__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 a_{0 }= 13.0, a_{1 }=
-4.59 x 10^{-2} m^{-1} s, a_{2 }= -1.16 K^{-1}
km, a_{3 }= -6.17 x 10^{-4} J^{-1} kg and a_{4 }=
-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*.