An Examination of Wind Decay, Sustained Wind Speed Forecasts, and Gust Factors for Recent Tropical Cyclones in the Mid-Atlantic Region of the United States

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BRYCE TYNER AND ANANTHA AIYYER North Carolina State University, Raleigh, North Carolina

JONATHAN BLAES NOAA/NWS, Raleigh, North Carolina

DONALD REID HAWKINS NOAA/NWS, Wilmington, North Carolina

(Manuscript received 28 October 2013, in ﬁnal form 10 November 2014)

ABSTRACT

In this study, several analyses were conducted that were aimed at improving sustained wind speed and gust forecasts for tropical cyclones (TCs) affecting coastal regions. An objective wind speed forecast analysis of recent TCs affecting the mid-Atlantic region was ﬁrst conducted to set a benchmark for improvement. Forecasts from the National Digital Forecast Database were compared to observations and surface wind analyses in the region. The analysis suggests a general overprediction of sustained wind speeds, especially for areas affected by the strongest winds. Currently, National Weather Service Weather Forecast Ofﬁces use a software tool known as the Tropical Cyclone Forecast/Advisory (TCM) wind tool (TCMWindTool) to develop their wind forecast grids. The tool assumes linear decay in the sustained wind speeds when in- terpolating the National Hurricane Center 12–24-hourly TCM product to hourly grids. An analysis of post- landfall wind decay for recent TCs was conducted to evaluate this assumption. Results indicate that large errors in the forecasted wind speeds can emerge, especially for stronger storms. Finally, an analysis of gust factors for recent TCs affecting the region was conducted. Gust factors associated with weak sustained wind speeds are shown to be highly variable but average around 1.5. The gust factors decrease to values around 1.2 2 for wind speeds above 40 knots (kt; 1 kt 5 0.51 m s 1) and are in general insensitive to the wind direction, suggesting local rather than upstream surface roughness largely dictates the gust factor at a given location. Forecasters are encouraged to increase land reduction factors used in the TCMWindTool and to modify gust factors to account for factors including the sustained wind speed and local surface roughness.

1. Introduction Gridded Forecast Editor (GFE; Hanson et al. 2001)is currently used by NWS Weather Forecast Offices Developing gridded forecasts of sustained wind speeds (WFOs) to develop wind forecast grids when a given and gusts associated with landfalling tropical cyclones region is impacted by a TC. The TCMWindTool auto- (TCs) remains a significant challenge posed to Na- matically interpolates the 34-, 50-, and 64-knot (kt; 1 kt 5 tional Weather Service (NWS) forecasters in the mid- 2 0.51 m s 1) 12–24-hourly four-quadrant maximum wind Atlantic region of the United States. A software tool radii forecasts from the National Hurricane Center’s known as the Tropical Cyclone Forecast/Advisory (NHC) Tropical Cyclone Forecast/Advisory (TCM) (TCM) wind tool (TCMWindTool) included in the product to an hourly 2.5 km 3 2.5 km grid. The algorithm assumes linear temporal decay in wind speeds when in- terpolating the 12–24-hourly TCM product to hourly Corresponding author address: Bryce Tyner, Dept. of Marine, grids. The bilinear interpolation in space is conducted Earth, and Atmospheric Sciences, 2800 Faucette Drive, Rm. 1125 Jordan Hall, North Carolina State University, Raleigh, NC 27695- assuming a modified Rankine vortex wind field [see 8208. Mueller et al. (2006) for details on the modified Rankine E-mail: [email protected] vortex]. Forecasters at the WFOs select various options

DOI: 10.1175/WAF-D-13-00125.1

Ó 2015 American Meteorological Society Unauthenticated | Downloaded 09/30/21 08:44 PM UTC 154 WEATHER AND FORECASTING VOLUME 30 from the TCMWindTool with the aim of improving the Durst 1960; Krayer and Marshall 1992; Yu and Chowdhury raw output from the TCM product. These include 2009). In Hsu (2003), 148 samples of Automated Surface a background wind field used to smooth the winds outside Observing System (ASOS) data at various airports while of the TCM product wind field and a universal multi- impacted by 11 Atlantic TCs were used to calculate the plicative factor by which to decrease the surface wind gust factor based on the 2-min averaging period. The speeds over land to account for surface friction. Fur- calculated mean gust factor from the data was 1.42, with a thermore, the forecaster chooses the number of pie standard deviation of 0.18. In Hsu (2001), 2-min gust slices to which the winds are interpolated, with more factor data for Hurricane Opal (1995) for select offshore, pie slices creating a smoother transition between the coastal, and inland locations were compared to an em- four quadrants with different radii. Based on these pirical formula for calculating the gust factor. The results parameters, the TCMWindTool generates an output suggested an increase in gust factor associated with on- grid that represents a base sustained wind speed fore- shore conditions compared to offshore conditions. Further cast. Forecasters at the WFOs are then tasked with al- analysis needs to be conducted in order to support the tering these grids by ‘‘applying local knowledge and mean gust factor on these shorter wind averaging periods mesoscale expertise to produce the final set of explicit/ both spatially and temporally. Furthermore, the varia- deterministic wind forecasts for the WFO’s Area of Re- tions in the gust factor must also be examined in order to sponsibility’’ (information available online at http://www. aid forecasters developing wind gust grids. srh.noaa.gov/rtimages/crp/tig/2011_TCMWindTool.pdf). We conducted an informal survey of 13 forecasters The decay of TCs over land has been studied in a from NWS WFOs in the mid-Atlantic region to motivate number of empirical studies. Malkin (1959) examined At- the current research. The results of the survey suggested a lantic TCs making landfall and determined that there was lack of consistency in scientific reasoning for developing a tendency for the most intense hurricanes to weaken most the final sustained wind speed and gust grids in TC re- rapidly once over land. Furthermore, as the fraction of the gimes. Following are some of the key survey results al- storm that remained over water after landfall decreased, luding to this subjectivity in the forecast process: the rate of weakening increased. In Schwerdt et al. (1979), d Most of the surveyed forecasters stated that they were the authors provide evidence showing the rate of decay in not aware of a formal climatological analysis of land wind speeds once over land also varies based on the geo- reduction factors over the study region. A few re- graphical region. The rate of decay was shown to be slowest sponders referred to an informal, unpublished study over the Gulf of Mexico coastline, quickest over Florida, conducted by former hurricane specialist Dr. J. Pelissier and medium along the rest of the East Coast. It was con- at NHC. The study was for Atlantic TCs during 1999– cluded in both studies that any linear interpolation scheme 2005 and suggested a wind reduction of 10% within 5 mi employed to estimate wind speeds at intermediate time of the coast, with 20% to be used at areas farther inland steps can be inaccurate. Furthermore, decay rate was to account for surface frictional effects. shown to be proportional to intensity and largest just after d Forecasters diverged on how to develop and even the time of landfall. Motivated by some of these early define a gust factor. While most forecasters indicated studies, Kaplan and Demaria (1995) developed an em- a percentage above sustained wind speeds is appro- pirical model for predicting sustained TC wind speeds priate, some suggested a percentage of the maximum after landfall that avoids a linear interpolation assump- low-level mixed layer winds may be more effective. tion, based on data from all TCs making landfall in the d Forecasters reported using a wide range of percent- United States during 1967–93. ages above the sustained wind speeds to use as a gust After the sustained wind forecast has been developed, factor. Suggestions ranged from 15% to 40% above the forecasters are then tasked with creating a wind gust sustained wind speeds, depending on such factors as the forecast grid, developed using gust factor values. The degree of mixing and downward momentum transport, gust factor is typically defined as the ratio of the peak low-level lapse rates, presence/absence of convective wind speed to the sustained wind speed. A number of precipitation, wind direction, and distance from coast- studies have examined gust factors when applied to TC line and storm center. In addition, there were large conditions; however, few of the studies have examined discrepancies in suggested values among forecasters these gust factors in terms of the 2-min averaging period within several of the same WFOs. that NWS forecasters use for their forecasts. The 2-min average is calculated by averaging 24 discrete 5-s wind The survey results suggest a need for a comprehensive samples, which are based on 1-s wind observations. Most examination of the wind fields for recent TCs affecting gust factor studies are based on a 10-min averaging pe- the study region. Furthermore, the lack of consistency in riod, consistent with practices of wind engineers (e.g., standardizing wind averaging periods as well as

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FIG. 1. The analysis region, along with key cities that are mentioned throughout the paper. instrumentation heights in past gust factor studies mo- and South Carolina. A map of the analysis region along tivates this analysis. The focuses for this study are on the with key cities mentioned throughout the paper is shown steps of the current forecast process at the various in Fig. 1. It is important to examine recent wind speed WFOs and providing insight into potential areas of im- forecasts made by the various NWS forecast offices provement. The primary goals of the study are to within the study region in order to set a benchmark for improvement. All available National Digital Forecast d conduct an objective analysis of NWS sustained wind Database (NDFD) sustained wind speed forecasts were speed forecasts during times of TC influence, obtained from the National Climatic Data Center (NCDC) d examine the rates of decay in the sustained wind speeds for the study region and were used to conduct the forecast for a TC after landfall, and analysis. The NDFD was available starting in 2006, when d examine gust factors in the study region, specifically gridded wind speed forecasts became operational at the examining variability based on wind direction, sustained NWS offices. Remnant storms that made landfall along wind speed, and proximity to coastline. the Gulf Coast and later propagated into the study region The structure of this paper is as follows. The data and were not examined, since these are not often represen- analysis tools used for the study are enumerated in tative of true TC environments. TCs that formed off the section 2 and results are presented in section 3. The final mid-Atlantic coast and impacted the study region were section of the paper provides some discussion of the results included in the selection of storms. Since the number of as well as areas of future work that will be investigated by storms was limited in the study period, the NDFD anal- the authors. ysis was extended beyond landfalling TCs to include storms grazing the coastline. Table 1 lists the six TCs and the analysis dates for which NDFD forecasts were ex- 2. Data and methods overview amined based on these criteria. For this study, the analysis region was defined as the The analysis was completed using a combination of area encompassing Maryland, Virginia, North Carolina, the Hurricane Research Division’s (HRD) Real-time

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TABLE 1. Storms used to examine NDFD forecasts. The number of available CRONOS stations is also listed for each storm.

Year Storm Time period examined No. of stations H*Wind analyses 2006 Ernesto 1200 UTC 31 Aug–0600 UTC 3 Sep 191 0130 UTC 31 Aug–0430 UTC 1 Sep 2007 Gabrielle 0000 UTC 9 Sep–0000 UTC 11 Sep 189 0730 UTC 8 Sep–1630 UTC 9 Sep 2008 Cristobal 0000 UTC 19 Jul–0000 UTC 21 Jul 191 1930 UTC 19 Jul–1930 UTC 20 Jul 2008 Hanna 1800 UTC 5 Sep–0000 UTC 7 Sep 193 0130 UTC 5 Sep–1030 UTC 6 Sep 2010 Earl 1800 UTC 2 Sep–0000 UTC 4 Sep 237 1330 UTC 2 Sep–1930 UTC 3 Sep 2011 Irene 1800 UTC 26 Aug–1200 UTC 28 Aug 242 0730 UTC 26 Aug–1030 UTC 28 Aug

Hurricane Wind Analysis System (H*Wind) and hourly both data sources are examined and incorporated into surface observations from the State Climate Office of North the analysis. It should be noted that the NDFD sustained Carolina Climate Retrieval and Observations Network of wind forecasts are based on a 2-min averaging period, the Southeast Database (CRONOS; available online at consistent with CRONOS. The H*Wind analyses are http://www.nc-climate.ncsu.edu/cronos). The H*Wind sur- based on a 1-min averaging time, leading to potential face analyses are advantageous in that they blend model error when comparing to NDFD. However, the maxi- data with observations from U.S. Air Force and NOAA mum error accounting for these different averaging times aircraft, ships, buoys, and land-based surface platforms is expected to be less than 13% (Harper et al. 2010). (Powell and Houston 1998). All data are quality con- To reduce bias in the wind forecasts due to TC track trolled and then standardized to a 10-m height and 1-min and intensity uncertainty prior to affecting the region, wind speed averaging period. After landfall, when drop- only the NDFD forecasts issued immediately prior to sondes can no longer be deployed, the analyses are the analysis times were examined in this study. Follow- largely driven by available surface data as well as surface- ing this method, the study uses 1-h NDFD wind forecasts adjusted reconnaissance observations converted to open valid at each hourly analysis time (Glahn and Ruth 2003; terrain (Powell et al. 1998). In times of significant data Glahn 2005). The NDFD forecasts and H*Wind analy- outages and limited reconnaissance data, the H*Wind ses were bilinearly interpolated onto a common grid to analyses still provide an estimate of the analyzed wind allow for direct comparison of forecasted and analyzed speeds, but are largely weighted toward short-term model wind speeds at various locations. The interpolated com- forecasts. Unfortunately, H*Wind analyses are often only mon grid contained 220 3 220 grid points within the created for short periods after landfall, as shown in Table 1. latitude range of 308–408N and the longitude range of Furthermore, the analyses are only available at approxi- 758–858W, with a grid spacing of approximately 0.04583 mately 3-h intervals, leading to some discontinuity in the 0.0458. Similarly, the NDFD forecasts were bilinearly maximum winds at a given location throughout the du- interpolated to the CRONOS station locations. For both ration of a TC. analyses, bias was calculated as the difference between Because of the inherent limitations in the H*Wind the maximum NDFD-forecasted wind speed at each in- analyses, hourly surface observations from CRONOS terpolated grid point over the period of analysis and the were also examined. CRONOS included available ASOS, maximum analyzed value at the grid point over the same Automated Weather Observing System (AWOS), and time period. For example, Table 1 indicates H*Wind North Carolina Environment and Climate Observing analyses are available for Ernesto (2006) during the pe- Network (ECONet) stations. A standard 10-m observa- riod from 0130 UTC 31 August to 0430 UTC 1 September. tion height was used for all of the stations, allowing for To allow for direction comparison to forecasts, only direct comparison to the NDFD forecasts. For quality NDFD forecasts valid from 0100 UTC 31 August to control, probability distribution functions of the sustained 0400 UTC 1 September were examined for the H*Wind wind speeds were calculated for all stations during times analysis. To account for the spatial discontinuity in the of storm impact. Stations with greater than 40% of the H*Wind analyses and because H*Wind analyses were sustained wind observations equaling less than 2 kt were often not available beyond several hours after TC im- removed from the analysis. Routine inspection of the pact, only grid points that had analyses available for at sustained wind speed data for the remaining stations least half of the forecast valid times were used in the suggests hourly observations are not available for all study. Also following Table 1, maximum data available locations and times of storm impact. The missing data from CRONOS during times of TC impact were exam- can be attributed to mechanical problems as well as ined and compared to NDFD forecasts valid for the communication failures and power outages at the vari- same period of TC impact. ous stations, especially during times of significant storm As previously noted, the TCMWindTool interpolates impact. Due to the inherent limitations in each dataset, the 12–24-hourly wind field forecast from NHC to hourly

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TABLE 2. Landfalling TCs in the study region, 2002–11, for which TABLE 3. All TCs impacting the study region for which the gust the land decay analysis was conducted. factors were analyzed, 2000–11.

Year Storm Approx landfall time and date Year Storm Dates of storm impact 2002 Kyle 1700 UTC 11 Oct 2002 Kyle 11–12 Oct 2003 Isabel 1700 UTC 18 Sep 2003 Isabel 18–19 Sep 2004 Charley 1400 UTC 14 Aug 2004 Charley 14–15 Aug 2004 Gaston 1400 UTC 29 Aug 2004 Gaston 28–31 Aug 2006 Ernesto 0400 UTC 1 Sep 2006 Ernesto 31 Aug–2 Sep 2007 Gabrielle 1500 UTC 9 Sep 2007 Barry 2–4 Aug 2008 Hanna 0700 UTC 6 Sep 2007 Gabrielle 8–11 Sep 2011 Irene 1200 UTC 27 Aug 2008 Cristobal 18–21 Jul 2008 Hanna 5–7 Sep 2010 Earl 2–3 Sep forecast grids. The tool assumes linear changes in the 2011 Irene 26–28 Aug wind speeds within each 12–24-h interval. Hourly Rapid Update Cycle (RUC) analyses with a horizontal grid 2-min averaging time used to calculate the sustained wind spacing of 20 km (Benjamin et al. 2004) are available speed. Between 2005 and 2009, the ASOS stations were from NCDC for 2002–11. The RUC analyses were ob- upgraded to Ice Free Wind Sensors, and the averaging tained for all landfalling TCs in the study region during period for wind gusts was reduced to 3 s. Childs and this period of availability in order to evaluate the as- Lewis (2001) investigated the impact of changing the sumption of linear change. While there are inherent ASOS wind gust averaging period from 5 to 3 s using limitations of the RUC analysis resolving TC intensity, a data from Sterling, Virginia. The results indicated a comparison to H*Wind analyses showed the hourly anal- positive bias for the shorter averaging period, but the yses were still able to resolve the general storm structure as bias was found to be only 0–2 kt. Based on the results of well as changes in the wind and pressure fields with time this study, the ASOS sensor change is not expected to (not shown). Furthermore, RUC analyses have been affect the overall results of the gust factor analysis pre- used to study TC structure in several past studies. For sented in this paper. For each storm, gust factors were example, Davies (2006) examined hourly RUC sound- calculated at each ASOS station during times of TC ings at select locations to study the characteristics of TC influence. The gust factor was calculated at each time tornadic environments, including storm-relative helicity and location as the ratio of the wind gust to the sustained at the locations. wind speed value. After a comparison to NHC TC best-track data (available online at http://www.nhc.noaa.gov/data/#hurdat), it was determined that eight TCs made landfall in the 3. Results study region during the selected analysis years. A list of a. NDFD analysis the eight analyzed storms and their approximate times of landfall is presented in Table 2. The land decay analysis 1) ERNESTO (2006) was conducted based on storm quadrant in order to account for the azimuthal differences in storm structure and The wind forecasts for six TCs affecting the study area respective wind fields. To allow for comparison of storms were examined, and the tracks of these storms are shown of various sizes, analyzed wind speeds were examined in Fig. 2. According to the NHC storm report, Ernesto within the sectors consistent with the NHC best-track 34- (2006) made landfall near Oak Island, North Carolina, and 50-kt maximum wind radii. The storm center was at approximately 0340 UTC 1 September, with maxi- calculated based on RUC-analyzed hourly minimum sea mum sustained winds near 60 kt and a minimum central level pressure associated with the TCs. pressure of 985 hPa (Knabb and Mainelli 2007). Before ASOS 1-min sustained wind speed and gust data are the passage of the TC, a predecessor rain event occurred available to the public from NCDC since 2000. For the over much of Virginia and North Carolina. Furthermore, gust factor analysis, this ASOS data were obtained for northerly flow from a surface high pressure located over all available locations in the study region during TC southern Canada led to a weak cold-air damming event impact from 2000 to 2011, as listed in Table 3. It is im- for the region beginning on 31 August (Moore et al. portant to note that the averaging period for calculating 2013). After landfall, the tropical storm gradually weak- wind gusts has not been consistent at these ASOS sta- ened as it moved northward through northeastern North tions. Prior to 2005, wind gusts were calculated as the Carolina and over eastern Virginia before becoming ex- maximum 5-s wind speed within the past minute of the tratropical at around 1800 UTC 1 September.

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wind speeds throughout the storm duration for much of the study region. Figure 3d shows the difference between the maximum NDFD-forecasted sustained wind speed and the maximum hourly observed wind speed at the available CRONOS stations. With these data available, the maximum sustained wind speeds over much of eastern South Carolina, North Carolina, and Virginia appeared to have been overpredicted. This overprediction was highest in northeastern South Carolina and southeastern North Carolina, where overprediction of up to 20 kt is seen at some CRONOS stations. Weak overprediction is also apparent over central North Carolina and Virginia, with overprediction values near 4–12 kt. In summary, prior to the landfall of Ernesto (2006), there was a general underprediction of wind speeds over much of east-central North Carolina and southeastern Virginia. After landfall, when the strongest wind speeds affected much of the study region, a general overprediction of wind speeds was observed, following the CRONOS analysis. It is hypothesized that the competing influence of boundary layer stabilization from the predecessor rain event along with increased gradient wind flow from the cold-air damming led to a sustained wind forecasting challenge. A literature survey suggests most cold-air damming observational and modeling studies have focused on TC precipitation distribution impacts (e.g., Srock and FIG. 2. Tracks for all storms in which NDFD forecasts were ex- Bosart 2009). To the knowledge of the authors, a com- amined. Red, orange, green, and blue lines indicate max sustained winds of category 2 hurricanes, category 1 hurricanes, tropical prehensive investigation into the influence of cold-air storms, and tropical depressions, respectively. damming on the surface winds as it interacts with a TC in the region is lacking. Cold-air damming can be thought of Plots of maximum H*Wind-analyzed 10-m wind as having competing impacts on the surface winds for an speed as well as the difference between the maximum impending TC. The cold air from the associated parent NDFD- and H*Wind-analyzed wind speed are shown in surface high pressure over the northeastern region of the Figs. 3a and 3c. For the available H*Wind analysis times, United States stabilizes the environment, reducing the the core of maximum winds over land was located from near-surface lapse rates and preventing vertical mixing of central North Carolina eastward to the coastline (Fig. 3a). winds aloft to the surface. However, the parent high also Maximum sustained surface wind speeds were analyzed increases the pressure gradient as the TC approaches. A to be around 32–36 kt over much of this region, with future comprehensive study of this nature would help a local maximum of 40–44 kt near the location of landfall improve wind forecasts for these complex scenarios. in southeastern North Carolina. There is a widespread 2) GABRIELLE (2007) underprediction of sustained wind speeds over much of east-central North Carolina and southeastern Virginia of Tropical Storm Gabrielle (2007) made landfall near 4–8 kt during the analysis time (Fig. 3c). The maximum Cape Lookout, North Carolina, at 1400 UTC 9 September underprediction of these wind speeds was located in with maximum sustained winds near 50 kt, based on the southeastern North Carolina, with an underprediction of NHC best-track data. After making landfall, the storm 16–20 kt in a localized area. The H*Wind analyses were moved quickly toward the northeast and off the coastline only available up to 0430 UTC 1 September, which was near Kill Devil Hills, North Carolina. As the NHC storm near the time of landfall (Table 1). As a result, much of report indicates, strong northerly upper-level winds the region had not yet been affected by the stronger TC sheared the convection, keeping the strongest winds off- winds located farther to the south near the storm core. shore (Brown 2008). Figures 4a and 4c show the maxi- Because the H*Wind analyses are not available for mum H*Wind-analyzed wind speed and the difference Ernesto (2006) beyond the time of landfall, the H*Wind between the maximum NDFD-forecasted and available analysis presented is not representative of the maximum H*Wind-analyzed wind speed. The H*Wind analyses are

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FIG. 3. Ernesto (2006) (a) max H*Wind-analyzed wind speed (kt) over all available analysis times, (b) max CRONOS wind speed (kt) station data, (c) wind speed difference between NDFD and H*Wind (NDFD 2 H*Wind; kt), and (d) wind speed difference between NDFD and CRONOS (NDFD 2 CRONOS; kt). only available for approximately 2 h after landfall (Table 1). Figure 4c indicates a widespread region of overprediction However, as a result of the strongest winds to the east of of maximum wind speeds in eastern North Carolina by the storm center and the rapid northeasterly track of the approximately 4–8 kt. The overprediction was largest storm,theperiodinwhichtheregionwasmostdirectly over much of the Outer Banks, where the strongest ob- impacted is captured from the H*Wind analysis. The served wind speeds occurred. In this region, there was a maximum H*Wind analysis shows the strongest winds widespread overprediction of wind speeds by approxi- were indeed conﬁned to the coastline and areas just off- mately 8–12 kt. Farther west, there was large region of shore, consistent with reduced surface roughness in those underprediction of wind speeds of 4–8 kt in the region of locations as well as the increased proximity to the storm weaker analyzed wind speeds. Figure 5 shows the center. There is a large region of 28–36-kt maximum sus- County Warning Areas (CWA) of the various NWS tained winds in eastern North Carolina. The peak winds WFOs. It is important to note that the underprediction– over land were conﬁned to the Outer Banks, with maximum overprediction dipole closely aligns with the various analyzed surface winds over 44 kt in a narrow region over WFO boundaries. The overprediction of wind speeds Cape Hatteras. Farther to the west, maximum sustained in North Carolina was restricted to east-central North wind speeds gradually decreased, with maximum analyzed Carolina, with underprediction of wind speeds in the wind speeds over central North Carolina near 8–16 kt. bordering WFOs.

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FIG.4.AsinFig. 3, but for Gabrielle (2007).

The analysis using CRONOS stations in Fig. 4d is forecast process. A GFE tool has been developed that quite similar to the analysis using H*Wind data. This will promote this collaboration of land reduction factors. includes a large region of overprediction of wind speeds Details of this tool are discussed more thoroughly in of 4–8 kt in eastern North Carolina, with even higher section 4 of this paper. overprediction in select locations. In the areas farther 3) CRISTOBAL (2008) inland that were affected by weaker wind speeds, a widespread underprediction of wind speeds of around According to the NHC storm report, Cristobal (2008) 4–8 kt is visible. In between these regions, there is an developed from a decaying frontal boundary off the mid- area where the observed maximum sustained wind Atlantic coastline (Avila 2009). As the system drifted speeds closely matched the NDFD-forecasted wind westward toward the Outer Banks on 20 July, it strength- speeds. ened into a weak tropical storm. The storm then gradually In summary, the H*Wind and CRONOS wind speed accelerated northeastward in the Atlantic away from analyses yield similar overall results, with strong over- land. As a result of this northeasterly track, the H*Wind prediction in wind speeds for areas affected by the analyses were available for sufﬁcient time to capture the strongest sustained wind speeds. Sharp gradients in the strongest wind speeds impacting the study region. The forecasted wind speeds across WFO boundaries storm never made landfall and the strongest wind speeds suggest a need for greater collaboration on land re- remained off the coastline (Fig. 6a). The H*Wind surface duction factors used in the TCMWindTool during the analysis indicates that maximum sustained wind speeds

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with maximum sustained winds near 60 kt. After making landfall, the storm continued to track northward over northeastern North Carolina and southeastern Virginia and through the mid-Atlantic states. As described in Eastin et al. (2012), outer rainbands associated with Hanna led to the development of a strong surface cold pool over much of central North Carolina and Virginia. This surface cold pool developed as the precipitation fell into dry low-level air, eventually resulting in an ageo- strophic wind adjustment of flow from the northeast. The diabatically forced northeasterly flow was consistent with an in situ cold-air damming event for the region (Bailey et al. 2003). The H*Wind analyses for Hanna (2008) were only available shortly after landfall (Table 1). As a result, the verification using H*Wind analysis is for the period prior to the strongest wind speeds impacting much of north- FIG. 5. CWAs for the various NWS WFOs in the study region. eastern North Carolina and eastern Virginia. Maximum over 25 kt were confined to parts of the Outer Banks. wind speeds greater than 20 kt occurred over much of Furthermore, the analysis indicates there was a sharp eastern South Carolina and North Carolina during the decrease in wind speeds away from the coastline, with analysis period (Fig. 7a). Similar to Gabrielle (2007) and locations just slightly inland experiencing maximum sus- Cristobal (2008), the strongest wind speeds were contained winds of less than 16 kt. fined to locations east of the storm center, where maxi- There was a general overprediction in sustained wind mum sustained wind speeds were analyzed to be greater speeds throughout the eastern portions of the study re- than 28 kt. The maximum difference plot shows an ex- gion (Fig. 6c). As was the case in Gabrielle (2007), the tensive region of overprediction in maximum wind areas with the strongest sustained wind speeds were speeds throughout much of east-central North Carolina consistent with the largest values of overprediction. This and Virginia (Fig. 7c). The overprediction was approx- includes much of extreme eastern North Carolina, with imately 8–12 kt ahead of the main TC circulation. Far- a general overprediction in wind speeds near 8–12 kt. ther to the west and east of this region, the forecasts Farther to the north over eastern Virginia and farther matched closely with the H*Wind-analyzed maximum southwest over eastern South Carolina, the analysis in- sustained wind speeds. dicates widespread weak overprediction of wind speeds, When the entire period of storm impact is considered, with values near 4–8 kt. Over central North Carolina and the CRONOS analysis in Fig. 7d suggests more extensive Virginia, where the wind speeds were the weakest, Fig. 6 overprediction of wind speeds associated with Hanna shows widespread close agreement between the fore- (2008). Over much of the eastern portion of the study casted and analyzed sustained wind speeds, with just a region, the overprediction was between 12 and 20 kt in few locations observing slight underprediction of wind many areas. The overprediction is much lower toward speeds. western North Carolina, in the region affected by weaker A comparison to the CRONOS analysis for Cristobal wind speeds. (2008) reveals many of these same spatial features In summary, the region affected by the strongest wind (Fig. 6d). Over the coastal regions, where the strongest speeds displayed an overprediction for Hanna (2008). wind speeds occurred, an overprediction of approxi- The overprediction was also observed ahead of the storm mately 8–12 kt for many locations is apparent, consis- prior to the strongest wind speeds impacting the region, tent with the H*Wind analysis. Over central and as indicated by the H*Wind analysis. In the regions af- western North Carolina and Virginia, in the areas affected by weaker winds to the west, the forecasted winds fected by the periphery of the storm, the forecasted were much closer to the observed and analyzed wind maximum wind speeds closely matched the CRONOS field. Similar to Ernesto (2006), it is hypothesized that the observations. cold-air damming ahead of the storm complicated the forecast process for the wind speeds. As previously 4) HANNA (2008) mentioned, future work should thoroughly examine the Hanna (2008) made landfall near the border between impact of cold-air damming on near-surface wind speeds North and South Carolina at 0700 UTC 6 September during times of TC impact.

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FIG.6.AsinFig. 3, but for Cristobal (2008).

5) EARL (2010) For locations west of this region, maximum analyzed wind speed values were below 12 kt. Earl (2010) approached the southeastern United Most of the eastern portions of the study region saw a States as a category 2 hurricane (Fig. 2). During its strong overprediction in maximum surface wind speeds. recurvature to the northeast, it weakened quickly from As in the case of Gabrielle (2007) and Cristobal (2008), a category 2 hurricane at 1200 UTC 2 September to the areas experiencing some of the strongest wind a category 1 storm at 1200 UTC 3 September. At its speeds were in line with areas of strongest over- closest approach to the coastline, the storm passed ap- prediction. In the Outer Banks, the overprediction proximately 75 miles to the east of Cape Hatteras on 3 peaked near 8–16 kt (Fig. 8c). The large overprediction September. After impacting the North Carolina coastline, in the coastal regions was also present when evaluating the storm accelerated to the northeast. Similar to Gabri- with the CRONOS stations (Fig. 8d). The maximum elle (2007), the maximum wind speeds for Earl (2010) overprediction was near 12–16 kt over much of this re- were conﬁned to portions of the Outer Banks (Fig. 8a). In gion, which is quantitatively consistent with the H*Wind this area, maximum wind speeds were around 30–36 kt, analysis. The overprediction is not as large over portions with a peak over Cape Hatteras of near 48 kt. There was of east-central North Carolina and extreme southeast- a sharp spatial gradient in the maximum wind speeds, with ern Virginia, with values near 4–8 kt over much of the areas over east-central North Carolina and Virginia ex- area. In the region affected by the weaker wind speeds periencing weaker sustained winds of around 12–20 kt. farther to the west, the forecasted wind speeds closely

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FIG.7.AsinFig. 3, but for Hanna (2008). matched the H*Wind analyzed as well the wind speeds H*Wind surface analyses were created by HRD long observed from the CRONOS stations. after landfall for Irene (2011), providing a more complete picture for the NDFD analysis than for several of 6) IRENE (2011) the other storms examined. The maximum difference plot Irene (2011) made landfall near Cape Lookout, reveals a strong overprediction in wind speeds over much North Carolina, at 1200 UTC 27 August with maximum of the study region. The H*Wind analysis indicates the sustained winds of 75 kt, according to the NHC storm maximum overprediction was across portions of eastern report (Avila and Cangialosi 2012). After landfall, the Virginia and east-central North Carolina, where maximum storm continued to move northeast over eastern North overprediction was around 16–20 kt (Fig. 9c). There was Carolina and Virginia and along the coastline up to a sharp reduction in the maximum wind speed error over New England. The strongest winds were mainly con- central North Carolina following within the Raleigh fined to along and east of the storm track (Fig. 9a). This WFO area of responsibility, shown previously in Fig. 5. included areas along the Outer Banks, where wide- Based on some of the preliminary results of some of the spread maximum sustained wind speeds over 62 kt work presented here, forecasters at the Raleigh WFO were analyzed. Over much of east-central North Car- noted using exceptionally high land reduction factors in olina and Virginia, maximum wind speeds were near the TCMWindTool of 30%–35% compared to neigh- 32–40 kt, diminishing to 16–24 kt over the central por- boring offices (G. Hartfield, NOAA/NWS Raleigh, 2011, tions of these states. personal communication). This suggests the increased

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FIG.8.AsinFig. 3, but for Earl (2010). land reduction factors may be necessary for operational and Virginia is not likely representative of the true over- forecasters in future landfalling TCs, especially for loca- prediction in the region (Fig. 9d). The overprediction would tions near the coastline experiencing some of the stron- likely have been reduced if the stronger wind speeds during gest maximum sustained winds. major TC impact had been recorded. Hence, for this storm, The CRONOS analysis indicates an overprediction of it is suggested that the H*Wind analyses better quantita- wind speeds along the coastline of South Carolina, North tively capture the overprediction in the areas impacted by Carolina, and Virginia (Fig. 9d). The neutral colors over the stronger wind speeds than analyses using CRONOS. central North Carolina suggest the forecasted maximum b. Land decay analysis winds were comparable to observations for areas over the Raleigh WFO, consistent with the H*Wind analysis. The As previously mentioned, eight TCs made landfall in numbers of hourly observations that were unavailable for the study region during the selected analysis years. The select stations impacted by the storm are plotted in hourly four-quadrant 10-m winds within the NHC best- Fig. 10. Several locations in eastern North Carolina and track 34- and 50-kt maximum wind radii were examined Virginia reported missing observations as a result of for these eight TCs. Consistent with the results pre- power outages. Because of these power outages, many of sented in Kaplan and Demaria (1995), it was determined these stations were unable to record observations when that the weaker storms had much slower rates of intensity the strongest wind speeds impacted the location. Thus, the change after making landfall. Because of these slower extreme overprediction for much of eastern North Carolina rates of decay, the assumption of linear decay was not

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FIG.9.AsinFig. 3, but for Irene (2011). shown to result in significant error for these TCs. How- approximately 24 kt 1 h later (Fig. 13). In the south- ever, two of the TCs examined were much more intense eastern quadrant, the period of decay began around 5 h and hence the results of the land decay for these storms are after landfall, with the median wind speed within this presented in detail. storm radius decaying by approximately 22 kt within Isabel (2003) and Irene (2011) were strong TCs that a2-hperiod. impacted the region during the period of study. The tracks Isabel (2003) took a nearly perpendicular angle of of Isabel (2003) and Irene (2011) are shown in Fig. 11. approach to the coastline, with the western quadrants of Time series of median four-quadrant 10-m winds within the storm reaching land first (Fig. 11). The rapid decay the NHC best-track 34- and 50-kt maximum wind radii once over land is a reflection of this direct angle of ap- are shown for Isabel (2003) in Figs. 12 and 13. The plots proach at landfall, consistent with the results presented indicate that in all four storm quadrants, there was a 2–4-h in Malkin (1959). This direct angle of approach resulted period of rapid decrease in wind speeds. The period of in rapid weakening of the storm, as well as increased decayof10-mwindspeedsforthewestsideofthestorm surface roughness, leading to frictional reduction in preceded the decay to the east, consistent with the left near-surface wind speeds. The rapid weakening oc- quadrants of the TC moving over land prior to the right. curred on time scales much shorter than the available For example, in the southwestern quadrant, the median 12–24-hourly NHC forecast data. The linear decay as- wind speed decreased within the 50-kt maximum sumption used to create the hourly wind grids in the wind radius from around 42 kt 2 h after landfall to TCMWindTool is thus unable to capture the decay in

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FIG. 10. The number of missing hourly observations for select ASOS stations impacted by Irene (2011). The station abbreviations are as listed in Table 4 (here the initial ‘‘K’’ is omitted), and RWI: Rocky Mount, NC; MRH: Beaufort, NC; AKQ: Wakeﬁeld, VA. wind speeds after landfall that was observed in the RUC analyses. Applying a linear decay function would lead to strong error in wind speeds after the storm makes landfall, given the rapid decay in wind speeds over FIG. 11. Storm tracks for Isabel (2003) and Irene (2011). Red, or- a short time interval. To better depict this, dashed lines ange, and green lines indicate max sustained winds of category 2 hurricanes, category 1 hurricanes, and tropical depressions, respectively. in Figs. 12 and 13 are overlaid, showing linear changes in wind speed over the 12-h period analyzed for all four quadrants. Because of the rapid decay, the interpolated period of 2–4 h of rapid decay approximately 24 h after wind speeds are too low prior to the period of rapid landfall, especially for the northeastern and southeastern decay and too high afterward. The amount of error in quadrants within the 50-kt maximum wind radius. As in the the wind speeds is as high as 50%. case of Isabel (2003), the application of linear decay would Irene (2011) made landfall in southeastern North lead to strong bias in wind speeds during the period of rapid Carolina before moving northeastward and exiting the decay, resulting in large errors for the hourly grids. The de- coastline near the North Carolina–Virginia border (Fig. 11). cay of wind speeds within the weaker 34-kt maximum wind The storm then continued to move northward, moving radii was much more gradual, resulting in minimal error roughly parallel to the coastline before a second landfall when assuming linear decay over the periods of 12–24 h. over southern New Jersey. Temporal analyses of four- As previously mentioned, the current tool only allows quadrant decay in median wind speeds for the 34- and the use of one universal land decay value. An improved 50-kt maximum wind radii are plotted in Figs. 14 and 15, version of the TCMWindTool would help take into ac- respectively. For the western quadrants of the storms, the count periods of rapid decay, both as a result of hourly wind speeds underwent a brief period of reduction within changes in storm strength as well as differences in surface the ﬁrst few hours of landfall. The wind speeds increased roughness at the various locations affected by the wind as the storm moved off the coastline approximately 12 h speeds. This could be achieved by creating a grid-to-model after landfall, particularly for the median wind within the reduction due to surface roughness as well as adding 50-kt maximum wind radius. The eastern quadrants did a slider bar within the TCMWindTool to alter the linear not undergo this period of reduction in wind speeds, change within the 24-h four-quadrant maximum wind consistent with reduced surface roughness for these radii. These options are currently being tested by the quadrants as well as continued strong convection on the collaborators for the project. As previously discussed, eastern hemisphere of the storm. As the storm made its though the 20-km RUC grid spacing is relatively coarse second landfall over southern New Jersey, the wind speeds to represent the strength of the TC, a comparison to underwent a period of rapid decay. The plots indicate a short various analysis datasets indicates that the general wind

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FIG. 12. Median RUC-analyzed four-quadrant wind speed (kt) within the 34-kt max wind radius at various times after landfall for Isabel (2003) (solid) along with a 12-h linear interpolation (dashed). The four quadrants represented are (a) northwest, (b) northeast, (c) southeast, and (d) southwest. structure is still well represented. Furthermore, Malkin Furthermore, a temporal analysis was conducted for (1959) showed that the rate of decay over land increases each storm at each station to examine how the gust with increasing wind speed. Based on this, it is suggested factors evolved as the TC passed. that the violation of the linear rate of decay in wind speeds 1) GUST FACTOR VERSUS SUSTAINED WIND SPEED presented in this analysis may even be stronger in actuality. Figure 16 shows histograms of available 1-min gust c. Gust factor analysis factors as a function of sustained wind speed. The results ASOS wind data were examined for all TCs impacting indicate a large variability in the gust factor for weak the region from 2000 to 2011, listed in Table 3. Gust sustained wind speeds. For wind speed values less than factors were calculated for each available observation. 30 kt, gust factors have a large degree of spread, with As previously mentioned, the gust factors were calcu- values from 1.0 to 2.2. In fact, there are near-equal fre- lated as a ratio of wind gust to sustained wind speed quencies of gust factors of 1.15–1.2, 1.2–1.25, and 1.25– value. The gust factors were not examined when the 1.30. For sustained wind speed values between 30 and sustained wind speed reported was less than 10 kt. Gust 40 kt, the gust factors shift slightly to lower values, with factors were analyzed based on sustained wind speed as most gust factors falling between 1.15 and 1.25. How- well as on wind direction over the study region. ever, there is a tail in the distribution of gust factors, with

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FIG. 13. As in Fig. 12, but for the 50-kt max wind. several observations greater than 1.5. The shift to lower used across the entire forecast area may be a poor ap- gust factor values is much more evident at sustained proach. It is suggested that forecasters consider using wind speeds between 40 and 50 kt, with very few ob- higher gust factors for locations impacted by weaker served gust factors greater than 1.5. Although there are sustained wind speeds than locations impacted by stron- few data for sustained wind speeds greater than 50 kt, ger TC sustained wind speeds. the available data indicate very little spread in gust 2) GUST FACTOR VERSUS WIND DIRECTION factors for wind speeds over 50 kt, with gust factors remaining relatively constant near 1.20. To confirm these In Paulsen and Schroeder (2005), the authors compare results, the standard deviation of the gust factors for the gust factors at 10-m averaging periods for TC envi- various wind speed bins was calculated. The value for ronments and non-TC environments. The results sustained wind speeds less than 30 kt was 0.21, compared showed that in both environments, gust factors were to a much smaller value of 0.14 for wind speeds greater higher when the wind came from a direction associ- than 50 kt. The reduced variability in gust factors ob- ated with higher upstream surface roughness. Based served at high wind speeds is consistent with the recent on this result, we hypothesized that the gust factors at work of Walsh et al. (2010), where drag coefficients were the various ASOS stations with 2-min averaging pe- shown to level off or even decay at high TC sustained riods would show bias based on wind direction. In wind speeds. Overall, the results suggest the methodology particular, values at locations near the coastline were used by many forecasters in which a single gust factor is expected to be higher for continental flow with higher

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FIG. 14. As in Fig. 12, but for Irene (2011). The vertical lines indicate the approximate time of second landfall for Irene (2011). associated upstream surface roughness compared to topography and associated surface roughness was maritime ﬂow. Gust factors from 14 coastal sites in the found to have a heavy inﬂuence on the gust factors study region were calculated for the storms and ana- associated with TCs. lyzed according to wind direction. Alist ofthese coastal 3) GUST FACTOR ANALYSIS:MARITIME VERSUS stations is presented in Table 4. Figure 17 shows a CONTINENTAL FLOW histogram of gust factors as a function of wind direction for these coastal sites. The histograms do not indicate a Based on the results presented in Hsu (2001),itwas conclusive difference in magnitudes of gust factors further hypothesized that locations immediately along basedonwinddirection.Thereisaclusteringofgust the coastline would observe lower gust factors than when factors near 1.25–1.4, with a gradual spread in other the wind was from a direction with a large fetch over land. values for all four wind directions. The mean gust fac- Hence, for these locations right along the coastline, gust tor from all four directions is approximately the same, factors were analyzed based on wind direction, and our consistent with the histogram results (Table 5). The results support this hypothesis. Figure 18 shows a histo- results suggest that other factors besides upstream gram of gust factors as a function of wind direction for surface roughness are important in determining the Ocean City, Maryland. The histogram suggests a prefer- gust factors. This is consistent with the results pre- ence in gust factors for this location based on wind di- sented in Vickery and Skerlj (2005),wherelocal rection. There is a tight clustering of gust factors below

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FIG. 15. As in Fig. 14, but for the 50-kt max wind.

1.3 when the wind direction is from the northeast or this station, the gust factors do not show a large prefer- southeast (Figs. 18b,d). Ocean City is located right along ence based on wind direction. The mean gust factor is the Atlantic coastline (Fig. 1). Hence, these wind di- approximately the same from all four wind quadrants rections are associated with maritime flow. This cluster- (Table 5). The results, combined with the results of the ing of gust factors toward lower values for maritime flow previous section, suggest gust factors are largely de- is consistent with the results presented in Hsu (2001), termined by local surface roughness conditions. For most where gust factors observed by buoys were found to be locations, the local upstream surface roughness is not clustered near 1.3. The gust factors display more spread vastly different based on wind direction. However, for when the wind direction is from the southwest and locations immediately adjacent to the coastline, the local northwest (Figs. 18a,c). Table 5 indicates the mean gust upstream surface conditions are inherently different, re- factors are lower when the wind direction is from a mar- sulting in a preference for lower gust factors for this itime direction, particularly from the northeast. After maritime flow. conducting a Student’s t test, it was shown that the dif- 4) GUST FACTOR TEMPORAL ANALYSIS:IRENE ferences in the means for the maritime flow compared to (2011) the continental flow were significant to the 99% confi- dence level. In contrast, Fig. 19 shows the gust factor as Gust factors were also examined at select stations a function of wind direction for Salisbury, Maryland, throughout the various stages of TC impact. A time se- a location approximately 50 km inland of Ocean City. For ries of gust factors is presented in Fig. 20 for Raleigh and

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FIG. 16. Histograms of gust factors for sustained wind speeds: (a) 10–30, (b) 30–40, (c) 40–50, and (d) greater than 50 kt.

New Bern during Irene (2011). Wind speed observations Carolina coastline (Fig. 10). As the wind speeds gradually are plotted at 10-min intervals in the ﬁgure. As the TC decreased after the storm passage and the sustained wind approached on 27 August, sustained wind speeds peaked speeds decreased on 28 August, the gust factors increased at around 17 kt at 1200 UTC 27 August at Raleigh. With in variability, with a mean value increasing slightly to these low wind speed values, gust factors exhibited a large around 1.3. Consistent with the previously presented re- degree of spread, with values ranging from 1.2 to 2.0 sults, as the wind speed increased in New Bern, the gust throughout the time of TC impact. The high degree in spread of gust factors for lower sustained wind speeds is consistent with the previous results presented for all times TABLE 4. List of coastal ASOS sites for which gust factors were of TC impact for the study region. analyzed according to wind direction. The gust factor temporal analysis for New Bern differs Location Name from that for Raleigh. As the TC approached, the observed sustained wind speeds increased to over 30 kt early Baltimore, MD KBWI Cape Hatteras, NC KHSE on 27 August. The gust factor values were noticeably Ocean City, MD KOXB lower for New Bern and the variability was also largely Wallops Island, VA KWAL reduced. This was especially the case when the wind Elizabeth City, NC KECG speed values were greater than 20 kt after 0300 UTC 27 Charleston, SC KCHS August, where the gust factors were closely clustered Swansboro, NC KNJM Salisbury, MD KSBY around 1.25. Unfortunately, because of a sensor outage, Newport News, VA KPHF sustained wind speeds and gusts are not available from Norfolk, VA KORF 0724 UTC 27 August to 2211 UTC 27 August, as the wind New Bern, NC KEWN speeds continued to increase. The data outage occurred Myrtle Beach, SC KMYR for many ASOS and AWOS stations along the North Wilmington, NC KILM

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FIG. 17. Histogram of gust factors for (a) northwesterly, (b) northeasterly, (c) southwesterly, and (d) southeasterly flow. factor variability was reduced and converged to a lower wind speeds, especially for areas affected by the stron- mean value. gest wind speeds. Forecasters are also encouraged to collaborate among WFOs on the land reduction factors they select when running the TCMWindTool to improve 4. Discussion and conclusions the sustained wind speed forecasts and consistency for A climatology of sustained wind speeds, gusts, and future TCs. A land reduction factor of 5% is suggested forecasts of recent TCs impacting the mid-Atlantic was along the immediate coastline, gradually increasing to presented. To set a benchmark for improvement, a sys- approximately 15% slightly farther inland and, finally, to tematic analysis of NDFD sustained wind speed fore- 35% for locations well inland. These suggested land casts was conducted for recent TCs impacting the study reduction factor values are somewhat heuristically region. The NDFD analysis using both the observations based. Future studies should strive to objectively from CRONOS and the H*Wind surface analyses suggested a general overprediction in sustained wind speeds for much of the study region. This overprediction was TABLE 5. Mean gust factor values for the various locations and seen in areas impacted by the strongest wind speeds. wind directions presented in the paper. Ernesto (2006) and Hanna (2008) were storms in which a Northeast Southeast Southwest Northwest cold-air damming event preceded the TC making land- Gust factor by direction fall. Future studies should examine this influence of Mean 1.27 1.28 1.26 1.29 cold-air damming on observed TC wind speeds. Based Gust factor by direction: KOXB on the analysis, forecasters are encouraged to consider Mean 1.23 1.32 1.36 1.35 using larger land reduction factors when running the Gust factor by direction: KSBY TCMWindTool in order to reduce the overprediction in Mean 1.29 1.26 1.27 1.28

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FIG. 18. As in Fig. 17, but for gust factors at Ocean City. determine these land reduction factor values to be the 12-h raw wind speed forecast guidance provided used in the TCMWindTool. by NHC. Currently, the TCMWindTool used to develop the ASOS data for recent TCs impacting the region were wind speed forecast grids assumes a linear decay within used to examine elements that ultimately determine the the 12–24-h wind speed forecast periods. Using RUC gust factors for a given location. The gust factors were analyses, it was shown that recent strong TCs making shown to have a high degree of spread at lower sustained landfall in the region underwent a period of rapid decay wind speeds between 10 and 30 kt. Forecasters are en- in terms of sustained wind speeds. The period of rapid couraged to use the mean gust factor for a given sus- decay was dependent on the angle of storm approach tained wind speed as a starting point. For the lower end with respect to the coastline. The decay occurred over a of the 10–30-kt range, a gust factor of 1.5 is appropriate, period much shorter than the 12–24-hourly temporal while for a 30-kt wind a gust factor of around 1.35 is a resolution of the NHC wind forecast data. The linear suggested starting point. The variation in the gust factor assumption used in the TCMWindTool to create hourly decreased for winds of 30–40 kt and decreased signiﬁ- grids resulted in large error in wind speeds that should cantly for winds greater than 40 kt. The gust factors ap- be accounted for in future times of TC landfall. It is peared to nearly asymptotically decay from 1.3 to 1.2 for suggested that an alternative automatic interpolation sustained wind speeds above 40 kt, although the sample option be added to the TCMWindTool to account for size was much lower for these higher sustained wind this lack of linear decay after landfall, where fore- speeds. No conclusive bias in gust factors was observed casters can select the period of rapid decay within based on wind direction for most locations, indicating that

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FIG. 19. As in Fig. 17, but for gust factors at Salisbury. large-scale upstream surface roughness does not largely characteristics is consistent with a recent analysis of ASOS determine the gust factor for a given location. Instead, data presented in Masters et al. (2010). Participants in the local upstream surface roughness was found to be im- project have developed a set of GFE tools and procedures portant, supported by the preference of lower gust factors to take into account the results of this study. The experi- for Ocean City when the wind direction was from the east. mental WindReductionFactor and WindGustFactor tools This location was located immediately along the coastline, provide forecasters the ﬂexibility to vary land reduction where a difference in local upstream surface roughness and gust factors spatially and temporally across the fore- would be signiﬁcantly different based on wind direction. cast area. The tools allow forecasters to integrate the The results are consistent with the results of several past collective impact of nonlinear storm decay, friction, and studies (e.g., Yu and Chowdhury 2009; Hsu 2001). Fore- fetch into the forecast process. These tools also allow casters should consider the sustained wind speed, wind forecasters to see the land reduction and gust factors from direction, and local upstream surface roughness when other WFOs, resulting in improved collaboration and choosing a gust factor to create wind gust forecasts. more consistent NDFD forecast products. By using the Currently, forecasters typically use the default land same methodology, the tools can provide forecasters with reduction factor in the TCMWindTool of 10% and ap- a common starting point prior to making local edits and ply a single gust factor for all locations in the WFO. The by retaining the previous shifts forecast edits, the meth- gust factor and NDFD analyses suggest that this is not an odology ensures more shift-to-shift continuity. Further- adequate practice. The dependence of both gust factors more, with the addition of the tools, forecasters can and land reduction factors on local surface roughness create reduction and gust factors prior to the NHC TCM

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simulations will examine the characteristics of large eddy circulations associated with TCs and how they impact surface sustained wind speeds, wind gusts, and gust factors. The results of the simulations will be combined with the results presented here to provide more complete guidance for NWS forecasters developing their wind grids during times of TC impact.

Acknowledgments. The authors wish to thank the members of the CSTAR TC Inland Winds group for helpful comments and assistance throughout the course of this project. This includes Gail Hartfield (NOAA/ NWS Raleigh, North Carolina), David Glenn and Carin Goodall (NOAA/NWS Newport, North Carolina), Robert Bright and Frank Alsheimer (NOAA/NWS Charleston, South Carolina), Carl Morgan (NOAA/ NWS Wilmington, North Carolina), John Billet (NOAA/NWS Wakefield, Virginia), and Dr. Michael Brennan (NOAA/National Hurricane Center, Miami, Florida). The authors also appreciate the prompt and useful feedback from Brian Miretzky (NOAA/NWS). The paper greatly benefited from comments provided by three anonymous reviewers. This research was supported by CSTAR Grant NA10NWS4680007.

REFERENCES

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