9.4 Satellite Data Applications for Oceanic Aviation Weather

Wednesday, 17 August 2016: 2:15 PM
Madison Ballroom CD (Monona Terrace Community and Convention Center)
Haig Iskenderian, MIT Lincoln Laboratory, Lexington, MA; and M. S. Veillette, C. J. Mattioli, P. M. Lamey, E. P. Hassey, J. R. Mecikalski, G. T. Stano, and R. Bass

Air traffic controllers and air traffic managers require accurate depictions of thunderstorms so they can safely and efficiently route aircraft around the hazards these storms contain (turbulence, hail, lightning). Over the US and just offshore, the land-based NEXRAD network provides detailed radar mosaics in near-real-time for air traffic management. Over the data-sparse oceans beyond NEXRAD range, satellite data represents an important source of weather information. However differences in view angle, data latency, and sensor design between radar and satellite makes it challenging for air traffic managers to interpret and use satellite imagery in their decisions.

This shortfall in aviation weather information over the ocean is motivating the Federal Aviation Administration and the Massachusetts Institute of Technology Lincoln Laboratory to develop the Offshore Precipitation Capability (OPC). The OPC uses a machine learning model to fuse data from the five channels on the current Geostationary Operational Environmental Satellite (GOES) with global lightning data from the ground-based Earth Network's Total Lightning Network and several fields from NOAA's Rapid Refresh (RAP) 13 km numerical weather prediction model to create the radar-like precipitation mosaics over the ocean. This presentation will describe the OPC capability and present examples of the oceanic radar-like precipitation mosaics for use in aviation.

Satellite data is also critical for OPC validation over the data-sparse ocean. Data from the NASA Global Precipitation Measurement Mission (GPM) Dual-frequency Precipitation Radar and the Microwave Imager (GMI) is currently being used in OPC validation. In preparation for the GOES-R era, we are also exploring channels from Himawari-8, cloud properties from GOES-R Algorithm Working Group Cloud Height Algorithm (ACHA), and lightning proxy data from NASA's Pseudo-Geostationary Lightning Mapper (PGLM) in preparation for GLM. This presentation will describe the use of these data in the development and validation of the OPC capability and the potential use of new generation satellites in the capability.

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