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NEXRAD Dual Polarization Data for FAA Aviation Products David J. Smalley, Michael F. Donovan, Betty J. Bennett, Kenta T. Hood, Elaine Griffin, Mark S. Veillette, and Earle R. Williams, Massachusetts Institute of Technology Lincoln Laboratory MIT Lincoln Laboratory Tech Transfer Algorithm Challenges Addressed Targeted Future Benefits to Aviation Weather Algorithm Products Validation and Verification Radar Calibration and Data Quality ● Federal Aviation Administration (FAA) Next-Generation Radar (NEXRAD) Program Office has been funding Lincoln Laboratory’s NEXRAD Algorithm Enhancements Program since 2001 ● Eight algorithms developed with seven fielded operational products ● 35+ algorithm enhancements as NEXRAD evolves ● Develop and test new techniques from in situ observations to further icing detection by radar ● Validate/verify new techniques against past or future in situ measurements ● Data quality remains paramount for automated FAA algorithms (no human-in-the-loop) ● Stable, calibrated dual pol data throughout the network will benefit the FAA algorithms Aviation Weather Hazard Detection Enabled by NEXRAD This work is sponsored by the Federal Aviation Administration (FAA) under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the United States Government. Convective Weather Relate in situ particle observations to radar data Wind Shear 2011 2001 2003 2005 2007 2009 2013 2015 2017 High Resolution Vertically Integrated Liquid Data Quality Assurance (DQA) High Resolution Enhanced Echo Tops Machine Intelligent Gust Front Algorithm DQA Edited Reflectivity 1990s Doppler 2010s Hydrometeors Dual Pol Icing Hazard Levels Dual Pol Hail Hazard Levels Microburst Detection Partial Beam Blockage Mitigation Dual Pol DQA Chaff, Sea Clutter Enabled through dual polarized capabilities Icing Hail First-ever sphere calibration of dual pol NEXRAD Use dual pol data to identify non-weather contamination Relate in situ particle observations to radar data Sizing Rely on mPING and CoCoRaHS reports Validation First-ever in situ validation of operational dual pol NEXRAD Icing Hazard Use dual pol data and improved hydrometeor classification responding to particle type to estimate icing hazard Hail Hazard Use dual pol data and improved hydrometeor classification to provide area coverage of hail severity and altitude Reveal mixed phase subclasses Expanded Icing Hazard Detection Data Quality Use dual pol data and improved hydrometeor classification to improve data quality of aviation weather products Max. hail size in column Top hail altitude in column Storm Intensity through Hail Chaff classification from dual pol needed Augment Methods/ID Chaff

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Page 1: NEXRAD Dual Polarization Data for FAA Aviation Products · NEXRAD Dual Polarization Data for FAA Aviation Products David J. Smalley, Michael F. Donovan, Betty J. Bennett, Kenta T

MIT Lincoln Laboratory Tech Transfer Algorithm Challenges Addressed Targeted Future Benefits to Aviation Weather Algorithm ProductsValidation and Verification

Radar Calibration and Data Quality

● Federal Aviation Administration (FAA) Next-Generation Radar (NEXRAD) Program Office has been funding Lincoln Laboratory’s NEXRAD Algorithm Enhancements Program since 2001

● Eight algorithms developed with seven fielded operational products

● 35+ algorithm enhancements as NEXRAD evolves

● Develop and test new techniques from in situ observations to further icing detection by radar

● Validate/verify new techniques against past or future in situ measurements

● Data quality remains paramount for automated FAA algorithms (no human-in-the-loop)

● Stable, calibrated dual pol data throughout the network will benefit the FAA algorithmsAviation Weather Hazard Detection Enabled by NEXRAD

This work is sponsored by the Federal Aviation Administration (FAA) under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the United States Government.

Convective Weather

Relate in situ particle observations to radar data

Wind Shear

20112001 2003 2005 2007 2009 2013 2015 2017

HighResolution Vertically

Integrated Liquid

Data Quality

Assurance (DQA)

HighResolution Enhanced Echo Tops

Machine Intelligent Gust Front Algorithm

DQA Edited Reflectivity

1990sDoppler