and the NCEP–DOE Second Atmospheric Model Intercomparison Project (AMIP-II) reanalysis (R2). An intercomparison between the CFSR, R1, R2, and observations over South America was made for the period 1979–2006. The CFSR shows notable improvements in the large-scale precipitation patterns compared with the previous reanalyses (R1 and R2). In spite of these improvements, the CFSR has substantial biases in intensity and frequency of occurrence of rainfall events. Over west-central Brazil, the core region of the South American monsoon system (SAMS), the CFSR displays a dry bias during the onset phase of the SAMS wet season and a wet bias during the peak and decay phases of the SAMS wet season. The CFSR also displays a dry bias along the South American coast near the mouth of the Amazon and along the east coast of northeastern Brazil. A wet bias exists in all seasons over southeast Brazil and over the Andes Mountains.

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Kingtse C. Mo, Muthuvel Chelliah, Marco L. Carrera, R. Wayne Higgins, and Wesley Ebisuzaki

Abstract

The large-scale atmospheric hydrologic cycle over the United States and Mexico derived from the 23-yr NCEP regional reanalysis (RR) was evaluated by comparing the RR products with satellite estimates, independent sounding data, and the operational Eta Model three-dimensional variational data assimilation (3DVAR) system (EDAS).

In general, the winter atmospheric transport and precipitation are realistic. The climatology and interannual variability of the Pacific, subtropical jet streams, and low-tropospheric moisture transport are well captured. During the summer season, the basic features and the evolution of the North American monsoon (NAM) revealed by the RR compare favorably with observations. The RR also captures the out-of-phase relationship of precipitation as well as the moisture flux convergence between the central United States and the Southwest. The RR is able to capture the zonal easterly Caribbean low-level jet (CALLJ) and the meridional southerly Great Plains low-level jet (GPLLJ). Together, they transport copious moisture from the Caribbean to the Gulf of Mexico and from the Gulf of Mexico to the Great Plains, respectively. The RR systematically overestimates the meridional southerly Gulf of California low-level jet (GCLLJ). A comparison with observations suggests that the meridional winds from the RR are too strong, with the largest differences centered over the northern Gulf of California. The strongest winds over the Gulf in the RR extend above 700 hPa, while the operational EDAS and station soundings indicate that the GCLLJ is confined to the boundary layer.

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Viviane B. S. Silva, Vernon E. Kousky, Wei Shi, and R. Wayne Higgins

Abstract

A gauge-only precipitation data quality control and analysis system has been developed for monitoring precipitation at NOAA’s Climate Prediction Center (CPC). Over the past 10 yr the system has been used to develop and deliver many different precipitation products over the United States, Mexico, and Central and South America. Here the authors describe how the system has been applied to develop improved gridded daily precipitation analyses over Brazil. Consistent with previous studies, comparisons between the the gridded analyses and station observations reveal fewer dry days, a greater number of low precipitation days, and fewer extreme precipitation events in the gridded analyses. Even though the gridded analysis system reduces the number of dry days and increases the number of wet days, there is still a good correlation between time series of the gridpoint precipitation values and observations.

Retrospective analyses are important for computing basic statistics such as mean daily/monthly rainfall, extremes, and probabilities of wet and dry days. The CPC gridded precipitation analyses can be used in hydrologic and climate variability studies dealing with large spatial-scale anomaly patterns, such as those related to ENSO. The analyses can also be used as a benchmark for evaluating model simulations, serve as a basis for real-time monitoring, and provide statistics on the occurrence of large-scale heavy rainfall events and dry periods.

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