The Impact of Entrainment on the Likelihood of Convective Initiation: Dilute CAPE as a Forecasting Tool

Forecasting whether deep, moist convection (DMC) will succeed or fail to initiate is a challenge for even experienced forecasters, since a myriad of factors must be examined. One of the fundamental requirements for DMC initiation is the existence of instability. Convective available potential energy (CAPE) is a well-studied way to quantify atmospheric instability and buoyancy, however simple parcel theory underlies nearly all CAPE calculations. Parcel theory is a highly idealized method for computing convective parcels, thus it can be quickly computed on modern computers. A downfall to parcel theory is the exclusion of entrainment, which ultimately yields a parcel that is typically excessively buoyant, for a given atmospheric profile. This excessive buoyancy will lead to deceptively high values of CAPE, as well as convective inhibition (CIN) too close to zero, and can ultimately lead forecasters astray when forecasting DMC initiation. On the other hand, cloud-resolving models (CRMs) more accurately calculate convective parcel attributes. Unfortunately, these models are typically too computationally intensive to be run as an operational, real-time forecasting tool. Even if ample computing resources are obtained, CRMs will only provide accurate parcel attributes if DMC initiates properly in the model. A middle ground approach, combining both the simplicity of parcel theory, and the benefits of including environmental entrainment into the convective parcel, is dilute CAPE. Dilute CAPE builds off the concept of mixed-layer CAPE (MLCAPE), but it continues to mix convective parcels, with the environment, well above the lowest layers of the atmosphere.

In this paper, dilute CAPE is examined in the context of operational forecasting applicability, and thus is calculated building off of the widely utilized SHARPpy Python Program (similar to the Storm Prediction Center’s NSHARP program). The implementation of entrainment in SHARPpy aims to calculate entrainment in the simplest, most efficient way, while continuing to be consistent with past research in the literature. Furthermore, dilute CAPE is employed to help inform the results of previous research on convective initiation, including situations where typical requirements for DMC were met, yet DMC failed to initiate. Ultimately, dilute CAPE can provide a more accurate representation of rising parcels during convective initiation, and may prove valuable as an additional forecasting diagnostic tool in the hands of meteorologists.