3D.7 Origins of the Caribbean Rainfall Bimodal Behavior

Friday, 13 November 2009: 10:00 AM
Mois├ęs E. Angeles, University of Puerto Rico, New York, NY; and J. E. Gonzalez, N. D. Ramirez-Beltran, C. A. Tepley, and D. E. Comarazamy

The annual precipitation pattern in the Caribbean basin shows a distinct bimodal behavior, where the first mode is called the Early Rainfall Season (ERS, April-July), and the second mode the Late Rainfall Season (LRS, August-November). The brief, relatively dry, period in July is usually referred to as the mid-summer drought (MSD). It has been hypothesized that the migration through the Caribbean basin of the Intertropical Convergence Zone (ITCZ) and increases in aerosols due to the passing of Saharan Dust across the Caribbean in the summer months may result in the observed precipitation pattern. This paper focuses on determining the origins of the Caribbean MSD. Multiple regression analysis was carried-out to determine if the ITCZ, the North Atlantic Oscillation (NAO) index, the Vertical Wind Shear (VWS), and different aerosol particle (AP) concentrations transported from northern Africa correlate with the Caribbean MSD. It is shown that the ITCZ and SST are weakly correlated with the Caribbean precipitation variability; however, the VWS and aerosol particles revealed an important contribution to rainfall during the summer months. Numerical experiments were then performed to quantify the influence of different VWS scenarios and different AP concentrations on the Caribbean precipitation bimodal behavior. The numerical approach uses the Regional Atmospheric Modeling System (RAMS) coupled with a new cloud microphysics module that allows discrimination between small and giant particles, as well as Cloud Concentration Nuclei (CCN) and Giant CCN (GCCN) activation. These numerical experiments support the statistical result that the VWS and the AP influence the rainfall production and pattern during the MSD. Results indicate that cloud microphysics play an important role in producing the observed climatological bimodal pattern, while variations in large-scale atmospheric dynamics (like the VWS) help explain variations in the strength and pattern of the bimodal events and behavior.
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