A Dust Prediction System with TOMS Initialization

Abstract

A dust prediction system, developed earlier at the University of Athens within the framework of the Mediterranean Dust Experiment (MEDUSE) project, was enhanced at Tel Aviv University to support the Israeli?American Mediterranean Israeli Dust Experiment (MEIDEX) project. These enhancements include development of a dust initialization approach using Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI) data and improved specification of the dust sources. The skill of the model against the TOMS AI measurements was tested during two periods in March and June 2000 using four different scores. It is shown that the TOMS-based initialization has a significant positive impact on all the scores. For instance, the average distance between the predicted and TOMS-observed dust plumes drops from 350?485 to less than 200 km. Verification of model forecasts against surface dust measurements in Tel Aviv shows correlations of up to 0.69 based on 27 predictions, for both 24 and 48 h. One example of a narrow dust plume over Israel, successfully forecast with the current system, is presented. This event occurred in midsummer (4 July) when dust bursts are rare over the Eastern Mediterranean.