1. Conference Call February 12, 2012
Recent project news
Climatology paper outline
Modeling results
Next steps

2. A New Approach to Improved Inland Wind Forecasts for Landfalling Tropical Cyclones
Bryce Tyner and Anantha Aiyyer
Department of Marine, Earth, and Atmospheric Sciences
North Carolina State University
Introduction
Wind Speed Climatology
Irene (2011)
Ongoing/Future Work
Accurate prediction of the tropical cyclone wind field after landfall is one of the greatest challenges for operational forecasters.
Many past studies have examined the evolution of the tropical cyclone wind field after landfall (Wong et al. 2008; Bhowmik et al. 2005; and Kaplan and DeMaria 2001).
The results of these studies have not been routinely incorporated into the techniques used by NWS forecasters in operational prediction.
Numerous past studies have shown surface winds can be
best described by a Weibull distribution. The two-parameter
Weibull distribution is defined as:
where:
η = scale parameter,
β = shape parameter (or slope),
Radar Reflectivity (dBZ)
The highest gust factors (>1.4) were observed in areas where the sustained wind speeds were much weaker. This occurred in areas further inland as well as after the storm passage in many areas. Weaker wind speeds were also consistent with higher variability in the gust factors.
In areas with strongest sustained wind speeds, gust factor values were lower, near 1.2, and variability in the gust factors was also lower.
Many coastal sites and areas near the mountains did not observe a significant increase in average values and variability in gust factors after the storm passed.
Simulated base radar reflectivity (left) and KMHX WSR-88D
radar reflectivity (right) near the time of landfall for Irene (2011)
Purpose
18/3 km nested run initialized 48 hours prior to landfall
accurately forecasted the location of landfall as well as
storm strength (model central SLP=950 hPa, best track
SLP=952 hPa)
The time of landfall was delayed in the model by approx.
6 hours. Sensitivity studies are being conducted to
produce a simulation with a more accurate landfall time.
Once a realistic simulation is produced, WRF-LES
simulations will be conducted in order to examine the
turbulence profiles for various locations in the model
domain.
The overall goal of this study is to improve the wind
speed and wind gust forecasts associated with tropical
cyclones.
The primary focuses for improvement are in the land
reduction factors and gust factors used in the
TCMWindTool.
Data and Methods
Proposed Final Product to be Used by NWS Forecasters:
Hourly wind speed observations for Maryland, Virginia, North Carolina, and South Carolina were obtained from the North Carolina State Climate Office CRONOS database for the months June-November These wind speed observations were used to develop a climatology of sustained wind speeds in the region.
Hourly wind speed observations were compared to surface wind analyses from the Hurricane Research Division’s H*Wind project.
Sustained speed forecasts of recent tropical cyclones affecting the region were compared to both H*Wind forecasts and surface wind speed observations. Ernesto (2006), Gabrielle (2007), Hanna (2008), and Irene (2011) were landfalling tropical cyclones in the region with forecast data available. Cristobal (2008) and Earl (2010) were also examined, although they did not make landfall in the region.
Land decay factors were analyzed for all tropical cyclones affecting the region (not shown). Only the ten closest stations to the center of the tropical cyclone were used in this analysis.
Output Grid: Land Reduction Factors
Ouput Grid: Gust Factors
Grid File: Land Use/Terrain Data
Basic Storm Information
Angle of storm approach
Size of Storm
Strength of Storm
Storm propagation speed
NHC Best Track Data
Grid File: Thermodynamic/Environmental Conditions
ET Transition?
Boundary layer conditions
Static Stability
Cold Air Damming?
(a)
(b)
References
Areas of highest elevation and locations near the coastline have the largest shape and scale parameters, indicative of highest mean wind speed values as well as largest spread in wind speed distributions.
There is a distinct minimum in mean sustained wind speeds as well as the spread in the wind speed distributions for much of Virginia and west-central North Carolina.
Topographic influences lead to significantly different mean wind speeds and distributions for areas in the same local region.
Bhowmik, S.K.R., S.D. Kotal, and S.R. Kalsi, 2005: An Empirical Model for Predicting the Decay of Tropical Cyclone Wind Speed after Landfall over the Indian Region. J. Appl. Meteor., 44,
Kaplan, J., and M. DeMaria, 2001: A note on the decay of tropical cyclone winds after landfall in the New England area. J. Appl. Meteor., 40,
Wong, M.L.M., J.C.L. Chan, and W. Zhou, 2008: A Simple Empirical Model for Estimating the Intensity Change of Tropical Cyclones after Landfall along the South China Coast. J. Appl. Meteor. Climatol.,47,
(c)
(d)
NDFD – HWIND Analysis at (a) August, (b) 1330
27 August, (c) August, and (d) August (UTC)
Boundaries of WFOs appear in analysis
Raleigh WFO appears to have smallest difference between forecast and HWind analysis (where forecasters used strongest land reduction factors of 33%)
Strongest over prediction of wind speeds present in coastal regions
Acknowledgements
This work is funded by NOAA Grant NA10NWS 2

3. The highest gust factors (>1
The highest gust factors (>1.4) were observed in areas where the sustained wind speeds were much weaker. This occurred in areas further inland as well as after the storm passage in many areas. Weaker wind speeds were also consistent with higher variability in the gust factors.
In areas with strongest sustained wind speeds, gust factor values were lower, near 1.2, and variability in the gust factors was also lower.
Many coastal sites and areas near the mountains did not observe a significant increase in average values and variability in gust factors after the storm passed.

4. Climatology Paper
Proposed Title: “A Climatological Look at Sustained Wind Speeds and Gusts of Landfalling Tropical Cyclones in the Mid-Atlantic, ”
Proposed Journal: Weather and Forecasting
Submission Date Goal: May 2012

5. Climatology Paper Outline
Introduction
Define Weibull distribution
Define gust factor
Literature survey on land decay papers and gust factors for the region
Methods/Data
NHC Best Track Data
HWind Surface Wind Analyses
Surface observations—1 min data for all ASOS stations
NC CRONOS data base (for land decay)
NDFD forecasts

6. Climatology Paper Outline
Results
Weibull distributions of wind speeds and gusts during times of landfalling TCs vs. climatology
Land decay for 10 (?) closest points to storm from CRONOS database with high order polynomial fit
NDFD verification for storms (using both CRONOS and HWind Analyses)
Spatial gust factor analysis for storms using ASOS data
Frequency of missing observations from ASOS data

7. Model Runs for Irene (2011)
As of 2/21/12

8. Runs Conducted Thus Far
All runs:
Initialized 8/25/1200 UTC
Terminated 8/29/12 UTC
Approximately 48 hours prior to best track landfall

9. Runs Conducted Thus Far
18 / 6 km nested run
Kain Fritsch convective scheme
ERA_Interim data
Model SST used

10. Runs Conducted Thus Far
9 / 3 km nested run
K.F. convective scheme (outer domain)
ERA_Interim data
Model SST used

11. Runs Conducted Thus Far
18 / 6 km nested run
K.F. convective scheme (outer domain)
GFS analysis data
Model SST used

12. Runs Conducted Thus Far
18 / 6 km nested run
Kain Fritsch convective scheme
ERA_Interim data
RTG SST data from 8/26/00 UTC used

13. Plots to Compare Simulated vs. radar mosaic
Best track SLP at time of landfall
10 m winds vs. HWIND at time of landfall
Landfall location
Track after landfall

14. Landfall Verification: Run 1
SIMULATED
LANDFALL TIME: 08/27/1800 UTC
LANDFALL CENTRAL SLP: 951 hPa
BEST TRACK
LANDFALL TIME: 08/27/1200 UTC
LANDFALL CENTRAL SLP: 952 hPa

15. Landfall Verification: Run 2
LANDFALL LOCATION ABOUT SAME AS IN RUN #1, BUT SLIGHTLY
SLOWER AND STRONGER
SIMULATED
LANDFALL TIME: 08/27/1900 UTC
LANDFALL CENTRAL SLP: 950 hPa
BEST TRACK
LANDFALL TIME: 08/27/1200 UTC
LANDFALL CENTRAL SLP: 952 hPa

16. Landfall Verification: Run 3
LANDFALL LOCATION ABOUT SAME AS IN RUN #1, BUT SLIGHTLY
QUICKER AND WEAKER
SIMULATED
LANDFALL TIME: 08/27/1600 UTC
LANDFALL CENTRAL SLP: 952 hPa
BEST TRACK
LANDFALL TIME: 08/27/1200 UTC
LANDFALL CENTRAL SLP: 952 hPa

17. Landfall Verification: Run 4
LANDFALL LOCATION ABOUT SAME AS OTHER RUNS, BUT MUCH WEAKER AND SLOWER
SIMULATED
LANDFALL TIME: 08/27/1500 UTC
LANDFALL CENTRAL SLP: 961 hPa
BEST TRACK
LANDFALL TIME: 08/27/1200 UTC
LANDFALL CENTRAL SLP: 952 hPa

18. HWIND ANALYSIS, 8/27/1330 UTC
Model Run 4, 8/27/1300 UTC

19. Landfall Verification: Run 4
GENERAL STORM STRUCTURE IS CORRECTLY SIMULATED (BANDS AHEAD OF STORM, WESTWARD EXTENT OF PRECIPITATION, EASTERN SIDE WINDS)

20. NEXT RUN RTG SST data updated every 6 hours
Once we have a run we are “happy with”, we can begin WRF-LES simulations

21. Current/Future Work Work on writing climatology paper
Get WRF run for Irene that is “reasonable”
Reading on hurricane WRF LES simulations (Zhu et al. 2008, Chen et al. 2010, etc)
Develop first WRF LES run for Irene, consult with Dr. Sukanta Basu

22. Output Grid: Land Reduction Factors
Ouput Grid: Gust Factors
Grid File: Land Use/Terrain Data
Basic Storm Information
Strength of Storm
Size of Storm
Angle of storm approach
Storm propagation speed
NHC Best Track Data
Grid File: Thermodynamic/Environmental Conditions
Static Stability
Boundary layer conditions
ET Transition?
Cold Air Damming?