Feature layer showing all the fire perimeters tracked by Cal OES GIS for year to date.Fire information is taken from the National Fire and Aviation Management (FAMWEB) in the form of ICS-209 reports. During normal operations these 209 reports are downloaded once a day at 0630, or soon after. During a SOC activation these 209 reports will be downloaded twice a day at 0630 and 1800. Cal OES GIS considers the FAMWEB ICS-209s as the authoritative fire information source.Fire perimeter data is downloaded from the National Interagency Fire Center (NIFC). The data for map is updated daily, M-F, by 0800, the map text by 0900, when there are active fires being tracked by Cal OES.If the SOC is activated the fire map will be updated daily, Sun-Sat, by 0800, the map text by 0900, until the SOC stands down.For a fire to be tracked by Cal OES GIS it needs to be:>100 acres in sizeHave an ICS-209 form.CalOES GIS indicates a fire as contained when it has reached >=90% containment.
NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated bathymetric-topographic DEMs are used to support tsunami forecasting and modeling efforts at the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory (PMEL). The DEMs are part of the tsunami forecast system SIFT (Short-term Inundation Forecasting for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers, and are used in the MOST (Method of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation, and inundation. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of Mean High Water (MHW) and horizontal datum of World Geodetic System 1984 (WGS84). Grid spacings for the DEM ranges from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).This DEM includes the Key West, Florida area of Monroe County (not the mainland portion of the county).While every effort has been made to ensure that these data are accurate and reliable within the limits of the current state of the art, NOAA cannot assume liability for any damages caused by any errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.The dataset is provided "as is," without warranty to its performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of this dataset is assumed by the user. This dataset should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.
This layer presents detectable thermal activity from VIIRS satellites for the last 7 days. VIIRS Thermal Hotspots and Fire Activity is a product of NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) Earth Observation Data, part of NASA's Earth Science Data.Consumption Best Practices:
As a service that is subject to very high usage, ensure peak performance and accessibility of your maps and apps by avoiding the use of non-cacheable relative Date/Time field filters. To accommodate filtering events by Date/Time, we suggest using the included "Age" fields that maintain the number of days or hours since a record was created or last modified, compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be efficiently provided to users in a high demand service environment.When ingesting this service in your applications, avoid using POST requests whenever possible. These requests can compromise performance and scalability during periods of high usage because they too are not cacheable.Source: NASA LANCE - VNP14IMG_NRT active fire detection - WorldScale/Resolution: 375-meterUpdate Frequency: Hourly using the aggregated live feed methodologyArea Covered: WorldWhat can I do with this layer?This layer represents the most frequently updated and most detailed global remotely sensed wildfire information. Detection attributes include time, location, and intensity. It can be used to track the location of fires from the recent past, a few hours up to seven days behind real time. This layer also shows the location of wildfire over the past 7 days as a time-enabled service so that the progress of fires over that timeframe can be reproduced as an animation.The VIIRS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.Fire points in this service are generally available within 3 1/4 hours after detection by a VIIRS device. LANCE estimates availability at around 3 hours after detection, and esri livefeeds updates this feature layer every 15 minutes from LANCE.Even though these data display as point features, each point in fact represents a pixel that is >= 375 m high and wide. A point feature means somewhere in this pixel at least one "hot" spot was detected which may be a fire.VIIRS is a scanning radiometer device aboard the Suomi NPP, NOAA-20, and NOAA-21 satellites that collects imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans in several visible and infrared bands. The VIIRS Thermal Hotspots and Fire Activity layer is a livefeed from a subset of the overall VIIRS imagery, in particular from NASA's VNP14IMG_NRT active fire detection product. The downloads are automatically downloaded from LANCE, NASA's near real time data and imagery site, every 15 minutes.The 375-m data complements the 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Hotspots and Fire Activity layer; they both show good agreement in hotspot detection but the improved spatial resolution of the 375 m data provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters.Attribute informationLatitude and Longitude: The center point location of the 375 m (approximately) pixel flagged as containing one or more fires/hotspots.Satellite: Whether the detection was picked up by the Suomi NPP satellite (N) or NOAA-20 satellite (1) or NOAA-21 satellite (2). For best results, use the virtual field WhichSatellite, redefined by an arcade expression, that gives the complete satellite name.Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel. This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence values are set to low, nominal and high. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (<15K) in the mid-infrared channel I4. Nominal confidence pixels are those free of potential sun glint contamination during the day and marked by strong (>15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.Please note: Low confidence nighttime pixels occur only over the geographic area extending from 11 deg E to 110 deg W and 7 deg N to 55 deg S. This area describes the region of influence of the South Atlantic Magnetic Anomaly which can cause spurious brightness temperatures in the mid-infrared channel I4 leading to potential false positive alarms. These have been removed from the NRT data distributed by FIRMS.FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).DayNight: D = Daytime fire, N = Nighttime fireHours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.Additional information can be found on the NASA FIRMS site FAQ.Note about near real time data:Near real time data is not checked thoroughly before it's posted on LANCE or downloaded and posted to the Living Atlas. NASA's goal is to get vital fire information to its customers within three hours of observation time. However, the data is screened by a confidence algorithm which seeks to help users gauge the quality of individual hotspot/fire points. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (<15K) in the mid-infrared channel I4. Medium confidence pixels are those free of potential sun glint contamination during the day and marked by strong (>15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.RevisionsMarch 7, 2024: Updated to include source data from NOAA-21 Satellite.September 15, 2022: Updated to include 'Hours_Old' field. Time series has been disabled by default, but still available.July 5, 2022: Terms of Use updated to Esri Master License Agreement, no longer stating that a subscription is required!This layer is provided for informational purposes and is not monitored 24/7 for accuracy and currency.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!
One-foot and two-foot contours derived from LiDAR terrain model. The DTM was developed to support the Florida Division of Emergency Management (FDEM) development and maintenance of Regional Evacuation Studies (Study), which include vulnerability assessments and assist disaster response personnel in understanding threats to Florida's citizens and visitors. Breaklines improve the digital elevation model in areas where the point density is insufficient.This data set is one component of a digital terrain model (DTM) for the Florida Division of Emergency Management's (FDEM) Project Management and Technical Services for Mapping within Coastal Florida (Contract 07-HS-34-14-00-22-469), encompassing the entire coastline of Florida. The dataset is comprised of mass points, 2-D and 3-D breakline features, 1-foot and 2-foot contours, ground control, vertical test points, and a footprint of the data set, in the ESRI ArcGIS File Geodatabase format. In accordance with the Baseline Specifications 1.2, the following breakline features are contained within the database: closed water bodies (lakes, reservoirs, etc) as 2-D or 3-D polygons; linear hydrographic features (streams, shorelines, canals, swales, embankments, etc) as 3-D breaklines; coastal shorelines as 2-D or 3-D linear features; edge of pavement road features as 3-D breaklines; soft features (ridges, valleys, etc.) as 3-D breaklines; low confidence areas as 2-D polygons; island features as 2-D or 3-D polygons; overpasses and bridges as 3-D breaklines. Contours were generated from a gridded DEM: 2-foot contours meet National Map Accuracy Standards, with 1-foot contours for visualization purposes. The LiDAR masspoints are delivered in the LAS file format based on the FDEM's 5,000' by 5,000' grid. Breakline features were captured to develop a hydrologically correct DTM. Bare earth LiDAR masspoint data display a vertical accuracy of at least 0.3-feet root mean square error (RMSE) in open unobscured areas.
This map service was created to support the National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management’s (OCM) Coastal Flood Exposure Mapper. The purpose of the online mapping tool is to provide coastal managers, planners, and stakeholders a preliminary look at exposures to coastal flooding hazards. The Mapper is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help communities initiate resilience planning efforts. Currently the extent of this map service and the Coastal Flood Exposure Mapper is limited to U.S. coastal counties along the Gulf of Mexico and Atlantic Ocean. The purpose of this map service is to depict areas most prone to coastal flood hazards by representing the number of coastal flood hazard zones that overlay an area. Creation of data displayed in this map service included analyses of the following ten flood hazard zones: Federal Emergency Management Agency (FEMA) V zones, FEMA A zones, FEMA shaded X zones, NOAA OCM Flood Frequency zones, NOAA OCM potential sea level rise inundation extents for 1 foot, 2 feet, and 3 feet above current Mean Higher High Water (MHHW), and Sea, Lake, and Overland Surges from Hurricanes (SLOSH) Maximum of the Maximums (MOMs) for categories 1,2 and 3 hurricanes.This is a cached map service. Tiles have been cached down to Level ID 15 (1:18,055).The dataset should be used only as a screening-level tool for management decisions. As with all remotely sensed data, all features should be verified with a site visit. The dataset is provided "as is," without warranty to its performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of this dataset is assumed by the user. This dataset should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes.For more information, visit the Coastal Flood Exposure Mapper (https://coast.noaa.gov/floodexposure).Send questions or comments to the NOAA Office for Coastal Management (coastal.info@noaa.gov).
A Letter of Map Amendment (LOMA) is an official amendment, by letter, to an effective National Flood Insurance Program (NFIP) map. A LOMA establishes a property's location in relation to the Special Flood Hazard Area (SFHA). LOMAs are issued because a property has been inadvertently mapped as being in the floodplain, but is actually on natural high ground above the base flood elevation.This dataset shows entire parcels that have a LOMA associated with them, but this doesn’t mean the LOMA applies to the entire parcel. In fact frequently a LOMA only applies to a particular part of a parcel. Additional research of the actual LOMA document should be completed for a better understanding of what portion of the property is affected.LOMA = Letter of Map Amendment
FEMA = Federal Emergency Management Agency
FIRM = Flood Insurance Rate Maps
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The Coastal Overview data layers identifies the lead authority for the management of discrete stretches of the English coast as defined by the Seaward of the Schedule 4 boundary of the Coastal Protection Act 1949. The data are intended as a reference for GIS users and Coastal Engineers with GIS capability to identify the responsible authority or whether the coast is privately owned. The information has been assigned from the following sources, listed in by preference: Shoreline Management Plans 1; Environment Agency’s RACE database; Consultation with Coastal Business User Group and Local Authority Maritime records where possible. A confidence rating is attributed based on where the data has been attributed from and the entry derived from the source data. The following data is intended as a reference document for GIS users and Coastal Engineers with GIS capability to identify the responsible authority and the assigned EA Coastal Engineer so as to effectively manage the coast for erosion and flooding. The product comprises 3 GIS layers that are based on the OS MasterMap Mean High Watermark and consists of the following data layers that are intended to be displayed as with the confidence factor that the information is correct. Coastal Overview Map [Polyline] –details the Lead Authority, EA Contact and other overview information for coast sections; Coastal Overview Map [Point] – shows the start point of the discrete stretch of coast and the lead authority; and Coastal Legislative Layer [Polyline] - represents the predominant risk; flooding or erosion, which are assigned to each section of the coastline. Attribution statement: Environment Agency Conditional Licence
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Feature layer showing all the fires tracked by Cal OES GIS for the year to date.Fire information is taken from the National Fire and Aviation Management (FAMWEB) in the form of ICS-209 reports. During normal operations these 209 reports are downloaded once a day at 0630, or soon after. During a SOC activation these 209 reports will be downloaded twice a day at 0630 and 1800. Cal OES GIS considers the FAMWEB ICS-209s as the authoritative fire information source.Fire perimeter data is downloaded from the National Interagency Fire Center (NIFC). The data for map is updated daily, M-F, by 0800, the map text by 0900, when there are active fires being tracked by Cal OES.If the SOC is activated the fire map will be updated daily, Sun-Sat, by 0800, the map text by 0900, until the SOC stands down.For a fire to be tracked by Cal OES GIS it needs to be:>100 acres in sizeHave an ICS-209 form.CalOES GIS indicates a fire as contained when it has reached >=90% containment.
Goal 11Make cities and human settlements inclusive, safe, resilient and sustainableTarget 11.1: By 2030, ensure access for all to adequate, safe and affordable housing and basic services and upgrade slumsIndicator 11.1.1: Proportion of urban population living in slums, informal settlements or inadequate housingEN_LND_SLUM: Proportion of urban population living in slums (%)Target 11.2: By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all, improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations, women, children, persons with disabilities and older personsIndicator 11.2.1: Proportion of population that has convenient access to public transport, by sex, age and persons with disabilitiesTarget 11.3: By 2030, enhance inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning and management in all countriesIndicator 11.3.1: Ratio of land consumption rate to population growth rateIndicator 11.3.2: Proportion of cities with a direct participation structure of civil society in urban planning and management that operate regularly and democraticallyTarget 11.4: Strengthen efforts to protect and safeguard the world’s cultural and natural heritageIndicator 11.4.1: Total per capita expenditure on the preservation, protection and conservation of all cultural and natural heritage, by source of funding (public, private), type of heritage (cultural, natural) and level of government (national, regional, and local/municipal)Target 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situationsIndicator 11.5.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationVC_DSR_MISS: Number of missing persons due to disaster (number)VC_DSR_AFFCT: Number of people affected by disaster (number)VC_DSR_MORT: Number of deaths due to disaster (number)VC_DSR_MTMP: Number of deaths and missing persons attributed to disasters per 100,000 population (number)VC_DSR_MMHN: Number of deaths and missing persons attributed to disasters (number)VC_DSR_DAFF: Number of directly affected persons attributed to disasters per 100,000 population (number)VC_DSR_IJILN: Number of injured or ill people attributed to disasters (number)VC_DSR_PDAN: Number of people whose damaged dwellings were attributed to disasters (number)VC_DSR_PDYN: Number of people whose destroyed dwellings were attributed to disasters (number)VC_DSR_PDLN: Number of people whose livelihoods were disrupted or destroyed, attributed to disasters (number)Indicator 11.5.2: Direct economic loss in relation to global GDP, damage to critical infrastructure and number of disruptions to basic services, attributed to disastersVC_DSR_GDPLS: Direct economic loss attributed to disasters (current United States dollars)VC_DSR_LSGP: Direct economic loss attributed to disasters relative to GDP (%)VC_DSR_AGLH: Direct agriculture loss attributed to disasters (current United States dollars)VC_DSR_HOLH: Direct economic loss in the housing sector attributed to disasters (current United States dollars)VC_DSR_CILN: Direct economic loss resulting from damaged or destroyed critical infrastructure attributed to disasters (current United States dollars)VC_DSR_CHLN: Direct economic loss to cultural heritage damaged or destroyed attributed to disasters (millions of current United States dollars)VC_DSR_CDAN: Number of damaged critical infrastructure attributed to disasters (number)VC_DSR_HFDN: Number of destroyed or damaged health facilities attributed to disasters (number)VC_DSR_EFDN: Number of destroyed or damaged educational facilities attributed to disasters (number)VC_DSR_CDYN: Number of other destroyed or damaged critical infrastructure units and facilities attributed to disasters (number)VC_DSR_BSDN: Number of disruptions to basic services attributed to disasters (number)VC_DSR_ESDN: Number of disruptions to educational services attributed to disasters (number)VC_DSR_HSDN: Number of disruptions to health services attributed to disasters (number)VC_DSR_OBDN: Number of disruptions to other basic services attributed to disasters (number)VC_DSR_DDPA: Direct economic loss to other damaged or destroyed productive assets attributed to disasters (current United States dollars)Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste managementIndicator 11.6.1: Proportion of municipal solid waste collected and managed in controlled facilities out of total municipal waste generated, by citiesEN_REF_WASCOL: Municipal Solid Waste collection coverage, by cities (%)Indicator 11.6.2: Annual mean levels of fine particulate matter (e.g. PM2.5 and PM10) in cities (population weighted)EN_ATM_PM25: Annual mean levels of fine particulate matter in cities, urban population (micrograms per cubic meter)Target 11.7: By 2030, provide universal access to safe, inclusive and accessible, green and public spaces, in particular for women and children, older persons and persons with disabilitiesIndicator 11.7.1: Average share of the built-up area of cities that is open space for public use for all, by sex, age and persons with disabilitiesIndicator 11.7.2: Proportion of persons victim of physical or sexual harassment, by sex, age, disability status and place of occurrence, in the previous 12 monthsTarget 11.a: Support positive economic, social and environmental links between urban, peri-urban and rural areas by strengthening national and regional development planningIndicator 11.a.1: Number of countries that have national urban policies or regional development plans that (a) respond to population dynamics; (b) ensure balanced territorial development; and (c) increase local fiscal spaceSD_CPA_UPRDP: Countries that have national urban policies or regional development plans that respond to population dynamics; ensure balanced territorial development; and increase local fiscal space (1 = YES; 0 = NO)Target 11.b: By 2020, substantially increase the number of cities and human settlements adopting and implementing integrated policies and plans towards inclusion, resource efficiency, mitigation and adaptation to climate change, resilience to disasters, and develop and implement, in line with the Sendai Framework for Disaster Risk Reduction 2015–2030, holistic disaster risk management at all levelsIndicator 11.b.1: Number of countries that adopt and implement national disaster risk reduction strategies in line with the Sendai Framework for Disaster Risk Reduction 2015–2030SG_DSR_LGRGSR: Score of adoption and implementation of national DRR strategies in line with the Sendai FrameworkSG_DSR_SFDRR: Number of countries that reported having a National DRR Strategy which is aligned to the Sendai FrameworkIndicator 11.b.2: Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategiesSG_DSR_SILS: Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national disaster risk reduction strategies (%)SG_DSR_SILN: Number of local governments that adopt and implement local DRR strategies in line with national strategies (number)SG_GOV_LOGV: Number of local governments (number)Target 11.c: Support least developed countries, including through financial and technical assistance, in building sustainable and resilient buildings utilizing local materials
Hurricane Helene's track and wind swath through the Carolinas. Data sources: NOAA National Hurricane Center, ESRI, Henderson CountyThe City of Hendersonville stands at the convergence of several creeks and streams within the French Broad River Basin. While the City is no stranger to localized flooding, the days of rain before Helene reached the area exceeded previous records, breaching levels past the 500-year floodplain. Hendersonville received 21.96 inches of rainfall through 8am Saturday, the 3rd highest recorded in the region. (The National Weather Service)
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!
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The high water levels are provided for a range of Average Recurrence Interval (ARI) events. Average recurrence interval is often referred to as a return period. These can be approximately converted to Annual Exceedance Probability (AEP), the probability of occurrence each year, by the following conversion table:ARI (yr)AEP (%)25052010102055021001The high water level values (1% AEP + 1 m sea level) are used to calculate the required height of habitable floors for developments in the coastal inundation hazard zone, as per Unitary Plan rules. High sea level values for Auckland were collected between 2013 and 2019, via four separate studies:In 2013, Auckland Council’s Civil Defence & Emergency Management Department commissioned NIWA to calculate and model coastal-storm inundation elevations for the entire Auckland region, primarily for emergency management purposes. NIWA calculated extreme high-water level values at fixed locations across the region, focusing on the open coasts and harbour areas.In 2016, NIWA calculated high water level values for the east coast estuaries.In 2020, DHI calculated high water levels for the Parakai/Helensville area to the south of the Kaipara Harbour. Inundation in this area is particularly complex due to the wide, low lying coastal plains sitting above the confluence of the Kaipara river with the harbour.Also in 2019, NIWA calculated high water levels for Great Barrier and Little Barrier for 16 sites at ARI scenarios of 1, 2, 5, 10, 20, 50 and 100 yearsDetails of each study and the high water level calculations are available in Technical Report 2020/024Credit:Data supplied by Resilient Land and Coasts, Auckland CouncilUse Limitations:Constraints– General:The high water level values were collated from tables within Technical Report 2020/024. They are made available in GIS to improve the workflow of Regulatory development engineers, specifically in relation to the calculation of habitable floor levels. The dataset is not meant to stand alone, and users outside of Regulatory should be directed to Technical Report 2020/024.Constraints– Legal:There are no legal constraints in relation to this dataset.Constraints– Security:Creative Commons – All Records
Last Updated: January 2015
Map Information
This nowCOAST time-enabled map service provides map depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in. (Cloud cover is not presently displayed due to a problem with the source data. Present weather information is also not available for display at this time.) Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing. The short lines or flags coming off the end of the long line are called barbs. The barb indicates the wind speed in knots. Each normal barb represents 10 knots, while short barbs indicate 5 knots. A flag represents 50 knots. If there is no wind barb depicted, an outer circle around the cloud cover symbol indicates calm winds. The map of observations are updated in the nowCOAST map service approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observation at a particular station may have not updated and may not update until after the next hour. For more detailed information about the update schedule, please see: http://new.nowcoast.noaa.gov/help/#section=updateschedule
Background Information The maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing from the U.S.A. and other countries. For terrestrial networks, the platforms including but not limited to ASOS, AWOS, RAWS, non-automated stations, U.S. Climate Reference Networks, many U.S. Geological Survey Stations via NWS HADS, several state DOT Road Weather Information Systems, and U.S. Historical Climatology Network-Modernization. For over maritime areas, the platforms include NOS/CO-OPS National Water Level Observation Network (NWLON), NOS/CO-OPS Physical Oceanographic Observing Network (PORTS), NWS/NDBC Fixed Buoys, NDBC Coastal-Marine Automated Network (C-MAN), drifting buoys, ferries, Regional Ocean Observing System (ROOS) coastal stations and buoys, and ships participating in the Voluntary Ship Observing (VOS) Program. Observations from MADIS are updated approximately every 10 minutes in the map service and those from NESDIS are updated every hour. However, not all stations report that frequently. Many stations only report once per hour sometime between 15 minutes before the hour and 30 minutes past the hour. For these stations, new observations will not appear until 22 minutes past top of the hour for land-based stations and 32 minutes past the top of the hour for maritime stations.
Time Information
This map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:
Issue a returnUpdates=true request for an individual layer or for
the service itself, which will return the current start and end times of
available data, in epoch time format (milliseconds since 00:00 January 1,
1970). To see an example, click on the "Return Updates" link at the bottom of
this page under "Supported Operations". Refer to the
ArcGIS REST API Map Service Documentation
for more information.
Issue an Identify (ArcGIS REST) or GetFeatureInfo (WMS) request against
the proper layer corresponding with the target dataset. For raster
data, this would be the "Image Footprints with Time Attributes" layer
in the same group as the target "Image" layer being displayed. For
vector (point, line, or polygon) data, the target layer can be queried
directly. In either case, the attributes returned for the matching
raster(s) or vector feature(s) will include the following:
validtime: Valid timestamp.
starttime: Display start time.
endtime: Display end time.
reftime: Reference time (sometimes reffered to as
issuance time, cycle time, or initialization time).
projmins: Number of minutes from reference time to valid
time.
desigreftime: Designated reference time; used as a
common reference time for all items when individual reference
times do not match.
desigprojmins: Number of minutes from designated
reference time to valid time.
Query the nowCOAST LayerInfo web service, which has been created to
provide additional information about each data layer in a service,
including a list of all available "time stops" (i.e. "valid times"),
individual timestamps, or the valid time of a layer's latest available
data (i.e. "Product Time"). For more information about the LayerInfo
web service, including examples of various types of requests, refer to
the nowCOAST help documentation at:
http://new.nowcoast.noaa.gov/help/#section=layerinfo
References
NWS, 2013: Sample Station Plot, NWS/NCEP/WPC, College Park, MD (Available at http://www.hpc.ncep.noaa.gov/html/stationplot.shtml). NWS, 2013: Terminology and Weather Symbols, NWS/NCEP/OPC, College Park, MD (Available at http://www.opc.ncep.noaa.gov/product_description/keyterm.shtml). NWS, 2013: How to read Surface weather maps, JetStream an Online School for Weather (Available at http://www.srh.noaa.gov/jetstream/synoptic/wxmaps.htm).
Last Revised: April 2016
Map Information
This nowCOAST™ time-enabled map service provides maps of NOAA/National Weather Service (NWS) and Office of Oceanic and Atmospheric Research (OAR) Multi-Radar/Multi-Sensor (MRMS) mosaics of quality-corrected base reflectivity images across the Contiguous United States (CONUS) as well as Puerto Rico, Hawaii, Guam and Alaska with a 1 kilometer (0.62 mile) horizontal resolution. The mosaics are compiled by combining regional base reflectivity radar data obtained from Weather Surveillance Radar 1988 Doppler (WSR-88D) also known as NEXt-generation RADar (NEXRAD) sites across the country operated by the NWS and the Dept. of Defense and also from data from Terminal Doppler Weather Radars (TDWR) at major airports. The combined data is then adjusted using a quality-control algorithm developed by the NOAA National Severe Storms Laboratory (NSSL), and published in both GRIB2 and RGB GeoTIFF formats. nowCOAST processes and displays the data from the GRIB2 files. The colors on the map represent the strength of the energy reflected back toward the radar. The reflected intensities (echoes) are measured in dBZ (decibels of z). The color scale is the same as used in the NWS RIDGE2 map viewer, however dBZ values are rounded down to the integer during processing in order to improve display performance. The radar data itself is updated by the NWS every 10 minutes during non-precipitation mode, but every 2-6 minutes during precipitation mode. nowCOAST™ downloads, processes, and displays the latest mosaics every 4 minutes. For more detailed information about layer update frequency and timing, please reference the nowCOAST™ Dataset Update Schedule.
Background Information
Reflectivity is related to the power, or intensity, of the reflected radiation that is sensed by the radar antenna. Reflectivity is expressed on a logarithmic scale in units called dBZ. The "dB" in the dBZ scale is logarithmic and is unitless, and is used only to express a ratio. The "Z" is the ratio of the density of water drops (measured in millimeters raised to the 6th power) in each cubic meter (mm^6/m^3). When the "Z" is large (many drops in a cubic meter), the reflected power is large. A small "Z" means little returned energy. In fact, "Z" can be less than 1 mm^6/m^3 and since it is logarithmic, dBZ values will become negative, as is often the case when the radar is in clear air mode and indicated by earth tone colors. dBZ values are related to the intensity of rainfall. The higher the dBZ, the stronger the rain rate. A value of 20 dBZ is typically the point at which light rain begins. The values of 60 to 65 dBZ is about the level where 3/4 inch hail can occur. However, a value of 60 to 65 dBZ does not mean that severe weather is occurring at that location. The base reflectivity is the lowest (1/2 degree elevation angle) reflectivity scan from the radar. The source of the base reflectivity mosaics is the NOAA Multi-Radar/Multi-Sensor (MRMS) System, which is developed by the NOAA National Severe Storms Laboratory (NSSL) and operated by NWS/National Centers for Environmental Prediction (NCEP) Central Operations (NCO).
Time Information
This map service is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.
In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.
This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.
This service is configured with time coverage support, meaning that the service will always return the most relevant available data, if any, to the specified time value. For example, if the service contains data valid today at 12:00 and 12:10 UTC, but a map request specifies a time value of today at 12:07 UTC, the data valid at 12:10 UTC will be returned to the user. This behavior allows more flexibility for users, especially when displaying multiple time-enabled layers together despite slight differences in temporal resolution or update frequency.
When interacting with this time-enabled service, only a single instantaneous time value should be specified in each request. If instead a time range is specified in a request (i.e. separate start time and end time values are given), the data returned may be different than what was intended.
Care must be taken to ensure the time value specified in each request falls within the current time coverage of the service. Because this service is frequently updated as new data becomes available, the user must periodically determine the service's time extent. However, due to software limitations, the time extent of the service and map layers as advertised by ArcGIS Server does not always provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time extent of the service:
Issue a returnUpdates=true request (ArcGIS REST protocol only)
for an individual layer or for the service itself, which will return
the current start and end times of available data, in epoch time format
(milliseconds since 00:00 January 1, 1970). To see an example, click on
the "Return Updates" link at the bottom of the REST Service page under
"Supported Operations". Refer to the
ArcGIS REST API Map Service Documentation
for more information.
Issue an Identify (ArcGIS REST) or GetFeatureInfo (WMS) request against
the proper layer corresponding with the target dataset. For raster
data, this would be the "Image Footprints with Time Attributes" layer
in the same group as the target "Image" layer being displayed. For
vector (point, line, or polygon) data, the target layer can be queried
directly. In either case, the attributes returned for the matching
raster(s) or vector feature(s) will include the following:
validtime: Valid timestamp.
starttime: Display start time.
endtime: Display end time.
reftime: Reference time (sometimes referred to as
issuance time, cycle time, or initialization time).
projmins: Number of minutes from reference time to valid
time.
desigreftime: Designated reference time; used as a
common reference time for all items when individual reference
times do not match.
desigprojmins: Number of minutes from designated
reference time to valid time.
Query the nowCOAST™ LayerInfo web service, which has been created to
provide additional information about each data layer in a service,
including a list of all available "time stops" (i.e. "valid times"),
individual timestamps, or the valid time of a layer's latest available
data (i.e. "Product Time"). For more information about the LayerInfo
web service, including examples of various types of requests, refer to
the
nowCOAST™ LayerInfo Help Documentation
References
Lin Tang, Jian Zhang, Carrie Langston and John Krause, Kenneth Howard,
Valliappa Lakshmanan, 2014: A Physically Based Precipitation–Nonprecipitation
Radar Echo Classifier Using Polarimetric and Environmental Data in a Real-Time
National System. Weather and Forecasting, 29, 1106–1119, doi: 10.1175/WAF-D-13-00072.1.
(Available at http://journals.ametsoc.org/doi/full/10.1175/WAF-D-13-00072.1).
NWS, 2013: Radar Images for GIS Software
(http://www.srh.noaa.gov/jetstream/doppler/gis.htm).
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Feature layer showing all the fire perimeters tracked by Cal OES GIS for year to date.Fire information is taken from the National Fire and Aviation Management (FAMWEB) in the form of ICS-209 reports. During normal operations these 209 reports are downloaded once a day at 0630, or soon after. During a SOC activation these 209 reports will be downloaded twice a day at 0630 and 1800. Cal OES GIS considers the FAMWEB ICS-209s as the authoritative fire information source.Fire perimeter data is downloaded from the National Interagency Fire Center (NIFC). The data for map is updated daily, M-F, by 0800, the map text by 0900, when there are active fires being tracked by Cal OES.If the SOC is activated the fire map will be updated daily, Sun-Sat, by 0800, the map text by 0900, until the SOC stands down.For a fire to be tracked by Cal OES GIS it needs to be:>100 acres in sizeHave an ICS-209 form.CalOES GIS indicates a fire as contained when it has reached >=90% containment.