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«THESIS EVALUATION OF CONVECTIVE WIND FORECASTING METHODS DURING HIGH WIND EVENTS by Christopher J Kuhlman March 2006 Thesis Advisor: Wendell A. Nuss ...»

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NAVAL

POSTGRADUATE

SCHOOL

MONTEREY, CALIFORNIA

THESIS

EVALUATION OF CONVECTIVE WIND FORECASTING

METHODS DURING HIGH WIND EVENTS

by

Christopher J Kuhlman

March 2006

Thesis Advisor: Wendell A. Nuss Second Reader: Carlyle H. Wash Approved for public release; distribution is unlimited.

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1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED March 2006 Master’s Thesis

4. TITLE AND SUBTITLE: Evaluation of Convective Wind Forecasting 5. FUNDING NUMBERS Methods During High Wind Events

6. AUTHOR(S) Christopher J. Kuhlman

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION

REPORT NUMBER

Naval Postgraduate School Monterey, CA 93943-5000

9. SPONSORING /MONITORING AGENCY NAME(S) AND 10. SPONSORING/MONITORING

ADDRESS(ES) AGENCY REPORT NUMBER

N/A

11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government.

12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for public release; distribution is unlimited

13.

Abstract

(maximum 200 words) This study investigates convective wind gust forecasting methods for reported gusts in the Midwest, Central, and Northeast United States from June and July 2005. Three methods are examined using MM5 model data; the T1 and T2 methods and the WINDEX method. The model-derived wind gusts determined by each method are then compared to wind reports from the Storm Prediction Center’s severe storm reports archive and reports from observing stations. Model-derived wind gusts are then compared to the observed wind gusts for varying times of day and observed wind gust ranges. Wind gust frequency plots are examined for each wind method to determine accuracy and to characterize any patterns. The T1 method was the most accurate overall for this study, but was shown to be less sensitive to varying atmospheric conditions. The T2 method was the least accurate of the three methods during all situations. The WINDEX method performed well in most situations and was nearly as accurate as the T1 method, while WINDEX also proved to be the most sensitive of the three to varying mesoscale conditions.

–  –  –

This study investigates convective wind gust forecasting methods for reported gusts in the Midwest, Central, and Northeast United States from June and July 2005. Three methods are examined using MM5 model data; the T1 and T2 methods and the WINDEX method. The model-derived wind gusts determined by each method are then compared to wind reports from the Storm Prediction Center’s severe storm reports archive and reports from observing stations. Model-derived wind gusts are then compared to the observed wind gusts for varying times of day and observed wind gust ranges. Wind gust frequency plots are examined for each wind method to determine accuracy and to characterize any patterns. The T1 method was the most accurate overall for this study, but was shown to be less sensitive to varying atmospheric conditions.

The T2 method was the least accurate of the three methods during all situations.

The WINDEX method performed well in most situations and was nearly as accurate as the T1 method, while WINDEX also proved to be the most sensitive of the three to varying mesoscale conditions.

–  –  –

I. INTRODUCTION

A. THESIS OBJECTIVES AND MILITARY SIGNIFICANCE

B. CONVECTIVELY DRIVEN HIGH WINDS

1. Climatology of Damaging Wind Events

2. Understanding the Downdraft

3. Types of Downdrafts

II. TECHNIQUE

A. OVERVIEW OF CONVECTIVE WIND FORECASTING METHODS.. 13

1. T1 Gust Method

2. T2 Gust Method

3. WINDEX Gust Method

III. DATA AND METHODS

A. DATA USED

1. Storm Reports

2. Model Data

B. DATA PROCESSING

1. Method Calculations





2. Upper Air Soundings

3. Visual Program

IV. DATA ANALYSIS

A. OVERALL RESULTS

1. T1 Gust Method

2. T2 Gust Method

3. WINDEX Gust Method

B. DIURNAL EFFECTS

1. T1 Gust Method

2. T2 Gust Method

3. WINDEX Gust Method

C. REPORTS OF UNKNOWN WIND SPEED

D. WIND METHOD COMPARISON

E. DISCUSSION OF RESULTS

V. CONCLUSIONS AND RECOMMENDATIONS

A. CONCLUSIONS

B. RECOMMENDATIONS

LIST OF REFERENCES

INITIAL DISTRIBUTION LIST

–  –  –

Figure 1.1.

Area of responsibility (AOR) for the 15th Operational Weather Squadron (OWS). The 15th OWS is responsible for 190 different military units including 13 active duty locations within its AOR............. 1 Figure 1.2.

Monthly distribution of occurrences of thunderstorms related wind damaged (light gray) gusts between 25.8 and 33.5 m s-1 (gray) and gusts greater than 33.5 m s-1 (black) (After Kelly et al. 1985).............. 4 Figure 1.3. Hourly distribution in NST of occurrences of thunderstorm related wind damage (stippled) gusts between 25.8 and 33.5 m s-1 (upper left to lower right hatching) and gusts greater than 33.5 m s-1 (cross hatching) (From Kelly et al. 1985)

Figure 1.4.

Dashed black lines are isopleths of one. Values greater than 11 and 17 are shaded gray and black, respectively (After Kelly et al.

1985).

Figure 1.5.

Schematic cross section through the gust front of a thunderstorm (After Wakimoto 2001)

Figure 1.6.

Schematic view of the supercell thunderstorm at the surface. The gray shading encompasses the radar echo. The gust front structure is depicted using a solid line and frontal symbols. Surface position of the updraft is hatched while the forward-flank downdraft (FFD) and rear-flank downdraft (RFD) are crosshatched (From Wakimoto 2001).

Figure 1.7.

Conceptual model of a microburst hypothesized to explain ground damage patterns. Three stages of development are shown. A midair microburst may or may not descend to the surface. If it does, the outburst winds develop immediately after reaching the surface (From Wakimoto 2001).

Figure 1.8.

A typical evolvement of radar echoes associated with bow echoes that produce strong and extensive downbursts (From Wakimoto 2001).

Figure 2.1.

Given a calculated T2 value, wind gust potential can be estimated using the curves (After Miller 1972)

Figure 3.1.

Sample SPC storm report map from 08 June 2005 (From Ref.

Storm Prediction Center Severe Weather Events Archive, http://www.spc.noaa.gov/climo/, February 2006)

Figure 3.2.

Sample of NEXRAD imagery from 08 June 2005 at 22Z (From Ref.

National Climatic Data Center, http://www4.ncdc.noaa.gov/cgiwin/wwcgi.dll?WWNEXRAD~Images2, February 2006)

Figure 3.3.

Observed atmospheric sounding from 00Z. Pressure in millibars on the left and temperature in degrees Celsius on the bottom................ 23 Figure 3.4. MM5 06Z model run sounding valid at 00Z. Pressure in millibars on the left and temperature in degrees Celsius on the bottom................ 24 ix Figure 3.5. Example of computed WINDEX gusts with dark blue colors representing low wind gusts and dark green colors representing high wind gusts. Contour intervals every 10 knots

Figure 4.1.

Computed T1 gust value versus observed wind gusts for June and July of 2005.

Figure 4.2.

For observed reports between 35-44 knots: Computed T1 wind gusts are compared to the frequency of times computed it was computed within the range of observed gusts.

Figure 4.3.

For observed reports between 45-54 knots: Computed T1 wind gusts are compared to the frequency of times computed it was computed within the range of observed gusts.

Figure 4.4.

For observed reports between 55-64 knots: Computed T1 wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.5.

For observed reports between 65-74 knots: Computed T1 wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.6.

Computed T2 gust value versus observed wind gusts for June and July of 2005.

Figure 4.7.

For observed reports between 35-44 knots: Computed T2 wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.8.

For observed reports between 45-54 knots: Computed T2 wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.9.

For observed reports between 55-64 knots: Computed T2 wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.10.

For observed reports between 65-74 knots: Computed T2 wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.11.

Computed WINDEX gust value versus observed wind gusts for June and July of 2005.

Figure 4.12.

For observed reports between 35-44 knots: Computed WINDEX wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.13.

For observed reports between 45-54 knots: Computed WINDEX wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.14.

For observed reports between 55-64 knots: Computed WINDEX wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

Figure 4.15.

For observed reports between 65-74 knots: Computed WINDEX wind gusts are compared to the frequency of times it was computed within the range of observed gusts.

x Figure 4.16.

Computed T1 gust value versus observed wind gusts for 21Z events during June 2005.

Figure 4.17.

Computed T1 gust value versus observed wind gusts for 06Z events during June 2005.

Figure 4.18.

Computed T2 gust value versus observed wind gusts for 21Z events during June 2005

Figure 4.19.

Computed T2 gust value versus observed wind gusts for 06Z events during June 2005

Figure 4.20.

Computed WINDEX gust value versus observed wind gusts for 21Z events during June 2005.

Figure 4.21.

Computed WINDEX gust value versus observed wind gusts for 06Z events during June 2005.

Figure 4.22.

For unknown wind gusts: Computed T1 wind gusts are compared to the frequency of times it was computed.

Figure 4.23.

For unknown wind gusts: Computed T2 wind gusts are compared to the frequency of times it was computed.

Figure 4.24.

For unknown wind gusts: Computed WINDEX wind gusts are compared to the frequency of times it was computed

–  –  –

Table 2.1.

T1 convective gust potential (After Miller 1972)

Table 3.1.

Example of storms reports from SPC from 08 June 2005 (After Ref.

Storm Prediction Center Severe Weather Events Archive, http://www.spc.noaa.gov/climo/, February 2006)

Table 4.1.

Percentage difference between the method computed wind gusts and observed gusts for each three hour time frame for June 2005.... 55 Table 4.2.

Percentage difference between the method computed wind gusts and observed gusts for each three hour time frame for July 2005...... 55 Table 4.3. Computed forecast mean values in knots for each method for given observed gust ranges

Table 4.4.

One standard deviation values in knots for each method for given observed gust ranges

–  –  –



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