资源环境科技发展态势分析平台

The Levant region is dominated in the summer by the persistent Persian Trough. Thus, the current synoptic classifications lack the ability to reflect inter-diurnal variations in the local weather conditions. This study aims to overcome this weakness and has two objectives: to develop operative prediction equations for the local weather conditions based on synoptic-scale data, and to propose a new synoptic classification, based on the environment to climate approach, to better reflect the local climatic stress. Prediction equations were derived for the national heat-stress (NHS) and the height of the persistent marine inversion (inversion base, IB). The potential predictors are comprised of atmospheric variables found correlated with these weather attributes together with indices representing synoptic to large-scale features. The indices were derived through a composite maps analysis of days with extreme values of these attributes. The Climatic Stress Index (CSI) developed is a combination of the heat-stress and the inversion height, for which a separate prediction equation was derived. The spectrum of the calculated daily CSI values was divided into three parts of equal size, used as the basis of the new synoptic types, defined as: comfort', medium', and discomfort'. The attribution of a certain day to one of these types is determined according to its calculated CSI. Our proposed classification was found to better delineate the NHS and the height of the IB in Israel. The downscaling schemes and the new synoptic classification are applicable for both operative weather prediction and climate prediction. The latter enables the assessment of future trends in the climatic stress, in general, and heat-stress, in particular. This is due to being compatible with the output of operative weather prediction models as well as for the format of the disseminated output of climate models.