Convective Cold Pools: Properties and Sea-Surface Temperature Dependence

Monday, 18 April 2016: 9:00 AM
Ponce de Leon C (The Condado Hilton Plaza)
Aryeh J. Drager, Colorado State University, Fort Collins, CO; and S. C. van den Heever

Convective cold pools have an important role in tropical, oceanic regions. However, this role can be difficult to characterize due to its multifaceted, sometimes contradictory nature. For instance, convective cold pools can reduce the near-surface moist static energy (MSE) by transporting low-MSE air from aloft down to the surface. Meanwhile, convective cold pools also enhance near-surface moist static energy by enhancing surface heat fluxes by virtue of their associated gust fronts. Convective cold pools also modulate the organization of individual storm cells into larger systems through a combination of these thermodynamic processes and dynamical forcing mechanisms.

The role of cold pools, in turn, is modulated by the properties of the cold pools themselves. How often do they occur? And when they do occur, how deep are they? How cold are they, and how quickly do they expand? This study uses an idealized modeling framework to examine the extent to which these properties vary as a function of sea-surface temperature (SST).

The Regional Atmospheric Modeling System (RAMS) is used to perform several large-domain (3000 km × 200 km × 25 km), cloud-resolving (Δx = Δy = 1 km; 75 vertical levels with Δz increasing from 70 m near the surface to 1 km aloft) simulations. The simulations are highly idealized, with no diurnal cycle, no Coriolis acceleration, and periodic lateral boundaries. Each simulation has an oceanic surface with a fixed, uniform SST typical of tropical ocean regions; the simulations differ in the particular value of SST that is prescribed.

Each simulation is run for many weeks and allowed to approach a state of radiative-convective equilibrium (RCE). Once a state of approximate RCE has been reached, the simulations continue to run for several days, and a cold-pool tracking algorithm is deployed in order to identify and analyze the convective cold pools that develop during this time period. By virtue of large area of the domain and the long duration of the analysis period, many cold pools are identified within each simulation. The statistical properties of the cold pool populations within the respective simulations are then compared, and the physical mechanisms leading to these results are investigated.

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