Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1175/JAS-D-18-0368.1 |
Explaining Scales and Statistics of Tropical Precipitation Clusters with a Stochastic Model | |
Ahmed, Fiaz; Neelin, J. David | |
2019-10-01 | |
发表期刊 | JOURNAL OF THE ATMOSPHERIC SCIENCES |
ISSN | 0022-4928 |
EISSN | 1520-0469 |
出版年 | 2019 |
卷号 | 76期号:10页码:3063-3087 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Precipitation clusters are contiguous raining regions characterized by a precipitation threshold, size, and the total rainfall contained within-termed the cluster power. Tropical observations suggest that the probability distributions of both cluster size and power contain a power-law range (with slope similar to -1.5) bounded by a large-event "cutoff." Events with values beyond the cutoff signify large, powerful clusters and represent extreme events. A two-dimensional stochastic model is introduced to reproduce the observed cluster distributions, including the slope and the cutoff. The model is equipped with coupled moisture and weak temperature gradient (WTG) energy equations, empirically motivated precipitation parameterization, temporally persistent noise, and lateral mixing processes, all of which collectively shape the model cluster distributions. Moisture-radiative feedbacks aid clustering, but excessively strong feedbacks push the model into a self-aggregating regime. The power-law slope is stable in a realistic parameter range. The cutoff is sensitive to multiple model parameters including the stochastic forcing amplitude, the threshold moisture value that triggers precipitation, and the lateral mixing efficiency. Among the candidates for simple analogs of precipitation clustering, percolation models are ruled out as unsatisfactory, but the stochastic branching process proves useful in formulating a neighbor probability metric. This metric measures the average number of nearest neighbors that a precipitating entity can spawn per time interval and captures the cutoff parameter sensitivity for both cluster size and power. The results here suggest that the clustering tendency and the horizontal scale limiting large tropical precipitating systems arise from aggregate effects of multiple moist processes, which are encapsulated in the neighbor probability metric. |
英文关键词 | Atmosphere Tropics Deep convection Mesoscale systems Extreme events Primitive equations model |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000485871400001 |
WOS关键词 | MESOSCALE CONVECTIVE SYSTEMS ; GROSS MOIST STABILITY ; SELF-AGGREGATION ; STRATIFORM PRECIPITATION ; ADJUSTMENT SCHEME ; CIRCULATION MODEL ; DEEP CONVECTION ; COLD POOLS ; CUMULUS ; VARIABILITY |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/187463 |
专题 | 地球科学 |
作者单位 | Univ Calif Los Angeles, Dept Atmospher & Ocean Sci, Los Angeles, CA 90024 USA |
推荐引用方式 GB/T 7714 | Ahmed, Fiaz,Neelin, J. David. Explaining Scales and Statistics of Tropical Precipitation Clusters with a Stochastic Model[J]. JOURNAL OF THE ATMOSPHERIC SCIENCES,2019,76(10):3063-3087. |
APA | Ahmed, Fiaz,&Neelin, J. David.(2019).Explaining Scales and Statistics of Tropical Precipitation Clusters with a Stochastic Model.JOURNAL OF THE ATMOSPHERIC SCIENCES,76(10),3063-3087. |
MLA | Ahmed, Fiaz,et al."Explaining Scales and Statistics of Tropical Precipitation Clusters with a Stochastic Model".JOURNAL OF THE ATMOSPHERIC SCIENCES 76.10(2019):3063-3087. |
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