Big Science, Big Data, and Big Computing for Advanced Hurricane Prediction
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The document discusses advancements in hurricane monitoring and prediction, highlighting significant improvements in track forecast accuracy over the last 25 years, while intensity forecast accuracy has been relatively stagnant until recent interventions. It details the contributions of the Hurricane Forecast Improvement Program (HFIP), high-resolution observations, and advanced data assimilation techniques in enhancing prediction capabilities. Furthermore, it emphasizes the need for continued investment in big data and collaborative research to further improve hurricane forecasting technologies.
Big Science, Big Data, and Big Computing for Advanced Hurricane Prediction
- 1. Big Science, Big Data and Big Computing for Advanced Hurricane Monitoring & Prediction Fuqing Zhang Director, Center for Advanced Data Assimilation and Predictability Techniques Professor, Department of Meteorology and Atmospheric Science Pennsylvania State University Research sponsored by NSF, ONR, NOAA and NASA FROM RESEARCH TO INDUSTRY: How Earth system science enables private sector innovation
- 2. Track forecasts have improved drastically over past 25 years: a 3- day forecast today is as accurate as a 1-day forecast was in 1989. Intensity forecast accuracy has remained generally stagnant over that same period, except for the last few years, thanks to the Hurricane Forecast Improvement Program (HFIP) led by NOAA. National Hurricane Center Official TC Forecast Errors
- 3. NSF HPC Computing At Texas Advanced Computing Center System Name: Ranger Operating System: Linux Number of Cores: 62,976 Total Memory: 123TB Peak Performance: 579.4TFlops Total Disk: 1.73PB (shared) HFIP Allocation : 30M SUs (July 1, 2008- 31 March 2009) Goals of NOAA’s Hurricane Forecast Improvement Project (HFIP) • Reduce average track and intensity forecast error by half for days 1 through 5 • Significantly increase the probability of detection for rapid intensity change and decrease false alarm ratio • Extend lead time for hurricane forecasts out to Day 7 My team’s HFIP effort co-funded by ONR, NSF and NASA
- 4. How to make better input to the hurricane models? High-resolution observations from Hurricane Hunters and UAVs: Provide crucial airborne inflight measurements, dropsondes, Doppler Radar Winds, … 50° ~ 3 km Data assimilation: The process of generating initial conditions for weather prediction models through combining the background model estimate, and all applicable up-to-date observations. NOAA P3 NASA Global Hawk
- 5. PSU WRF-EnKF Hurricane Analysis & Prediction System with advanced assimilation of airborne Doppler Radar Vr Evaluated for all 100+ P3 TDR missions during 2008-2012 The PSU system uses the NCAR’s WRF model; TDR Methodology now adopted by NOAA . (F. Zhang and Y. Weng 2015, Bulletin of the American Meteorological Society) PSU WRF-EnKF Hurricane Intensity error (knots)
- 7. ext Frontier: Geostationary Satellite GOES-R from NASA to NOAA
- 8. Assimilating All-sky GOES-R Radiances: Harvey (2017) Independent observations vs. EnKF analysis of channel 10 PSU WRF-EnKF assimilates channel 8 radiances every 1 hour Research Funding Provided by ONR, NASA, NOAA and NSF
- 9. Independent Observations vs. EnKF analysis Assimilating All-sky Satellite Radiances: Harvey (2017)
- 10. PSU WRF-EnKF Harvey Forecast with GOES-R Assimilation in comparison with WRF(NoDA), operational HWRF & best track Research Supported by ONR, NASA, NOAA and NSF
- 11. Research Supported by ONR, NASA, NOAA and NSF FV3 Prediction of Hurricane Harvey with a 3-km nested domain PSU WRF-EnKF GOES-R assimilation used for FV3 initial vortex FV3 3km-nest simulated radar reflectivity (left) vs. observations (right) at Landfall KCRPKCRP KHGXKHGXKEWX KEWX KGRKKGRK
- 12. Research Supported by ONR, NASA, NOAA and NSF FV3 Prediction of Hurricane Harvey with a 3-km nested domain PSU WRF-EnKF GOES-R assimilation used for FV3 initial vortex FV3-forecasted (left) vs. observed event total rainfall (right) with 6-day lead time KCRP KHGX KEWX KGRK KLCH KPOE KSHV KLIX KCRP KHGX KEWX KGRK KLCH KPOE KSHV KLIX Point maximum of 40+ inches Point maximum of 50+ inches
- 13. Promises of US’s Next-Generation Global Prediction System: FV3 Comparison with EC model on 1-year-mean 10-day-forecast 500mb anomaly correlations Forecast lead time (h) FV3 model with EC model initial condition (IC) comparable to EC day 1-7 but better thereafter; FV3 model with current GFS initial condition is considerably worse than either run with EC IC; US forecast is inferior due mostly to poorer IC, inferior data assimilation ingesting less data Courtesy of Linus Magnusson at ECMWF and SJ Lin at NOAA/GFDL AnomalyCorrelationCoefficient(ACC)
- 14. From Research to Industry Concluding Remarks: Invest on big data hurricane science • There are great potentials and needs for improving hurricane prediction through collaborative research and sustained federal investment on data, science and personnel • Future hurricane prediction advances may come from the following areas: • Observations: advanced observing systems such as those from airborne dropsondes, Doppler radar and weather satellites • Model: cutting-edge higher-resolution weather prediction models with more accurate numerics and physics • Data assimilation: comprehensive algorithms and methodologies that that can more effectively ingest existing and future observations into state-of-science models • Computing: high-performance computing facilities that can perform advanced analysis and forecasting in a timely manner.
- 15. + 3 kts initial intensity error Shear only Initial V + shear Track Initial + track Initial inner core moisture error Predictability and Error Sources of Hurricane Intensity Forecast (Emanuel and Zhang 2016, Journal of Atmospheric Sciences)
- 16. With realtime EnKF assimilation of airborne Doppler winds (Zhang and Weng, 2015 BAMS) What “big data” means for hurricane research: ensembles
- 17. Research Supported by ONR, NASA, NOAA and NSF FV3 Prediction of Hurricane Harvey with a 3-km nested domain PSU WRF-EnKF GOES-R assimilation used for FV3 initial vortex in comparison with FV3(GFS), operational GFS, EC & best track Ongoing PSU collaboration with NOAA/GFDL