Tomorrow.io’s Statistical Weather Data API: Go Beyond the Forecast
Analyze and interpret weather events with Tomorrow.io’s best-in-class Statistical Weather Data API.
The Value of a Statistical Weather Data API
Access a Robust Library of Parameters for Comprehensive Statistical Weather Data
Take a Statistical Approach to Weather Data
With a variety of API data points, businesses can build their own statistical-based analytic tools. Some Tomorrow.io customers work with the API to build data models and algorithms that help make predictions. Historical and analytical data gives businesses a competitive advantage as they identify customer behavior patterns and changes based on weather.
Using weather data, organizations already save millions on future events. Take the insurance industry as an example. Weather events damage homes, threaten lives, and damage other assets like cars. Not only do insurance companies care about weather, but their customers do too. Insurance companies currently use the Tomorrow.io API to gather data and build statistical tools to then alert their customers of impending weather events. A survey showed that 90% of their customers appreciated the notifications and found value in messages warning of future weather events. Notifications warn users of floods, hurricanes, fires, high winds, hail and other events that could damage property. With these notifications, insurance customers could prepare ahead of time so that there is less damage to their property. The statistical information helps customers avoid damage but also saves the insurance company millions in claims.
Another example of the power of statistical data is the way Uber uses Tomorrow.io to optimize their estimated time of arrival (ETA) shown to riders and better prepare for an increase in ride requests. Not only does Uber optimize operations, but they use Tomorrow.io’s API to drive revenue. Using statistical data from our API, Uber’s algorithms more accurately provides riders with ETA information and makes decisions in real-time. The API contains numerous data points for minute-by-minute granular weather patterns so that any changes are already accounted for in the app. Uber also works with the Tomorrow.io API historical data to create artificial intelligence-driven insights so that they can make changes to operations quickly and provide safe transportation for their drivers and passengers across the globe.
Using Statistical Parameters
Developers can build hyper-accurate applications using the Tomorrow.io API due to the numerous data points available across locations and even get historical data to identify patterns and trends that would not be available with basic API data. Several industry leaders already use the Tomorrow.io API for statistical analysis of weather events that drive consumer patterns, buying habits, preparation, and travel and transportation habits.
Because the Tomorrow.io has so many data layers, it’s completely flexible to your own use case and industry needs. The API returns JSON data sets, allowing developers to integrate it into any platform, language, application or environment. You can integrate today, tomorrow, or yesterday’s events into algorithms and applications. Choose from the many parameters available to build your own analytics applications.
Weather API Capabilities
Learn more about the Tomorrow.io Weather API’s enterprise-grade capabilities:
Leverage our Statistical Weather Data API for a Variety of Real-World Use Cases
import requests
url = "https://api.tomorrow.io/v4/timelines?location=YOUR_LOCATION&fields=visibility&units=metric×teps=1h&apikey=YOUR_KEY"
headers = {"Accept": "application/json"}
response = requests.request("GET", url, headers=headers)
print(response.text)
{
"data": {
"timelines": [
{
"timestep": "1h",
"endTime": "2022-03-08T10:00:00Z",
"startTime": "2022-03-03T22:00:00Z",
"intervals": [
{
"startTime": "2022-03-03T22:00:00Z",
"values": {
"visibility": 16
}
},
{
"startTime": "2022-03-03T23:00:00Z",
"values": {
"visibility": 16
}
},
{
"startTime": "2022-03-04T00:00:00Z",
"values": {
"visibility": 16
}
},
{
"startTime": "2022-03-04T01:00:00Z",
"values": {
"visibility": 16
}
},
snipped for brevity....
}
]
}
}
Each interval in the JSON data set contains values for the parameters we requested, which was visibility. This example returns only one field, but you can choose from 60 fields listed in the core documentation.
