Results 1  10
of
21
2005: Further improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS
 Wea. Forecasting
"... Modifications to the Atlantic and east Pacific versions of the operational Statistical Hurricane Intensity Prediction Scheme (SHIPS) for each year from 1997 to 2003 are described. Major changes include the addition of a method to account for the storm decay over land in 2000, the extension of the fo ..."
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Cited by 95 (17 self)
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Modifications to the Atlantic and east Pacific versions of the operational Statistical Hurricane Intensity Prediction Scheme (SHIPS) for each year from 1997 to 2003 are described. Major changes include the addition of a method to account for the storm decay over land in 2000, the extension of the forecasts from 3 to 5 days in 2001, and the use of an operational global model for the evaluation of the atmospheric predictors instead of a simple dryadiabatic model beginning in 2001. A verification of the SHIPS operational intensity forecasts is presented. Results show that the 1997–2003 SHIPS forecasts had statistically significant skill (relative to climatology and persistence) out to 72 h in the Atlantic, and at 48 and 72 h in the east Pacific. The inclusion of the land effects reduced the intensity errors by up to 15 % in the Atlantic, and up to 3 % in the east Pacific, primarily for the shorterrange forecasts. The inclusion of land effects did not significantly degrade the forecasts at any time period. Results also showed that the 4–5day forecasts that began in 2001 did not have skill in the Atlantic, but had some skill in the east Pacific. An experimental version of SHIPS that included satellite observations was tested during the 2002 and 2003 seasons. New predictors included brightness temperature information from Geostationary Operational
An operational statistical typhoon intensity prediction scheme for
 the Western North Pacific, Weather and Forecasting
, 2005
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Statistical Tropical Cyclone Wind Radii Prediction Using Climatology and Persistence
, 2005
"... An operational model used to predict tropical cyclone wind structure in terms of significant wind radii (i.e., 34, 50, and 64kt wind radii, where 1 kt � 0.52 m s �1) at the National Oceanic and Atmospheric Administration/National Hurricane Center (NHC) and the Department of Defense/Joint Typhoon ..."
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Cited by 11 (4 self)
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An operational model used to predict tropical cyclone wind structure in terms of significant wind radii (i.e., 34, 50, and 64kt wind radii, where 1 kt � 0.52 m s �1) at the National Oceanic and Atmospheric Administration/National Hurricane Center (NHC) and the Department of Defense/Joint Typhoon Warning Center (JTWC) is described. The statisticalparametric model employs aspects of climatology and persistence to forecast tropical cyclone wind radii through 5 days. Separate versions of the model are created for the Atlantic, east Pacific, and western North Pacific by statistically fitting a modified Rankine vortex, which is generalized to allow wavenumber1 asymmetries, to observed values of tropical cyclone wind radii as reported by NHC and JTWC. Descriptions of the developmental data and methods used to formulate the model are given. A 2yr verification and comparison with operational forecasts and an independently developed wind radii forecast method that also employs climatology and persistence suggests that the statisticalparametric model does a good job of forecasting wind radii. The statisticalparametric model also provides reliable operational forecasts that serve as a baseline for evaluating the skill of operational forecasts and other wind radii forecast methods in these tropical cyclone basins. 1.
Advances and Challenges at the National Hurricane Center
, 2008
"... The National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over t ..."
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Cited by 5 (0 self)
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The National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15–20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation’s hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges. 1.
Experiments with a Simple Tropical Cyclone Intensity Consensus
, 2007
"... Consensus forecasts (forecasts created by combining output from individual forecasts) have become an integral part of operational tropical cyclone track forecasting. Consensus aids, which generally have lower average errors than individual models, benefit from the skill and independence of the conse ..."
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Cited by 4 (4 self)
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Consensus forecasts (forecasts created by combining output from individual forecasts) have become an integral part of operational tropical cyclone track forecasting. Consensus aids, which generally have lower average errors than individual models, benefit from the skill and independence of the consensus members, both of which are present in track forecasting, but are limited in intensity forecasting. This study conducts experiments with intensity forecast aids on 4 yr of data (2003–06). First, the skill of the models is assessed; then simple consensus computations are constructed for the Atlantic, eastern North Pacific, and western North Pacific basins. A simple (i.e., equally weighted) consensus of three topperforming intensity forecast models is found to generally outperform the individual members in both the Atlantic and eastern North Pacific, and a simple consensus of two topperforming intensity forecast models is found to generally outperform the individual members in the western North Pacific. An experiment using an ensemble of dynamical model track forecasts and a selection of model fields as input in a statistical–dynamical intensity forecast model to produce intensity consensus members is conducted for the western North Pacific only. Consensus member skill at 72 h is low (0.4 % to 14.2%), and there is little independence among the members. This experiment demonstrates that a consensus of these
A deterministic rapid intensification aid
 Weather Forecast
, 2011
"... Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. ..."
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Cited by 2 (1 self)
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Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)21; or 12.9, 15.4, and 18.0 m s21 (24 h)21] for the 24h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50 % probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40 % threshold for producing the RI aid initially. The 40 % threshold is available for approximately 8 % of all verifying forecasts, produces approximately 4 % reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill). 1.
2006: PassiveMicrowaveEnhanced Statistical Hurricane Intensity Prediction Scheme
 Wea. Forecasting
"... The formulation and testing of an enhanced Statistical Hurricane Intensity Prediction Scheme (SHIPS) using new predictors derived from passive microwave imagery is presented. Passive microwave imagery is acquired for tropical cyclones in the Atlantic and eastern North Pacific basins between 1995 and ..."
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Cited by 1 (0 self)
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The formulation and testing of an enhanced Statistical Hurricane Intensity Prediction Scheme (SHIPS) using new predictors derived from passive microwave imagery is presented. Passive microwave imagery is acquired for tropical cyclones in the Atlantic and eastern North Pacific basins between 1995 and 2003. Predictors relating to the innercore (within 100 km of center) precipitation and convective characteristics of tropical cyclones are derived. These predictors are combined with the climatological and environmental predictors used by SHIPS in a simple linear regression model with change in tropical cyclone intensity as the predictand. Separate linear regression models are produced for forecast intervals of 12, 24, 36, 48, 60, and 72 h from the time of a microwave sensor overpass. Analysis of the resulting models indicates that microwave predictors, which provide an intensification signal to the model when aboveaverage precipitation and convective signatures are present, have comparable importance to vertical wind shear and SSTrelated predictors. The addition of the microwave predictors produces a 2%–8 % improvement in performance for the Atlantic and eastern North Pacific tropical cyclone intensity forecasts out to 72 h when compared with an environmentalonly model trained from the same sample. Improvement is also observed when compared against the current version of SHIPS. The improvement in both basins is greatest for substantially intensifying or weakening tropical cyclones. Improvement statistics are based on calculating the forecast error for each tropical cyclone while it is held out of the training sample to approximate the use of independent data. 1.
A statistical model to forecast shortterm Atlantic hurricane intensity
 Weather and Forecasting
, 2007
"... An alternative 24h statistical hurricane intensity model is presented and verified for 13 hurricanes during the 2004–05 seasons. The model uses a new method involving a discriminant function analysis (DFA) to select from a collection of multiple regression equations. These equations were developed ..."
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An alternative 24h statistical hurricane intensity model is presented and verified for 13 hurricanes during the 2004–05 seasons. The model uses a new method involving a discriminant function analysis (DFA) to select from a collection of multiple regression equations. These equations were developed to predict the future 24h wind speed increase and the 24h pressure drop that were constructed from a dataset of 103 hurricanes from 1988 to 2003 that utilized 25 predictors of rapid intensification. The accuracy of the 24h wind speed increase models was tested and compared with the official National Hurricane Center (NHC) 24h intensity forecasts, which are currently more accurate on average than other 24h intensity models. Individual performances are shown for Hurricanes Charley (2004) and Katrina (2005) along with a summary of all 13 hurricanes in the study. The average error for the 24h wind speed increase models was 11.83 kt (1 kt 0.5144 m s1) for the DFAselected models and 12.53 kt for the official NHC forecast. When the DFA used the correctly selected model (CSM) for the same cases, the average error was 8.47 kt. For the 24h pressure reduction models, the average error was 7.33 hPa for the DFAselected models, and 5.85 hPa
1 Deterministic forecasting and verification: A busted system?
, 2006
"... The continuous forecast probability distribution, now approachable from operational ensemble prediction systems, provides an avenue to take a fresh look at the theory of deterministic forecasting and verification. Traditional deterministic forecast verification in terms of summary verification measu ..."
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Cited by 1 (0 self)
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The continuous forecast probability distribution, now approachable from operational ensemble prediction systems, provides an avenue to take a fresh look at the theory of deterministic forecasting and verification. Traditional deterministic forecast verification in terms of summary verification measures (e.g. rootmeansquared error, mean absolute error) has engendered forecast strategies to minimize these measures. Although used deterministically, these strategies are formally related to the forecast probability distribution; the mean of the distribution minimizes the expected squared error, while the median minimizes the expected absolute error. It is not clear, however, that a deterministic forecast strategy demanding prediction of the mean or the median of the forecast probability distribution is actually desirable. If one accepts that the goal of deterministic forecasting should be to predict the most likely future outcome, the correct strategy is to predict the mode of the forecast probability distribution. Promotion of such a forecast strategy can be accomplished through (summary measure) verification only if the mode of the forecast probability distribution happens to equal the mean or the median, as in a Gaussian distribution. For a nonGaussian forecast probability distribution, this correspondence is lost, leaving no route to encourage prediction of the most likely outcome through verification. We conclude then, that the coupled system of deterministic forecasting and verification is not defensible when forecast probability distributions can be nonGaussian. The necessary recourse is to adopt a fully probabilistic system of forecasting and verification.
ANNUAL SUMMARY Atlantic Hurricane Season of 2009
, 2010
"... The 2009 Atlantic season was marked by belowaverage tropical cyclone activity with the formation of nine tropical storms, the fewest since the 1997 Atlantic hurricane season. Of these, three became hurricanes and two strengthened into major hurricanes (category 3 or higher on the Saffir–Simpson Hur ..."
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The 2009 Atlantic season was marked by belowaverage tropical cyclone activity with the formation of nine tropical storms, the fewest since the 1997 Atlantic hurricane season. Of these, three became hurricanes and two strengthened into major hurricanes (category 3 or higher on the Saffir–Simpson Hurricane Wind Scale). In addition, there were two tropical depressions that did not reach storm strength. The numbers of tropical storms and hurricanes were below the longterm averages of 11 named storms and 6 hurricanes, although the number ofmajor hurricanes equaled the longtermaverage of 2. Many of the cyclones remained relatively weak. Only one tropical cyclone, Tropical Storm Claudette, made landfall in the United States, although Ida affected the northern Gulf Coast as a tropical storm before moving inland as an extratropical cyclone.HurricaneBill andTropical StormDanny indirectly affected theEastCoast byproducinghigh surf, rip currents, and beacherosion;Bill also produced tropical stormconditions overBermudaandparts ofAtlanticCanada.Hurricane Idamade landfall in Nicaragua and also affected parts of Honduras, the Yucatan Peninsula of Mexico, and western Cuba. Tropical StormErika hadminor effects on the northern Leeward Islands, mainly in the form of light rain, and Tropical StormGrace moved through the Azores with little impact. The death toll from the 2009 Atlantic tropical cyclones was six. A verification of National Hurricane Center official forecasts during 2009 is also presented. Official track errors and forecast skill set records for accuracy at lead times between 24 and 72 h. Official intensity forecast errors were mostly larger than the previous 5yr means, although intensity forecast skill was at or above historical highs since the intensity skill baseline [i.e., DecayStatistical Hurricane Intensity Forecast model version 5 (DecaySHIFOR5)] errors were well above average. 1.