National Hurricane Center Forecast Research Articles

Operational Storm Surge Forecasting at the National Hurricane Center: The Case for Probabilistic Guidance and the Evaluation of Improved Storm Size Forecasts Used to Define the Wind Forcing

Abstract The primary source of guidance used by the Storm Surge Unit (SSU) at the National Hurricane Center (NHC) for issuing storm surge watches and warnings is the Probabilistic Tropical Storm Surge model (P-Surge). P-Surge is an ensemble of Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model forecasts that is generated based on historical error distributions from NHC official forecasts. A probabilistic framework is used for operational storm surge forecasting to account for uncertainty related to the tropical cyclone track and wind forcing. Previous studies have shown that the size of a storm’s wind field is an important factor that can affect storm surge. A simple radius of maximum wind (RMW) prediction scheme was developed to forecast RMW based on NHC forecast parameters. Verification results indicate this scheme is an improvement over the RMW forecasts used by previous versions of P-Surge. To test the impact of the updated RMW forecasts in P-Surge, retrospective cases were selected from 25 storms from 2008 to 2020 that had an adequate number of observations. Evaluation of P-Surge forecasts using these improved RMW forecasts shows that the probability of detection is higher for most probability of exceedance thresholds. In addition, the forecast reliability is improved, and there is an increase in the number of high probability forecasts for extreme events at longer lead times. The improved RMW forecasts were recently incorporated into the operational version of P-Surge (v2.9), and serve as an important step toward extending the lead time of skillful and reliable storm surge forecasts.

An Examination of Model and Official National Hurricane Center Tropical Cyclone Size Forecasts

AbstractWhile the National Hurricane Center (NHC) has been issuing analyses and forecasts of tropical cyclone wind radii for several years, little documentation has been provided about the errors in these forecasts. A key hurdle in providing routine verification of these forecasts is that the uncertainty in the wind radii best tracks is quite large for tropical cyclones that are well away from land and unmonitored by aircraft reconnaissance. This study evaluates the errors of a subset of NHC and model 34-, 50-, and 64-kt (1 kt = 0.514 m s−1) wind radii forecasts from 2008 through 2012 that had aircraft reconnaissance available at both the initial and verification times. The results show that the NHC wind radii average errors increased with forecast time but were skillful when compared against climatology and persistence. The dynamical models, however, were not skillful and had errors that were much larger than the NHC forecasts, with substantial negative (too small) biases even after accounting for their initial size differences versus the tropical cyclone’s current wind radii. Improvements in wind radii forecasting will come about through a combination of better methods for observing tropical cyclone size as well as enhanced prediction techniques (dynamical models, statistical methods, and consensus approaches).

A Consensus Forecast for Tropical Cyclone Gale Wind Radii

Abstract The National Hurricane Center (NHC) has been forecasting gale force wind radii for many years, and more recently (starting in 2004) began routine postanalysis or “best tracking” of the maximum radial extent of gale [34 knots (kt; 1 kt = 0.514 m s−1)] force winds in compass quadrants surrounding the tropical cyclone (wind radii). At approximately the same time, a statistical wind radii forecast, based solely on climatology and persistence, was implemented so that wind radii forecasts could be evaluated for skill. If the best-track gale radii are used as ground truth (even accounting for random errors in the analyses), the skill of the NHC forecasts appears to be improving at 2- and 3-day lead times, suggesting that the guidance has also improved. In this paper several NWP models are evaluated for their skill, an equally weighted average or “consensus” of the model forecasts is constructed, and finally the consensus skill is evaluated. The results are similar to what is found with tropical cyclone track and intensity in that the consensus skill is comparable to or better than that of the individual models. Furthermore, the consensus skill is high enough to be of potential use as forecast guidance or as a proxy for official gale force wind radii forecasts at the longer lead times.

Global Ensemble Forecast Tracks for Tropical Storm Debby

Abstract Operational-model track forecasts for Tropical Storm Debby (June 2012) diverged as much as 180°, making the National Hurricane Center forecast particularly challenging. Forecast tracks from the members of the National Centers for Environmental Prediction Global Ensemble Forecast System (GEFS) were similarly divergent; some forecast Debby to turn westward, some forecast Debby to go northward, and others forecast Debby to go eastward. Part of the divergence in the operational models can be from differences in model code, but the divergence in the GEFS is due only to differences in initial conditions. To understand the meteorological reasons for this model divergence, GEFS forecasts for Debby were examined in detail. Debby formed in the south-central Gulf of Mexico and then became a tropical storm by 1200 UTC 23 June 2012. Careful examination of the GEFS tracks showed that those storms turning east were stronger and deeper than those turning west. The storm strength was measured by the mean sea level pressure at the center of the storms and the maximum 10-m wind speed. The correlation coefficients between these two quantities and the longitude 12 and 24 h later were between 0.60 and 0.90, for all GEFS model runs initialized between 0000 UTC 24 June and 1200 UTC 26 June 2012. Further investigation showed that the initial midlevel moisture (specific humidity at 850 and 700 hPa) determined the subsequent strength and depth of the member storms. This variation in depth changed the effective layer for steering currents, which determined the direction to which the storms moved.

Consistency in hurricane surface wind forecasting: an improved parametric model

A parametric hurricane wind model has been developed based on the asymmetric Holland-type vortex model. The model creates a two-dimensional surface wind field based on the National Hurricane Center forecast (or observed) hurricane wind and track data. Three improvements have been made to retain consistency between the input parameters and the model output and to better resolve the asymmetric structure of the hurricane. First, in determination of the shape parameter B, the Coriolis effect is included and the range restriction is removed. It is found that ignoring the Coriolis effect can lead to an error greater than 20% in the maximum wind speed for weak but large tropical cyclones. Second, the effect of the translational velocity of a hurricane is excluded from the input of specified wind speeds before applying the Holland-type vortex to avoid exaggeration of the wind asymmetry. The translational velocity is added back in at the very end of the procedure. Third, a new method has been introduced to develop a weighted composite wind field that makes full use of all wind parameters, not just the largest available specified wind speed and its 4-quadrant radii. An idealized hurricane and two historical Gulf of Mexico hurricanes have been used to test the model. It is found that the modified parametric model leads to better agreement with field observation compared with the results from the unmodified model. This will result in better predictions of hurricane waves and storm surges.

Statistical Extension of the National Hurricane Center 5-Day Forecasts

Abstract U.S. National Hurricane Center (NHC) forecasts for tropical cyclone tracks and wind speeds are extended in time to produce spatially disaggregated probability forecasts for landfall location and intensity, using a weighted bootstrap procedure. Historical analogs, with respect to the forecast characteristics (location, heading, and wind speed) of a current storm, are selected. These are resampled by translating their locations to random positions consistent with the current forecast, and recent NHC forecast accuracy statistics. The result is a large number of plausible Monte Carlo realizations that jointly approximate a probability distribution for the future track and intensity of the storm. Performance of the resulting forecasts is assessed for U.S. tropical cyclone landfall probabilities during 1998–2006, and the forecasts are shown to be skillful and exhibit excellent reliability, even beyond the 120-h forecast horizon of the NHC advisory forecasts upon which they are based.

Eastern North Pacific Hurricane Season of 2007

Abstract The hurricane season of 2007 in the eastern North Pacific Ocean basin is summarized, individual tropical cyclones are described, and a forecast verification is presented. The 2007 eastern North Pacific season was not an active one. There were 11 tropical storms, of which only 4 became hurricanes. Only one cyclone became a major hurricane. One hurricane struck Mexico and one tropical storm made landfall near the Guatemala–Mexico border. The 2007 National Hurricane Center forecast track errors were lower than the previous 5-yr means at all forecast lead times, and especially so for the 72-, 96-, and 120-h periods when the errors were 16%, 22%, and 20% lower, respectively. The official intensity forecasts had only limited skill.

A Statistical Model to Forecast Short-Term Atlantic Hurricane Intensity

AbstractAn alternative 24-h 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 24-h wind speed increase and the 24-h 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 24-h wind speed increase models was tested and compared with the official National Hurricane Center (NHC) 24-h intensity forecasts, which are currently more accurate on average than other 24-h 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 24-h wind speed increase models was 11.83 kt (1 kt = 0.5144 m s−1) for the DFA-selected 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 24-h pressure reduction models, the average error was 7.33 hPa for the DFA-selected models, and 5.85 hPa for the CSM. This shows that the DFA performed well against the NHC, but improvements can still be made to make the accuracy even better.

Trends in Track Forecasting for Tropical Cyclones Threatening the United States, 1970–2001

Previous studies have identified statistically significant long-term improvements in forecasts issued by the National Hurricane Center (NHC) for Atlantic basin tropical cyclones. Recently, however, attention has been focused on the forecast accuracy of landfall location and timing, and the long-term improvement trends for this relatively small sample of forecasts were mixed. These results may lead some to conclude that the accuracy of NHC forecasts close to the United States has not improved over time. A statistically robust dataset can be obtained by considering “landfall-threatening” storms, defined as one for which tropical cyclone watches or warnings are in effect for some portion of the continental United States. In this study, long-term trends in accuracy are determined for NHC forecasts issued during these periods of threat and compared to trends for the Atlantic basin overall. A second set of trends are determined for forecasts verifying during the periods of threat. The analysis shows that NHC forecasts for land-threatening tropical cyclones are improving. These improvement trends are statistically significant, although the improvement rates for the land-threatening storms are smaller than those for the basin overall. Over the period 1970–2001, forecasts issued during the watch/warning stage improved at annual average rates of 0.7%, 1.6%, and 1.9% at 24,48, and 72 h, respectively.