This research concentrated on platforms that are available to the common forecaster in West Texas, including atmospheric soundings taken at 1200 and 0000 UTC in Midland and Amarillo, TX, and surface observations taken from the Texas Tech University West Texas Mesonet. With these data a multitude of variables (that could be useful in the forecasting of convective initiation along the dryline) were calculated for qualified dryline cases that occurred in the spring months of 2004 and 2005. Once all of the variables were calculated, their significance was tested using a stepwise logistic regression process, and a prediction equation was generated for the probability that a dryline in West Texas will initiate deep moist convection.
Significant variables from the analysis included the 1200 UTC 500 hPa height difference between Amarillo and Midland, TX, the 700 to 500 hPa and 850 to 500 hPa lapse rates, and the surface dewpoint depression. Case studies utilizing this probability equation showed that the predictive equation is best suited for determining which drylines will be convectively active, but is less conducive for determining what points along the dryline will have deep moist convection initiate. This paper will examine how the probability equation was generated and then show its usefulness through a validation study.