The Convection, Aerosol, and Synoptic-Effects in the Tropics (CAST) Experiment: Building an Understanding of Multiscale Impacts on Caribbean Weather via Field Campaigns
Hosannah, N. ; González, J. ; Rodriguez-Solis, R. ; Parsiani, H. ; Moshary, F. ; Aponte, L. ; Armstrong, R. ; Harmsen, E. ; Ramamurthy, P. ; Angeles, M. ; León, L. ; Ramírez, N. ; Niyogi, D. ; Bornstein, B.
Année de publication
Modulated by global-, continental-, regional-, and local-scale processes, convective precipitation in coastal tropical regions is paramount in maintaining the ecological balance and socioeconomic health within them. The western coast of the Caribbean island of Puerto Rico is ideal for observing local convective dynamics as interactions between complex processes involving orography, surface heating, land cover, and sea-breeze–trade wind convergence influence different rainfall climatologies across the island. A multiseason observational effort entitled the Convection, Aerosol, and Synoptic-Effects in the Tropics (CAST) experiment was undertaken using Puerto Rico as a test case, to improve the understanding of island-scale processes and their effects on precipitation. Puerto Rico has a wide network of observational instruments, including ground weather stations, soil moisture sensors, a Next Generation Weather Radar (NEXRAD), twice-daily radiosonde launches, and Aerosol Robotic Network (AERONET) sunphotometers. To achieve the goals of CAST, researchers from multiple institutions supplemented existing observational networks with additional radiosonde launches, three high-resolution radars, continuous ceilometer monitoring, and air sampling in western Puerto Rico to monitor convective precipitation events. Observations during three CAST measurement phases (22 June–10 July 2015, 6–22 February 2016, and 24 April–7 May 2016) captured the most extreme drought in recent history (summer 2015), in addition to anomalously wet early rainfall and dry-season (2016) phases. This short article presents an overview of CAST along with selected campaign data.