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Summary of GOES-R Activities at CIMSS/ASPB and Recommendations for the Future

Summary of GOES-R Activities at CIMSS/ASPB and Recommendations for the Future Steven Ackerman, Tom Achtor GOES-R Algorithm Working Group GOES-R Risk Reduction GOES-R Proving Ground High Impact Weather. GOES-R Algorithm Working Group (AWG) 19 Tasks with direct responsibility for

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Summary of GOES-R Activities at CIMSS/ASPB and Recommendations for the Future

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  1. Summary of GOES-R Activities at CIMSS/ASPB and Recommendations for the Future Steven Ackerman, Tom Achtor • GOES-R Algorithm Working Group • GOES-R Risk Reduction • GOES-R Proving Ground • High Impact Weather

  2. GOES-R Algorithm Working Group (AWG) • 19 Tasks with direct responsibility for • 22 baseline algorithms developed by CIMSS/ASPB science teams • 11 option 2 algorithms developed by CIMSS/ASPB science teams • 5 hemispheric and regional simulated data sets created leveraging supercomputer time (Proxy) • Instrument performance and waiver requests through GRAFIIR • Visualization and analysis through McIDAS-V

  3. GOES-R Risk Reduction • 12 tasks exploring ideas, testing innovative approaches and demonstrating utility of GOES-R measurements • 1 EPO task • 2 travel grants • Ability to explore and innovate has enabled new approaches to be developed and tested (FAA, NASA, NextGen, DOD) • Volcanic Cloud Alert System • Nowcasting system development • Convective Storm Forecast Improvement • Fusion / Synergy of multiple observations

  4. GOES-R Proving Ground • Test and validate technologies and products to enable transition to operational use • Work in collaboration with AWG and R3 teams to evaluate baseline and option 2 products • Provide user assessments and feedback to product developers • Expand partnerships with GOES-R data and product users • Emphasis on NWS and NCEP Centers

  5. GOES-R High Impact Weather • Focus on combined use of hyperspectral sounder data from POES with imaging products from ABI • Research conducted on scales from mesoscale storms to tropical systems to mid latitude cyclones • Focus on nowcasting and short range forecast improvement • Excellent example of fusion/synergy approach to using multiple sources of information in product development

  6. GOES-R Activities: Recommendations for the Future • GOES-R research and development must be well supported now and beyond launch • Science tests – post launch and ongoing calibration/validation studies are crucial • Build upon the early GOES GIMPAP project as a model for future development • Option 2 (SO2, turbulence, cryospheric, convection, icing, fog, etc) cutting edge GOES-R satellite based decision support needs adequate resources to continue development for innovative integration into operations prior to launch • Post launch research and development will continue to exploit the new measurements with improved products

  7. GOES-R Activities: Recommendations for the Future • Continue Proving Ground to support end-to-end research to operations • Continue to leverage NESDIS CIs’ research infrastructure and data processing capabilities to further the success of the GOES-R program • Validation will be a key post launch component • Expand on education and training, from the professional level to EPO

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