A New Approach for Examining Water Vapor and Deep Convection Interactions in the Tropics

Abstract:

The complex interactions/feedbacks between water vapor fields and deep atmospheric convection remains one of the outstanding problems in Tropical Meteorology. The lack of high spatial/temporal resolution, all-weather observations in the Tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. GNSS (Global Navigation Satellite System) meteorology, which provides all-weather, high frequency (5 minutes), precipitable water vapor, can help. From 3.5 years of GNSS meteorological data in Manaus, (Central Amazonia), 320 convective events were analyzed. Results reveal two characteristic time scales of water vapor convergence; an 8 h time scale of weak convergence and 4 h timescale of intense water vapor convergence associated with the shallow-to-deep convection transition. The 4 h shallow-to-deep transition time scale is particularly robust, regardless of convective intensity, seasonality, or nocturnal versus daytime convection. We also present a summary of the Amazon Dense GNSS Meteorological Network experiment, the first ever in the Tropics, was created with the explicit aim of examining the wv/deep convection relationships at the mesoscale. This innovative, international experiment, consisted of two mesoscale (100km x100km) networks: (1) a one-year (April 2011 to April 2012) campaign (20 GNSS meteorological sites) in and around Manaus , and (2) a 6 week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, this latter in collaboration with the CHUVA GPM in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor: for sea breeze convection in Belem and, for assessing the influence seasonal and topographic influences for Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor spatial and temporal evolution in high resolution models.