What is Storm Data?
Storm Data is a comprehensive database maintained by the National Weather Service (NWS) that provides detailed information about severe weather events in the United States. It includes data on various types of storms such as tornadoes, hurricanes, floods, and thunderstorms. Storm Data contains records of storm occurrence, location, intensity, damage, and fatalities, allowing researchers, meteorologists, and emergency management officials to analyze and study severe weather patterns and their impacts.
Examples of Storm Data include information on hurricanes, tornadoes, thunderstorms, and other severe weather events. Storm Data is used for analyzing and studying weather patterns, assessing the impact of storms, and improving forecasting models. In this page, you’ll find the best data sources for storm data.
Best Storm Datasets & APIs
CustomWeather API | Severe Weather Data | Global Severe Weather Advisories For 85,000 Weather Forecast Locations | Storm Data
wetter.com data | Storm warning data | Severe Weather Warning data | Custom Weather Alert | Rainfall data | Wind data
CustomWeather | Flood Risk Data | 5-Day Ahead Flood Outlook PDFs | Map Data| Severe Weather Data | Weather Forecasts | Storm Data
PredictHQ's Intelligent Event Data | Historical Severe Weather | Florida | April 2023 - March 2024
Monetize data on Datarade Marketplace
Storm Data Use Cases
Frequently Asked Questions
What is Storm Data?
Storm Data refers to weather-related data that is used to monitor and predict severe weather events, such as hurricanes, tornadoes, and thunderstorms.
How is Storm Data collected?
Storm Data is collected through a variety of methods, including radar, satellites, weather stations, and citizen science initiatives. The data is then analyzed and used to create weather forecasts and predictions.
What is Storm Data used for?
Storm Data has numerous practical applications in various industries, including agriculture, transportation, energy, construction, emergency management, and tourism. It is used to monitor weather patterns, predict potential risks, and optimize operations.
What’s a quality checklist for Storm Data?
A quality checklist for Storm Data should include factors such as data accuracy, reliability, availability, interpretability, coverage, cost, and privacy. Addressing these factors can help ensure that the data is of high quality and suitable for the intended purpose.
How is Storm Data priced?
The price of Storm Data varies depending on the data provider, the level of detail required, and the frequency of updates. Commercial providers typically offer subscription plans and pricing tiers based on the volume of data and the level of access required. Some providers also offer free trials and sample data sets to help customers test the data before making a purchase.