In 2023, there were 78 named storms registered worldwide, down from 87 storms in the previous year. Overall, there was an average of 87 named tropical cyclones registered per year from 1980 to 2023. Japan was the country most exposed to this type of event worldwide.

What is a tropical cyclone?Tropical cyclones are intense rotating storms that form over warm tropical waters, characterized by heavy rain and strong winds. Once a cyclone sustains wind speeds exceeding 63 kilometers per hour, they are considered a tropical storm and receive a name. Named tropical storms can also receive further classification depending on their intensity and location (also known as basin). High-speed cyclones in the Northern Atlantic and Eastern Pacific basins are called hurricanes, while in the Western Pacific they are called typhoons. When the event takes place within the South Pacific and Indian Ocean, it is known as a cyclone.

Frequency of tropical cyclones worldwide

The Northwest Pacific basin is one of the most active for tropical cyclones worldwide. In 2023, there were 16 named storms reported in the region, of which more than half were classified as hurricanes. Meanwhile, the North Indian Ocean represented one of the least active basins for tropical cyclones, with an annual average of five named storms recorded from 1990 to 2023.

This dataset details all tropical cyclones that are known to have occurred in the region south of the equator between 90E and 160E. The data has been sourced from the Tropical Cyclone Database, maintained by the Bureau of Meteorology (BOM). This record represents a snapshot of the data taken on 23/03/2023 for the purposes of generating a mapping visualisation of recent cyclone activity. The most current database can be downloaded from the BOM website: http://www.bom.gov.au/cyclone/tropical-cyclone-knowledge-centre/databases/

Point data from the BOM has been converted into cyclone tracks for visualisation. The data and mapping layer will be refreshed annually following cyclone season (May-June each year).

Last updated 21st November 2023.

Time series of tropical cyclone "best track" position and intensity data are provided for all ocean basins where tropical cyclones occur. Position and intensity data are available at 6-hourly intervals over the duration of each cyclone's life. The general period of record begins in 1851, but this varies by ocean basin. See the inventories [http://rda.ucar.edu/datasets/ds824.1/inventories/] for data availability specific to each basin. This data set was received as a revision to an NCDC tropical cyclone data set, with data generally available through the late 1990s. Since then, the set is being continually updated from the U.S. NOAA National Hurricane Center and the U.S. Navy Joint Typhoon Warning Center best track archives. For a complete history of updates for each ocean basin, see the dataset documentation [http://rda.ucar.edu/datasets/ds824.1/docs/].

Datasets consisting of 10,000 years of synthetic tropical cyclone tracks, generated using the Synthetic Tropical cyclOne geneRation Model (STORM) algorithm (see Bloemendaal et al, Generation of a Global Synthetic Tropical cyclone Hazard Dataset using STORM, in review). The dataset is generated using historical data from IBTrACS and resembles present-climate conditions. The data can be used to calculate tropical cyclone risk in all (coastal) regions prone to tropical cyclones.

VERSION UPDATE (30 Sept 2020): The Saffir-Simpson category thresholds were wrongly calculated in the previous version, this has now been corrected.

VERSION UPDATE (18 March 2021): The old version of STORM contained some duplicate cyclone tracks. These have now been removed.

VERSION UPDATE (22 July 2022): The last version accidentally still had the old wrong categories ... This version has the right categories AND the duplicates removed! :-)

During the start of the current decade, the number of reported deaths due to tropical cyclones worldwide amounted to 2,670. The 10-year period with the highest recorded figures was between 2000 and 2009, where 167,300 deaths were reported due to tropical cyclones. Since 1970, almost 800 thousand deaths due to cyclones have been registered across the globe. Meanwhile, the number of tropical cyclones globally has increased continuously in the past half a century.

Tropical cyclones (TCs) pose a major risk to societies worldwide. While data on observed cyclones tracks (location of the center) and wind speeds is publicly available these data sets do not contain information about the spatial extent of the storm and people or assets exposed. Here, we apply a simplified wind field model to estimate the areas exposed to wind speeds above 34, 64, and 96 knots. Based on available spatially-explicit data on population densities and Gross Domestic Product (GDP) we estimate 1) the number of people and 2) the sum of assets exposed to wind speeds above these thresholds accounting for temporal changes in historical distribution of population and assets (TCE-hist) and assuming fixed 2015 patterns (TCE-2015). The associated country-event level exposure data (TCE-DAT) covers the period 1950 to 2015. It is considered key information to 1) assess the contribution of climatological versus socioeconomic drivers of changes in exposure to tropical cyclones, 2) estimate changes in vulnerability from the difference in exposure and reported damages and calibrate associated damage functions, and 3) build improved exposure-based predictors to estimate higher-level societal impacts such as long-term effects on GDP, employment, or migration. We validate the adequateness of our methodology by comparing our exposure estimate to estimated exposure obtained from reported wind fields available since 1988 for the United States. We expect that the free availability of the underlying model and TCE-DAT will make research on tropical cyclone risks more accessible to non-experts and stakeholders.

Files included in the data set: (1) TCE-DAT_historic-exposure_1950-2015.csv: Exposed population and assets by event and country using historical socio-economic exposure estimates.(2) TCE-DAT_2015-exposure_1950-2015.csv: Exposed population and assets by event and country using fixed socio-economic exposure at 2015 values.(3) Data-description_TCE-DAT_2017.005.pdf: full description of the data set including information on data sources and the description of variables/ data columns

EcoDRR global classification scheme based on spatial combination of ecosystem coverage and natural hazard physical exposure. The physical exposure data-set shows the product of hazard frequency and people exposed to this hazard in the same 100 square kilometer cell. For a specific natural hazard, a 0.01 degree resolution raster is generated, showing hazard annual frequency weighted with portion of pixel potentially affected. In the case of tropical cyclones, annual frequency is calculated using the category one of the Saffir-Simpson scale. It corresponds to the largest wind buffer of each past event footprint.

Sources: The dataset includes an estimate of tropical cyclone frequency of Saffir-Simpson category 1. It is based on two sources: 1) IBTrACS v02r01 (1969 - 2008, http://www.ncdc.noaa.gov/oa/ibtracs/), year 2009 completed by online data from JMA, JTWC, UNISYS, Meteo France and data sent by Alan Sharp from the Australian Bureau of Meteorology. 2) A GIS modeling based on an initial equation from Greg Holland, which was further modified to take into consideration the movement of the cyclones through time. Unit is expected average number of event per 100 years multiplied by 100. This product was designed by UNEP/GRID-Europe for the Global Assessment Report on Risk Reduction (GAR). It was modeled using global data. Credit: Raw data: IBTrACS, compilation and GIS processing UNEP/GRID-Europe.

Dataset used for the analysis of the effect of climate change on tropical cyclones derived ocean waves, as part of the article entitled "Tropical Cyclone Wind Waves in the Gulf of Mexico under a Changing Climate", under review for the journal Geophysical Research Letters, and available as a preprint at: doi.org/10.1002/essoar.10508611.1
The readme.txt file has a description of the available information.

The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles. The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder.

Hurricane tracks and positions provide information on where the storm has been, where it is currently located, and where it is predicted to go. Each storm location is depicted by the sustained wind speed, according to the Saffir-Simpson Scale. It should be noted that the Saffir-Simpson Scale only applies to hurricanes in the Atlantic and Eastern Pacific basins, however all storms are still symbolized using that classification for consistency.Data SourceThis data is provided by NOAA National Hurricane Center (NHC) for the Central+East Pacific and Atlantic, and the Joint Typhoon Warning Center for the West+Central Pacific and Indian basins. For more disaster-related live feeds visit the Disaster Web Maps & Feeds ArcGIS Online Group.Sample DataSee Sample Layer Item for sample data during inactive Hurricane Season!Update FrequencyThe Aggregated Live Feeds methodology checks the Source for updates every 15 minutes. Tropical cyclones are normally issued every six hours at 5:00 AM EDT, 11:00 AM EDT, 5:00 PM EDT, and 11:00 PM EDT (or 4:00 AM EST, 10:00 AM EST, 4:00 PM EST, and 10:00 PM EST).Public advisories for Eastern Pacific tropical cyclones are normally issued every six hours at 2:00 AM PDT, 8:00 AM PDT, 2:00 PM PDT, and 8:00 PM PDT (or 1:00 AM PST, 7:00 AM PST, 1:00 PM PST, and 7:00 PM PST).Intermediate public advisories may be issued every 3 hours when coastal watches or warnings are in effect, and every 2 hours when coastal watches or warnings are in effect and land-based radars have identified a reliable storm center. Additionally, special public advisories may be issued at any time due to significant changes in warnings or in a cyclone. For the NHC data source you can subscribe to RSS Feeds.North Pacific and North Indian Ocean tropical cyclone warnings are updated every 6 hours, and South Indian and South Pacific Ocean tropical cyclone warnings are routinely updated every 12 hours. Times are set to Zulu/UTC.Scale/ResolutionThe horizontal accuracy of these datasets is not stated but it is important to remember that tropical cyclone track forecasts are subject to error, and that the effects of a tropical cyclone can span many hundreds of miles from the center.Area CoveredWorldGlossaryForecast location: Represents the official NHC forecast locations for the center of a tropical cyclone. Forecast center positions are given for projections valid 12, 24, 36, 48, 72, 96, and 120 hours after the forecast's nominal initial time. Click here for more information.

Forecast points from the JTWC are valid 12, 24, 36, 48 and 72 hours after the forecast’s initial time.Forecast track: This product aids in the visualization of an NHC official track forecast, the forecast points are connected by a red line. The track lines are not a forecast product, as such, the lines should not be interpreted as representing a specific forecast for the location of a tropical cyclone in between official forecast points. It is also important to remember that tropical cyclone track forecasts are subject to error, and that the effects of a tropical cyclone can span many hundreds of miles from the center. Click here for more information.The Cone of Uncertainty: Cyclone paths are hard to predict with absolute certainty, especially days in advance.

The cone represents the probable track of the center of a tropical cyclone and is formed by enclosing the area swept out by a set of circles along the forecast track (at 12, 24, 36 hours, etc). The size of each circle is scaled so that two-thirds of the historical official forecast errors over a 5-year sample fall within the circle. Based on forecasts over the previous 5 years, the entire track of a tropical cyclone can be expected to remain within the cone roughly 60-70% of the time. It is important to note that the area affected by a tropical cyclone can extend well beyond the confines of the cone enclosing the most likely track area of the center. Click here for more information.Coastal Watch/Warning: Coastal areas are placed under watches and warnings depending on the proximity and intensity of the approaching storm.Tropical Storm Watch is issued when a tropical cyclone containing winds of 34 to 63 knots (39 to 73 mph) or higher poses a possible threat, generally within 48 hours. These winds may be accompanied by storm surge, coastal flooding, and/or river flooding. The watch does not mean that tropical storm conditions will occur. It only means that these conditions are possible.Tropical Storm Warning is issued when sustained winds of 34 to 63 knots (39 to 73 mph) or higher associated with a tropical cyclone are expected in 36 hours or less. These winds may be accompanied by storm surge, coastal flooding, and/or river flooding.Hurricane Watch is issued when a tropical cyclone containing winds of 64 knots (74 mph) or higher poses a possible threat, generally within 48 hours. These winds may be accompanied by storm surge, coastal flooding, and/or river flooding. The watch does not mean that hurricane conditions will occur. It only means that these conditions are possible.Hurricane Warning is issued when sustained winds of 64 knots (74 mph) or higher associated with a tropical cyclone are expected in 36 hours or less. These winds may be accompanied by storm surge, coastal flooding, and/or river flooding. A hurricane warning can remain in effect when dangerously high water or a combination of dangerously high water and exceptionally high waves continue, even though winds may be less than hurricane force.RevisionsNov 20, 2023: Added Event Label to 'Forecast Position' layer, showing arrival time and wind speed localized to user's location.Mar 27, 2022: Added UID, Max_SS, Max_Wind, Max_Gust, and Max_Label fields to ForecastErrorCone layer.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to NOAA or JTWC sources for official guidance.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

The TRMM Cyclone Precipitation Feature (TCPF) Database - Level 1 provides Tropical Rainfall Measuring Mission (TRMM)-based tropical cyclone data in a common framework for hurricane science research. This dataset aggregated observations from each of the TRMM instruments for each satellite orbit that was coincident with a tropical cyclone in any of the six TC-prone ocean basins. These swath data were co-located and subsetted to a 20-degree longitude by 20-degree latitude bounding box centered on the tropical storm, which is typically large enough to observe the various sizes of TCs and their immediate environments. The TCPF Level 1 dataset was created by researchers at Florida International University (FIU) and the University of Utah (UU) from the UU TRMM Precipitation Feature database. The TCPF database was built by extracting those precipitation features that are identified as tropical cyclones (TC) using the TC best-track data provided by National Hurricane Center or the US Navy's Joint Typhoon Warning Center.

The countries most exposed to tropical cyclones across the globe are located in Asia and the Caribbean. According to a risk index which considers the number of people exposed to this type of event per year, the Dominican Republic ranked first with a score of 10 as of 2024, followed by the Philippines, which received a score of 9.3. Hurricane, typhoon or cyclone? Tropical cyclone is a general term used to describe powerful storms that form over warm ocean waters near the equator, characterized by strong winds, heavy rainfall, and low pressure at its center. The names used to identify them depend on the region where they originate. For instance, hurricanes are tropical cyclones that occur in the North Atlantic Ocean and the central-eastern North Pacific Ocean, and they commonly affect regions such as the Caribbean, the Gulf of Mexico, and the southeastern United States. Meanwhile, typhoons occur in the northwestern Pacific Ocean and hit countries such as Japan, China, Taiwan, and the Philippines. Lastly, simply cyclones describe tropical cyclones in the Indian Ocean and the South Pacific Ocean. Why is Japan on top of the list? Japan has the perfect cocktail for tropical cyclones. It is located in the northwestern part of the Pacific Ocean, where warm waters can fuel the development and intensity of these powerful storms. The country’s mountainous terrain can cause rapid changes in wind speed and direction, while its atmospheric conditions – such as the East Asian monsoon – also contribute to the formation and movement of tropical cyclones. This is topped by Japan’s island geography, characterized by a large coastline that increases the likelihood of typhoon landfalls in the country. Altogether, in order to mitigate the risks associated with tropical cyclones, Japan invests heavily in disaster prevention, including resilient infrastructure and early warning systems.

This Story Map Series presents maps, data, and apps for hurricanes and tropical cyclones around the world.Esri is supporting organizations that are responding to hurricane/cyclone disasters with software, data, imagery, project services, and technical support. If you are in need of software or support, complete the Request Assistance form. All requests should be justified in the message section of the form and are subject to approval.More information

We present the formulation of an open-source, statistical–parametric model of tropical cyclones (TCs) for use in hazard and risk assessment applications. The model derives statistical relations for TC behaviour (genesis rate and location, intensity, speed and direction of translation) from best-track datasets, then uses these relations to create a synthetic catalogue based on stochastic sampling, representing many thousands of years of activity. A parametric wind field, based on radial profiles and boundary layer models, is applied to each event in the catalogue that is then used to fit extreme-value distributions for evaluation of return period wind speeds. We demonstrate the capability of the model to replicate observed behaviour of TCs, including coastal landfall rates which are of significant importance for risk assessments. Citation: Arthur, W. C.: A statistical–parametric model of tropical cyclones for hazard assessment, Nat. Hazards Earth Syst. Sci., 21, 893–916, https://doi.org/10.5194/nhess-21-893-2021, 2021.

The Tropical Cyclone Risk Model (TCRM) is a statistical-parametric model of tropical cyclone behaviour and effects. A statistical model is used to generate synthetic tropical cyclone events. This is then combined with a parametric wind field model to produce estimates of cyclonic wind hazard.

The forecast of tropical cyclone trajectories is crucial for the protection of people and property. Although forecast dynamical models can provide high-precision short-term forecasts, they are computationally demanding, and current statistical forecasting models have much room for improvement given that the database of past hurricanes is constantly growing. Machine learning methods, that can capture non-linearities and complex relations, have only been scarcely tested for this application. We propose a neural network model fusing past trajectory data and reanalysis atmospheric images (wind and pressure 3D fields). We use a moving frame of reference that follows the storm center for the 24 h tracking forecast. The network is trained to estimate the longitude and latitude displacement of tropical cyclones and depressions from a large database from both hemispheres (more than 3,000 storms since 1979, sampled at a 6 h frequency). The advantage of the fused network is demonstrated and a comparison with current forecast models shows that deep learning methods could provide a valuable and complementary prediction. Moreover, our method can give a forecast for a new storm in a few seconds, which is an important asset for real-time forecasts compared to traditional forecasts.

Tropical Cyclone (TC) Tracy impacted Darwin early on Christmas Day, 1974. The magnitude of damage was such that Tracy remains deeply ingrained in the Australian psyche. Several factors contributed to the widespread damage, including the intensity of the cyclone and construction materials employed in Darwin at the time. Since 1974, the population of Darwin has grown rapidly, from 46,000 in 1974 to nearly 115,000 in 2006. If TC Tracy were to strike Darwin in 2008, the impacts could be catastrophic. We perform a validation of Geoscience Australia's Tropical Cyclone Risk Model (TCRM) to assess the impacts TC Tracy would have on the 1974 landscape of Darwin, and compare the impacts to those determined from a post-impact survey. We then apply TCRM to the present-day landscape of Darwin to determine the damage incurred if a cyclone identical to TC Tracy impacted the city in 2008. In validating TCRM against the 1974 impact, we find an underestimate of the damage at 36% of replacement cost (RC), compared the survey estimate of 50-60% RC. Some of this deficit can be accounted for through the effects of large debris. Qualitatively, TCRM can spatially replicate the damage inflicted on Darwin by the small cyclone. The northern suburbs suffer the greatest damage, in line with the historical observations. For the 2008 scenario, TCRM indicates a nearly 90% reduction in the overall loss (% RC) over the Darwin region. Once again, the spatial nature of the damage is captured well, with the greatest damage incurred close to the eye of the cyclone. Areas that have been developed since 1974 such as Palmerston suffer very little damage due to the small extent of the severe winds. The northern suburbs, rebuilt in the years following TC Tracy, are much more resilient, largely due to the influence of very high building standards put in place between 1975 and 1980. Article published in the Australian Journal of Emergency Management

This dataset comprises a series of CSV files, each of which catalogues a suite of information for an individual cyclone track for the Northern Hemisphere. Detection and tracking are conducted using version 13.2 of the Lagrangian cyclone detection and tracking algorithm described by Crawford et al. (2021). This algorithm is applied to sea-level pressure data from Version 5 of the European Centre for Medium-Range Weather Forecasts (ECMWF) Retrospective Analysis (ERA-5) at a 3-hour temporal resolution and 25-km spatial resolution for the period 1950 – present (updated annually). Each CSV file contains information regarding the location, propagation, intensity, and size of the storm for each observation time. Whether a storm is a multi-center cyclone or interacting (splitting or merging) with other storm systems is also noted. Only cyclones that last at least 24 hours and travel at least 1000 km are included. These standard criteria are necessary to remove spurious systems (i.e., reduce the false positive rate).

This layer features tropical storm (hurricanes, typhoons, cyclones) tracks, positions, and observed wind swaths from the past hurricane season for the Atlantic, Pacific, and Indian Basins. These are products from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC). They are part of an archive of tropical storm data maintained in the International Best Track Archive for Climate Stewardship (IBTrACS) database by the NOAA National Centers for Environmental Information.Data SourceNOAA National Hurricane Center tropical cyclone best track archive.Update FrequencyWe automatically check these products for updates every 15 minutes from the NHC GIS Data page.The NHC shapefiles are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.Area CoveredWorldWhat can you do with this layer?Customize the display of each attribute by using the ‘Change Style’ option for any layer.Run a filter to query the layer and display only specific types of storms or areas.Add to your map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools like ‘Enrich Data’ on the Observed Wind Swath layer to determine the impact of cyclone events on populations.Visualize data in ArcGIS Insights or Operations Dashboards.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to NOAA or JTWC sources for official guidance.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

The National Hurricane Center and Central Pacific Center Tropical Weather Summary Web Service is a web service that contains the tropical cyclone data for possible storms throughout the United States and its territories. Specific storms can be identified on this summary service by the storm’s wallet. Wallet information is found in the "idp_source" with a field alias GIS Source attribute field of the data as the leading three characters.This web service visually displays potential impact of tropical cyclones on coastal communities. The provided wind, probability of flooding, surge inundation layers, watch warnings and tidal masks offers critical information for emergency preparedness and response efforts. This includes helping residents, emergency managers, and policymakers understand the potential severity of coastal flooding and take appropriate precautions. This web service covers a wide range of coastal areas prone to tropical cyclones, ensuring that stakeholders across different regions have access to essential tropical storm information. This comprehensive coverage enhances the service's utility and relevance for a diverse audience.However, understanding the full extent of risk requires a comprehensive view of the affected areas. Therefore, it's highly recommended to complement the National Hurricane Center and Central Pacific Center Tropical Weather Web Service is complimented with the use of additional resources including NHC Peak Storm Surge Web Service that provide information about major roads, railways, landmarks, and areas likely to be flooded. Incorporating data on past flood levels can further enrich the analysis and aid in predicting future impacts.One such valuable asset is the NWS National Viewer’s Tropical Site, which offers a wealth of supplementary information to enhance situational awareness and risk assessment. By integrating these complementary resources, stakeholders can gain a holistic understanding of the potential impacts of tropical cyclones and make more effective decisions to safeguard lives, property, and critical.Layer Descriptions:2 Day Outlook depicts the 2-day Graphic Tropical Weather Outlook from the NHC.7 Day Outlook depicts the 7-day Graphic Tropical Weather Outlook from the NHC.Forecast Points depicts the and current position and forecast positions of the storm out to 120 hours.Forecast Track is a line connecting the forecast points.Forecast Cone depicts the forecast "Cone of uncertainty".Watch-Warning depicts a "watch/warning" line indicating which sections of the coastline are in a watch/warning state due to the storm.Past Points depicts the "best" track of the storm to the current time.Past Track is a line connecting the past points.Best Wind Radii shows how the size of the storm has changed and the areas potentially affected so far by sustained winds.Surface Wind Field is intended to show the areas potentially being affected by sustained winds of tropical storm force (34 knot), (50 knot) and hurricane force (64 knot).Forecast Wind Radii are intended to show the expected size of the storm and the areas potentially affected by sustained winds of tropical storm force (34 Knot), (50 knot) and hurricane force (64 knot).Arrival Time of TS Winds depicts the earliest reasonable or the most likely arrival time of tropical storm force winds.Inundation depicts the total water level that occurs on normally dry ground as a result of the storm tide.Tidal Mask depicts the total water level that occurs on normally dry ground as a result of the storm tide, plus intertidal zones/estuarine wetlands.Probabilistic Winds depicts the probability of 34, 50 and 64 knot winds.Update Frequency: Every 6 hours and every 3 hours if the storm is approaching the shore.Link to graphical web page: https://www.nhc.noaa.govLink to data download (shapefile): https://www.nhc.noaa.gov/gisLink to metadataQuestions/Concerns about the service, please contact the DISS GIS team.Time Information: This service is not time enabled.