The use of the North Alabama Lightning Mapping Array in the real-time operational warning environment during the March 2nd, 2012 severe weather outbreak in northern Alabama.
White, Kristopher ; Stano, Geoffrey T; Carcione, Brian

The North Alabama Lightning Mapping Array (NALMA) is a very high frequency (VHF) detection network consisting of 11 sensors spread across north central Alabama and two sensors located in the Atlanta, Georgia region. The primary advantage of this network is that it detects total lightning, or the combination of both cloud-to-ground and intra-cloud lightning, instead of cloud-to-ground lightning alone. This helps to build a complete picture of storm evolution and development, and can serve as a proxy for storm updraft strength, particularly since intra-cloud lightning makes up the majority of all lightning in a typical thunderstorm. While the NALMA data do not directly indicate severe weather, they can indirectly indicate when a storm is strengthening (weakening) due to increases (decreases) in updraft strength, as the updraft is responsible for charging mechanisms within the storm. Data from the NALMA have been ported into the Advanced Weather Interactive Processing System (AWIPS) for National Weather Service (NWS) offices in Huntsville, AL, Nashville, TN, Morristown, TN, and Birmingham, AL, in near real-time. Operationally, these data have been used at the Huntsville NWS office since early 2003 through a collaborative effort with NASA s Short-term Prediction Research and Transition Center. The total lightning data can increase a forecaster s confidence to either issue or not issue a warning since the NALMA data provide additional insight into the storm s evolution between radar volume scans.

This presentation will discuss the use of these data in the operational forecast environment at the Huntsville NWS office on the morning of March 2, 2012, as severe thunderstorms affected the region. The use of the NALMA data led to an increase in the lead time for the initial thunderstorm warning that morning, and served as an important decision support tool, indicating that a storm was likely to undergo rapid strengthening, and that a warning was necessary.