MCS Maintenance Probability (MMP)

The MMP is derived from an analysis of 269 observed proximity soundings taken ahead of persistent quasi-linear MCSs. Using discriminant analysis on hundreds of sounding parameters, it is found that a combination of the very deep vertical wind shear, mid-level lapse rates, most unstable CAPE, mean low-to-upper-level wind speed provide the best discrimination between the mature and dissipating MCSs. The figure below depicts the surprising ability of the very deep shear (defined as the maximum shear vector magnitude obtained using any level between 0-1 km as the lower bound and any level between 6-10 km as the upper bound) and the mid-level (3-8 km) lapse rates to discriminate between these two groups.

The four parameters mentioned above are then used as input predictors to logistic regression to derive a conditional probability equation for a strong and mature MCS:

where the regression coefficients are a₀ = 13.0, a₁ = -4.59 x 10^-2 m^-1 s, a₂ = -1.16 K^-1 km, a₃ = -6.17 x 10^-4 J^-1 kg and a₄ = -0.17 m^-1 s and the MMP is zeroed out if the MUCAPE < 100 J kg^-1, regardless of the values of the other predictors.

We envision the best real-time application of the MMP would use observational data or short-term model output at a time close to convective initiation to give guidance on the regions most likely to sustain strong MCSs that do develop. This could directly benefit Day 1 Severe Weather Outlooks, Mesoscale Discussions, and the issuance of Severe Weather Watches at the Storm Prediction Center (SPC), and short-term forecasts issued by local forecast offices.

For more information, see Coniglio et al (2007) in Weather and Forecasting.