Weather Data Quality Control Services
Accurate weather information is essential for various sectors, including agriculture, transportation, emergency management, climate research, and more. Reliable data helps in making informed decision, minimizing risk, and improving overall preparedness for extreme weather events.
Quality control is a crucial process to ensure the accuracy and reliability of the data from our Weather Data API. This process involves identifying and correcting errors, inconsistencies, and outliers in the data to provide trustworthy insights to all our users.
Weather data is collected from a variety of sources and each type of weather stations collects and reports data a little differently. When data is added to the Synoptic Weather API it is immediately run through our Basic Quality Control, which includes range checks, rate of change checks, and persistence checks for most variables. This means that the data is in a plausible range for each data type in the Weather API.
Just because weather data falls within range and rate checks it doesn’t necessarily mean it’s always true for the surrounding conditions. Weather stations and sensors can malfunction quickly and without warning. This is why Synoptic developed its proprietary Advance Quality Control to help identify values that are physically plausible but are still clearly outliers. The Advanced Quality Control filters out bad data values based on spatial value checks and a variety of percentile checks to ensure the accuracy and reliability of the data you use through the Weather Data API.