NASA SPoRT prepares for the Geostationary Lightning Mapper

NASA's Short-term Prediction Research and Transition (SPoRT) program is a contributing partner with the GOES-R Proving Ground (PG) helping prepare forecasters understand and utilize the unique products to come in the GOES-R era. This particular presentation focuses on SPoRT helping prepare the end user community for the Geostationary Lightning Mapper (GLM). This preparation is a collaborative effort with SPoRT's National Weather Service partners, the lightning Algorithm Working Group (AWG), and the Proving Ground as part of the Hazardous Weather Testbed's Spring Program in Norman, Oklahoma. SPoRT continues to use its effective paradigm of matching capabilities to forecast problems through collaborations with our end users and developing effective evaluations. Furthermore, SPoRT continues to develop software plug-ins so that these products will be available to forecasters in their own decision support system, AWIPS and eventually AWIPS II.

In 2009, the SPoRT program developed the pseudo geostationary lightning mapper (PGLM) flash extent product to serve as a demonstration for what forecasters may see once the GLM is launched. Developed from total lightning data from four ground-based networks (North Alabama, Kennedy Space Center, Oklahoma, and Washington D.C.), this product was used operationally during the 2010 Spring Program. This presentation will address the feedback received during the Spring Program and SPoRT's continuing efforts to evaluate this product to help improve the transition of the AWG's official GLM proxy. In addition, this will discuss a new lightning trend product that can be applied to the PGLM and future AWG proxy.

In addition to real-time GLM demonstration products, the Spring Program received the lightning threat algorithm for use in the National Severe Storm Laboratory's WRF model. This algorithm was used operationally during the 2010 Spring Program and uses graupel flux and vertically integrated ice to forecast where and when lightning will occur. The ultimate goal of this project will be to incorporate GLM data as an input data set in numerical modeling once GOES-R is launched.