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Enhancing Inland Wind Forecasts: A Comprehensive Analysis of Wind Data Comparisons

This project update focuses on refining inland wind forecasts by comparing HWind simulations with ASOS wind data. Recent verifications highlight the impact of storms like Irene (2011) on NDFD forecasts, revealing advantages and limitations of utilizing HWind analyses. Data assimilation from various sources provides gridded information but comes with challenges such as shortages and biases. The study aims to address discrepancies in forecasting cycles and aims to refine gust factor calculations, paving the way for more accurate wind predictions and climatology reports.

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Enhancing Inland Wind Forecasts: A Comprehensive Analysis of Wind Data Comparisons

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  1. CIMMSE Improving Inland Wind ForecastsOctober 2011 Project Update

  2. Project Focuses This Period • HWind vs. ASOS Station Verification • NDFD Verification: Irene (2011) • ASOS wind data outages?

  3. HWind/Observation Station Comparison • Motivation: last conference call, it was suggested to use HWind analyses for NDFD forecast verification • Advantages of HWind analyses: • Data assimilation from multiple sources (METAR, satellite, buoys, etc.) • Gridded data available (much easier to work with) • Disadvantages of HWind analyses: • Gridded data only available since 2000 • Different data sources for each storm, based on availability (inter-storm comparison may have bias) • Analysis stops shortly after landfall for most storms • Grid moves with storm (area of interest sometimes outside of HWind domain • Three hour resolution

  4. HWind/Observation Station Comparison • NDFD wind data available since 2005 • Storms affecting region since 2005: - Ernesto (2006) -Gabrielle (2007) • Hanna (2008) -Irene (2011) • Cristobal (2008) -Earl (2010) • Can interpolate NDFD/HWind analysis to a common grid and compare to station data

  5. HWind Analysis: Irene (2011) 8/27/2011 0130 UTC: Wind Speeds (m/s)

  6. HWind - NDFD • Interpolated HWind and NDFD data at each time to common grid • Used latest forecast cycle when making comparisons (eliminate as much as possible track/NHC guidance bias)

  7. HWind – NDFD: Irene (2011)

  8. HWind – NDFD: Irene (2011)

  9. HWind – NDFD (Irene 2011)

  10. HWind – NDFD (Irene 2011)

  11. HWind – NDFD (Irene 2011)

  12. HWind – NDFD (Irene 2011)

  13. HWind – NDFD: Irene (2011) • Boundaries of WFOs appear in analysis • Raleigh WFO appears to have smallest different between forecast and HWind analysis, at least when comparing to most recent forecast cycles • Strongest overprediction of wind speeds present in coastal regions • Suggests the 33% reduction used by Raleigh forecasters worked well

  14. HWind – NDFD: Various Forecast Cycles • Several collaborators have suggested verifying different forecast cycles (inter-forecaster bias) • Examined forecasts issued: • 8/25 at 22 UTC (Thursday evening) • 8/26 at 10 UTC (Friday morning) • 8/26 at 22 UTC (Friday evening)

  15. HWind – NDFD: Various Forecast Cycles Forecasted Issued 8/25 at 22 UTC

  16. HWind – NDFD: Various Forecast CyclesForecasted Issued 8/26 at 10 UTC

  17. HWind – NDFD: Various Forecast Cycles Forecasted Issued 8/26 at 22 UTC

  18. Different Forecast Cycles • Some offices differ rather significantly between forecast cycles versus other offices • Provides further evidence for the lack of scientific processes going into the forecast • Future work will better quantify these differences, relative to the differences in track/intensity forecasts

  19. ASOS: Missing Data Effect? • Several collaborators have suggested observation stations can go down during storms • We need to incorporate this influence in developing the climatology • Compared wind data while storm was influencing the region to four days prior

  20. ASOS: Missing Data Effect?

  21. ASOS: Missing Data Effect? • Up to 45% less data when storm is present • Most reduction for: Able (1952), Barbara (1953), Connie (1955), Hazel (1954), and Ione (1955) • Temporal element appears to be present • Other noteworthy reductions: Fran (1996): 11% Floyd (1999): 13% Bertha (1996): 20% Isabel (2003): 23% Hanna (2008): 20%

  22. Goal for Final Product • It has become clear that a more systematic approach to the land reduction factor and gust factor be developed • Adjustment factor to account for TCM wind inflation (gross) • Distance from storm center • Local topography • Strength of system, speed of propagation • Mesoscale environmental adjustment (thermodynamic factors, etc.)

  23. Upcoming goals • Gust factors derived for select stations (similar to analysis of Larry Brown) • Quantitative results for comparing HWind and surface wind obs. • Begin modeling studies (with assistance of Dr. Sukanta Basu) • Other NDFD verification: compare 4 quadrant data to NDFD vs. HWind (added value from forecasters) • Final climatology report (gust factors, Weibull distributions, NDFD verification, Obs. vs. HWind analysis)—to be posted on blog for comments

  24. Key areas for discussion • Suggestions for improvement in the TCM tool for GFE developers (led by JB?) • Other ways to verify NDFD forecasts • Irene (2011) forecaster observations/notes • Other suggestions for final product?

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