Synoptic Classes as a Predictor of Hourly Surface Wind Regimes: The Case of the Central and Southern Israeli Coastal Plains

被引:16
作者
Berkovic, Sigalit [1 ]
机构
[1] Israel Inst Biol Res, Dept Math, Ness Ziona, Israel
关键词
SELF-ORGANIZING MAPS; SEA LAND-BREEZE; FLOW PATTERNS; AIR-QUALITY; MESOSCALE; VARIABILITY; CLASSIFICATION; IDENTIFICATION; CLIMATOLOGY; CIRCULATION;
D O I
10.1175/JAMC-D-16-0093.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This work considers whether it is possible to use semiobjective synoptic classes as a year-round predictor of hourly surface winds in Israel. Previous literature has quantitatively characterized the hourly surface flow during the summer under a single synoptic group-the Persian trough-but no quantitative verification has been made for the other seasons. This study undertook a statistical characterization of the surface winds under frequent synoptic classes. The calculated statistical parameters were averages, standard deviations, steadiness, and statistical significance, determined using measurements from 12 weather stations of the Israel Meteorological Service. High steadiness of the surface wind field was found for a significant number of hours. The verification of the characterization at 0000 UTC by two calculations, the first according to the class defined at the previous 1200 UTC and the second according to the next 1200 UTC, showed similar results. Therefore, the synoptic class can be used as a predictor of hourly surface winds during the entire year. These statistical results provide an automatic prediction of the hourly surface wind average and standard deviation according to synoptic class. They may aid in risk assessment or statistical downscaling of seasonal or monthly winds. Such applications can be employed in other parts of Israel. Typical values for hours at which steady flow was obtained are as follows: steadiness > 0.65, wind direction standard deviation, < 60 degrees, wind speed standard deviation of 1-2 ms(-1), and sector direction widths of 50 degrees-150 degrees, within 70% statistical significance.
引用
收藏
页码:1533 / 1547
页数:15
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