Integrated GOES-R GLM/ABI Approaches for the Detection and Forecasting of Convectively Induced Turbulence

The Federal Aviation Administration estimates that thunderstorm related flight delays are responsible for the loss of approximately 2 billion dollars annually to the commercial aviation industry. Along with icing and lightning hazards, turbulence contributes to the substantial risk to aviation from thunderstorms. In addition to monetary losses resulting from delays or rerouting, there is also a significant risk to passenger safety from unexpected turbulence events. A multi-sensor approach (utilizing lightning, satellite, radar, and turbulence metrics) will be combined with knowledge of suitable conditions for the production of gravity waves to detect and potentially forecast Convectively Induced Turbulence (CIT). This exploratory study is in support of the Geostationary Operational Environmental Satellite series-R risk reduction (GOES-R3) project.

Tracking significant radar inferred convective features using the Warning Decision Support System-Integrated Information (WDSS-II) software will allow for Lagrangian, cell based comparisons between multiple remote sensing platforms. Cloud top cooling and overshooting top (OT) detections from GOES-14 will be used as a proxy for the GOES-R Advanced Baseline Imager (ABI). Data from Lightning Mapping Arrays (LMA) and the Earth Networks Total Lightning Network (ENTLN) will serve as a proxy for the GOES-R Geostationary Lightning Mapper (GLM) instrument's total lightning (in-cloud and cloud-to-ground) capability. In cases where the presence of lightning is confirmed within a convective cell, the flash rate and most importantly the trends in flash rate will be assessed for value in the detection of hazards to aircraft. Ongoing research at the University of Alabama in Huntsville has shown that increases in the flash rate, termed ‘lightning jumps', are well correlated with increases in updraft intensity and the subsequent onset of severe weather. This study will extend the prior results by evaluating whether a lightning jump can provide any useful information toward the forecasting of CIT. Total lightning trends and satellite derived products will be combined with (aircraft independent) National Center for Atmospheric Research (NCAR) Eddy Dissipation Rate (EDR) data to test if the correlation between remotely sensed intensity metrics and the updraft will allow detection and potentially the forecasting of CIT. In the absence of EDR reports, the co-evolving relationship between radar, lightning jump, cloud top cooling, and OT occurrence will be documented carefully as few studies have integrated these multi-sensor observations into a suitable conceptual model for the detection of high impact weather in a variety of convective modes.