The statistic presents the most costly hurricanes to the insurance industry worldwide from 2011 to 2018. Apart from the costs to the insurance industry, total losses have also been included for reference. Hurricane Harvey, which struck the U.S. from August 25th to September 1st 2017, caused insured losses amounting to 30 billion U.S. dollars and total losses reaching 95 billion U.S. dollars.

As of 2024, the Tohoku earthquake and tsunami, which struck Japan in March 2011, remained the most expensive insured loss event since 1900, as it incurred insured losses amounting to 332 billion U.S. dollars. Insuring against natural disasters Insuring is the practice of transferring risk from one entity to another in exchange for payment. It is important, especially if one lives, owns property, or has a business in an area prone to natural disasters, to take out coverage for a range of storms, catastrophic events, and natural disasters. These could cause damage to real estate.When considering this type of insurance, it is indispensable to ask a lot of the important questions up front. How long will it take for a claim to be settled? For example, not all insurers settle claims with the same speed. Many also provide specific exclusions, be they for floods, earthquakes, or other types of natural events. A detailed inspection of exclusions in a policy is important to find out which coverage is still needed. Obviously, the extent of coverage that one should take out is wholly dependent on the area in which one lives. In the United States, as well as in the rest of the world, there are low-risk areas and there are high-risk areas.Despite this, no one can be sure where a natural disaster will occur and the severity of the destruction it could bring with it when it does. No one can stop natural disasters or the economic impact that they have, but insurance helps to mitigate the loss caused by them.

This statistic shows the number of insurance claims filed after Hurricane Irma in Florida as of September 17, 2017, broken down by line of business. The number of commercial property insurance claims amounted to ***** in Florida as of that date.

Overview of Data Sources

Flooding Event Data: The flooding event summaries were developed using the NOAA Storm Events Database, available for download at NOAA National Centers for Environmental Information website. While there are many weather events provided in the NOAA Storm Events Database, only the following values were selected for inclusion in the locality summaries: coastal flood, flash flood, flood, heavy rain, hurricane (typhoon), and tropical storm. Detailed descriptions of event types are provided in Appendix A of NOAA's National Weather Service documentation. The data included in this summary includes events recorded from January 1996 through August 2021.

FEMA National Flood Insurance Program Claims: The NFIP claims data were obtained through the FIMA NFIP Redacted Claims data, available through the OpenFEMA data portal. The data used in this analysis was last updated December 6, 2021.

While every effort has been made to obtain current information about the flood events and flood insurance claims contained herein, no representation or assurance is made regarding the accuracy of the underlying data. Please contact HRDPC staff with questions regarding this dashboard product.

Climate-Risk Home Insurance Market Outlook

According to our latest research, the global climate-risk home insurance market size reached USD 97.4 billion in 2024, driven by a surge in extreme weather events and heightened awareness of climate-related hazards. The market is projected to expand at a CAGR of 8.2% from 2025 to 2033, reaching a forecasted value of USD 189.1 billion by 2033. This robust growth trajectory is primarily attributed to increasing climate volatility, regulatory mandates, and the growing need for tailored insurance products that address specific climate risks.

The primary growth factor for the climate-risk home insurance market is the escalating frequency and severity of natural disasters, such as floods, wildfires, hurricanes, and earthquakes, which have heightened the vulnerability of residential properties globally. Climate change has fundamentally altered risk landscapes, prompting insurers to innovate and expand their product offerings to cover a broader spectrum of climate-induced perils. Homeowners, landlords, and tenants are increasingly seeking comprehensive coverage that not only protects against traditional risks but also addresses new and emerging threats associated with climate change. This shift in consumer demand is compelling insurers to develop more flexible and customizable policies, thereby fueling market expansion.

Another significant driver is the tightening of regulatory frameworks and government policies that mandate adequate protection for residential properties against climate risks. Many governments, especially in regions prone to extreme weather events, are enforcing stricter building codes and insurance requirements. In addition, public-private partnerships are being established to enhance the resilience of communities against climate-related disasters. These initiatives are fostering greater market penetration as insurers collaborate with governmental agencies to design and distribute climate-risk home insurance products. Furthermore, advancements in risk modeling and data analytics are enabling insurers to more accurately price premiums and manage exposure, thereby increasing the accessibility and affordability of climate-risk home insurance.

Technological advancements are also playing a crucial role in the growth of the climate-risk home insurance market. The integration of artificial intelligence, machine learning, and IoT devices is revolutionizing risk assessment, claims processing, and customer engagement. Insurers are leveraging real-time data from smart sensors and satellite imagery to monitor environmental conditions and proactively mitigate damages. These innovations not only enhance the efficiency and effectiveness of insurance operations but also improve customer satisfaction by enabling faster claims settlements and personalized policy offerings. As digital transformation accelerates across the insurance sector, it is expected to further boost the adoption of climate-risk home insurance solutions.

From a regional perspective, North America currently dominates the climate-risk home insurance market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The high prevalence of climate-related disasters, coupled with a mature insurance ecosystem and strong regulatory support, positions North America as a key growth engine. Meanwhile, Asia Pacific is witnessing the fastest growth rate, driven by rapid urbanization, increasing property values, and heightened climate vulnerability. Europe’s market is characterized by robust regulatory frameworks and rising investments in climate resilience. Latin America and the Middle East & Africa are also emerging as promising markets, albeit at a comparatively nascent stage, as awareness and infrastructure development continue to improve.

Coverage Type Analysis

The climate-risk home insurance market is segmented by coverage type into flood insurance, wildfire insurance, hurricane insurance, earthquake insurance, multi-peril insurance, and others. Flood insurance remains one of the most critical segments, particularly in regions prone to heavy rainfall and rising sea levels. The increasing incidence of catastrophic flooding events, exacerbated by climate change, has made flood insurance indispensable for homeowners and landlords. Insurers are enhancing their flood risk models and partnering with government agencies to offer more comprehensive and affordable flood insurance products. In

This statistic shows the number of residential property insurance claims filed after Hurricane Irma in Florida as of ******************, broken down by type. The number of homeowners insurance claims amounted to ******* in Florida as of that date.

National Risk Index Version: March 2023 (1.19.0)A Hurricane is a tropical cyclone or localized, low-pressure weather system that has organized thunderstorms but no front (a boundary separating two air masses of different densities) and maximum sustained winds of at least 74 miles per hour (mph). Annualized frequency values for Hurricanes are in units of events per year.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

Natural Disaster Insurance Market Outlook

The global natural disaster insurance market size was valued at approximately USD 90 billion in 2023 and is projected to reach USD 145 billion by 2032, growing at a CAGR of 5.5% over the forecast period. This growth trajectory underscores the increasing awareness and need for financial protection against the catastrophic losses caused by natural disasters. As climate change intensifies the frequency and severity of such events, the demand for insurance solutions that can mitigate economic risks is rising. This burgeoning market is bolstered by advancements in technology, government policies promoting insurance uptake, and a growing recognition of the importance of risk management strategies among businesses and individuals alike.

One of the primary growth drivers of the natural disaster insurance market is the escalating incidence and severity of natural calamities. Climate change has undeniably increased the frequency of disasters such as hurricanes, floods, wildfires, and earthquakes, leading to unprecedented economic damages. These events have heightened awareness among individuals and organizations about the catastrophic financial impacts of such occurrences, driving the demand for comprehensive insurance coverages. Moreover, the integration of advanced predictive analytics and risk assessment technologies is enabling insurers to offer more tailored and accurate insurance products. This technological evolution not only increases the efficiency of insurance underwriting but also enhances customer satisfaction by providing more personalized solutions.

Government initiatives and policies also play a crucial role in the expansion of the natural disaster insurance market. Many governments worldwide are implementing mandatory insurance policies and providing subsidies to encourage the uptake of disaster insurance. Such initiatives are pivotal in markets where insurance penetration is traditionally low, ensuring that even vulnerable populations have access to financial protection. Additionally, collaborations between public and private sectors are fostering innovative insurance products that are more accessible and affordable, further fueling market growth. In regions prone to specific disasters, governments are also partnering with international organizations to develop risk pooling mechanisms, which help distribute risk and make insurance more viable.

The growing participation of the private sector in offering disaster insurance coverages is another significant factor contributing to market growth. There is an increasing trend among businesses to include disaster risk management as a core component of their strategic plans. Corporations are investing in insurance products to safeguard their assets against potential losses due to natural catastrophes, ensuring business continuity. Insurers, in response, are developing innovative products that cater specifically to the unique needs of various industries, enhancing their market share. This trend is particularly prevalent in sectors such as agriculture, real estate, and infrastructure, which are highly susceptible to natural disasters.

Regionally, North America is expected to lead the natural disaster insurance market due to its high insurance penetration and frequent exposure to natural calamities. The Asia Pacific region is also anticipated to witness substantial growth, driven by rapid urbanization, economic development, and increased vulnerability to extreme weather events. Europe follows closely, benefitting from stringent regulations mandating disaster insurance coverage. Conversely, the Middle East & Africa and Latin America, while experiencing slower growth rates, are gradually increasing their market presence through governmental reforms and international partnerships aimed at enhancing insurance accessibility.

Coverage Type Analysis

Within the natural disaster insurance market, coverage types play a pivotal role in defining the range and scope of protection offered to policyholders. Property insurance remains one of the most sought-after coverage types, primarily because of its direct correlation with asset protection. As real estate and infrastructure investments grow, so too does the need for robust property insurance solutions that can safeguard these investments against natural calamities. This segment is witnessing significant innovations, with insurers offering comprehensive packages that cover a wide array of risks, from floods and earthquakes to hurricanes and wildfires. Insurers are leveraging data analytics and geographic information systems (GIS) to assess risk levels accurately, thus enhancing

The home and property insurance market is experiencing robust growth, driven by increasing urbanization, rising property values, and a growing awareness of the need for risk protection. While precise market sizing data was not provided, considering the presence of major players like State Farm, Allstate, and GEICO, and assuming a conservative CAGR (Compound Annual Growth Rate) of 5% based on industry averages, a 2025 market size of approximately $250 billion USD is reasonable. This figure reflects a healthy expansion from the historical period (2019-2024). Key growth drivers include the escalating frequency and severity of natural disasters such as hurricanes and wildfires, necessitating higher insurance coverage. Technological advancements like smart home devices and improved risk assessment models are also contributing to market expansion. The increasing adoption of online insurance platforms simplifies the purchasing process, attracting a wider customer base and fostering competition. However, several restraints are impacting the market's trajectory. These include fluctuating economic conditions that impact consumer spending on insurance, increased regulatory scrutiny and compliance costs for insurers, and the challenges of accurately assessing and pricing risks in the face of climate change. Segmentation within the market includes individual homeowners insurance, commercial property insurance, and specialized coverage like flood or earthquake insurance. Furthermore, competitive pressures among established players and the emergence of Insurtech startups are reshaping market dynamics, leading to innovations in product offerings and customer service. Regional variations exist, with North America and Europe currently holding significant market share. The forecast period (2025-2033) suggests continued growth, albeit potentially at a moderated CAGR, reflecting the balancing act between growth drivers and market constraints.

As of January 2025, Hurricane Katrina, which occurred between 25 and 30 August 2005, was still the most expensive hurricane to ever hit the United States. It caused insured property losses amounting to almost *** billion U.S. dollars.

The most expensive catastrophe for the Mexican insurance industry as of November 2023 was the COVID-19 pandemic, which began in early 2020. The pandemic resulted in almost 3.5 billion U.S. dollars of insured losses. This was followed by Hurricane Wilma, which hit Mexican coasts in October 2005. This storm was responsible for over 2.6 billion U.S. dollars of insurance claims paid.

National Risk Index Version: March 2023 (1.19.0)The National Risk Index Counties feature layer contains county-level data for the Risk Index, Expected Annual Loss, Social Vulnerability, and Community Resilience.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

National Risk Index Version: March 2023 (1.19.0)A Hurricane is a tropical cyclone or localized, low-pressure weather system that has organized thunderstorms but no front (a boundary separating two air masses of different densities) and maximum sustained winds of at least 74 miles per hour (mph). Annualized frequency values for Hurricanes are in units of events per year.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

Two out of the most expensive winter storms globally for the insurance industry occurred in the United States. The winter storm with the highest insured losses was winter storm Uri, which first hit the Pacific Northwest on February 13, 2021 before moving across the country. Insured losses from Uri reached 15 billion U.S. dollars.

This mesh can be used to analyze the flood hazard exposure for a variety of features, including critical facilities, stormwater and wastewater systems, roadways, etc. The 1-acre cell size was chosen due to the fact that 84+% of the residential parcels in the Tampa Bay region can be individually encompassed by these 1-acre cells. Other considerations included ease of computing and a more accurate representation of spatial transitions afforded by a hexagonal cell shape.Flood hazards include:FEMA 100 and 500-year floodplainsStorm surge- high frequency (Category 1-3) and low frequency (Category 4 & 5)Sea level projections*King tide + sea level projections*10-year storm surge + sea level projections **NOAA Intermediate Low and Intermediate High for 2020, 2040, and 2070 Each AHI point (development from the Assisted Housing Inventory) for the Tampa Bay area is assigned a composite exposure value calculated by summing the presence of potential flood hazards over the time period 2020 - 2070, with a maximum score of 23. Parcel exposure, rounded to the nearest whole number, is as follows:<!- "None" = 0 composite exposure<!--"Low" = 1 - 7 composite exposure<!--"Medium" = 8 - 15 composite exposure<!--"High" = 16 - 23 composite exposureData sources include: <!--FEMA floodplain data are “FLOOD HAZARD ZONES OF THE DIGITAL FLOOD INSURANCE RATE MAP (DFIRM) IN THE STATE OF FLORIDA - OCTOBER 2020,” and obtained from Florida Geographic Data Library (FGDL) (https://fgdl.org/metadataexplorer/explorer.jsp). Metadata for this layer can be found here https://www.fla-etat.org/meta/dfirm_100_floodzones.xml. Storm surge data were obtained from the NOAA National Hurricane Center’s National Storm Surge Hazard Maps, and depict projected surge inundation based on SLOSH modeling and coastal Digital Elevation Models (DEMs). The data and metadata can be found here: https://www.nhc.noaa.gov/nationalsurge/.o Storm surge exposure is divided into low frequency (categories 4 & 5) and high frequency (categories 1-3) groups. This grouping was determined based on the frequency of occurrence of direct hurricane impacts to Florida over the period of 1851 to 2018 (https://www.aoml.noaa.gov/hrd-faq/#1569507388495-a5aa91bb-254c). <!--Sea level rise (SLR) projections were developed by the Tampa Bay Regional Planning Council (TBRPC) based on the 2017 NOAA sea level rise curves (“Intermediate High” and “Intermediate Low”), local tidal data, and Digital Elevation Model (DEM) data using the TBRPC’s Flood Master tool. It should be noted that the Intermediate High projections are consistent with the Florida’s 2021 "Statewide Flooding and Sea Level Rise Resilience" bill and the FEMA National Flood Insurance Program.o Sea level rise projections were calculated for each of the SLR scenarios for the years 2020, 2040 and 2070, and then adjusted using the St. Petersburg tide gauge (for Pinellas, Manatee, Sarasota, Hillsborough and Pasco counties) and the Cedar Key gauge (for Citrus and Hernando counties). Reference tide gauges were based on recommendations from the Climate Science Advisory Panel of Tampa Bay, and tidal data was obtained from the US Army Corps of Engineers SLR calculator: https://cwbi-app.sec.usace.army.mil/rccslc/slcc_calc.html. Mean tide was selected for all runs performed for this project. o TBRPC’s Flood Master tool uses Digital Elevation Models (DEMs) to then determine the areas of inundation associated with the projected sea level rise, as well as the high tide and 10-year event storm surge scenarios. Additional tide gauges and drainage basin boundaries within the TBRPC region were used to refine the inundation estimations. Additional information and the data can be found here: https://opendata-tbrpc.hub.arcgis.com/.<!--King tide + SLR / 10-year storm surge + SLR projections. High tide flooding is derived from “coastal flood frequency” data layers obtained from NOAA Digital Coast (https://coast.noaa.gov/slrdata/), and the 10-year storm surge is derived from a SLOSH study conducted by AECOM. TBRPC combined these two layers with SLR scenarios to provide further inundation analysis. <!--Satellite imagery of flooded land area post-Hurricane Irma (September, 2017) was sourced from Atmospheric and Environmental Research (AER; https://www.aer.com/). This is an experimental flooded land composite satellite data product derived from the NASA Advanced Microwave Scanning Radiometer group of sensors (AMSR-E, AMSR2: https://earthdata.nasa.gov/about/sips/sips-amsr-e-2), the Global Precipitation Measurement Microwave Imager (GMI: https://pmm.nasa.gov/gpm/flight-project/gmi), and the Special Sensor Microwave Imager (SSM/I: https://podaac.jpl.nasa.gov/SSMI). It should be noted that this product was used to provide an interim indication of interior land areas prone to flooding. (Atmospheric and Environmental Research, 2017, ARC Flood Extent Depiction Algorithm Description Document, AFED Version V03R01, Document Revision R03, Lexington, MA. 56pp.)

Data Utilized:Coventry Emergency Operations Center webpage displays live weather conditions at the Coventry Town Hall Annex building. This station is maintained by Coventry Environmental Management Agency (CEMA).Hospitals, Fire Stations, Emergency Medical Services, Law Enforcement datasets display emergency service details and locations as represented by data available from RIGIS.Rhode Island Flood Hazard Areas dataset displays generalized Rhode Island flood hazard areas as represented by FEMA Digital Flood Insurance Rate Map (DFIRM) data available from RIGIS.Tropical Cyclones - Watches, Warnings, and Track/Intensity Forecasts dataset displays the latest NWS/National Hurricane Center (NHC) and Central Pacific Hurricane Center (CPHC) tropical storm and hurricane information. This dataset is updated twice per hour to display up-to-date information. This map service also provides a "working best track" or "best track" for presently active storms, with a forecast uncertainty as conveyed by the track forecast "cone".WAZE Live Map website displays the latest, community-based traffic conditions as represented by data available from WAZE. Windy website displays the latest weather conditions as represented by data available from windy.com.

National Risk Index Version: March 2023 (1.19.0)The National Risk Index Census Tracts feature layer contains Census tract-level data for the Risk Index, Expected Annual Loss, Social Vulnerability, and Community Resilience.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

National Risk Index Version: March 2023 (1.19.0)An Ice Storm is a freezing rain situation (rain that freezes on surface contact) with significant ice accumulations of 0.25 inches or greater. Annualized frequency values for Ice Storms are in units of event-days per year.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

This data layer is an element of the Oregon GIS Framework. This feature dataset contains the following feature classes: 1. FEMA Flood Insurance Study base flood elevation (BFE) lines: The FEMA_BFE feature class is a compilation of FEMA Flood Insurance Study base flood elevation (BFE) lines for the state of Oregon. The FEMA Flood Insurance Study base flood elevation (BFE) lines were derived from Digital Flood Insurance Rate Maps and georeferenced paper Flood Insurance Rate Maps. 2. FEMA Flood Insurance Study inundation zones: The FEMA_FLD_HAZ_AR feature class is a compilation of FEMA Flood Insurance Study inundation zones for the state of Oregon. The FEMA Flood Insurance Study inundation zones were derived from Digital Flood Insurance Rate Maps and georeferenced paper Flood Insurance Rate Maps. 3. FEMA Letter of Map Change (LOMC) Locations: The FEMA_LOMC feature class is a compilation of FEMA Letter of Map Change (LOMC) Locations for the state of Oregon. The FEMA Letter of Map Change (LOMC) Locations were downloaded from the FEMA Map Service Center Website. The LOMC points were precisely located using county-level assessor data, orthoimagery, and lidar hillshades. 4. FEMA Flood Insurance Study profile baselines: The FEMA_PROFIL_BASLN feature class is a compilation of FEMA Flood Insurance Study profile baselines for the state of Oregon. The FEMA Flood Insurance Study profile baselines were derived from Digital Flood Insurance Rate Maps and paper Flood Insurance Rate Maps. 5. FEMA Flood Insurance Study cross section (XS) lines: The FEMA_XS feature class is a compilation of FEMA Flood Insurance Study cross section (XS) lines for the state of Oregon. The FEMA Flood Insurance Study cross section (XS) lines were derived from Digital Flood Insurance Rate Maps and paper Flood Insurance Rate Maps. See feature class metadata for detailed information about each feature class.

In recent years, severe convective storms, or cyclones, caused the highest insured losses in the United States. In 2023, insured losses due to these storms amounted to almost ** billion U.S. dollars, while losses due to drought amounted to approximately *** billion U.S. dollars. Hurricanes in the U.S. The term “tropical cyclone” is a meteorological term which refers to both hurricanes and typhoons. As of 2023, the most expensive natural disaster to have occurred in the U.S. was Hurricane Katrina, which occurred in 2005 and resulted in costs amounting to over *** billion U.S. dollars at the time. Hurricane Ian was the latest hurricane to occur in the United States, and cost around *** billion U.S. dollars. Hurricane Katrina also caused insured property losses worth over ** billion U.S. dollars in 2005. Natural disasters globally Natural disasters are defined as events which are caused by naturally occurring phenomena that result in catastrophe. The global insured losses caused by natural disasters over time has been considerable, with costs amounting to more than *** billion U.S. dollars in 2021 alone. In 2023, the global estimate of insured loss stood at well over *** billion U.S. dollars. At the same time, the estimated economic losses incurred as a result of natural disasters worldwide amounted to almost *** billion U.S. dollars.