| description abstract | The North American Regional Reanalysis (NARR) atmospheric water cycle is examined from 1980 to 1999 using a budget approach, with a particular emphasis on annual component interactions and the role of hourly precipitation assimilation. NARR?s summertime atmospheric water cycle and diurnal component interactions are examined in Part II of this study. NARR?s high-resolution reanalysis and precipitation assimilation allow an improved climatology of mean water cycle components over North America, which is very attractive for applications, climate impact assessments, and as a basis for comparison with other products. A 20-yr climatology of precipitation, evaporation, moisture flux convergence, and the residual error term are produced for comparison to observations, other reanalyses and models, and future climate scenarios. Maps of the normalized covariance of annual precipitation with each of the other water cycle components identify regimes of seasonal interaction that form an additional basis for comparison. The annual cycle of assimilated precipitation is compared to high-resolution precipitation products as an example, and points of interest for continuing studies are identified. Analysis of the mean and transient balances reveals a significant effect from NARR?s precipitation assimilation scheme, which is investigated using an estimate of NARR?s underlying model precipitation (before assimilation), generated using the precipitation assimilation increment as a proxy. Biases of the precipitation assimilation scheme are then characterized spatially and temporally to inform the interpretation of NARR applications and comparisons. These model precipitation estimates reveal a more tightly closed atmospheric water cycle with predominantly excessive precipitation, resulting in too vigorous evaporation and moisture flux convergences. The sign and magnitude of evaporation and moisture flux convergence biases are found to be related to the precipitation assimilation correction and are important to consider in applications of NARR output. | |
