Global bimodal precipitation seasonality: A systematic overview

被引:30
|
作者
Knoben, Wouter J. M. [1 ]
Woods, Ross A. [1 ]
Freer, Jim E. [2 ]
机构
[1] Univ Bristol, Dept Civil Engn, Woodland Rd 93-95, Bristol BS8 1US, Avon, England
[2] Univ Bristol, Sch Geog Sci, Bristol, Avon, England
基金
英国工程与自然科学研究理事会;
关键词
analytical framework; bimodal seasonality; global climate; rainfall; GRIDDED PRECIPITATION; RAINFALL SEASONALITY; SURFACE TEMPERATURE; SIMPLEX-METHOD; SOUTH-AMERICA; CLIMATE; VARIABILITY; PATTERNS; SERIES;
D O I
10.1002/joc.5786
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Global precipitation patterns lead to differences in seasonal distributions of rainfall between locations in the form of alternating dry and wet seasons. Many locations experience a single wet and dry season per year, but some studies report the occurrence of two wet and dry seasons per year. This bimodal rainfall pattern is commonly associated with locations within the tropics but is reported outside the tropics as well. However, this information is fragmented, and studies of bimodality are mainly restricted to monthly rainfall totals. Here, we use a gridded global data set and simple harmonic analysis to provide a systematic overview of global bimodal rainfall and rain-day frequency. We find good agreement between the various regional studies concerning bimodal precipitation and our global overview, showing that bimodal rainfall occurs on approximately 7% of the global land surface. In the tropics, regions of bimodal rainfall totals (P) and regions of bimodal rain-day frequency (N) tend to overlap due to the presence of dry seasons that have zero precipitation. Outside the tropics, P and N are more independent, which leads to complex within-year patterns of precipitation intensity. A secondary outcome of our results is an improved low-dimensional global parameterization of monthly rainfall regimes. Our results provide the first gridded global overview of bimodal rainfall patterns and show the usefulness of simple mathematical approaches for detecting patterns in large data sets.
引用
收藏
页码:558 / 567
页数:10
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