OnPoint Climatology

The Most Accurate, Robust Climatology

Data on the Market

Climatology is the statistical representation of weather over time.

OnPoint Climatology offers valuable information such as: the “normal” or “average” (mean) weather for any location at any point in time; departures from normal (standard deviations); and frequency of occurrence for specific weather parameters such as precipitation or extreme temperatures.

Frequency of occurrence insights reveal how often certain conditions occur at your location of interest, for example, how often it snows within the range of 1 to 2 inches or how many times it typically rains on a given day.

This information is extremely useful for business planning. For instance, a road salt distributor is more concerned with how many unique snow events are “normal” on a particular day than with how many inches it is likely to snow on said day.


Climatology + Weather Data = Success

OnPoint Climatology can be used in combination with OnPoint Weather to identify and rank departures from normal. For example, pairing temperature forecasts from OnPoint Weather with the associated OnPoint Climatology temperature means can yield forecasted anomalies. Departures from normal can have significant influence on consumer behavior and business operations.

Our revelations take the guesswork out of organizational decisions that may be affected by changes in weather. For example, sales of iced coffee accelerate during abnormally high temperatures and drop during unseasonably cool ones. Therefore, a coffee chain using OnPoint Climatology can drive efficiencies by planning inventory and staff schedules accordingly during periods of anomalies.

Long-Range Forecasting

OnPoint Climatology is also useful as a long-range forecasting tool. The majority of forecasts can only provide a reliable outlook of 7 to 10 days, after which point certain weather parameters such as wind and cloud cover become less accurate. More advanced projections may be able to look forward a few weeks with some detail, but beyond that, long-range forecasts tend to be even less precise.

Using our cutting-edge climatological technology, Weather Source is able to go beyond these challenges to provide accurate forecasts of up to 15 days with an enhanced and extended forecast out to 42 days.

OnPoint Climatology in Action

A large pharmaceutical company seeking to proactively market asthma medication used OnPoint Climatology to identify weather parameters that trigger the condition. After successfully correlating certain weather parameters to the start of asthma season, Weather Source created a predictive model that monitored U.S. forecasts for those parameters in addition to anomalies such as unseasonably warm spring temperatures. The company was then able to market their product in those areas in advance of the competition, enabling them to instantly provide potential customers with a free, 30-day trial prescription.

A nationwide retailer used OnPoint Weather to make decisions regarding when to mark-down or remove seasonal products in advance of the next season. Weather Source performed analysis on certain seasonal products to identify what weather parameters resulted in lower sales activity. We also applied OnPoint Climatology to create a predictive model to establish when to move seasonal inventory based on “normal” weather. This was then compared with OnPoint Weather forecast data to identify departures from normal and help the customer determine when to mark-down products, remove inventory, or keep products on the shelf at full price.

A global technology company was searching for the ideal location to build a ground-based satellite imaging station. With concerns that fog, precipitation, and cloud cover could negatively affect the satellite imaging quality, the company sought locations where those conditions were least likely to occur in 12-hour increments. Weather Source used hourly OnPoint Climatology data to create a heat map of the customer’s desired locations and revealed the ideal location to build the imaging station.

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