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Enhancing Hurricane Analysis and Forecasting Using HIWRAP Data: Methods, Problems, and Solutions

This study focuses on the use of HIWRAP data for hurricane analysis and forecasting. Researchers examine the set-up and methods used, highlighting challenges encountered and providing solutions. Results show improved storm position and intensity forecasts with the assimilation of HIWRAP data, compared to non-data assimilation (NODA) methods. The study discusses the importance of incorporating various data sources like VWP, dropsondes, and VR to enhance the accuracy of forecasts. The deterministic forecasts based on HIWRAP data demonstrate promising results, indicating the usefulness of this data in tropical cyclone analysis. Ongoing experiments and future work aim to further improve hurricane forecasts by integrating additional data from Global Hawk-based sources.

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Enhancing Hurricane Analysis and Forecasting Using HIWRAP Data: Methods, Problems, and Solutions

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Presentation Transcript

  1. Updates on the used of HIWRAP data for hurricane analysis and forecasting Jason Sippel, Gerry Heymsfield, Lin Tian, and Scott Braun- NASAs GSFC YonghuiWeng and Fuqing Zhang – Penn State University

  2. Methods Experiment setup • Looking at Karl (2010) – only hurricane that HIWRAP data is available for • WRF-EnKF from Zhang et al. (2009) with 30 members • Similar setup as Sippel et al. (2013) OSSEs 3-km nest Model domains Karl’s track

  3. Methods Problems and solutions • Significant issues for GRIP data • Outer beam unavailable for Karl • Unfolding not possible for some legs • Heavy QC required for Vr • Solutions • Try assimilating HIWRAP VWPs instead (avoids DA issues with w, and less heavy QC required) • Assimilate position & intensity (P/I) in addition to HIWRAP data

  4. Methods Assimilation details • Assimilating position beforehand helps with bad first guess • Assimilate position first, then position + VWP, then P/I + VWP Karl assimilation schematic

  5. Results Results: EnKF storm position Track evolution from EnKF analyses • Both analyses better than NODA • Lower error and spread with VWP than PIONLY

  6. Results Results: EnKF max intensity • Both experiments improve upon NODA • PI-ONLY distribution looks good, but analysis is weak • VWP shows improvement and spins up faster with less spread Maximum intensity evolution from EnKF analyses

  7. Results Results: Wind radii Wind radii evolution from various EnKF analyses • PIONLY produces a storm that is much too large, especially for smaller radii • Analysis with VWP data is in much better agreement with best-track and spins up faster

  8. Results Results: Vertical structure Azimuthal mean wind speeds at last cycle • PIONLY analysis produces a shallower, broad vortex that looks unrealistic for a major hurricane • VWP analysis is much more realistic with a tall, compact inner core • VWP experiment structure agrees better with obs

  9. Results Results: Adding dropsondes Surface winds and isobars from various EnKF analyses • VWP clearly needed to capture compact inner core • Addition of dropsondes strengthens outer wind field, closer to best track

  10. Results Results: Brief VAD/Vr comparison Surface wind speeds and pressure at last cycle • Vr-assimilating analysis has trouble capturing compact/intense core • Limited OSSE testing suggests analyses using inner beam slower to spin up

  11. Results Results: Deterministic forecasts Comparison of best track with NODA and EnKF-initialized intensity forecasts • Both PIONLY and VWP-based forecasts better than NODA, but VWP-based forecast best due to a better initial structure Comparison of best track with NODA and EnKF-initialized track forecasts

  12. Summary + Future Work • HIWRAP data appears to be useful for EnKF analyses of TCs • Despite difficulties with early HIWRAP data, EnKF analyses with HIWRAP VWP data produce accurate estimates of maximum intensity, location, and wind radii • Vr assimilation experiments are ongoing & looking decent • Future work will examine the impacts of additional Global-Hawk-based data, including dropsondes, surface wind speeds from HIRAD and water vapor and temperature retrievals from S-HIS

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