The Potential of an Index for Mesoscale Activity – Based on High Resolution INCA-Analysis Data

This abstract is dedicated to late Prof. Lev Gutman whom I met in Israel. I had several personal impressions after his arrival to my Dept of Geophysics at Tel Aviv University and became senior member in 1978. The present research is strongly related to the major topic Prof. Gutman was a world leader in.

The representation of sub-grid Meso-Scale and Micro-Scale processes is a largely invested and investigated topic in meteorological and climatological research over the past decades, due to the potential of improving the accuracy of Numerical Weather Prediction (NWP) and climate models. This is expected to yield a better understanding of these processes that are not resolved correctly in current models’ simulations and of developing new methods to better represent these small processes in the models. In this work, I used the INCA analysis surface wind data, in order to calculate an Index of Meso-Scale activity, first proposed by Alpert et al. (JCAM, 1985) (referred in this work as – Meso-Index). The Meso-Index is defined as the ratio between the diurnal and interdiuranl variabilities of the wind speed, over a specific location, and therefore representing the dominance of Meso-Scale processes in shaping the diurnal wind cycle. The Meso-Index maps, revealed very distinguished and persistent spatial distribution patterns in the Meso-Index values during the summer months. The highest Meso-Index values were produced over lowland regions and valleys (with values higher than 8 at some locations during the summer months), while the lowest values (ranging between 1.5-2.5) were produced over mountainous regions. Relatively low values were also produced over locations next to the shoreline and over densely populated coastal urban areas (Tel-Aviv metropolitan), due to the effects of urban roughness and the urban heat/dry island (UHI/UDI). The Meso-Index fields were compared to average-night fields of wind direction, temperature and humidity fields. Over areas with a large density of wind measuring stations and over areas with complex terrain, the Meso-Index maps were able to represent the dominance and properties of the regional Meso-Scale processes correctly, during the summer.