Evaluation of WRF-Chem-RTFDDA dust forecasts over the MENA region using in-situ and remote-sensing observations

We employed the combined WRF-Chem-RTFDDA model to forecast dust storms in Middle East and North Africa (MENA). WRF-Chem simulates emission, transport, mixing, chemical transformation of trace gases aerosols simultaneously with meteorology. RTFDDA continuously assimilates both conventional nonconventional meteorological observations provides improved initial conditions for analyses forecasts. was run at a horizontal resolution 9 km using only option without inclusion anthropogenic reactions. The synoptic events were characterized by cold front low level an upper-level low-pressure system over Western Mediterranean. continuous assimilation mode, assimilating only, launching 48-h free forecasts (FF) every 6 h. Two starts (CSs) data emissions initiation performed during study period. NCEP/GFS global provided lateral boundary conditions. No used initialization no assimilated. analyzed skill reproducing vertical distributions comparing FF Meteosat SEVIRI images, MODIS AOD retrievals, CALIPSO extinction coefficients CAMS aerosols-reanalysis calculations. as function lead time period from CSs. RMSE, bias correlation between modeled measured also examined. reproduced main features studied reasonably well. distance CSs played more significant role determining dust-forecast than free-forecast time. Since external information model, spin-up critical extent well once spun-up. False alarms rates range 0.03 0.26, many below 0.15, indicating satisfactory performance warning system. This shows feasibility minimal input MENA region.