Most weather data today is collected and stored at weather stations all over the globe. They are all around us and go unnoticed. Many reside at our local airports or municipal locations. When you are looking for weather history data for your location, most weather systems will simply return data from your nearest station. Knowing how close your weather station is to you can help guide you on how relevant the data is for you whether you want to rely upon it for decision making. More intelligent systems like http://www.visualcrossing.com will use multiple stations, triangulate your exact location and interpolate the results. This is especially useful if you are not terribly close to a major, reputable weather station as is often found in rural locations.
How do I find the weather station nearest to me?
You can find your nearest weather station by following these simple steps:
- Visit the https://www.visualcrossing.com/weather-history free weather dashboard
- Enter your full address into the location box. (if you do not have a full address, you can enter zip codes, cities, states, latitude/longitude values and more)
- Click on the View Data button
- The results will show you a dashboard of the weather history for this location and a map of your location represented as a red point as well the nearest weather stations represented by blue points.
- Change from Map to List view and you will see the list of all nearby weather stations sorted by Distance from your entered location.
The list of weather stations will show the station name, ID (often the airport appended), distance from the location you entered and finally the Latitude and Longitude.
Multi-Station Approach to Weather Data
Visual Crossing by default takes the 3 nearest weather stations to the location entered to compute the accurate weather at your location. The distance to the weather stations are weighted by distance for the final result. If your location is 10, 40, 50 miles away from weather stations, they will be weighted by these distances. It greatly helps areas that are far from weather stations to both determine through interpolation the most accurate values. Additionally Visual Crossing uses the multiple station approach to cleanse inaccurate or missing data. On rare occasions, data for a specific location may be missing or incorrect. By comparing data across stations, a more accurate report can be determined by eliminating empty values and values that outside of reasonable ranges.