The interannual variability of pre-storm environments of intense convective systems in West Africa: Application to future climate scenarios

Well-organized convective systems with intense convection represent the 10th percentile of convective system intensity in West Africa. Despite their small numbers, they are a critical part of the West African hydrological cycle, delivering the majority of seasonal rainfall, and are responsible for extreme events throughout the region, both dry (haboobs) and wet (flooding).

Despite their importance, intense convective systems represent infrequent, sub-grid phenomena in the model configurations used in developing future climate scenarios. We develop a technique to predict the potential impact of intense convective systems that focuses on their dynamical and thermodynamical pre-storm environments rather than the occurrence of the intense convective system phenomena directly. We derive probability density functions for particular combinations of selected hydrometeorological state variables from several datasets, including surface observations and model output at several different resolutions (0.5 to 2.5 deg), for 1998-2007. We show how these probability density functions can be used to generate a seasonal estimate of intense convective system activity.

This study extends earlier work on the environments of intense convective systems in West Africa by Nicholls and Mohr (2009) and the interannual variability of convective system intensity by Mohr et al. (2009). Nicholls and Mohr (2009) studied intense convective systems from 2003 and identified a series of hydrometeorological state variables (e.g., low-level shear, surface equivalent potential temperature) that best describe the pre-storm environments of these systems. Our investigation uses their convective case selection criteria and recommended state variables. In Mohr et al. (2009), probability of occurrence of intense convective systems remained stable throughout their decadal study, although the number of intense convective systems varied from year to year.

Here, we investigate how the probability of favorable pre-storm conditions varies such that the number of intense convective systems varies but the probability of occurrence does not. Because we focus on environmental conditions, we can utilize a typical model strength, the dynamical core, to assess the potential for intense convective systems in future climates.