Atmospheric Dynamics of Sub-Tropical Dust Storms
AuthorPokharel, Ashok Kumar
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Meso-α/β scale observational and meso-β/γ scale numerical model analyses were performed to study the atmospheric dynamics responsible for generating Harmattan, Saudi Arabian, and Bodélé Depression dust storms. For each dust storm case study, MERRA reanalysis datasets, WRF simulated very high resolution datasets, MODIS/Aqua and Terra images, EUMETSAT images, NAAPS aerosol modelling plots, CALIPSO images, surface observations, and rawinsonde soundings were analyzed. The analysis of each dust storm carried out separately and an in-depth comparison of the events shows some similarities among the three case studies: (1) the presence of a well-organized baroclinic synoptic scale system, (2) small scale dust emission events which occurred prior to the formation of the primary large-scale dust storms, (3) cross mountain flows which produced a strong leeside inversion layer prior to the large scale dust storm, (4) the presence of thermal wind imbalance in the exit region of the mid-tropospheric jet streak in the lee of the mountains shortly after the time of the inversion formation, (5) major dust storm formation was accompanied by large magnitude ageostrophic isallobaric low-level winds as part of the meso-β scale adjustment process, (6) substantial low-level turbulence kinetic energy (TKE), (7) formation in the lee of nearby mountains, and (8) the emission of the dust occurred initially in narrow meso-β scale zones parallel to the mountains, and later reached the meso-α scale when suspended dust was transported away from the mountains. In addition to this there were additional meso-β scale and meso-γ scale adjustment processes resulting in Kelvin waves in the Harmattan and the Bodélé Depression cases and the thermally-forced MPS circulation in all of these three cases. The Kelvin wave preceded a cold pool accompanying the air behind the large scale cold front instrumental in the major dust storm. The Kelvin wave organized the major dust storm in a narrow zone parallel to the mountains before it expanded upscale. The thermally-forced meos-γ scale adjustment processes, which occurred in the canyons/small valleys, resulted in the numerous dust streaks leading to the entry of the dust into the atmosphere due to the presence of significant vertical motion and the TKE generation. This indicates that there were meso-β to meso-γ scale adjustment processes at the lower levels after the imbalance within the exit region of the upper level jet streaks and these processes were responsible for causing the large scale dust storms. Most notably, the sub-tropical jet streak caused the dust storm nearer to the equatorial region after its interaction with the thermally perturbed air mass on the lee of the Tibesti Mountains in the Bodélé case study, which is different than the two other cases where the polar jet streaks played this same role at higher latitudes. This represents an original finding. Additionally, a climatological analysis of 15 years (1997-2011) of dust events over the NASA Dryden Flight Research Center (DFRC) in the desert of Southern California was performed to evaluate how the extratropical systems influenced the cause of dust storms over this region. This study indicates that dust events were associated with the development of a deep convective boundary layer, turbulent kinetic energy ≥3 J/kg, a lapse rate between dry adiabatic and moist adiabatic, wind speed above the frictional threshold wind speed necessary to ablate dust from the surface (≥7.3m/s), above the surface the presence of a cold trough, and strong cyclonic jet. These processes are similar in many ways to the dynamics in the other subtropical case studies. This also indicated that the annual mean number of dust events, their mean duration, and the unit duration per number of event were positively correlated with each of the visibility ranges, when binned for <11.2km, <8km, <4.8km, <1.6km, and <1km. The percentage of the dust events by season show that most of the dust events occurred in autumn (44.7%), followed by spring (38.3%) and equally in summer and winter with these seasons each accounting for 8.5% of events.