Impact of atmospheric moisture storage on precipitation recycling
Impact of atmospheric moisture storage on precipitation recycling
复制标题
DOI：
10.1175/jcli3691.1
复制
发表时间：
2006-04-15
影响因子：
4.9
通讯作者：
Ting, MF
中科院分区：
文献类型：
--
作者：
Dominguez, F;Kumar, P;Ting, MF
使用分析模型进行降水循环计算通常是在大气柱中水分储存变化可忽略不计的假设下进行的。由于水分存储期限在较小的时间尺度上是不可忽略的，因此大多数使用分析模型的回收研究都是在每月或更长时间尺度上进行的。开发了一种动态降水回收模型，其中包含水分储存的变化。 If 是从质量守恒方程中正式导出的，并以简单且计算高效的形式呈现。该模型允许在一系列时间范围内（从每天到每月或更长时间）进行回收分析。与不包含存储项的传统模型相比，新模型呈现出几乎相同的空间和时间变化。但预测每月的再循环率要高出 12%-33%。该动态模型用于利用 1979 年至 2000 年的 Reanalysis-II 数据来研究美国本土每月降水再循环的变化。平均而言，美国东南部和西南部地区的夏季再循环率较高。与美国东北部和西北部的低值形成鲜明对比。科罗拉多地区的回收率也很高。使用 EOF 分析确定回收中时空变异的主要模式。第一种模式捕捉到了 1986 年、1992 年和 1998 年夏季美国西部地区的强劲回收率。第二种模式捕捉到了 1988 年和 1989 年美国中部地区异常高的回收率，以及 1980 年和 1993 年期间异常低的回收率。
Computations of precipitation recycling using analytical models are generally performed under the assumption of negligible change in moisture storage in the atmospheric column. Because the moisture storage term is nonnegligible at smaller time scales, most recycling studies using analytical models are done at monthly or longer time scales. A dynamic precipitation recycling model, which incorporates the change in moisture storage, is developed. If is derived formally from the conservation of mass equation and is presented in a simple and computationally efficient form. This model allows for recycling analysis at a range of temporal scales, from daily to monthly and longer. In comparison to the traditional models that do not include the storage term, the new model presents almost identical spatial and temporal variability. but predicts recycling ratios that are 12%-33% larger at a monthly level.The dynamic model is used to study the variability of monthly precipitation recycling over the conterminous United States using Reanalysis-II data from 1979 to 2000. On average, the southeastern and southwestern parts of the country exhibit high summer recycling ratios. contrasting with the low values in the northeastern and northwestern United States. The Colorado region also presents high recycling ratios. Dominant modes of spatiotemporal variability in recycling are identified using EOF analysis. The first mode captures strong recycling ratios over the western United States during the summers of 1986, 1992, and 1998. The second mode captures anomalous high recycling ratios during 1988 and 1989 over the central part of the country, and anomalous low ratios during 1980 and 1993.