Weather Source™ API

Powered by OnPOINT® Weather

Past Weather Data Updated Hourly

Access 4 Standard Data Sets: Hourly Latitude/Longitude; Daily Latitude/Longitude; Hourly Postal Code; Daily Postal Code.

  • Easy to follow Documentation
  • A pragmatically RESTful interface
  • JSON and JSONP response formats
  • Detailed error reporting
  • Always on SSL connections
  • Account management tools
  • An SDK for PHP

Why OnPOINT® Weather Data is Superior to Weather Station Observations

Proximity and Relevance

Weather stations are typically located at airports, which tend to be scattered among major cities. In the US, the distance between airport weather stations is typically 50 miles, and frequently over 100 miles. Trying to correlate these station observations to business metrics (sales, etc) is often futile since the weather recorded at the station is very different from what occurred at the business of interest.

In contrast, OnPOINT® Weather is spatially very dense such that in North America OnPOINT® data is always within 2 miles from your points of interest, and within 10 miles for international locations outside North America.

Data Quality

The purpose and priority of airport weather stations is to provide pilots with the real-time weather information. The follow-on care and archiving of this weather information by government agencies is less critical, and often results in data errors and gaps. In general, every original time-series of weather observations from government stations contains numerous errors and gaps that can negatively impact the utility of this weather data for business purposes.

So while real-time weather station data is great for aviation, it is not good fit for business needs. With OnPOINT® Weather, the priority is to provide accurate and reliable past, present, and forecast weather, and the OnPOINT® system is engineered for this purpose.

Key Benefits

  • Hyper-local weather information ensures relevance
  • Global coverage from a consistent weather data product – no need to source numerous weather datasets
  • Data is available on hourly and daily units and can be aggregated to fit your specific needs
  • Unparalleled accuracy and reliability
  • Data is available from January 2000 to current time
  • Weather and climate values can be combined to provide departures from normal.

OnPOINT® Weather is the result of years of research by a team of top meteorologists, data scientists, and mathematicians who remain focused on the challenge of building a comprehensive system to provide the most accurate and reliable past, present and forecast weather to our customers and partners.

The OnPOINT® Weather system processes an array of weather input data sources (e.g. weather observations, satellite, radar, weather models, etc) to produce OnPOINT® data. The system embodies intelligence to identify and correct data errors that regularly occur within the various input sources. These intelligent data analysis methods are a fusion of meteorological and statistical expertise and have proven to be very effective for correcting real data errors while preserving actual extreme weather that may otherwise be falsely ‘corrected’ by less capable methods.

OnPOINT® Weather is staged on geographic grids, from which the Weather Source™ API can provide weather at any lat/lon point, and for many common geographic areas such as postal codes and DMAs. Our North American grid provides very fine scale resolution where the closest OnPOINT® data is always 2 miles or less from any point of interest. In addition, our API will smartly interpolate between 4 nearby OnPOINT® locations to provide the most accurate weather for any location of interest. The International OnPOINT® grid operates the same way, but on a grid where the closest OnPOINT® data is always 10 miles or less from any point of interest. In total OnPOINT® covers nearly 2 million points globally. Comparatively, there are less than 10,000 viable weather observation stations in the world; these stations are often too far away from your point interest to be effective.

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