Note: This is a real-time dataset. If you do not see any data on the map, there may not be an event taking place. The Atlantic hurricane season begins on June 1 and ends on November 30, and the eastern Pacific hurricane season begins on May 15 and ends on November 30.Hurricanes, also known as typhoons and cyclones, fall under the scientific term tropical cyclone. Tropical cyclones that develop over the Atlantic and eastern Pacific Ocean are considered hurricanes.Meteorologists have classified the development of a tropical cyclone into four stages: tropical disturbance, tropical depression, tropical storm, and tropical cyclone. Tropical cyclones begin as small tropical disturbances where rain clouds build over warm ocean waters. Eventually, the clouds grow large enough to develop a pattern, where the wind begins to circulate around a center point. As winds are drawn higher, increasing air pressure causes the rising thunderstorms to disperse from the center of the storm. This creates an area of rotating thunderstorms called a tropical depression with winds 62 kmph (38 mph) or less. Systems with wind speeds between 63 kmph (39 mph) and 118 kmph (73 mph) are considered tropical storms. If the winds of the tropical storm hit 119 kmph (74 mph), the storm is classified as a hurricane. Tropical cyclones need two primary ingredients to form: warm water and constant wind directions. Warm ocean waters of at least 26 degrees Celsius (74 degrees Fahrenheit) provide the energy needed for the storm to become a hurricane. Hurricanes can maintain winds in a constant direction at increasing speeds as air rotates about and gathers into the hurricane’s center. This inward and upward spiral prevents the storm from ripping itself apart. Hurricanes have distinctive parts: the eye, eyewall, and rain bands. The eye is the calm center of the hurricane where the cooler drier air sinks back down to the surface of the water. Here, winds are tranquil, and skies are partly cloudy, sometimes even clear. The eyewall is composed of the strongest ring of thunderstorms and surrounds the eye. This is where rain and winds are the strongest and heaviest. Rain bands are stretches of rain clouds that go far beyond the hurricane’s eyewall, usually hundreds of kilometers. Scientists typically use the Saffir-Simpson Hurricane Wind Scale to measure the strength of a hurricane’s winds and intensity. This scale gives a 1 to 5 rating based on the hurricane’s maximum sustained winds. Hurricanes rated category 3 or higher are recognized as major hurricanes. Category 1: Wind speeds are between 119 and 153 kmph (74 and 95 mph). Although this is the lowest category of hurricane, category 1 hurricanes still produce dangerous winds and could result in damaged roofs, power lines, or fallen tree branches. Category 2: Wind speeds are between 154 and 177 kmph (96 and 110 mph). These dangerous winds are likely to cause moderate damage; enough to snap or uproot small trees, destroy roofs, and cause power outages. Category 3: Wind speeds are between 178 and 208 kmph (111 and 129 mph). At this strength, extensive damage may occur. Well-built homes could incur damage to their exterior and many trees will likely be snapped or uprooted. Water and electricity could be unavailable for at least several days after the hurricane passes. Category 4: Wind speeds are between 209 and 251 kmph (130 and 156 mph). Extreme damage will occur. Most of the area will be uninhabitable for weeks or months after the hurricane. Well-built homes could sustain major damage to their exterior, most trees may be snapped or uprooted, and power outages could last weeks to months. Category 5: Wind speeds are 252 kmph (157 mph) or higher. Catastrophic damage will occur. Most of the area will be uninhabitable for weeks or months after the hurricane. A significant amount of well-built, framed homes will likely be destroyed, uprooted trees may isolate residential areas, and power outages could last weeks to months. This map is built with data from the NOAA National Hurricane Center (NHC) and the Joint Typhoon Warning Center (JTWC). The map shows recent, observed, and forecasted hurricane tracks and positions, uncertainties, wind speeds, and associated storm watches and warnings. This is a real-time dataset that is programed to check for updates from the NHC and JTWC every 15 minutes. If you are in an area experiencing a tropical cyclone, tune into local sources for more up-to-date information and important safety instructions. This map includes the following information: Forecast position points: These points mark the locations where the NHC predict the tropical cyclone will be at 12, 24, 36, 48, 72, 96, and 120 hours in the future.Observed position points: These points mark the locations where the tropical cyclone has been.Forecast track: This is the line that connects the forecast points and marks the expected path of the hurricane.Observed track: This line marks the path the tropical cyclone has already taken.Cone of uncertainty: Due to the complexity of ocean atmospheric interactions, there are many different factors that can influence the path of a hurricane. This uncertainty is represented on the map by a cone. The further into the future the forecast is, the wider the cone due to the greater uncertainty in the precise path of the storm. Remember rain, wind, and storm surge from the hurricane will likely impact areas outside the cone of uncertainty. This broader impact of wind can be seen if you turn on or off Tropical Storm Force (34 Knots) 5-Day Wind Probability, Strong Tropical Storm Force (50 Knots) 5-Day Wind Probability, or Hurricane Force (64 Knots) 5-Day Wind Probability map layers.Watches and warnings: Storm watches or warnings depend on the strength and distance from the location of the forecasted event. Watches indicate an increased risk for severe weather, while a warning means you should immediately move to a safe space.Tropical storm watch: The NHC issues this for areas that might be impacted by tropical cyclones with wind speeds of 34 to 63 knots (63 to 119 kilometers per hour or 39 to 74 miles per hour) in the next 48 hours. In addition to high winds, the region may experience storm surge or flooding.Tropical storm warning: The NHC issues this for places that will be impacted by hurricanes with wind speeds of 34 to 63 knots (63 to 119 kilometers per hour or 39 to 74 miles per hour) in the next 36 hours. As with the watch, the area may also experience storm surge or flooding.Hurricane watch: The NHC issues this watch for areas where a tropical cyclone with sustained wind speeds of 64 knots (119 kilometers per hour or 74 miles per hour) or greater in the next 48 hours may be possible. In addition to high winds, the region may experience storm surge or flooding.Hurricane warning: The NHC issues this warning for areas where hurricanes with sustained wind speeds of 64 knots (119 kilometers per hour or 74 miles per hour) or greater in the next 36 hours are expected. As with the watch, the region may experience storm surge or flooding. This warning is also posted when dangerously high water and waves continue even after wind speeds have fallen below 64 knots.Recent hurricanes: These points and tracks mark tropical cyclones that have occurred this year but are no longer active.

Want to learn more about how hurricanes form? Check out Forces of Nature or explore The Ten Most Damaging Hurricanes in U.S. History story.

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. Now includes 'Danger Area' Polygons from JTWC, detailing US Navy Ship Avoidance Area when Wind speeds exceed 34 Knots!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.RevisionsMar 13, 2025: Altered 'Forecast Error Cone' layer to include 'Danger Area' with updated symbology.Nov 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 GRIP Hurricane Imaging Radiometer (HIRAD) V1 dataset contains measurements of brightness temperature taken at 4, 5, 6 and 6.6 GHz, as well as MERRA 2 m wind speed data and JPL MUR Sea Surface Temperature data. The data is provided in netCDF format. The data were collected during the Genesis and Rapid Intensification Processes (GRIP) experiment from September 1, 2010 through September 16, 2010 for storms EARL and KARL. Rain rate and wind speed files may be obtained from the V0 HIRAD dataset. The major goal was to better understandhow tropical storms form and develop into major hurricanes. NASA used the DC-8 aircraft, the WB-57 aircraft and the Global Hawk Unmanned AirborneSystem (UAS), configuredwith a suite of in situ and remote sensing instruments that were used to observe and characterize the lifecycle of hurricanes.HIRAD is a hurricane imaging, single-polarization passive C-band radiometer with both cross-track and along-track resolution that measures strong ocean surface winds through heavy rain from an aircraft or space-based platform. Its swath width is approximately 60 degrees in either direction.

The intensity and spatial extent of tropical cyclone precipitation (TCP) often shapes the risk posed by landfalling storms. Here we provide a comprehensive climatology of landfalling TCP characteristics as a function of tropical cyclone strength, using daily precipitation station data and Atlantic US landfalling tropical cyclone tracks from 1900-2017. We analyze the intensity and spatial extent of ≥ 1 mm/day TCP (Z1) and ≥ 50 mm/day TCP (Z50) over land. We show that the highest median intensity and largest median spatial extent of Z1 and Z50 occur for major hurricanes that have weakened to tropical storms, indicating greater flood risk despite weaker wind speeds. We also find some signs of TCP change in recent decades. In particular, for major hurricanes that have weakened to tropical storms, Z50 intensity has significantly increased, indicating possible increases in flood risk to coastal communities in more recent years.

Methods 1. Station precipitation and tropical cyclone tracks

We use daily precipitation data from the Global Historical Climatology Network (GHCN)-Daily station dataset (Menne et al., 2012) and TC tracks archived in the revised HURricane DATabase (HURDAT2) database (Landsea & Franklin, 2013). HURDAT2 is a post-storm reanalysis that uses several datasets, including land observations, aircraft reconnaissance, ship logs, radiosondes, and satellite observations to determine tropical cyclone track locations, wind speeds and central pressures (Jarvinen et al., 1984; Landsea & Franklin, 2013). We select 1256 US stations from the GHCN-Daily dataset that have observations beginning no later than 1900 and ending no earlier than 2017 (though most station records are not continuous throughout that period). These 1256 land-based stations are well distributed over the southeastern US and Atlantic seaboard (see Supporting Figure S1).

We use the HURDAT2 Atlantic database to select locations and windspeeds of TC tracks that originated in the North Atlantic Ocean, Gulf of Mexico and Caribbean Sea, and made landfall over the continental US. Though tracks are determined at 6-hourly time steps for each storm (with additional timesteps that indicate times of landfall, and times and values of maximum intensity), we limit our analysis to track points recorded at 1200 UTC, in order to match the daily temporal resolution and times of observation of the GHCN-Daily precipitation dataset (Menne et al., 2012), as well as the diurnal cycle of TCP (Gaona & Villarini, 2018). Although this temporal matching technique may omit high values of precipitation from the analysis, it reduces the possibility of capturing precipitation that is not associated with a TC.

1. Tropical cyclone and Lifetime Maximum Intensity (LMI) categories

For each daily point in the tropical cyclone track, we use the maximum sustained windspeed to place the storm into one of three Extended Saffir-Simpson categories: tropical storms (“TS”; 34-63 knots), minor hurricanes (“Min”; categories 1 and 2; 64-95 knots), and major hurricanes (“Maj”; categories 3 to 5; > 96 knots) (Schott et al., 2012). Additionally, for each track, we record the category of the lifetime maximum intensity (LMI), based on the maximum windspeed found along the whole lifetime of the track (i.e., using all available track points). LMI is a standard tropical cyclone metric, and is considered a robust measure of track intensity through time and across different types of data integrated into the HURDAT2 reanalysis (Elsner et al., 2008; Kossin et al., 2013, 2014). Therefore, for each track point, a dual category is assigned: the first portion of the classification denotes the category of the storm for a given point (hereafter “point category”), while the second denotes the LMI category. The combination of the two can thus be considered a “point-LMI category”. For example, the point on August 27, 2017 at 1200 UTC along Hurricane Harvey’s track is classified as TS-Maj because it is a tropical storm (TS) at this point but falls along a major hurricane LMI track (see starred location in Supporting Figure S2a). Given that the LMI category for a given point cannot be weaker than the point category itself, the set of possible point-LMI category combinations for each track point is TS-TS, TS-Min, TS-Maj, Min-Min, Min-Maj, and Maj-Maj. This dual classification allows us to explore climatological TCP spatial extents and intensities during the tropical cyclone lifetime. Our dual classification does not account for the timing of the point category relative to the LMI category for a given point along a track (i.e., the time-lag between the LMI and point in consideration). However, the majority of points selected in our analysis occur after the TC has reached its LMI and are in the weakening stage (see Supporting Table S1 for more details). This could be expected, as our analysis is focused on land-based precipitation stations, and TCs weaken over land. However, a small fraction of TC points analyzed occur over the ocean before making landfall, but are close enough to land for precipitation gauges to be impacted.

1. Moving neighborhood method for TCP spatial extent and intensity

   We first find the distribution of tropical cyclone precipitation (TCP) intensity using all daily land precipitation values from all available stations in a 700 km-radius neighborhood around each point over land on each tropical cyclone track (Figure 1a and Supporting Figure S2). We then create two new binary station datasets, Z1(x) and Z50(x), which indicate whether or not a station meets or exceeds the 1 mm/day or 50 mm/day precipitation threshold, respectively, on a given day. The 50 mm/day threshold is greater than the 75th percentile of TCP across all tropical cyclone categories (Figure 1a), allowing us to capture the characteristics of heavy TCP while retaining a robust sample size. The 1 mm/day threshold captures the extent of the overall TCP around the TC track point.

We use the relaxed moving neighborhood and semivariogram framework developed by Touma et al. (2018) to quantify the spatial extent of Z1 and Z50 TCP for each track point. Using a neighborhood with a 700 km radius around each track point, we select all station pairs that meet two criteria: at least one station has to exhibit the threshold precipitation on that given day (Z(x) = 1; blue and pink stations in Supporting Figure S2b), and at least one station has to be inside the neighborhood (black and pink stations in Supporting Figure S2b). We then calculate the indicator semivariogram, g(h), for each station pair selected for that track point (Eq. 1):

γh=0.5*[Z(x+h)-Z(x)]2, Eq. 1

where h is the separation distance between the stations in the station pair. The indicator semivariogram is a function of the separation distance, and has two possible outcomes: all pairs with two threshold stations (Z(x) = Z(x+h) = 1) have a semivariogram value of 0, and all pairs with one threshold station and one non-threshold station (Z(x) = 1 and Z(x+h) = 0) have a semivariogram value of 0.5.

We then average the semivariogram values for all station pairs for equal intervals of separation distances (up to 1000 km) to obtain the experimental semivariogram (Supporting Figure S2c). To quantify the shape of the experimental semivariogram, we fit three parameters of the theoretical spherical variogram (nugget, partial sill, and practical range) to the experimental semivariogram (Eq. 2):

γ(h) = 0, for h=0

γ(h) = c+b*((3/2)(h/α)-(1/2)(h/α)3), for 0<h≤α

γ(h) = c+b, for h≥α, Eq. 2

where c is the nugget, b is the partial sill, and a is the practical range (Goovaerts, 2015). The nugget quantifies measurement errors or microscale variability, and the partial sill is the maximum value reached by the spherical semivariogram (Goovaerts, 2015). The practical range is the separation distance at which the semivariogram asymptotes (Supporting Figure S2c). At this separation distance, station pairs are no longer likely to exhibit the threshold precipitation (1 mm/day or 50 mm/day) simultaneously (Goovaerts, 2015; Touma et al., 2018). Therefore, as in Touma et al. (2018), we define the length scale – or spatial extent – of TCP for that given track point as the practical range.

There are some subjective choices of the moving neighborhood and semivariogram framework, including the 700 km radius of neighborhood (Touma et al. 2018). Previous studies found that 700 km is sufficient to capture the extent to which tropical cyclones influence precipitation (e.g., Barlow, (2011), Daloz et al. (2010), Hernández Ayala & Matyas (2016), Kim et al. (2014), Knaff et al. (2014), Knutson et al. (2010) and Matyas (2010)). Additionally, Touma et al. (2018) showed that although the neighborhood size can slightly impact the magnitude of length scales, it has little impact on their relative spatial and temporal variations.

1. Analysis of variations and trends

We use Mood’s median test (Desu & Raghavarao, 2003) to test for differences in the median TCP intensity and spatial extent among point-LMI categories, adjusting p-values to account for multiple simultaneous comparisons (Benjamini & Hochberg, 1995; Holm, 1979; Sheskin, 2003). To test for changes in TCP characteristics over time, we divide our century-scale dataset into two halves, 1900-1957 and 1958-2017. First, the quartile boundaries are established using the distributions of the earlier period (1900-1957), with one-quarter of the distribution falling in each quartile. Then, we find the fraction of points in each quartile in the later period (1958-2017) to determine changes in the distribution. We also report the p-values of the Kolmogorov-Smirnov

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/].

The 2020 Pacific Northwest hurricane season is an event whereby tropical cyclones form in the Northwest Pacific region in 2020, mainly from May to December. This is the 6th late in history storm starting season (the first occurrence of land loss). After four months of silence, the first hurricane formed on May 8 (Vongfong) and made landfall in the Philippines. The orbit of the storms also deviates much to the West, with storms mainly affecting the Korean peninsula, China and Vietnam. In August, Typhoon Sinlaku hit Thanh Hoa; Nuri (June), Hagupit, Mekkhala, Higos (August) caused damage in China. During August and September, four hurricanes Jangmi, Bavi, Maysak, and Haishen made landfall and caused great damage on the Korean peninsula. The second half of September, the first half of October, three storms and one tropical depression directly affecting Vietnam, are Noul (landing in Thua Thien-Hue), Linfa (landing in Quang Ngai) and Nangka (landing in Quang Ngai). Ninh Binh) and the tropical depression Ofel (landing in Quang Nam) combined with cold air, tropical convergence strip causing heavy rains, extensive flooding and historic floods causing heavy damage in Central Vietnam.

This dataset is described and explored in Rice et al. 2025, "Projected Increases in Tropical Cyclone-induced U.S. Electric Power Outage Risk", published in Environmental Research Letters (doi.org/10.1088/1748-9326/adad85)

This dataset collects peak outage levels modeled for 900,000 synthetic tropical cyclones (TCs; also commonly known as hurricanes) representative of a modeled historical (1980-2015) and future (2066-2100) period under SSP5-8.5 warming. Synthetic TCs are generated with the Risk Analysis Framework for Tropical Cyclones (RAFT; see Xu et al. 2024 and Balaguru et al. 2023), forced by climate simulation data from the Coupled Model Intercomparison Project phase 6 (CMIP6; see Eyring et al. 2016). Outages are modeled with the newly introduced Electric Power Outages from Cyclone Hazards (EPOCH) model, which was trained on county-level outage data from 23 historical TC events in the EAGLE-I dataset (Brelsford et al. 2024).

The EPOCH model predicts outages based on county population and the maximum wind speed and rainfall rate experienced during the TC. Predicted outage levels are provided in the form of peak outage fraction: the maximum fraction of electricity customers expected to experience an outage at any one time during the storm's lifetime. Although we do not model outage duration, other research suggests peak outage level is strongly correlated with duration (Jamal and Hasan, 2023).

Data Format

The data is provided in NetCDF4 files, one for each CMIP6 model and time period. Each NetCDF4 files has the following:

Dimensions:

• ncounties = 2715. The counties in the study domain
• ntracks = 50000. The number of storms

Variables:

• int pseudofips(ncounties). The FIPS code for each county. Puerto Rico data is not available at county level, but instead for six utility-defined regions. We assign "pseudo-FIPS" codes to these region starting at 100000
• double centroid_lons(ncounties). Longitude of approximate center of county, in the range [-180, 0].
• double centroid_lats(ncounties). Latitude of approximate center of county, in the range [0, 90].
• float outage_prediction(ntracks, ncounties). The predicted peak outage fraction for each county, for each storm. Due to the particularities of ensemble models, some predictions may be slightly below zero or above one; we clip these values to the range [0,1] before any analysis in our study.
• ubyte prediction_complete_flag(ntracks). A verification flag used during dataset generation. This flag should equal 1 everywhere for complete data.

Each file also contains the raw predictors at a county level for every storm, inside the 'predictors' group, for feature analysis.

Also provided for convenience is 'counties_pseudofips.csv', which maps the pseudo-FIPS codes to the the name and spatial extent (WKT format) of each county. It can be read easily by Python GeoPandas, or other software.

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. Now includes 'Danger Area' Polygons from JTWC, detailing US Navy Ship Avoidance Area when Wind speeds exceed 34 Knots!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.RevisionsMar 13, 2025: Altered 'Forecast Error Cone' layer to include 'Danger Area' with updated symbology.Nov 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!

Mid-September is traditionally considered the peak of hurricane season. These turbulent storms develop in the oceans, but are there any places along the world’s oceans that don’t experience hurricanes?

This dataset contains a coastal erosion hazards analysis for Hurricane Michael. The analysis is based on a storm-impact scaling model that combines observations of beach morphology with hydrodynamic models to predict how sandy beaches, the first line of defense for many coasts exposed to tropical storms and hurricanes, will respond during a direct landfall. Storm-induced total water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change - collision (dune erosion), overwash, and inundation. The storm surge elevations along the open coast were obtained from the National Oceanic and Atmospheric Administration's (NOAA) probabilistic surge forecast (psurge), which is based on conditions specific to the landfalling storm. Errors in hurricane forecasts are included in order to identify probable surge levels. The 10% exceedance surge level was used to represent the worst-case scenario. Maximum wave heights in 20-m water depth, obtained from the NOAA WaveWatch3 model 7-day forecast, were used to compute wave runup elevations at the shoreline. Dune elevations were extracted from lidar topographic surveys.

Disclaimer: This product is based on published research results of the USGS National Assessment of Coastal Change Hazards Project and is intended to indicate the potential for coastal change caused by storm surge and wave runup. This product is based on an analysis that simplifies complex coastal change processes to two important aspects - measured dune elevations and predicted total water levels. As such, the actual changes that occur during extreme storms may be different than what is described here. Results apply to open coast environments and do not consider potential coastal change along inland waters. The public should not base evacuation decisions on this product. Citizens should follow the evacuation advice of local emergency management authorities.

This dataset contains a coastal erosion hazards analysis for Hurricane Ian. The analysis is based on a storm-impact scaling model that combines observations of beach morphology with hydrodynamic models to predict how sandy beaches, the first line of defense for many coasts exposed to tropical storms and hurricanes, will respond during a direct landfall. Storm-induced total water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change - collision (dune erosion), overwash, and inundation. The storm surge elevations along the open coast were obtained from the National Oceanic and Atmospheric Administration's (NOAA) probabilistic surge forecast (psurge), which is based on conditions specific to the landfalling storm. Errors in hurricane forecasts are included in order to identify probable surge levels. The 10% exceedance surge level was used to represent the worst-case scenario. Maximum wave heights in 20-m water depth, obtained from the NOAA WaveWatch3 model 7-day forecast, were used to compute wave runup elevations at the shoreline. Dune elevations were extracted from lidar topographic surveys.

Disclaimer: This product is based on published research results of the USGS National Assessment of Coastal Change Hazards Project and is intended to indicate the potential for coastal change caused by storm surge and wave runup. This product is based on an analysis that simplifies complex coastal change processes to two important aspects - measured dune elevations and predicted total water levels. As such, the actual changes that occur during extreme storms may be different than what is described here. Results apply to open coast environments and do not consider potential coastal change along inland waters. The public should not base evacuation decisions on this product. Citizens should follow the evacuation advice of local emergency management authorities.

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.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!

CrisisMMD is a large multi-modal dataset collected from Twitter during different natural disasters. It consists of several thousands of manually annotated tweets and images collected during seven major natural disasters including earthquakes, hurricanes, wildfires, and floods that happened in the year 2017 across different parts of the World. The provided datasets include three types of annotations.

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. The storm surge zones data used in this application were generated using the Sea - Lake - and Overland Surges from Hurricanes (SLOSH) model. SLOSH is a computerized model run by the National Weather Service to estimate storm surge heights resulting from historical - hypothetical - or predicted hurricanes. The model creates its estimates by assessing the pressure - size - forward speed - track - and wind data from a storm. Graphical output from the model displays color-coded storm surge heights for a particular area. The calculations are applied to a specific locale's shoreline - incorporating the unique bay and river configurations - water depths - bridges - roads - and other physical features. This file is generated as part of the Hazards Analysis within the Hurricane Evacuation Study for the Maryland Western Shore. Last Updated: Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/Weather/MD_StormSurge/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

This dataset contains a coastal erosion hazards analysis for Hurricane Idalia. The analysis is based on a storm-impact scaling model that combines observations of beach morphology with hydrodynamic models to predict how sandy beaches, the first line of defense for many coasts exposed to tropical storms and hurricanes, will respond during a direct landfall. Storm-induced total water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change - collision (dune erosion), overwash, and inundation. The storm surge elevations along the open coast were obtained from the National Oceanic and Atmospheric Administration's (NOAA) probabilistic surge forecast (psurge), which is based on conditions specific to the landfalling storm. Errors in hurricane forecasts are included in order to identify probable surge levels. The 10% exceedance surge level was used to represent the worst-case scenario. Maximum wave heights in 20-m water depth, obtained from the NOAA WaveWatch3 model 7-day forecast, were used to compute wave runup elevations at the shoreline. Dune elevations were extracted from lidar topographic surveys.

Disclaimer: This product is based on published research results of the USGS National Assessment of Coastal Change Hazards Project and is intended to indicate the potential for coastal change caused by storm surge and wave runup. This product is based on an analysis that simplifies complex coastal change processes to two important aspects - measured dune elevations and predicted total water levels. As such, the actual changes that occur during extreme storms may be different than what is described here. Results apply to open coast environments and do not consider potential coastal change along inland waters. The public should not base evacuation decisions on this product. Citizens should follow the evacuation advice of local emergency management authorities.

This dataset contains a coastal erosion hazards analysis for Hurricane Helene. The analysis is based on a storm-impact scaling model that combines observations of beach morphology with hydrodynamic models to predict how sandy beaches, the first line of defense for many coasts exposed to tropical storms and hurricanes, will respond during a direct landfall. Storm-induced total water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change - collision (dune erosion), overwash, and inundation. The storm surge elevations along the open coast were obtained from the National Oceanic and Atmospheric Administration's (NOAA) probabilistic surge forecast (psurge), which is based on conditions specific to the landfalling storm. Errors in hurricane forecasts are included in order to identify probable surge levels. The 10% exceedance surge level was used to represent the worst-case scenario. Maximum wave heights in 20-m water depth, obtained from the NOAA WaveWatch3 model 7-day forecast, were used to compute wave runup elevations at the shoreline. Dune elevations were extracted from lidar topographic surveys.

Disclaimer: This product is based on published research results of the USGS National Assessment of Coastal Change Hazards Project and is intended to indicate the potential for coastal change caused by storm surge and wave runup. This product is based on an analysis that simplifies complex coastal change processes to two important aspects - measured dune elevations and predicted total water levels. As such, the actual changes that occur during extreme storms may be different than what is described here. Results apply to open coast environments and do not consider potential coastal change along inland waters. The public should not base evacuation decisions on this product. Citizens should follow the evacuation advice of local emergency management authorities.

San Francisco Flood Health Vulnerability

Socioeconomic, Demographic, Health, and Housing Indicators

By City of San Francisco [source]

About this dataset

This dataset provides a comprehensive composite index that captures the relative vulnerability of San Francisco communities to the health impacts of flooding and extreme storms. Predominantly sourced from local governmental health, housing, and public data sources, this index is constructed from an array of socio-economic factors, exposure indices,Health indicators and housing attributes. Used as a valuable planning tool for both health and climate adaptation initiatives throughout San Francisco, this dataset helps to identify vulnerable populations within the city such as areas with high concentrations of children or elderly individuals. Data points included in this index include: census blockgroup numbers; the percentage of population under 18 years old; percentage of population above 65; percentage non-white; poverty levels; education level; yearly precipitation estimates; diabetes prevalence rate; mental health issues reported in the area; asthma cases by geographic location;; disability rates within each block group measure as well as housing quality metrics. All these components provide a broader understanding on how best to tackle issues faced within SF arising from any form of climate change related weather event such as floods or extreme storms

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How to use the dataset

This dataset can be used to analyze the vulnerability of the population in San Francisco to the health impacts of floods and storms. This dataset includes a number of important indicators such as poverty, education, demographic, exposure and health-related information. These indicators can be useful for developing effective strategies for health and climate adaptation in an urban area.

To get started with this dataset: First, review the data dictionary provided in the attachments section of this metadata to understand each variable that you plan on using in your analysis. Second, see if there are any null or missing values in your columns by checking out ‘Null Value’ column provided in this metadata sheet and look at how they will affect your analysis - use appropriate methods to handle those values based on your goals and objectives. Thirdly begin exploring relationships between different variables using visualizations like pandas scatter_matrix() & pandas .corr() . These tools can help you identify potential strong correlations between certain variables that you may have not seen otherwise through simple inspection of the data.

Lastly if needed use modelling techniques like regression analysis or other quantitative methods like ANOVA’s etc., for further elaboration on understanding relationships between different parameters involved as per need basis

Research Ideas

• Developing targeted public health interventions focused on high-risk areas/populations as identified in the vulnerability index.
• Establishing criteria for insurance premiums and policies within high-risk areas/populations to incentivize adaption to climate change.
• Visual mapping of individual indicators in order to identify trends and correlations between flood risk and socioeconomic indicators, resource availability, and/or healthcare provision levels at a granular level

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: san-francisco-flood-health-vulnerability-1.csv | Column name | Description | |:---------------------------|:----------------------------------------------------------------------------------------| | Census Blockgroup | Unique numerical identifier for each block in the city. (Integer) | | Children | Percentage of population under 18 years of age. (Float) | | Children_wNULLvalues | Percentage of population under 18 years of age with null values. (Float) | | Elderly | Percentage of population over 65 years of age. (Float) | | Elderly_wNULLvalues | Percentage of population over 65 years of age with null values. (Float) | | NonWhite | Percentage of non-white population. (Float) ...

These files contain data that support an analysis of the effects of two major hurricanes on coral reefs that have been extensively studied for more than three decades. Major tropical storms are destructive phenomena with large effects on the community dynamics of multiple biomes. On coral reefs, their impacts have been described for decades, leading to the expectation that future storms should have effects similar to those recorded in the past. This expectation relies on the assumption that storm intensities will remain unchanged, and the impacted coral reef communities are similar to those of the recent past; neither assumption is correct. These data support a study quantifying the effects of two category five hurricanes on the reefs of St. John, US Virgin Islands, where 31 y of time-series analyses reveal chronic coral mortality, increasing macroalgal abundance, and five major hurricanes that caused acute coral mortality. Contextualized by these trends, the effects of the most recent storms, Hurricanes Irma and Maria (September 2017), on coral cover were modest. While mean absolute coral cover declined 1\u20134% depending on site, these effects were not statistically discernable. Following decades of increasing abundance of macroalgae, this functional group responded to the recent hurricanes with large increases in abundance on both absolute and relative scales. Decades of chronic mortality have changed the coral assemblages of St. John to create degraded communities that are resistant to severe storms. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv acquisition_description=Photoquadrats at Yawzi Point and Tektite were recorded using cameras attached to a framer that held them perpendicular to the reef. A Nikonos V (35-mm format) was used from 1987-1999, and digital cameras thereafter, with 3.3 MP resolution from 2000\u20132006, 6.1 MP from 2006\u20132010, 12.1 MP in 2011, 16.2 from 2012\u20132015, and 36.3 MP from 2016\u2013present. Cameras were fitted with a strobe (Nikonos SB 105) and the images resolved objects \u2265 1-cm diameter.

The analyses at Yawzi Point and Tektite were augmented in 1992 with six additional sites that were selected using random coordinates constrained to hard substrata. This sampling focused on a habitat where boulders and cliffs of igneous rock are common, mean coral cover has remained < 5%, and\u00a0Orbicella annularis\u00a0has not been common since at least 1992. Five sites are at 9-m depth, with one at 7-m depth (RS9), and they have been recorded annually. These sites serve as replicates of reefs between Cabritte Horn and White Point, and are analyzed as the pooled random sites (PRS). Results from 1995 (May) and 1996 (May) are used to evaluate the effects of Hurricanes Luis and Marilyn, and from 2017 (July and November) to evaluate the effects of Hurricanes Irma and Maria. Each site consists of a permanently marked transect at a constant depth that was 20-m long from 1992\u20131999 (n ~ 18 photoquadrats site-1), but was extended to 40 m in 2000 when digital photography was implemented (n ~ 40 photoquadrats site-1). Photoquadrats (0.5 \u00d7 0.5 m) were recorded at random positions along each transect (and re- randomized annually) using cameras (as described above) attached to a framer that held them perpendicular to the reef. Cameras were attached to two strobes (Nikonos SB 105), and resolved objects to at least 5-mm diameter.

Photoquadrats were analyzed by overlaying them with a grid of 200 randomly- located dots and identifying the substratum beneath each dot. Images were analyzed manually prior to 2005, from 2005\u20132011 using CPCe software, and from 2012 to present, using CoralNet software with manual annotations. With this approach, the abundance of each substratum type is defined by the total number of dots that occur on top of it in each image, and when expressed as a percentage of the dot population on each image, provides a measure of percentage cover (hereafter \u201ccover\u201d) (Menge 1976). Two resolutions were applied to the analyses, first to resolve three functional groups (FG), coral (combined cover of scleractinians), macroalgae (algae \u2265 1-cm high, mostly\u00a0Halimeda, Lobophora, Padina, and\u00a0Dictyota), and a combined category of crustose coralline algae, algal turf, and bare space (CTB). Second, scleractinians were resolved to the lowest taxonomic level possible, which was genera at Yawzi Point and Tektite, and a combination of species and genera at the PRS.

In addition to the hurricanes described herein, St. John also was impacted by Hurricane Lenny on 17 November 1999 (Table S1). However, underwater damage attributed to this storm was minor, probably due to the modest local wind speeds (150 km h-1), and propagation of damaging waves east and south that reduced their impacts on the southern shore of St. John. The effects of Hurricane Lenny are not considered in the present analysis. Given the vagaries of fieldwork extending over 31 Years, it was not possible to standardize the timing of sampling that took place before and after each storm episode. Sampling took place 6 weeks after Hurricane Hugo, 8 months after Hurricane Luis, and 9 weeks after Hurricane Maria. Sampling after the two most recent storms was comparable to sampling after Hurricane Hugo with regards to the delay following the storms and, therefore, probably quantified mostly coral mortality directly attributable to physical damage, and blooms of macroalgae commensurate with the growth that is possible in two autumn months. The longer delay in sampling after Hurricanes Marilyn and Luis probably resulted in measurements of coral mortality that was caused both by direct physical damage and delayed-onset disease, as well as blooms of macroalgae that can grow over 8 months extending from autumn to spring. awards_0_award_nid=55191 awards_0_award_number=DEB-0841441 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=0841441&HistoricalAwards=false awards_0_funder_name=National Science Foundation awards_0_funding_acronym=NSF awards_0_funding_source_nid=350 awards_0_program_manager=Saran Twombly awards_0_program_manager_nid=51702 awards_1_award_nid=55194 awards_1_award_number=DEB-0343570 awards_1_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=0343570&HistoricalAwards=false awards_1_funder_name=National Science Foundation awards_1_funding_acronym=NSF awards_1_funding_source_nid=350 awards_1_program_manager=Saran Twombly awards_1_program_manager_nid=51702 awards_2_award_nid=562593 awards_2_award_number=DEB-1350146 awards_2_data_url=http://www.nsf.gov/awardsearch/showAward?AWD_ID=1350146 awards_2_funder_name=NSF Division of Environmental Biology awards_2_funding_acronym=NSF DEB awards_2_funding_source_nid=550432 awards_2_program_manager=Betsy Von Holle awards_2_program_manager_nid=701685 awards_3_award_nid=722162 awards_3_award_number=OCE-1801335 awards_3_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1801335 awards_3_funder_name=NSF Division of Ocean Sciences awards_3_funding_acronym=NSF OCE awards_3_funding_source_nid=355 awards_3_program_manager=Daniel Thornhill awards_3_program_manager_nid=722161 cdm_data_type=Other comment=Coral community structure at Yawazi Point and Tektite in St. John before and after five hurricanes from 1988-2017 PI: Peter J. Edmunds Version: 2018-11-26 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.750060.1 infoUrl=https://www.bco-dmo.org/dataset/750060 institution=BCO-DMO instruments_0_acronym=camera instruments_0_dataset_instrument_description=Photoquadrats at Yawzi Point and Tektite were recorded using cameras attached to a framer that held them perpendicular to the reef. instruments_0_dataset_instrument_nid=750065 instruments_0_description=All types of photographic equipment including stills, video, film and digital systems. instruments_0_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L05/current/311/ instruments_0_instrument_name=Camera instruments_0_instrument_nid=520 instruments_0_supplied_name=cameras metadata_source=https://www.bco-dmo.org/api/dataset/750060 param_mapping={'750060': {}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/750060/parameters people_0_affiliation=California State University Northridge people_0_affiliation_acronym=CSU-Northridge people_0_person_name=Peter J. Edmunds people_0_person_nid=51536 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Woods Hole Oceanographic Institution people_1_affiliation_acronym=WHOI BCO-DMO people_1_person_name=Mathew Biddle people_1_person_nid=708682 people_1_role=BCO-DMO Data Manager people_1_role_type=related project=RUI-LTREB projects_0_acronym=RUI-LTREB projects_0_description=Describing how ecosystems like coral reefs are changing is at the forefront of efforts to evaluate the biological consequences of global climate change and ocean acidification. Coral reefs have become the poster child of these efforts. Amid concern that they could become ecologically extinct within a century, describing what has been lost, what is left, and what is at risk, is of paramount importance. This project exploits an unrivalled legacy of information beginning in 1987 to evaluate the form in which reefs will persist, and the extent to which they will be able to resist further onslaughts of environmental challenges. This long-term project continues a 27-year study of Caribbean coral reefs. The diverse data collected will allow the investigators to determine the roles of local and global disturbances in reef degradation. The data will also reveal the structure and function of reefs in a future with more human disturbances, when corals may no longer dominate tropical reefs. The broad societal impacts of this project include advancing understanding of an ecosystem that has long been held emblematic of

This dataset contains a coastal erosion hazards analysis for Hurricane Milton. The analysis is based on a storm-impact scaling model that combines observations of beach morphology with hydrodynamic models to predict how sandy beaches, the first line of defense for many coasts exposed to tropical storms and hurricanes, will respond during a direct landfall. Storm-induced total water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change - collision (dune erosion), overwash, and inundation. The storm surge elevations along the open coast were obtained from the National Oceanic and Atmospheric Administration's (NOAA) probabilistic surge forecast (psurge), which is based on conditions specific to the landfalling storm. Errors in hurricane forecasts are included in order to identify probable surge levels. The 10% exceedance surge level was used to represent the worst-case scenario. Maximum wave heights in 20-m water depth, obtained from the NOAA WaveWatch3 model 7-day forecast, were used to compute wave runup elevations at the shoreline. Dune elevations were extracted from lidar topographic surveys.

Disclaimer: This product is based on published research results of the USGS National Assessment of Coastal Change Hazards Project and is intended to indicate the potential for coastal change caused by storm surge and wave runup. This product is based on an analysis that simplifies complex coastal change processes to two important aspects - measured dune elevations and predicted total water levels. As such, the actual changes that occur during extreme storms may be different than what is described here. Results apply to open coast environments and do not consider potential coastal change along inland waters. The public should not base evacuation decisions on this product. Citizens should follow the evacuation advice of local emergency management authorities.

The GRIP WB-57 Navigation and Housekeeping data was collected on flight days occuring between July 13 , 2010 to September 17, 2010 during the Genesis and Rapid Intensification Processes (GRIP) field campaign. The major goal was to better understand how tropical storms form and develop into major hurricanes. The NASA WB-57 is a weather research aircraft capable of operating for extended periods of time (~6.5 hours) from sea level to altitudes well over 60,000 feet (12 miles high). Both data in IWG1 format and error logs are part of this dataset.