When severe weather occurs in the United States, there are networks of humans and sensors that observe and report the events and their details to the National Weather Service. These storm reports are aggregated and archived by NOAA's National Centers for Environmental Information. With over 1.7 million records over 70 years, the Storm Events Database is the most comprehensive, official record of severe weather in the U.S. This layer is a simplified version of the full database, providing information on:DateLocationEvent TypeNumber of injuries and deathsEstimated property damageEvent/episode summariesUse the NOAA Storm Events Database Explorer ArcGIS Dashboard for a more interactive data exploration. Known Data Quality Issue: approximately 650,000 of the 1.71 million features do not include latitude or longitude values in the original NOAA data source. To address these issues in the 2021 data update, the following has been done:Use the county and state fields the geolocate unknown locations using the ArcGIS World Geocoding Service. These events will all appear at the county centroid. There are a total of 646,039 records in this category. The field LatLon Known describes if an original geolocation was provided (Yes) or if it was generated per above (No).Marine (CZ_Type = M) locations without a known lat/lon were not included. There are a total of 3,987 records in this category. For related archives of weather information, please see the Windstorm Points and Paths, Hailstorm Points and Paths, and Historical Hurricane layers.Data caveatsPer NCEI, the "National Weather Service receives their information from a variety of sources, which include but are not limited to: county, state and federal emergency management officials, local law enforcement officials, skywarn spotters, NWS damage surveys, newspaper clipping services, the insurance industry and the general public, among others." However, these sources are all population-dependent, and many severe weather events are assumed to not be reported in areas of low population. Not only does this bias occur across space, but also across time as many areas had lower populations in the mid-20th Century, and more advanced networks and reporting methods have evolved with technology.

The Severe Weather Data Inventory (SWDI) is an integrated database of severe weather records for the United States. SWDI enables a user to search through a variety of source data sets in the NCDC (now NCEI) archive in order to find records covering a particular time period and geographic region, and then to download the results of the search in a variety of formats. The formats currently supported are Shapefile (for GIS), KMZ (for Google Earth), CSV (comma-separated), and XML. The current data layers in SWDI are: Storm Cells from NEXRAD (Level-III Storm Structure Product); Hail Signatures from NEXRAD (Level-III Hail Product); Mesocyclone Signatures from NEXRAD (Level-III Meso Product); Digital Mesocyclone Detection Algorithm from NEXRAD (Level-III MDA Product); Tornado Signature from NEXRAD (Level-III TVS Product); Preliminary Local Storm Reports from the NOAA National Weather Service; Lightning Strikes from Vaisala NLDN.

This dataset contains data on damages, deaths, and injuries associated with eight aggregate extreme weather event types by county and year-month, covering the lower 48 states from 1995 to 2022. This dataset is created by processing the NOAA Storm Events database and used in an analysis of the impacts of extreme weather events across across the contiguous United States in the Resources blog post Series “Storm Watch Series: Weather Volatility in the United States”.

The Storm Events Database is an integrated database of severe weather events across the United States from 1950 to this year, with information about a storm event's location, azimuth, distance, impact, and severity, including the cost of damages to property and crops. It contains data documenting: The occurrence of storms and other significant weather phenomena having sufficient intensity to cause loss of life, injuries, significant property damage, and/or disruption to commerce. Rare, unusual, weather phenomena that generate media attention, such as snow flurries in South Florida or the San Diego coastal area. Other significant meteorological events, such as record maximum or minimum temperatures or precipitation that occur in connection with another event. Data about a specific event is added to the dataset within 120 days to allow time for damage assessments and other analysis.

Documentation

https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00773

Update Frequency

Monthly

License

Open Data. There are no restrictions on the use of this data. Use of the data should cite NOAA and NESDIS/NCEI as the dataset creator and the Severe Weather Data Inventory as the dataset.

Storm Data is provided by the National Weather Service (NWS) and contain statistics on personal injuries and damage estimates. Storm Data covers the United States of America. The data began as early as 1950 through to the present, updated monthly with up to a 120 day delay possible. NCDC Storm Event database allows users to find various types of storms recorded by county, or use other selection criteria as desired. The data contain a chronological listing, by state, of hurricanes, tornadoes, thunderstorms, hail, floods, drought conditions, lightning, high winds, snow, temperature extremes and other weather phenomena.

Storm Data is provided by the National Weather Service (NWS) and contain statistics on...

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.

The Aotearoa New Zealand (ANZ) Extreme Weather Events (EWE) database (EWE_database_V1.0.0.xlsx) is a comprehensive record of extreme weather events in ANZ. The events listed in this database have been carefully assessed and categorized based on their meteorological significance, considering their rarity and whether they broke records or triggered official weather warnings. Some of the metrics used to classify each event rely on subjective judgment and expert opinions. The database captures meteorologically significant events, including those that have caused substantial damage to properties or led to casualties, and, in some cases, includes supplementary information about their socioeconomic impacts. The information in the EWE database is primarily sourced from the Meteorological Service of New Zealand Ltd (MetService) and the National Institute of Water and Atmospheric Research (NIWA). Additional impact data have been added from various media sources, with insured loss data for some events sourced from the Insurance Council of New Zealand (ICNZ).

Note - For more information about the database and the other additional files, please look into the Metadata (Metadata_EWE_V.1.0.0.docx) and the supplementary document (Supplementary document on EWE_V.1.0.0.docx).

This dataset includes national holidays and days before and after them, recorded storms, and major delays at airports. Sources include the National Centers for Environmental Information Storm Events Database and official holidays.

During the late afternoon and evening of 23 July 2010, an intense supercell storm produced severe wind gusts, an EF0 tornado, and extremely large hail as it tracked southeastward across south-central South Dakota. The largest hailstone preserved from the storm was found in Vivian, SD and would go on to set United States records for maximum weight and diameter. The dataset is taken directly from the National Oceanic and Atmospheric Administration, National Centers for Environmental Information Storm Events Database. The Storm Events Database contains the records used to create the official NOAA Storm Data publication.

Source: The Emergency Events Database (EM-DAT) , Centre for Research on the Epidemiology of Disasters (CRED) / Université catholique de Louvain (UCLouvain), Brussels, Belgium – www.emdat.be.Category: Climate and WeatherData series: Climate related disasters frequency, Number of Disasters: TOTAL  Climate related disasters frequency, Number of Disasters: Drought  Climate related disasters frequency, Number of Disasters: Extreme temperature  Climate related disasters frequency, Number of Disasters: Flood  Climate related disasters frequency, Number of Disasters: Landslide  Climate related disasters frequency, Number of Disasters: Storm  Climate related disasters frequency, Number of Disasters: Wildfire Climate related disasters frequency, People Affected: Drought  Climate related disasters frequency, People Affected: Extreme temperature  Climate related disasters frequency, People Affected: Flood  Climate related disasters frequency, People Affected: Landslide  Climate related disasters frequency, People Affected: Storm  Climate related disasters frequency, People Affected: Wildfire Climate related disasters frequency, People Affected: TOTAL  Disaster IntensityMetadata:EM-DAT: The International Disasters Database - Centre for Research on the Epidemiology of Disasters (CRED), part of the University of Louvain (UCLouvain) www.emdat.be, Brussels, Belgium. Only climate related disasters (Wildfire, Storm, Landslide, Flood, Extreme Temperature, and Drought) are covered. See the CID Glossary for the definitions. EM-DAT records country level human and economic losses for disasters with at least one of the following criteria: i.          Killed ten (10) or more people  ii.         Affected hundred (100) or more people  iii.        Led to declaration of a state of emergency iv.        Led to call for international assistance   The reported total number of deaths “Total Deaths” includes confirmed fatalities directly imputed to the disaster plus missing people whose whereabouts since the disaster are unknown and so they are presumed dead based on official figures. “People Affected” is the total of injured, affected, and homeless people. Injured includes the number of people with physical injuries, trauma, or illness requiring immediate medical assistance due to the disaster. Affected includes the number of people requiring immediate assistance due to the disaster. Homeless includes the number of people requiring shelter due to their house being destroyed or heavily damaged during the disaster. Disaster intensity is calculated by summing “Total Deaths” and 30% of the “People Affected”, and then dividing the result by the total population. For each disaster and its corresponding sources, the population referred to in these statistics and the apportionment between injured, affected, homeless, and the total is checked by CRED staff members. Nonetheless, it is important to note that these are estimates based on certain assumptions, which have their limitations. For details on the criteria and underlying assumptions, please visit https://doc.emdat.be/docs/data-structure-and-content/impact-variables/human/. Methodology:Global climate related disasters are stacked to show the trends in climate related physical risk factors.

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

Climate affects many aspects of our daily lives. Transportation, industrial processes, tourism, environment, and agriculture are closely tied to climatic factors. Even our recreation and general lifestyles are influenced by the climate of our region. Because of this, one of the primary objectives of the SCO is to provide accurate and thorough climate information to all of North Carolina's citizens, including private industry, community economic development authorities, state agencies, schools, community colleges, universities, and other community organizations. The SCO provides a wealth of information which is available to everyone.

Climate Monitoring Services Available include:

• Climate Retrieval and Observations Network Of the Southeast (CRONOS)

enables the public to quickly and easily retrieve archived weather observations from 216 stations in and around North Carolina.

• AgNet

a network of automated weather stations located at most of the outlying research stations and field laboratories.

• Drought

Links to web sites with drought monitoring data and information.

• NC ECONet

North Carolina Environment and Climate Observing Network

• Station Density

  Analysis of Monitoring Station Density of the North Carolina Environment and Climate Observing System (NC ECONet)

• Storm Events Database

Access the National Climatic Data Center's Storm Events Database.

Access All Products: https://climate.ncsu.edu/cronos

[Summary Extracted from the State Climate Office of North Carolina Home Page]

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

This is a source of data about funding, projects and outputs related to research on extreme weather events. It was co-ordinated by the New Zealand Research Information System team to enable the sharing of ideas across the science and innovation sector during New Zealand’s response to the extreme weather events of 2023 including Cyclone Gabrielle.

This Event Duration Monitoring (EDM) dataset relates to the performance of storm overflows in England. Data are provided by Water and Sewerage Companies (WaSCs) to the Environment Agency each year as part of their regulatory Annual Return, to fulfil their permitted conditions to discharge from these storm overflows under the Environmental Permitting Regulations.

Data files are provided by year (2024, 2023, 2022, 2021 & 2020) and include a sheet for each of the 10 WaSCs with storm overflows in England. Each WaSC sheet shows how often and how long each monitored storm overflow discharged during that year. From 2021 onwards the dataset also includes reasons why event duration monitors (EDM) may have provided information for <90% of the relevant return period, and why an overflow may have high spill counts in that period. These data reflect the best available information held by the WaSC at time of submission.

The data file for each year also contains key summary data tables. These include: number of storm overflows with EDM, number of storm overflows returning spill counts, average spill duration and average spill count for each WaSC. A dataset README guide is also provided which provides further information to help use and understand the data.

A sixth data file contains the annual key summary data from respective years plus a table showing long-term trends from 2016-2024.

Previously curated at: http://cedadocs.ceda.ac.uk/1314/ Contact for resource: Georgina.Endfield@liverpool.ac.uk. The publish date on this item was its original completed date. This work was funded by: AHRC. Associated projects: Spaces of Experience and Horizons of Expectation: Extreme weather in the UK, past, present and future (AH/K005782/1) Main files in this record: TEMPEST data quality statement.docx Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Dr Lucy Veale. Transferred to CEDA document repository community on Zenodo on 2022-11-24 This document provides a statement of the data quality within the TEMPEST (Tracking Extremes of Meteorological Phenomena as Experienced in Space and Time) database of extreme weather event narratives as detailed in primary archival sources.

A database of verified tornado occurrences across Canada has been created covering the 30-year period from 1980 to 2009. The tornado data have undergone a number of quality control checks and represent the most current knowledge of past tornado events over the period. However, updates may be made to the database as new or more accurate information becomes available. The data have been converted to a geo-referenced mapping file that can be viewed and manipulated using GIS software.

This database, and the accompanying website called ‘SurgeWatch’ (http://surgewatch.stg.rlp.io), provides a systematic UK-wide record of high sea level and coastal flood events over the last 100 years (1915-2014). Derived using records from the National Tide Gauge Network, a dataset of exceedence probabilities from the Environment Agency and meteorological fields from the 20th Century Reanalysis, the database captures information of 96 storm events that generated the highest sea levels around the UK since 1915. For each event, the database contains information about: (1) the storm that generated that event; (2) the sea levels recorded around the UK during the event; and (3) the occurrence and severity of coastal flooding as consequence of the event. The data are presented to be easily assessable and understandable to a wide range of interested parties. The database contains 100 files; four CSV files and 96 PDF files. Two CSV files contain the meteorological and sea level data for each of the 96 events. A third file contains the list of the top 20 largest skew surges at each of the 40 study tide gauge site. In the file containing the sea level and skew surge data, the tide gauge sites are numbered 1 to 40. A fourth accompanying CSV file lists, for reference, the site name and location (longitude and latitude). A description of the parameters in each of the four CSV files is given in the table below. There are also 96 separate PDF files containing the event commentaries. For each event these contain a concise narrative of the meteorological and sea level conditions experienced during the event, and a succinct description of the evidence available in support of coastal flooding, with a brief account of the recorded consequences to people and property. In addition, these contain graphical representation of the storm track and mean sea level pressure and wind fields at the time of maximum high water, the return period and skew surge magnitudes at sites around the UK, and a table of the date and time, offset return period, water level, predicted tide and skew surge for each site where the 1 in 5 year threshold was reached or exceeded for each event. A detailed description of how the database was created is given in Haigh et al. (2015). Coastal flooding caused by extreme sea levels can be devastating, with long-lasting and diverse consequences. The UK has a long history of severe coastal flooding. The recent 2013-14 winter in particular, produced a sequence of some of the worst coastal flooding the UK has experienced in the last 100 years. At present 2.5 million properties and £150 billion of assets are potentially exposed to coastal flooding. Yet despite these concerns, there is no formal, national framework in the UK to record flood severity and consequences and thus benefit an understanding of coastal flooding mechanisms and consequences. Without a systematic record of flood events, assessment of coastal flooding around the UK coast is limited. The database was created at the School of Ocean and Earth Science, National Oceanography Centre, University of Southampton with help from the Faculty of Engineering and the Environment, University of Southampton, the National Oceanography Centre and the British Oceanographic Data Centre. Collation of the database and the development of the website was funded through a Natural Environment Research Council (NERC) impact acceleration grant. The database contributes to the objectives of UK Engineering and Physical Sciences Research Council (EPSRC) consortium project FLOOD Memory (EP/K013513/1).