UNIVERSITY  OF  MIAMI          

VERIFICATION  OF  TROPICAL  CYCLONE  WIND  RADII,  INTENSITY,  AND  TRACK  FORECAST  GUIDANCE  IN  THE  ATLANTIC  BASIN  

   By    

KEVIN  RODRIGUEZ      

A  THESIS    

Submitted  to  the  Faculty  of  the  Rosenstiel  School  of  Marine  and  Atmospheric  Science  

       

Coral  Gables,  Florida    

May  2014    

  2  

Verification of Tropical Cyclone Wind Radii, Intensity, and Track Forecasts Guidance in the

Atlantic Basin Abstract: The  National  Hurricane  Center  (NHC)  is  the  official  source  for  public  information  and  produces  professional  forecasts  for  tropical  cyclones.  Creating  these  forecasts  involves  the  use  of  human  interpretation  and  numerical  guidance  models.  Of  interest  to  the  public  is  to  know  where  the  storm  is  headed,  how  strong  it  will  be,  and  what  impacts  it  will  have.  The  NHC  produces  forecasts  for  storm  track,  intensity,  and  wind  radii,  among  other  parameters.  The  guidance  models  also  produce  forecasts  for  these  three  parameters,  however  there  can  often  be  large  errors  associated  with  these  forecasts.  The  purpose  of  this  study  is  to  analyze  the  errors  in  tropical  cyclone  wind  radii,  intensity,  and  track  forecast  of  operational  and  nonoperational  (or  research)  models  as  compared  to  those  of  the  NHC’s  forecast.  In  this  project  a  code  is  used  that  compares  the  NHC’s  best  track  to  each  storms  model  output.  This  evaluation  is  done  every  six  hours  over  the  entire  storms  lifecycle.  The  project  verified  that  the  global,  regional,  and  statistical  operational  models  excelled  at  accurately  predicting  a  storms  track,  intensity,  and  wind  radii,  respectively.  The  nonoperational  models  showed  some  level  of  skill,  though  they  need  to  be  improved  if  they  are  to  reach  the  same  level  as  the  operational  models.  In  conclusion,  the  NHC  creates  the  best  forecasts  by  using  the  guidance  model  data  and  combining  it  with  the  skills  and  expertise  of  the  forecasters.     1. Introduction Forecasting tropical cyclones is an evolving science that requires numerical modeling and operational skills. The National Hurricane Center (NHC) is the official source for public information and professional forecasts of tropical cyclones. The NHC, stationed in Miami, Florida, provides the public with forecasts, advisories, watches and warnings for tropical cyclones in the Atlantic basin that affect North and Central America, and the Caribbean. The NHC is also in charge of issuing advisories for tropical cyclones in the eastern North Pacific that affect the west coast of Mexico. As a component of the National Centers for Environmental Prediction, the NHC’s mission is to “save lives, mitigate property loss, and improve economic efficiency by issuing the best watches, warnings, forecasts, and analysis of hazardous tropical weather and by increasing understanding of these hazards.” (2012 NHC Forecast Verification Report) As defined by the NHC, a tropical cyclone is a “A warm-core non-frontal synoptic-scale cyclone, originating over tropical or subtropical waters, with organized deep convection and a closed surface wind circulation about a well-defined center. Once formed, a tropical cyclone is maintained by the extraction of heat energy from the ocean at high temperature and heat export at the low temperatures of the upper troposphere. In this they differ from extratropical cyclones, which derive their energy from horizontal temperature contrasts in the atmosphere (baroclinic effects).”

  3  

A tropical storm is a tropical cyclone that has maximum sustained surface winds (using the U.S. 1-minute average) ranging from 39mph (34-kt) to 73mph (63-kt). A hurricane is tropical cyclone with maximum sustained winds of 74mph (64-kt) or greater. The term hurricane is used for tropical cyclones in the Northern Hemisphere that form east of the International Dateline to the Greenwich Meridian, which encompasses the eastern North Pacific, and Atlantic Ocean. An average season in the Atlantic produces 11 tropical storms, 6 hurricanes, and 3 major hurricanes (category 3 or higher). Before continuing on this project, it is important to be familiar with how the NHC issues its tropical cyclone forecasts. NHC forecasts are initialized every six hours at 0000, 0600, 1200, and 1800 UTC, with its projections valid at 12, 24, 36, 48, 72, 96, and 120 hours. My research focuses on analyzing errors in forecasts of hurricane wind radii, intensity, and track, and whether they are correlated to one another. By looking at the tropical cyclones in the NHC database, we will compare and contrast the different operational and nonoperational guidance models against the NHC best track and determine the biases inherent in the numerical models.

Table  1:  NHC  Forecast  Cone  Circle  radii  (nautical  miles)  in  2013.  Changes  from  2012  values  are  expressed  in  nautical  miles  and  percent  are  given  in  the  parenthesis.      

  4  

                             Figure  1:  NHC  Forecast  Track  Error                                        Figure  2:  NHC  Intensity  Forecast  Error  

To begin the verification process we will first review the synoptic history of the five 2012 Atlantic storms, and Hurricane Irene (2011), and the numerical models and methods used in this project. Again, the overall goal is to investigate the operational models and see what their inherent biases and errors are in terms of 34-knot (WRAD-34), 50-knot (WRAD-50) and 64-knot (WRAD-64) wind radii (WRAD), intensity or maximum wind speed (MWND), and forecast track mean absolute error (MAE). The second half will evaluate operational and nonoperational models together with the focus on nonoperation models that could be of potential use to the NHC in the future. 2. Analysis of Atlantic Tropical Cyclones This analysis will look at and discuss the synoptic features of five storms in the 2012 Atlantic Hurricane Season. It will also include the error figures from the NHC Verification reports. This analysis will help us understand the underlying conditions in which these storms were forecasted. A. Irene From NHC Verification Report: Avila and Cangialosi 2011 Lifetime: 21-28 August 2011 Irene was a category 3 hurricane that impacted the northeastern Bahamas, then made its way up the east coast of the United States before making landfall in North Carolina and again in New Jersey. Irene’s biggest impacts were felt in the Northeast as flooding devastated parts of New Jersey, Massachusetts, and Vermont.

  5  

Irene was classified as a tropical storm at 0000 UTC on 21 August. Irene moved west-northwestward and made landfall the next day near Punta Santiago, Humacao, Puerto Rico with sustained winds of 60 knots. Just after landfall, Irene was upgraded to a hurricane after Doppler weather radar indicated hurricane force winds. On 23 August,

Irene tracked near the northeast coast of Hispaniola. Interaction with the mountainous terrain likely kept Irene from strengthening further. After moving away from Hispaniola, Irene began to strengthen and reached its peak intensity of 105 knots (category 3 hurricane) on 24 August. Irene continued its west-

northwest movement as it

crossed Acklins and Crooked Islands later that day. Over the next two days a mid-tropospheric trough developed in the eastern United States and the subtropical jet that had been steering Irene shifted eastward. This opened a path for Irene and the storm began moving northward while impacting the Bahamas as a category 2 hurricane. Irene moved well eastward of Florida and Georgia while weakening. The hurricane made landfall near Cape Lookout, North Carolina at 1200 UTC 27 August with 75-knot winds. Irene continued north-northeastward as its center moved parallel to the Delmarva Peninsula, before making landfall near Atlantic City, New Jersey on 28 August. Approximately four hours later, Irene made landfall for the third time in two days in Coney Island, New York. At this point the storm had maximum winds of 55-knots as it moved inland. Irene became an extratropical system at 0000 UTC on 29 August. B. Ernesto From NHC Verification Report: Brown 2012 Lifetime: 1-10 August 2012 Ernesto was a category 2 hurricane that made landfall in along the southern coast of the Yucatan Peninsula. Prior to becoming a hurricane in the Caribbean Sea, Ernesto affected the Windward Islands as a tropical storm.

Figure  3:  Best  Track  of  Hurricane  Irene

  6  

The NHC issued the first forecast for a newly formed depression by 1200 UTC on 1 August. The depression quickly moved westward to west-northwestward riding the southern edge of a strong mid-level cyclone. The next day convective banding around the center became more concentrated and the depression was upgraded to Tropical Storm Ernesto at 1200 UTC on 2 August. The center of the 40-knot storm passed to the north of Barbados before 0600 UTC on 3 August.

On 6 August, Ernesto was tracking into the western Caribbean Sea. The next day, a period of rapid intensification began as Ernesto moved west-northwestward over the northwestern Caribbean Sea. Ernesto gained hurricane strength at 1200 UTC on 7 August when it was about 225 nautical miles east of Chetumal, Mexico. The hurricane turned westward and continued to strengthen as it approached the coast of the southern Yucatan Peninsula of Mexico. Ernesto first made landfall at Cayo Norte in the Banco Chinchorro Islands of Mexico around 0100 UTC on 8 August. The hurricane continued to strengthen and reached an estimated peak intensity (Figure 4) of 85-knots (category two on the Saffir-Simpson Hurricane Wind Scale) as it made a second landfall at 0315 UTC that same day, on the southern part of the Yucatan Peninsula near Majahual, Mexico. After landfall, Ernesto continued westward and weakened below hurricane strength over the south-central Yucatan Peninsula by 1200 UTC.

Figure  5:  Best  Track  of  Hurricane  Ernesto

Figure  4:  Ernesto  at  peak  strength  on  August  8  (HFIP)

  7  

C. Isaac From NHC Verification Report: Berg 2012 Lifetime: 21 August – 1 September 2012 Isaac developed from a tropical wave in the central Atlantic on 21 August. Over the next few days the storm gained strength as it moved quickly westward by riding a strong deep-layer subtropical ridge over the western Atlantic. The center of the tropical storm moved through the Leeward Islands between the islands of Guadeloupe and Dominica, between 1800 UTC 22 August and 0000 UTC 23 August.

Isaac continued moving westward over the eastern Caribbean Sea until early on 24 August aircraft and satellite data indicated that the structure of the cyclone became less organized when the low-level center reformed farther south and the circulation became more tilted. Nonetheless, Isaac strengthened to an intensity of 55-knot on 24 August when it

turned northwestward toward Hispaniola. Isaac made landfall on the southern coast of Haiti near the city of Jacmel around 0600 25 August. Isaac continued northwestward over the Gulf of Gonâve during the early morning hours of 25 August, and moved just south of the Windward Passage, making landfall along the southeastern coast of Cuba near Cajobabo, Guantánamo, around 1500 UTC with maximum winds of 50-knot. The center emerged from the northern coast of Cuba into the Atlantic near Rafael Freyre, Holguín, around 2015 UTC. Isaac grew in size with tropical-storm-force winds extending up to 180 nautical miles to the north of the center.

Figure  6:  Best  Track  of  Hurricane  Isaac

  8  

After emerging into the Atlantic on 26 August, Isaac turned west-northwestward and gained forward speed while sandwiched between a large deep-layer low over the northwestern Caribbean Sea and a ridge over the western Atlantic. Isaac had maximum sustained winds of 50-knots while moving parallel to Cuba towards the Strait of Florida, and passing the Florida Keys later that day.

On 27 August, Isaac moved into the Gulf of Mexico while its forward progress slowed due to interaction with a subtropical ridge, as seen in Figure 7. The wind field remained large and microwave data showed an organized ring of deep convection around the center. Isaac became a hurricane on 28 August at 1200 UTC when it was 75 nautical miles southeast of the Mississippi River Delta. A mid-level blocking ridge caused Isaac to slow

considerably as it approached the Gulf Coast. Isaac made its first landfall on 29 August at 0000UTC at Southwest Pass near the mouth of the Mississippi River; maximum sustained winds were 70-knots. The center of the storm then wobbled westward over open water and made a second landfall at 0800 UTC near Port Fourchon, Louisiana. D. Michael From NHC Verification Report: Kimberlain and Zelinksi 2012 Lifetime: 3-11 September 2012 Michael was a category 3 hurricane that stayed out over the mid-Atlantic. Michael was an interesting storm because it developed from a non-tropical weather system; it’s only the fifth major hurricane in the satellite era to do so.

Figure  7:  Surface  level  and  thickness  map  of  Isaac  on  27  Aug.  (HFIP)

  9  

On 3 September a small, but well-defined low pressure area formed 730 nautical miles southwest of the Azores, and later that day the wave was upgraded to a tropical depression. The next day at 0600 UTC the depression was upgraded to Tropical Storm Michael. After, Michael entered a region with weak steering flow ahead of a mid-latitude trough that was approaching from

the west. Late on 4 September, vertical wind shear decreased over Michael and it allowed the system to become vertically aligned. An upper-level high had also developed over Michael, and with help from the upper-level trough helped to enhance the outflow over the storm. The next day, Michael then entered a period of rapid intensification that saw its wind speeds increase by 50-knots in 24 hours.

 Figure  9:  500mb  Map  of  Michael  on  4  September  (HFIP)  

On 6 September, the mid-latitude trough passed to the north of Michael and took with it the favorable upper-level pattern that had helped Michael intensify. Michael experienced northwesterly shear that eroded convection on the western side of the storm and caused it to slow and turn towards the northwest. However, as the trough

moved away from Michael the wind shear decreased and allowed the storm to regain its strength. It is estimated that Michael reached its second peak intensity of 90-knots on 8 September.

Figure  5:  Best  Track  of  Hurricane  Michael Figure  8:  Best  Track  of  Hurricane  Michael  

  10  

 Figure  10:  500mb  Map  of  Michael  on  10  September  (HFIP)  

This second intensification phase was short-lived as Michael was steered westward on 9 September under the influence of a mid-level shortwave ridge that developed over the central Atlantic between Hurricane Leslie and Michael. As Michael moved around the ridge, the outflow of Hurricane Leslie led to an increase in northerly vertical wind shear. In addition,

dry air wrapped around the center and was entrained into the inner core, helping to erode the deep convection. As a result Michael weakened to a tropical storm at 0000 UTC 11 September and dissipated 18 hours later. E. Nadine From NHC Verification Report: Brown 2012 Lifetime: 10 September – 3 October 2012 On 11 September, there was enough convection around a newly formed tropical depression, and geostationary satellite imagery and scatterometer data indicate that the depression had grown into a tropical storm. Nadine quickly intensified over the next 24 hours when it was within a low-shear environment and over warm waters. While moving northwestward toward a break in the subtropical ridge, Nadine reached an intensity of 60-knots at 0000 UTC on 13 September. However, the storm started to weaken when it

entered a region of moderate southwesterly shear. Early on 14 September, Nadine turned northward around the western portion of the ridge. Despite the moderate shear, the inner-core convective structure gradually improved that day, and Nadine became a hurricane by 1800 UTC on 14 September. Figure  11:  Nadine's  Surface  level  pressure  and  thickness  map  on  14  September  (HFIP)

  11  

Nadine strengthened slightly over the next few days as it moved eastward around the northern side of a subtropical ridge. Early on 17 September, Nadine decelerated and as it turned towards the east-northeast strong westerly shear caused the deep convection to be separated from the low level center. This led to Nadine being downgraded to a tropical storm. On 18 September, Nadine turned

towards the north before a blocking ridge formed to the north of the storm. After drifting eastward just south of the Azores for two days, the ridge weakened and this pushed Nadine towards the east-southeast. A cold front associated with an upper-level made its way towards Nadine, which caused dry air to wrap around the storm and diminish all deep convection. Nadine lost tropical storm status on 21 September.

On 23 September, the remnant low turned eastward and slowed over an area with warmer waters and less wind shear. This allowed deep convection to redevelop and low was upgraded to Tropical Storm Nadine. A blocking ridge developed north of Nadine again, which caused the storm to move west-northwestward. By 26 September, Nadine was moving south-

southwestward when thunderstorm activity began to blossom around the center. For two days Nadine drifted southward over favorable waters and regained hurricane strength on 28 September. Nadine continued moving northwestward around a mid to upper-level ridge over the central Atlantic. With still favorable conditions, Nadine strengthened to a category 3 hurricane with sustained winds of 80-knots on 30 September. Shortly thereafter, Nadine’s

Figure  13:  Best  Track  of  Hurricane  Nadine

Figure  12:  SLP  map  of  Nadine  on  18  September  (HFIP)

  12  

forward progress was slowed when it became trapped between ridges to the east and west and a trough to the north. On 1 October, an increase in shear and cooler waters caused Nadine to weaken and the storm was downgraded to a tropical storm. The next day, Nadine turned to the southeast, then to the east ahead of a deep-layer trough moving in from Canada. By 3 October, continued shear had weakened Nadine to a tropical storm with winds of 45-knots and on 4 October Nadine became a post-tropical storm.

 Figure  14:  500mb  map  of  Nadine  on  30  September  (HFIP)

Nadine is the fourth longest-lived tropical cyclone in the Atlantic basin, lasting a total of 22.25 days (non-consecutive). F. Sandy From NHC Verification Report: Blake and co. 2012 Lifetime: 22-29 October 2012 Sandy was a once-in-a-lifetime late season hurricane. After developing in the Caribbean in late October, Sandy headed north and made landfalls in Jamaica and Cuba as a category 1 and category 3 hurricane, respectively. After making its way into the Atlantic Sandy tracked north and began a complex evolution, which had Sandy eventually merging with a trough and slamming into the New Jersey coast as a powerful post-tropical system. A tropical wave that had made its way across the Atlantic and into the Caribbean had organized itself enough to be classified as a tropical depression on 22 October. Air Force Reserve Hurricane Hunter aircrafts investigating the storm found the system had reached tropical storm strength only six hours after its genesis. After tracking around in a loop early on the 23 October, Sandy began to strengthen and move northward towards

  13  

Jamaica. At 1200 UTC on 24 October, Sandy gained hurricane status with winds of 75-knots. At 1900 UTC the storm made landfall near Bull Bay, Jamaica. Sandy was unfazed by its brief interaction with land and intensified to a category 3 storm with winds of 100-knots before making landfall west of Santiago de Cuba. After emerging from Cuba, Sandy was affected

by significant southwesterly shear that caused it to weaken to a tropical storm at 0000 UTC on 27 October. However before weakening, a shortwave ridge and negatively tilted upper-level trough had caused Sandy to move northwestward over the Bahamas. Although Sandy had weakened the size of the storm had gradually increased, with the average radii of tropical storm force winds roughly doubling since the time of landfall in Cuba. This was a result of Sandy’s interaction with an upper-level trough, including warm air advection aloft and an extensive increase in upper-level divergence.

 Figure  16:  500mb  map  of  Sandy  on  27  October  (HFIP)

After passing the Bahamas, Sandy gradually turned towards the northeast and its forward speed increased in response to a mid-tropospheric trough making its way through the

Figure  15:  Best  Track  of  Hurricane  Sandy

  14  

central United States. At 1200 UTC 27 October, Sandy regained hurricane strength, but by this point Sandy’s unusual structure showed it was being affected by the upper-level trough to its west. On 28 October, Sandy a few hundred miles southeast of North Carolina, and it took on a more typical tropical appearance with the development of an eye-like structure. On 29 October, Sandy’s track was bent towards the north when it encountered an anomalous blocking pattern over the North Atlantic. A large mid-tropospheric high had built over the northeastern states, and the trough over the central United States continued to deepen. A piece of this trough moved into the southeastern United States, and provided baroclinic forcing for Sandy, along with a significant decrease in vertical wind shear. These factors along with the warm Gulf Stream waters caused Sandy to reach its second peak intensity of 85-kt at 1200 UTC on 29 October. The piece of the trough that broke away into the southeastern United States, now helped to slingshot Sandy towards the northwest late on 29 October. As Sandy approached the New Jersey coast, it moved over cold waters and into a large cold air mass located over the northeastern United States. These factors helped strip Sandy of its tropical characteristics and Sandy became an extratropical system by 2100 UTC that day. Post-Tropical Storm Sandy made landfall near Brigantine, New Jersey at about 2330 UTC, with winds estimated at 70-knots and minimum central pressure of 945mb.

 Figure  17:  500mb  maps  showing  the  progression  of  Sandy  for  28-­‐29  September  (HFIP)  

  15  

3. Methods A. Models Numerical Models are one of the main forecast tools used by forecasters to help predict the weather. These models use a number of mathematical equations that represent the behavior and physics of the atmosphere. Table 2: Models and Parameters Models--Analysis Track Intensity WRAD

Dynamical Global

AVNO, FIM9, EMX

X AVNO, FIM9, EMX

Dynamical Regional

AHW4, COTC, GFDT, H213

AHW4, COTC, GFDT, H213

AHW4, COTC, GFDT, H213

Statistical X SHIPS DRCL, MRCL Human OFCL OFCL OFCL

*The NHC uses only the models in bold face type for their official forecast, other models are experimental. In all graphs and discussions that proceed, the OFCL and H213 are used as benchmarks for comparison of errors among the models. Some models are not used for analyzing certain parameters, because either the model does not produce data for that parameter (statistical models) or due to larger errors inherent from the model itself (global models struggle at intensity). I. Global-Dynamical Models a) AVNO AVNO is old language for the operational GFS model. GFS computes atmospheric variables at twenty-eight different levels in the atmosphere, over the entire global atmosphere. Although, it is considered a hybrid track/intensity type, GFS usually does a better job of predicting the track of a storm when compared to intensity. AVNO is the aviation component of the GFS. (“GFS Introduction”1) b) FIM9 The Flow-Following Finite-Volume Icosahedral Model (FIM) is a global weather prediction model currently under development in the Global Systems of Division of NOAA/ESRL. The 15-kilometer resolution model was developed in 2005. (“Earth System Research Lab”2)

                                                                                                               1  “GFS  Introduction”  < http://www.meted.ucar.edu/nwp/pcu2/avintro.htm>  2  “Earth System Research Laboratory: Global Systems Division: FIM.” <  http://fim.noaa.gov>

  16  

The FIM is a unique combination of three numerical design features. The first is the icosahedral horizontal grid that consists mostly of hexagons, except for 12 pentagons. The second is the isentropic-sigma hybrid vertical coordinate (F for “flow-flowing” in FIM). This feature allows for reduced nonphysical dispersion of tracers such as moisture, potential vorticity, and chemical compounds during lateral transport and lateral eddy mixing. Physical parameterization in the FIM match the ones used operationally by the GFS. The third is the finite-volume horizontal transport. (Bleck 2012) c) ECMWF The European Center for Medium Range Weather Forecasts (ECMWF) is a multi-layer global dynamical forecasting model. Beginning in 1979, the ECMWF consists of an atmospheric general circulation model, an ocean wave model, land surface model, an ocean general circulation model, and perturbation models for the data assimilation (EDA) and forecast (ENS) ensembles, producing forecasts from days to weeks to months ahead. (Andersson 2011) An ensemble of 52 individual ensemble members is created twice daily. One of the members is at a higher spatial resolution (this is called the HRES) and another member of the ensembles is at a lower spatial resolution than the HRES, this one is called the CNTL. The rest of the ensemble members are similar to the CNTL but their initial states and model physics have been perturbed to explore the currently understood uncertainty in their observations and the model. (“Medium Range Forecasts”3) The ECMWF Atmospheric Model high-resolution (HRES) 10-day forecast has a resolution of up to10 kilometers, the highest of any operational model. This allows for better representation of: topographical fields and the effect they have on large-scale flow. It also produces a more accurate description of horizontal and vertical structures. In this study the ECMWF is also referred to as the EMX (in graphics it appears as the EMXX). II. Regional-Dynamical Models a) AHW4 The Advanced Hurricane Weather Research Forecast Model (AHW) is a derivative of the Advanced Research WRF model that maintains a moving nested grid system that allows local resolution of approximately 1 kilometer or less. This makes the model ideal for the prediction of the multiple length scales present in hurricanes. The AHW4 uses an innermost nest of 4 kilometer grid spacing. (Davis et al. 2008)                                                                                                                3  “Medium  Range  Forecasts”  <  http://www.ecmwf.int/en/forecasts/tools-­‐and-­‐guidance/documentation-­‐and-­‐support/medium-­‐range-­‐forecasts>  

  17  

b) COTC The Coupled Ocean and Atmospheric Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) is the Navy’s operational mesoscale model used for research and Department of Defense operations. This model was developed for tropical cyclone analysis and prediction. It includes a 3-Dimensional vertical tropical analysis, synthetic observations for vortex initialization, and has resolutions ranging from 45 to 15 to 5 kilometers. (Doyle, “COAMPS-TC”4) c) GFDT The GFDL Hurricane Prediction System was developed in NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) in Princeton, New Jersey. The Navy has used versions of the GFDL model to provide operation guidance for storms in the Atlantic, Pacific, and other ocean basins. GFDL continues to work on improving this model and has run it during hurricane season for a few years now with significant success. Since its establishment in 1995, the GFDL has provided operational guidance for forecasters at the National Hurricane Center, and has quickly become one of the most reliable models at hand. The GFDT is an extension of the GFDL except that it uses the GFS vortex-tracking algorithm. (“Global Tech List”5) The current GFDL hurricane model is a grid point model that consists of three computational meshes, which are nested together with increasingly finer grid-point spacing in each mesh. The size of the outer mesh is approximately 5000 miles wide with grid points approximately spaced every 30 miles. The finest mesh has the grid points spaced only 5 miles apart and covers a 325 square mile area. This area of fine resolution moves with the hurricane to keep the storm centered in the middle of the innermost computational grid. GFDL is “nested” within the GFS system but specifically focuses on the Atlantic and Pacific basins. (Marchok 20126) d) HWRF/H213 The Hurricane Weather Research Forecast Model (HWRF) provides operational guidance for forecasters at the NHC in both the Atlantic and Pacific basins. Hurricane forecasts are produced on demand every six hours at 00, 06, 12, and 18 UTC for up to five tropical cyclones at one time. The HWRF hurricane model graphics are available at six-hour increments and up to 126 hours. The HWRF system is composed of the WRF model software infrastructure, the Non-Hydrostatic Mesoscale Model (NMM) dynamic core, the three-dimensional POM, the

                                                                                                               4  “The Development of the COAMPS-TC, Transition to Navy Operations, and Future Plans <  http://www.ofcm.gov/ihc14/presentations/Session2/s02-12Doyle%20IHC%20S2-12.pdf> 5  “Global  Tech  List”  < http://www.ral.ucar.edu/hurricanes/repository/techlist/>  6  Marchok  2012  < http://www.gfdl.noaa.gov/operational-hurricane-forecasting>  

  18  

NCEP coupler, and a physics suite tailored to the tropics, including air-sea interactions over warm water and under high wind conditions, and boundary layer and cloud physics developed for hurricane forecasts. It should be noted that even though the HWRF uses the same dynamic core as the NCEP North American Mesoscale (NAM) model, they are different because the HWRF is specifically designed for hurricanes and tropical forecast applications. (“NCEP Model Analysis & Guidance”7) In 2013 the HWRF received an upgrade to its infrastructure, data assimilation, vortex initialization, and physics and ocean processes. The upgraded HWRF is termed as the H213. In this project, the H213 was used because it had smaller errors and biases in the track, intensity, and wind radii forecasts. This is illustrated in figures 18A, 18B, and 18C.

                     Figure  18A:  Isaac  MWND  Error                              Figure  18B:  Isaac  MWND  Error                            Figure  18C:  Isaac  WRAD-­‐34  Error  

III. Statistical Models a) DRCL The DeMaria Climatology and Persistence Model (DRCL) is a statistical-parametric model that employs climatology and persistence to predict a tropical cyclone. This operation model is one of the main radii-CLIPER models used by the NHC to forecast tropical cyclone wind structure in terms of significant wind radii (34-, 50-, and 64-knot wind radii). This model uses a modified Rankine vortex that has been generalized to allow for a wavenumber-1 asymmetry. The DRCL assumes an idealized vortex, that is modified by storm motion and initial conditions. DRCL was developed for the Atlantic and eastern and western North Pacific basins, and produces forecasts through 120 hours. The DRCL has proven to be more skillful in WRAD through approximately 48-72 hours. (Knaff et al. 20078) b) MRCL The McAdie Climatology and Persistence Model (MRCL) is a statistical-parametric model that employs climatology and persistence to predict a tropical cyclone. This operation model is one of the main radii-CLIPER models used by the NHC to forecast                                                                                                                7  “NCEP  Model  Analysis  &  Guidance”  < http://products.weather.gov/PDD/NCEP_PDD_MAG.pdf>  8  Knaff  and  co.  2007  “http://rammb.cira.colostate.edu/resources/docs/Knaff_et_al_2007_wrclip.pdf>  

  19  

tropical cyclone wind structure in terms of significant wind radii (34-, 50-, and 64-knot wind radii). The MRCL was developed for the Atlantic basin and produces forecasts through 72 hours. The MRCL can also be distinguished from the DRCL by it’s 60 separate equations for physical processes. The MRCL has proven to be more skillful in mean absolute error, and in WRAD through approximately 36 hours. (Knaff et al. 20078) c) SHIPS Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a statistical-dynamical model based on statistical relationships between storm behavior and environmental conditions estimated from dynamical model forecasts as well as on climatology and persistence factors. The NHC has traditionally used SHIPS as one of its most skillful models for intensity guidance. SHIPS is based on a standard multiple regression techniques. The predictors for SHIPS include climatology and persistence, atmospheric environmental parameters, and oceanic input such as sea-surface temperatures and ocean heat content, and satellite data such as strength and symmetry of convection from infrared imagery. (“NHC Track and Intensity Models”9) IV. Human Forecast a) OFCL The OFCL is the official NHC forecast. The NHC uses a variety of models as guidance in preparation of their own forecast. The NHC issues its official forecast every six hours at 5 A.M., 11 A.M., 5 P.M., and 11 P.M. Eastern Daylight Time (0900, 1300, 1700, 2100 UTC). B. Verification I. NHC Reports/Best Track At the end of each hurricane season, the NHC issues a verification report that evaluates forecasts by comparing the projected position and intensities to the corresponding post-storm derived “best-track” positions and intensities for each cyclone. The reports allow the NHC to do a “self-evaluation” of its in season forecasts and determine areas they excelled or underperformed in. The NHC’s best track is a subjectively smoothed representation of a tropical cyclone’s location and intensity over its lifetime. The best track contains the cyclone's latitude, longitude, maximum sustained surface winds, and minimum sea-level pressure at 6-hour intervals. Best track positions and intensities may differ from values contained in storm advisories during the season. They also generally will not reflect the erratic motion implied by connecting individual center fix positions.                                                                                                                9  “NHC  Track  and  Intensity  Models”  <  http://www.nhc.noaa.gov/modelsummary.shtml>  

  20  

II. NHC Forecast Parameters Along with forecasts for wind speed and track, the NHC issues forecasts for the size of tropical cyclones. The wind radii forecasts are estimates of the maximum extent of winds at 34-, 50-, and 64-kt that is expected in each quadrant of a storm. However, there is insufficient surface wind information to allow the forecaster to accurately analyze the size of a tropical cyclone’s wind field. As a result, the post-storm best track wind radii are likely to have errors so large that it renders a verification of official radii forecasts unreliable, and potentially misleading. In the future, as our ability to measure surface wind field in tropical cyclones improves, it may be possible to perform a meaningful verification of NHC wind radii forecasts. (2012 NHC Verification Report) III. Mean Absolute Value Error The statistics and calculations for the following models/ensembles were computed for each storm: AVNO, HWRF, GFDT, DRCL, MRCL, FIM9, EMX, AHW4, COTC, and OFCL. It is also worth to note that the code used has some trouble graphing the European model and its ensemble members due to it being issued every 12 hours, instead of six. The three types of graphs that this project investigates are the 34-kt, 50-kt, and 64-kt radii error, maximum wind speed error, and track mean absolute error. The wind radii errors show the error in the 34-, 50-, and 64-kt winds averaged out over the lifetime of the storm. The maximum wind speed error shows the difference from what was predicted as compared to the best track, and then averaged out over the lifetime of the storm. The track mean absolute error compare the forecast (fi) with the actual true value (yi). So the mean absolute error is an average of the absolute errors, where fi is the forecast, yi is the verification, and n is the forecast times.

IV. Overview The track errors are analyzed over the entire 120-hour forecast period. The MWND and WRAD are evaluated up to 72 hours due to the complex nature and uncertainty involved in forecasting these two parameters. At the current moment this project cannot accurately verify if the models.

  21  

Observations that support WRAD analysis are limited. Satellite based instruments, such as scatterometers and radiometers, record data infrequently and rarely capture a storm system as a whole. Aircraft reconnaissance observations have assisted in determining wind radii in recent years, however it does not provide complete coverage of entire circulation’s wind field. (Landsea and Franklin 2012)

Figure  19:  WRAD-­‐34  errors  based  on  observational  capabilities  (Landsea  and  Franklin  2012)  

From the graph, WRAD-34 has an average uncertainty from satellite-only measurements of approximately 40 nautical miles regardless of intensity, ~30 nautical miles from satellite and aircraft measurements, ~25 nautical miles for systems making landfall. These uncertainties are quite large relative to the average WRAD itself. (Landsea and Franklin 2012). Hence, the analysis of

WRAD for hurricanes Ernesto, Michael, and Nadine are not included in this report. These storms spent the majority, if not all, of their lifecycle over open waters and only satellite-based measurements are available. Instead, the focus is on hurricanes Irene, Isaac, and Sandy, which subsequently made landfall in the United States making the verification of WRAD trustworthy. Also, it is important to note that the NHC does not produce any wind radii forecasts past 72 hours. In the results that follow, it is why there is such large error in the wind radii graphs for the 96 and 120-hour forecasts. Since the NHC has no input at that time, the code averages what the models has and gives us an error of the average minus zero from the NHC, thus we end up with extremely large errors. At this point, the NHC does not verify its wind speed radii in their annual verification report due to lack of sufficient and reliable data, and is also why they do not produce any past 3 days. 4. Results Due to the size and nature of this project, there are a few notes that should be kept in mind when looking at, comparing, and analyzing the results. The errors shown in the graphs are in comparison to the NHC’s best track. The error bars in the graphs encompass the range of errors in the models, with the upper and lower bounds being the model runs with the highest and lowest errors. All the graphs show the errors averaged over the entire life cycle of each hurricane. The forecasts are initialized every six hours at 0000, 0600, 1200, and 1800 UTC. The one exception is the EMX, which only runs every 12 hours, thus this model has a smaller sample size. Sections A, B, and C focus on the track, intensity, and wind radii, respectively. Section D looks at segmenting the hurricane’s life cycle. This is done to see if any one model

  22  

outperformed itself or other models during periods when the hurricane was intensifying, weakening, etc. Section E of this project analyzes the forecast initialized at 0000 and 1200 UTC (0,12Z) against those at 0600 and 1800 UTC (6,18Z). Section G provides a visual analysis of the errors mentioned in previous sections. A. Track

               Figure  20A:  Irene  Regional  Model  Track  Error                                Figure  20B:  Irene  Global  Model  Track  Error  

         Figure  20C:  Ernesto  Regional  Model  Track  Error                      Figure  20D:  Ernesto  Global  Model  Track  Error  

  23  

           Figure  20E:  Isaac  Regional  Model  Track  Error                                    Figure  20F:  Isaac  Global  Model  Track  Error  

 

         Figure  20G:  Michael  Regional  Model  Track  Error                    Figure  20H:  Michael  Global  Model  Track  Error  

 

                 Figure  20I:  Nadine  Regional  Model  Track  Error                          Figure  20J:  Nadine  Global  Model  Track  Error  

  24  

                 Figure  20K:  Sandy  Regional  Model  Track  Error                              Figure  20L:  Sandy  Global  Model  Track  Error  

B. Intensity

         Figure  21A:  Irene  Regional  Model  MWND  Error                        Figure  21B:  Irene  Statistical  Model  MWND  Error  

     Figure  21C:  Ernesto  Regional  Model  MWND  Error              Figure  21D:  Ernesto  Statistical  Model  MWND  Error  

  25  

           Figure  21E:  Isaac  Regional  Model  MWND  Error                        Figure  21F:  Isaac  Statistical  Model  MWND  Error  

     Figure  21G:  Michael  Regional  Model  MWND  Error            Figure  21H:  Michael  Statistical  Model  MWND  Error  

       Figure  21I:  Nadine  Regional  Model  MWND  Error                        Figure  21J:  Nadine  Statistical  Model  MWND  Error  

  26  

         Figure  21K:  Sandy  Regional  Model  MWND  Error                    Figure  21L:  Sandy  Statistical  Model  MWND  Error  

C. Wind Radii

                 Figure  22A:  Irene  Regional  Model  WRAD-­‐34  Error                                      Figure  22B:  Irene  Global  Model  WRAD-­‐34  Error                                          

                 Figure  22C:  Irene  Statistical  Model  WRAD-­‐34  Error  

  27  

                   Figure  23A:  Isaac  Regional  Model  WRAD-­‐34  Error                                            Figure  23B:  Isaac  Global  Model  WRAD-­‐34  Error                    

                               

                 Figure  23C:  Isaac  Statistical  Model  WRAD-­‐34  Error                                    Figure  24A:  Sandy  Regional  Model  WRAD-­‐34  Error                                                  

                         Figure  24B:  Sandy  Global  Model  WRAD-­‐34  Error                              Figure  24C:  Sandy  Statistical  Model  WRAD-­‐34  Error  

 

  28  

D. Segmented Analysis

                                 Figure  25A:  Nadine  Segment  1  Sept.  11-­‐16                                                                      Figure  25B:  Nadine  Segment  2  Sept.  16-­‐22  

 

                                 Figure  25C:  Nadine  Segment  3  Sept.  23-­‐29                                                              Figure  25D:  Nadine  Segment  4  Sept.  29-­‐Oct.  4  

The purpose of this section is to study the different segments of a hurricane’s lifecycle and find any correlations, if any, to the errors in the models. Nadine was chosen due to its long lifecycle of approximately 22 days. The first segment is from September 11-16, second segment is from 16-22 September, third segment is from 23-29 September, and the fourth segment is from 29 September – 4 October. The results however, are inconclusive. No patters emerged from analyzing different segments of the storm. There is no correlation between the models and parameters forecasted. In other words, per parameter there is no model that consistently has the smallest errors in all or most of the four segments. The WRAD is the only parameter to keep some semblance of consistency among the models as seen in Figures 25A-D, where the OFCL and H213 are among the best models for at least two of the segments. A conclusion can be made that the results can vary during different parts of the lifecycle of the tropical cyclone. This was only done for Hurricane Nadine, thus a bigger sample size is warranted in future studies to verify these results in other storms.

  29  

E. 0,12Z vs. 6,18Z Initialization Times

                             Figure  26A:  Isaac  0,12Z  WRAD-­‐34  Forecasts                                                        Figure  26B:  Isaac  6,18Z  WRAD-­‐34  Forecasts    

 

                             Figure  27A:  Sandy  0,12Z  WRAD-­‐34  Forecasts                                                      Figure  27B:  Sandy  6,18Z  WRAD-­‐34  Forecasts    

The 0,12Z and 6,18Z initialization times are looked at to see if there are any differences between the two. The results show that the errors between the two sets of initialized forecasts are negligibly small, so no one set of initialization time outperformed the other. Also, there is no consistency in regards to when errors grow or decay in terms of model and forecast hour. In terms of individual parameters, the WRAD provided the only sizable change in errors. The errors for 6,18Z are between 5-15 knots larger than the errors for 0,12Z. This provides an interesting benchmark to work on, though the sample size is relatively small so this will need to be examined in future studies. For MWND, the errors did grow and decay based on the initialization times, though there was never any consistency among them. There was no change in track errors between the two sets of initialization times. F. Model Ranks Table 3 tabularizes the results from the graphs seen above. With this table it is easier to see which models had good results and which did not. In parenthesis is the forecast time taken into account when ranking the models. The global models are highlighted in red,

  30  

regional models are blue, statistical models are green, and OFCL is black. Models that had better results than the NHC are shown in boldface type. Table 3: Storm-Model Rankings Storm/Ranking Track

Errors (120-hours)

MWND Errors

(72-hours)

WRAD-34 Errors

(72-hours)

WRAD-50 Errors

(72-hours)

WRAD-64 Errors

(72-hours) Irene Track Intensity 34-kt 50-kt 64-kt

Rank 1 AVNO COTC OFCL MRCL MRCL Rank 2 EMX H213 MRCL OFCL DRCL Rank 3 H213 AHW4 COTC DRCL OFCL Rank 4 OFCL SHIP AVNO H213 AHW4 Rank 5 FIM2 OFCL H213 AHW4 COTC Ernesto Track Intensity 34-kt 50-kt 64-kt Rank 1 EMX OFCL OFCL OFCL OFCL Rank 2 AVNO H213 MRCL AHW4 MRCL Rank 3 FIM9 COTC DRCL GFDT DRCL Rank 4 OFCL AHW4 H213 H213 GFDT Rank 5 H213 GFDT AHW4 AVNO AHW4 Isaac Track Intensity 34-kt 50-kt 64-kt

Rank 1 FIM9 AVNO OFCL OFCL COTC Rank 2 AVNO OFCL MRCL DRCL OFCL Rank 3 OFCL COTC DRCL MRCL MRCL Rank 4 H213 GFDT H213 COTC DRCL Rank 5 EMX H213 AVNO AHW4 AHW4 Michael Track Intensity 34-kt 50-kt 64-kt Rank 1 OFCL SHIP OFCL OFCL MRCL Rank 2 EMX H213 GFDT GFDT OFCL Rank 3 FIM9 OFCL COTC MRCL GFDT Rank 4 AVNO COTC AVNO COTC AHW4 Rank 5 H213 AHW4 H213 AHW4 COTC Nadine Track Intensity 34-kt 50-kt 64-kt Rank 1 EMX OFCL OFCL OFCL OFCL Rank 2 AVNO SHIP MRCL MRCL DRCL Rank 3 OFCL AVNO H213 DRCL MRCL Rank 4 FIM9 COTC AVNO H213 COTC Rank 5 H213 H213 AHW4 AVNO FIM9 Sandy Track Intensity 34-kt 50-kt 64-kt

Rank 1 EMX AHW4 H213 OFCL AHW4 Rank 2 OFCL OFCL AHW4 H213 COTC Rank 3 AVNO H213 GFDT AHW4 OFCL Rank 4 FIM9 COTC OFCL GFDT GFDT Rank 5 GFDT GFDT COTC AVNO AVNO

  31  

G. HFIP Analysis The Hurricane Forecast Improvement Project (HFIP) provides the basis for NOAA and other agencies to coordinate hurricane research needed to significantly improve guidance for hurricane track, intensity, and storm surge forecasts. The goal of HFIP is to improve the accuracy and reliability of hurricane forecasts, increase lead time for hurricane forecasts, and to increase confidence in hurricane forecasts.10 In this project, the HFIP graphs are used to give a visual representation of the statistics computed and derived conclusions. The HFIP and this project both look at the AVNO (GFS on HFIP), FIM9 GFDL (similar to GFDT), and H213 (HWRF on HFIP). Some of the largest spread among the models came during Hurricane Sandy. The following graphs give a visualization of the difference in errors among the models, as well as the difference in the wind field, and storm structure.

     Figure  28A:  FIM9  72-­‐hr  forecast  from  27  Oct.  at  00Z                                Figure  28B:  GFDL  72-­‐hr  forecast  from  27  Oct.  at  00Z                              

     Figure  28C:  GFS  72-­‐hr  forecast  from  27  Oct.  at  00Z                                      Figure  28D:  HWRF  72-­‐hr  forecast  from  27  Oct.  at  00Z                              

Figures 28A-D is the 72-hour forecast initialized on 27 October at 0000 UTC. The most important difference between the four models is the location of Hurricane Sandy. The HWRF has Sandy turning out to sea while the other three models have Sandy making landfall in the northeast from Delaware to New York. All four models had similar wind field, with maximum winds located to south and east of the center.                                                                                                                10  HFIP  Website  <  http://www.hfip.org/>    

  32  

     Figure  29A:  FIM9  24-­‐hr  forecast  from  29  Oct.  at  00Z                                Figure  29B:  GFDL  24-­‐hr  forecast  from  29  Oct.  at  00Z                              

         Figure  29C:  GFS  24-­‐hr  forecast  from  29  Oct.  at  00Z                                  Figure  29D:  HWRF  24-­‐hr  forecast  from  29  Oct.  at  00Z                              

Figures 29A-D is the 24-hour forecast initialized on 29 October at 0000 UTC. With Sandy only 24 hours from making landfall the most important characteristic in the models is the intensity of the storm. The regional models were superior as the global models are biased towards a weaker storm in terms of wind speed and surface pressure. Though, all the models are in fair agreement that Sandy will make landfall in New Jersey. 5. Discussion A. Track The models do relatively well in forecasting the track. The global models have skill in forecasting track over the regional models, and most of the time, over the OFCL forecast. For the first 72-hours, there is no substantial difference in errors between the OFCL and three global models. The difference is evident in the long-term forecast where the EMX and AVNO set themselves apart. While the general consensus gives the EMX an edge over the AVNO, this study has found that the AVNO has the same relative skill in forecasting track as the EMX. The NHC does and should continue to utilize the EMX and AVNO to their fullest when creating track forecasts. The FIM9 has some promise, though it is inconsistent at times. While the FIM proves astoundingly useful in other global weather forecasting parameters, its tropical and hurricane-forecasting abilities need to be improved. Overall, the NHC does a remarkable job in forecasting a hurricane’s track.

  33  

B. Intensity The skill in forecasting intensity of the regional models far surpasses those of the global models. This is due to the higher resolution regional models posses, which allows them to better create and model the smaller courser features within a hurricane’s inner structure. The AVNO is the only global model to have some success forecasting intensity, as it was the best model for Isaac, and second best model for Nadine. The EMX is the worst model for predicting intensity. The H213 is the most skillful of the regional and statistical models. The H213 is often equal to or better than the SHIPS model in all the storms, with the exception of Nadine. While SHIPS did have a bad year in 2012, it is interesting that the H213 outperformed one of the NHC’s best intensity models. The COTC also had an underperforming year in 2012, though its intensity forecasts were the second best among the regional models only behind the H213. The GFDT and AHW4 at times have shown skill in forecasting intensity, though neither model is consistent. When looking at the errors among the top models and OFCL per storm there is only a difference of approximately 5 knots. Meaning, in the critical forecasting period of up to 72-hours, the OFCL accurately predicted the intensity of each storm with the same level of confidence, if not higher, than SHIPS and the regional models. C. Wind Radii The wind radii is one of the hardest parameters for the NHC and guidance models to forecast. Still, it is clear from the graphs and table that the OFCL forecast has higher skill than the operational models in forecasting the wind speed radii. Sandy is the only instance where the OFCL was surpassed by any model. Again the WRAD analysis focuses on Irene, Isaac, and Sandy, because all three made landfall in the United States and have substantial satellite and aircraft reconnaissance data. The DRCL and MRCL are the simplest models for WRAD and form the benchmark that other models should reach. The statistical models are superior to the global models in predicting WRAD for all the hurricanes in the study, as is evident in Figures 22A-C, 23A-C and 24A-C. There are also cases where the statistical models outperform the regional models. Figures 23A and 23C show that for Hurricane Isaac, the DRCL and MRCL have greater skill than the H213 and AVNO, the best regional model and best global model in forecasting WRAD for this storm, respectively. From Table 2, the MRCL in particular bests all the other guidance models in WRAD-34 forecasts for hurricanes Irene, Ernesto, and Nadine. The regional models, still usually worse than the DRCL and MRCL, excelled in with the WRAD-34. The two WRF models had the smallest WRAD-34 errors for hurricanes Isaac and Sandy. The AHW4 was the best model for Sandy, though it was inconsistent with its predictions for other storms. The H213 is the most consistent regional model at forecasting WRAD-34, with the COTC showing some promise, though it struggled in the

  34  

early forecasts. The regional models do provide some added value for WRAD, however they should be used in junction with the statistical models when making forecasts. The global models struggled with the WRAD, though this is expected since these models do not have the resolution needed to zone in on the wind field of a hurricane (similar issue with the intensity forecasts). However, AVNO did relatively well compared to other global models. For hurricanes Irene and Isaac it was the third best dynamical model behind the H213 and COTC. As with intensity, the FIM9 and EMX struggled to predict the WRAD-34. The WRAD-50 errors for Irene, Isaac, and Sandy reflect the same patter as the WRAD-34 for those storms, except the errors are smaller. Typical values are between 30-50 knots. The WRAD-64 errors are consistent for all storms and models in terms of value. No model had errors larger than 20 knots for WRAD-64, and the 1-3 day forecast range most had errors around 10 knots. This level trend is to be expected, because the higher the wind speeds are, the smaller the radii of those winds are, and the easier it is to predict. Thus, the WRAD-50 and WRAD-64 rakings in Table 2 should not be taken too harshly as all the models had similar errors, and because there is no verification of radii data for hurricanes Ernesto, Michael, and Nadine due to lack of aircraft and observational data. From this study, it is a worthwhile recommendation that the NHC begin verifying its wind radii predictions to compliment the verifications from the models. At the very least, this could be on storms that made landfall and have substantial satellite and aircraft data available. 6. Summary The results so far from this project have given us an idea of how well the operational models match against the best track and NHC forecasts. The OFCL is the best forecast for the wind radii, and it is also among the best in terms of predicting intensity and track. The AVNO and EMX are the go-to models for track as is seen in Table 3. The H213 and COTC are the best regional models for intensity. However, the statistical models have shown they can match and even outperform the regional models when it comes to forecasting intensity. Thus, while the regional models do provide some added value they should not be solely relied upon for forecasting intensity. The DRCL and MRCL have an edge over the dynamical models in terms of predicting WRAD. With the exception of Sandy, the statistical models were more readily able to predict the extent of a hurricane’s wind field. It is also evident that in the 2012 season, no one model had significantly better results in track, intensity, or wind radii. Additionally, there are no outstanding correlation between wind radii errors and wind speed or track errors. Generally the trend was models that have smaller wind radii errors also have smaller track and wind speed errors.

  35  

It is fair to conclude, that the NHC does a spectacular job in creating the best forecast for the public by taking the data from the models discussed in this project, and combining it with the experience and skill of its forecasters. 7. Acknowledgments The author thanks Sharan Majumdar for his continued support and dedication throughout this project. Thanks also go out to Ryan Torn from the University of Albany and his PhD student, Jeremy Berman. Special considerations for Paquita Zuidema and Brian Mapes whose comments and contributions helped improve this paper.

  36  

References Andersson, Erik. “User Guide to ECMWF Forecast.” ECMWF. 23 July. 2013. Web. 29 April. 2014. <  http://old.ecmwf.int/products/forecasts/guide/user_guide.pdf> Avilia, Lixion A., Cangialosi, John P. “Tropical Cyclone Report Hurricane Irene.” National Hurricane Center. 14 December. 2011. Web. 23 April. 2014. <  http://www.nhc.noaa.gov/data/tcr/AL092011_Irene.pdf> Berg, Robbie. “Tropical Cyclone Report Hurricane Isaac.” National Hurricane Center. 28 January. 2013. Web. 9 December. 2013. <http://www.nhc.noaa.gov/data/tcr/AL092012_Isaac.pdf> Blake, Eric S., Kimberlain, Todd B., Berg, Robert. J., Cangialosi, John P., Beven III, John L. “Tropical Cyclone Report Hurricane Sandy.” National Hurricane Center. 12 February. 2013. Web. 9 December. 2013. <http://www.nhc.noaa.gov/data/tcr/AL182012_Sandy.pdf> Bleck, Rainer., et al. “FIM Documentation.” National Oceanic and Atmospheric Administration. 13 November. 2012. Web. 29 April. 2014 <  http://fim.noaa.gov/fimdocu_rb.pdf> Brown, Daniel P. “Tropical Cyclone Report Hurricane Ernesto.” National Hurricane Center. 20 February. 2013. Web. 9 December. 2013. <http://www.nhc.noaa.gov/data/tcr/AL052012_Ernesto.pdf> Brown, Daniel P. “Tropical Cyclone Report Hurricane Nadine.” National Hurricane Center. 8 January. 2013. Web. 9 December. 2013. <http://www.nhc.noaa.gov/data/tcr/AL142012_Nadine.pdf> Cangialosi, John P., and Franklin, James L. “2012 National Hurricane Center Forecast Verification Report.” National Hurricane Center. 22 March, 2013. Web. 15 December. 2013. <http://www.nhc.noaa.gov/verification/pdfs/Verification_2012.pdf> Davis, Christopher, et al., “Prediction of Landfalling Hurricanes with the Advanced Hurricane WRF Model.” Monthly Weather Review. June 2008. Web. 1 April. 2014. Doyle, James D., et al. “The Development of the COAMPS-TC, Transition to Navy Operations, and Future Plans.” Naval Research Laboratory, Monterey, California. n.d. Presentation. 29 March. 2014. <  http://www.ofcm.gov/ihc14/presentations/Session2/s02-12Doyle%20IHC%20S2-12.pdf> “Earth System Research Laboratory: Global Systems Division: FIM.” U.S. Department of Commerce/National Oceanic and Atmospheric Administration. 12 April. 2014. Web. 29 April. 2014. <  http://fim.noaa.gov>

  37  

Evans, Clark. “Hurricane Forecast Model Output.” University of Wisconsin-Milwaukee. 2007. Web. 23 September. 2013. <http://derecho.math.uwm.edu/models/models.html> “GFS Introduction.” MetEd. n.p. n.d. Web. 14 December. 2013. <  http://www.meted.ucar.edu/nwp/pcu2/avintro.htm> “Global Tech List.” Tropical Cyclone Guidance Project, NCAR. Vigh, John. n.d. Web. 9 December. 2013. <http://www.ral.ucar.edu/hurricanes/repository/techlist/> Hurricane Program Improvement Project. National Ocean and Atmospheric Administration. 2011. Web. November 2012. Kimberlain, Todd B., Zelinsky, David A. “Tropical Cyclone Report Hurricane Michael.” National Hurricane Center. 4 December. 2012. Web. 9 December. 2013. <http://www.nhc.noaa.gov/data/tcr/AL132012_Michael.pdf> Knaff, John A., Sampson, Charles R., DeMaria, Mark, Marchok, Timothy P., Gross, James M., McAdie, Colin J. “Statistical Tropical Cyclone Wind Radii Prediction Using Climatology and Persistence.” AMS. August 2007. Web. 13 December. 2013. <  http://rammb.cira.colostate.edu/resources/docs/Knaff_et_al_2007_wrclip.pdf> Landsea, Christopher W., Franklin, James L., “Atlantic Hurricane Database Uncertainty and Presentation of a New Database Format.” Monthly Weather Review. October 2013. Web. 11 January. 2014. Marchok, Tim. “Operational Hurricane Track and Intensity Forecasting.” Geophysical Fluid Dynamics Laboratory. n.p. n.d. Web. 14 December. 2013. <  http://www.gfdl.noaa.gov/operational-hurricane-forecasting> “Medium Range Forecasts.” ECMWF. n.d. Web. 29 April. 2014. <  http://www.ecmwf.int/en/forecasts/tools-and-guidance/documentation-and-support/medium-range-forecasts> “NHC Track and Intensity Models.” NOAA/NWS/NCEP/NHC. 24 July. 2009. Web. 29 April. 2014. <  http://www.nhc.noaa.gov/modelsummary.shtml> “Product Description Document: NCEP Model Analysis and Guidance.” n.p. July 2013. Web. 14 December. 2013. <  http://products.weather.gov/PDD/NCEP_PDD_MAG.pdf>