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  • 1
    Online Resource
    Online Resource
    Evaluating Environmental Impacts on Tropical Cyclone Rapid Intensification Predictability Utilizing Statistical Models
    American Meteorological Society ; 2015
    In:  Weather and Forecasting Vol. 30, No. 5 ( 2015-10-01), p. 1374-1396
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 30, No. 5 ( 2015-10-01), p. 1374-1396
    Abstract: New multi-lead-time versions of three statistical probabilistic tropical cyclone rapid intensification (RI) prediction models are developed for the Atlantic and eastern North Pacific basins. These are the linear-discriminant analysis–based Statistical Hurricane Intensity Prediction Scheme Rapid Intensification Index (SHIPS-RII), logistic regression, and Bayesian statistical RI models. Consensus RI models derived by averaging the three individual RI model probability forecasts are also generated. A verification of the cross-validated forecasts of the above RI models conducted for the 12-, 24-, 36-, and 48-h lead times indicates that these models generally exhibit skill relative to climatological forecasts, with the eastern Pacific models providing somewhat more skill than the Atlantic ones and the consensus versions providing more skill than the individual models. A verification of the deterministic RI model forecasts indicates that the operational intensity guidance exhibits some limited RI predictive skill, with the National Hurricane Center (NHC) official forecasts possessing the most skill within the first 24 h and the numerical models providing somewhat more skill at longer lead times. The Hurricane Weather Research and Forecasting Model (HWRF) generally provides the most skillful RI forecasts of any of the conventional intensity models while the new consensus RI model shows potential for providing increased skill over the existing operational intensity guidance. Finally, newly developed versions of the deterministic rapid intensification aid guidance that employ the new probabilistic consensus RI model forecasts along with the existing operational intensity model consensus produce lower mean errors and biases than the intensity consensus model alone.
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    URL: Article
    DOI: 10.1175/WAF-D-15-0032.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2015
    detail.hit.zdb_id: 2025194-4
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  • 2
    Online Resource
    Online Resource
    ProxyVis—A Proxy for Nighttime Visible Imagery Applicable to Geostationary Satellite Observations
    American Meteorological Society ; 2023
    In:  Weather and Forecasting Vol. 38, No. 12 ( 2023-12), p. 2527-2550
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 38, No. 12 ( 2023-12), p. 2527-2550
    Abstract: Visible satellite imagery is widely used by operational weather forecast centers for tropical and extratropical cyclone analysis and marine forecasting. The absence of visible imagery at night can significantly degrade forecast capabilities, such as determining tropical cyclone center locations or tracking warm-topped convective clusters. This paper documents ProxyVis imagery, an infrared-based proxy for daytime visible imagery developed to address the lack of visible satellite imagery at night and the limitations of existing nighttime visible options. ProxyVis was trained on the VIIRS day/night band imagery at times close to the full moon using VIIRS IR channels with closely matching GOES - 16 / 17 / 18 , Himawari - 8 / 9 , and Meteosat - 9 / 10 / 11 channels. The final operational product applies the ProxyVis algorithms to geostationary satellite data and combines daytime visible and nighttime ProxyVis data to create full-disk animated GeoProxyVis imagery. The simple versions of the ProxyVis algorithm enable its generation from earlier GOES and Meteosat satellite imagery. ProxyVis offers significant improvement over existing operational products for tracking nighttime oceanic low-level clouds. Further, it is qualitatively similar to visible imagery for a wide range of backgrounds and synoptic conditions and phenomena, enabling forecasters to use it without special training. ProxyVis was first introduced to National Hurricane Center (NHC) operations in 2018 and was found to be extremely useful by forecasters becoming part of their standard operational satellite product suite in 2019. Currently, ProxyVis implemented for GOES - 16 / 18 , Himawari - 9 , and Meteosat - 9 / 10 / 11 is being used in operational settings and evaluated for transition to operations at multiple NWS offices and the Joint Typhoon Warning Center. Significance Statement This paper describes ProxyVis imagery, a new method for combining infrared channels to qualitatively mimic daytime visible imagery at nighttime. ProxyVis demonstrates that a simple linear regression can combine just a few commonly available infrared channels to develop a nighttime proxy for visible imagery that significantly improves a forecaster’s ability to track low-level oceanic clouds and circulation features at night, works for all current geostationary satellites, and is useful across a wide range of backgrounds and meteorological scenarios. Animated ProxyVis geostationary imagery has been operational at the National Hurricane Center since 2019 and is also currently being transitioned to operations at other NWS offices and the Joint Typhoon Warning Center.
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    URL: Article
    URL: Article
    DOI: 10.1175/WAF-D-23-0038.1
    DOI: 10.1175/WAF-D-23-0038.s1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2023
    detail.hit.zdb_id: 2025194-4
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  • 3
    Online Resource
    Online Resource
    Satellite tools to monitor and predict Hurricane Sandy (2012): Current and emerging products
    Elsevier BV ; 2015
    In:  Atmospheric Research Vol. 166 ( 2015-12), p. 165-181
    Details
    In: Atmospheric Research, Elsevier BV, Vol. 166 ( 2015-12), p. 165-181
    Type of Medium: Online Resource
    ISSN: 0169-8095
    URL: Article
    DOI: 10.1016/j.atmosres.2015.06.005
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
    detail.hit.zdb_id: 2012396-6
    detail.hit.zdb_id: 233023-4
    SSG: 16,13
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  • 4
    Online Resource
    Online Resource
    A Revised Tropical Cyclone Rapid Intensification Index for the Atlantic and Eastern North Pacific Basins
    American Meteorological Society ; 2010
    In:  Weather and Forecasting Vol. 25, No. 1 ( 2010-02-01), p. 220-241
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 25, No. 1 ( 2010-02-01), p. 220-241
    Abstract: A revised rapid intensity index (RII) is developed for the Atlantic and eastern North Pacific basins. The RII uses large-scale predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to estimate the probability of rapid intensification (RI) over the succeeding 24 h utilizing linear discriminant analysis. Separate versions of the RII are developed for the 25-, 30-, and 35-kt RI thresholds, which represent the 90th (88th), 94th (92nd), and 97th (94th) percentiles of 24-h overwater intensity changes of tropical and subtropical cyclones in the Atlantic (eastern North Pacific) basins from 1989 to 2006, respectively. The revised RII became operational at the NHC prior to the 2008 hurricane season. The relative importance of the individual RI predictors is shown to differ between the two basins. Specifically, the previous 12-h intensity change, upper-level divergence, and vertical shear have the highest weights for the Atlantic basin, while the previous 12-h intensity change, symmetry of inner-core convection, and the difference in a system’s current and maximum potential intensity are weighted highest in the eastern North Pacific basin. A verification of independent forecasts from the 2006 and 2007 hurricane seasons shows that the probabilistic RII forecasts are generally skillful in both basins when compared to climatology. Moreover, when employed in a deterministic manner, the RII forecasts were superior to all other available operational intensity guidance in terms of the probability of detection (POD) and false alarm ratio (FAR). Specifically, the POD for the RII ranged from 15% to 59% (53% to 73%) while the FAR ranged from 71% to 85% (53% to 79%) in the Atlantic (eastern North Pacific) basins, respectively, for the three RI thresholds studied. Nevertheless, the modest POD and relatively high FAR of the RII and other intensity guidance demonstrate the difficulty of predicting RI, particularly in the Atlantic basin.
    Type of Medium: Online Resource
    ISSN: 1520-0434 , 0882-8156
    URL: Article
    DOI: 10.1175/2009WAF2222280.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2010
    detail.hit.zdb_id: 2025194-4
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  • 5
    Online Resource
    Online Resource
    The National Hurricane Center Tropical Cyclone Model Guidance Suite
    American Meteorological Society ; 2022
    In:  Weather and Forecasting Vol. 37, No. 11 ( 2022-11), p. 2141-2159
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 37, No. 11 ( 2022-11), p. 2141-2159
    Abstract: The National Hurricane Center (NHC) uses a variety of guidance models for its operational tropical cyclone track, intensity, and wind structure forecasts, and as baselines for the evaluation of forecast skill. A set of the simpler models, collectively known as the NHC guidance suite, is maintained by NHC. The models comprising the guidance suite are briefly described and evaluated, with details provided for those that have not been documented previously. Decay-SHIFOR is a modified version of the Statistical Hurricane Intensity Forecast (SHIFOR) model that includes decay over land; this modification improves the SHIFOR forecasts through about 96 h. T-CLIPER, a climatology and persistence model that predicts track and intensity using a trajectory approach, has error characteristics similar to those of CLIPER and D-SHIFOR but can be run to any forecast length. The Trajectory and Beta model (TAB), another trajectory track model, applies a gridpoint spatial filter to smooth winds from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model. TAB model errors were 10%–15% lower than those of the Beta and Advection model (BAM), the model it replaced in 2017. Optimizing TAB’s vertical weights shows that the lower troposphere’s environmental flow provides a better match to observed tropical cyclone motion than does the upper troposphere’s, and that the optimal steering layer is shallower for higher-latitude and weaker tropical cyclones. The advantages and disadvantages of the D-SHIFOR, T-CLIPER, and TAB models relative to their earlier counterparts are discussed. Significance Statement This paper provides a comprehensive summary and evaluation of a set of simpler forecast models used as guidance for NHC’s operational tropical cyclone forecasts, and as baselines for the evaluation of forecast skill; these include newer techniques that extend forecasts to 7 days and beyond.
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    URL: Article
    DOI: 10.1175/WAF-D-22-0039.1
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 2025194-4
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  • 6
    Online Resource
    Online Resource
    Further Improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS)
    American Meteorological Society ; 2005
    In:  Weather and Forecasting Vol. 20, No. 4 ( 2005-08-01), p. 531-543
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 20, No. 4 ( 2005-08-01), p. 531-543
    Abstract: 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 dry-adiabatic 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 shorter-range forecasts. The inclusion of land effects did not significantly degrade the forecasts at any time period. Results also showed that the 4–5-day 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 Environmental Satellite (GOES) channel 4 (10.7 μm) imagery, and oceanic heat content (OHC) estimates inferred from satellite altimetry observations. The OHC estimates were only available for the Atlantic basin. The GOES data significantly improved the east Pacific forecasts by up to 7% at 12–72 h. The combination of GOES and satellite altimetry improved the Atlantic forecasts by up to 3.5% through 72 h for those storms west of 50°W.
    Type of Medium: Online Resource
    ISSN: 1520-0434 , 0882-8156
    URL: Article
    DOI: 10.1175/WAF862.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2005
    detail.hit.zdb_id: 2025194-4
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  • 7
    Online Resource
    Online Resource
    A Deterministic Rapid Intensification Aid
    American Meteorological Society ; 2011
    In:  Weather and Forecasting Vol. 26, No. 4 ( 2011-08-01), p. 579-585
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 26, No. 4 ( 2011-08-01), p. 579-585
    Abstract: 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)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h 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).
    Type of Medium: Online Resource
    ISSN: 0882-8156 , 1520-0434
    URL: Article
    DOI: 10.1175/WAF-D-10-05010.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2011
    detail.hit.zdb_id: 2025194-4
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  • 8
    Online Resource
    Online Resource
    On the Decay of Tropical Cyclone Winds Crossing Narrow Landmasses
    American Meteorological Society ; 2006
    In:  Journal of Applied Meteorology and Climatology Vol. 45, No. 3 ( 2006-03-01), p. 491-499
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 45, No. 3 ( 2006-03-01), p. 491-499
    Abstract: A method is developed to adjust the Kaplan and DeMaria tropical cyclone inland wind decay model for storms that move over narrow landmasses. The basic assumption that the wind speed decay rate after landfall is proportional to the wind speed is modified to include a factor equal to the fraction of the storm circulation that is over land. The storm circulation is defined as a circular area with a fixed radius. Application of the modified model to Atlantic Ocean cases from 1967 to 2003 showed that a circulation radius of 110 km minimizes the bias in the total sample of landfalling cases and reduces the mean absolute error of the predicted maximum winds by about 12%. This radius is about 2 times the radius of maximum wind of a typical Atlantic tropical cyclone. The modified decay model was applied to the Statistical Hurricane Intensity Prediction Scheme (SHIPS), which uses the Kaplan and DeMaria decay model to adjust the intensity for the portion of the predicted track that is over land. The modified decay model reduced the intensity forecast errors by up to 8% relative to the original decay model for cases from 2001 to 2004 in which the storm was within 500 km from land.
    Type of Medium: Online Resource
    ISSN: 1558-8432 , 1558-8424
    URL: Article
    DOI: 10.1175/JAM2351.1
    RVK:
    UA 4547
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2006
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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  • 9
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    Online Resource
    An Upper Ocean Thermal Field Metrics Dataset
    MDPI AG ; 2022
    In:  Meteorology Vol. 1, No. 3 ( 2022-09-01), p. 327-340
    Details
    In: Meteorology, MDPI AG, Vol. 1, No. 3 ( 2022-09-01), p. 327-340
    Abstract: The upper ocean provides a source of thermal energy for tropical cyclone development and maintenance through a series of complex interactions. In this work, we develop a seventeen-year dataset of upper ocean thermal field metrics for use in tropical cyclone studies and development of tropical cyclone intensity prediction models. These metrics include the surface temperature, two different measures of vertically integrated heat content, and four different measures of vertically averaged temperature. Some metrics have been used to study upper-ocean energy response to tropical cyclone passage, while others have been employed to improve operational tropical cyclone intensity prediction models. The vertically integrated ocean heat content has been used to improve tropical cyclone intensity forecasts at U.S. tropical cyclone forecast centers and is an integral part of several operational intensity forecast models. A static 2005–2021 dataset that includes all twelve metrics described within is available on the Naval Research Laboratory web server, and a subset of six metrics have been produced in real-time at Fleet Numerical Meteorology and Oceanography Center and provided to the public via the GODAE server since 2021.
    Type of Medium: Online Resource
    ISSN: 2674-0494
    URL: Article
    DOI: 10.3390/meteorology1030021
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 10
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    Online Resource
    Objective Identification of Annular Hurricanes
    American Meteorological Society ; 2008
    In:  Weather and Forecasting Vol. 23, No. 1 ( 2008-02-01), p. 17-28
    Details
    In: Weather and Forecasting, American Meteorological Society, Vol. 23, No. 1 ( 2008-02-01), p. 17-28
    Abstract: Annular hurricanes are a subset of intense tropical cyclones that have been shown in previous work to be significantly stronger, to maintain their peak intensities longer, and to weaken more slowly than average tropical cyclones. Because of these characteristics, they represent a significant forecasting challenge. This paper updates the list of annular hurricanes to encompass the years 1995–2006 in both the North Atlantic and eastern–central North Pacific tropical cyclone basins. Because annular hurricanes have a unique appearance in infrared satellite imagery, and form in a specific set of environmental conditions, an objective real-time method of identifying these hurricanes is developed. However, since the occurrence of annular hurricanes is rare (∼4% of all hurricanes), a special algorithm to detect annular hurricanes is developed that employs two steps to identify the candidates: 1) prescreening the data and 2) applying a linear discriminant analysis. This algorithm is trained using a dependent dataset (1995–2003) that includes 11 annular hurricanes. The resulting algorithm is then independently tested using datasets from the years 2004–06, which contained an additional three annular hurricanes. Results indicate that the algorithm is able to discriminate annular hurricanes from tropical cyclones with intensities greater than 84 kt (43.2 m s−1). The probability of detection or hit rate produced by this scheme is shown to be ∼96% with a false alarm rate of ∼6%, based on 1363 six-hour time periods with a tropical cyclone with an intensity greater than 84 kt (1995–2006).
    Type of Medium: Online Resource
    ISSN: 1520-0434 , 0882-8156
    URL: Article
    DOI: 10.1175/2007WAF2007031.1
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2008
    detail.hit.zdb_id: 2025194-4
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