Forecasting Zonda Wind Occurrence with Vertical Sounding Data

Abstract

Zonda wind is a typical downslope windstorm over the eastern slopes of the Central Andes in Argentina, which produces extremely warm and dry conditions and creates substantial socioeconomic impacts. The aim of this work is to obtain an index for predicting the probability of Zonda wind occurrence. The Principal Component Analysis (PCA) is applied to the vertical sounding data on both sides of the Andes. Through the use of a binary logistic regression, the PCA is applied to discriminate those soundings associated with Zonda wind events from those that are not, and a probabilistic forecasting tool for Zonda occurrence is obtained. This index is able to discriminate between Zonda and non-Zonda events with an effectiveness close to 91%. The best model consists of four variables from each side of the Andes. From an event-based statistical perspective, the probability of detection of the mixed model is above 97% with a probability of false detection lower than 7% and a missing ratio below 1%. From an alarm-based perspective, models exhibit false alarm rate below 7%, a missing alarm ratio lower than 1.5% and higher than 93% for the correct alarm ratio. The zonal component of the wind on both sides of the Andes and the windward temperature are the key variables in class discrimination. The vertical structure of Zonda wind includes two wind maximums and an unstable lapse rate at midlevels on the lee side and a wind maximum at 700 hPa accompanied by a relatively stable layer near the mountain top.

焚风是阿根廷中安第斯山脉东坡典型的下坡风暴, 可导致极其温暖干燥的气象条件, 并产生巨大的社会经济影响, 通过主成分分析法( análisis de componentes principales, PCA),析法辨识与焚风相关的探空数据, 得到焚风的概率预报模型。该指数能够区分焚风和非焚风事件, 有效率接近91%。最佳模型由安第斯山脉两侧的四个变量组成。从已发生的焚风事件的统计结果看, 混合模型的探测效率在97%以上, 空探测率低于7%, 漏探测率低于1%, 漏报率低于1,5%, 预报准确率高于93%时的垂直结构特征为背风坡中层的两个风速峰值区和不稳定温度递减率以及迎风坡700 hPa处的风速峰值和接近山顶处的相对稳定层。