May 26 - July 31
Impact of Earth Networks Lightning Data and Dangerous Thunderstorm Alerts on Forecasters' Warning Decision and Confidence
Rashida Francis, Kristin Calhoun, and Daphne LaDue
What is already known:
- Increases in total lightning activity may signal an increase in severe weather potential.
- NOAA is considering incorporating lightning data and Earth Networks Inc. (ENI) decision-assistance tools — lightning cell tracking and thunderstorm alerts into forecasters' workstations.
- Whether total lightning data plus ENI decision-assistance products provide support for correct and confident warnings is unknown.
What this study adds:
- Total lightning data encourages issuance of warnings and also forecasters confidence in those warnings.
- Forecasters confidence is higher when provided with total lightning data and/or ENI guidance products.
- Some of these warnings were correct, but in some cases, forecasters were misled by the lightning data.
Abstract:
Increases in total lightning activity indicate an increase in updraft strength, and may, therefore, indicate that severe weather is about to occur. Earth Networks Incorporated (ENI) has multiple networks, including Earth Networks Total Lightning Detection (ENTLN), designed to detect total lightning. They also create decision-assistance products such as lightning cell tracking and Dangerous Thunderstorm Alerts to show enhanced severe weather conditions. A controlled experiment of 18 National Weather Service forecasters was run in the NOAA Hazardous Weather Testbed during 2014 to better understand the influence of these products on forecasters. For each simulation, the forecasters were separated into three different groups and provided access with different levels of data: 1) radar data only; 2) radar data plus total lightning data; or 3) radar data, total lightning and ENI guidance products (lightning cell, motion history and projection and DTAs). Forecasters worked through six cases with varying severe weather conditions. Two out of the six cases were reviewed in detail here: Fort Worth-Dallas, TX (FWD) and Birmingham, AL (BMX). Results from each of these cases suggest lightning data and ENI decision-assistance products could have either a positive or negative effect on forecasters' warning decisions and confidence. For FWD, there was a clear and evident increase in confidence in their warnings with the use of lighting data; most of these warnings were verified. However, during the BMX case, forecasters may have issued more warnings due to lightning data and ENI decision-assistance products. Their confidence fluctuated, and no warnings verified. There were no severe reports received, and the marginal environmental conditions.