Accurate & Agriculture-Specific Weather Data
Weather Terrain™ processes billions of data points daily using advanced methodologies, science, and technologies designed exclusively to deliver the best weather data for field-level decisions and agronomic modeling. Every design and processing decision is optimized for better agriculturally-relevant weather.
Our data center continuously imports and processes multiple high quality sources of raw meteorological data—never relying on just one data source for any location. Our ground station network spans the globe, and only includes agriculturally-relevant weather stations (those in fields or away from cities). Layered on top of that is Doppler radar and both public and exclusive satellite data. Our proprietary algorithms select the most appropriate sources and logic for each location, and we do all this with the same approach, quality, and resolution all around the globe.
Hyperlocal and Highly Accurate
We don't send your request to "the closest weather station." Instead, we have developed a sophisticated algorithm that interpolates and compares multiple sensors for each reported location value, taking to account local topography. A proprietary blended model of station, radar, satellites, and exclusive algorithms from CSU's Cooperative Institute for Research in the Atmosphere accounts for the variability of precipitation. This means that weather resolution is irrelevant—we provide the weather at any geolocation regardless resolution.
Moreover, our methodology is accurate to within +/-0.58°C in the US Corn Belt, and +/-0.68°C worldwide. For temperatures (and relative humidity), our 3D multi-point interpolation includes adiabatic corrections for the elevation differences between surrounding stations and the observation location. That is why our statistic is so consistent both in the Corn Belt where stations are often a few kilometers apart, and in Africa or Asia where stations can be 50-100 Km apart.
Our data is trusted by major agricultural companies as well as university and private research programs. In fact, one of the largest agricultural R&D organizations stopped deploying weather stations because our data was just as good and more reliable.
What is Important to Farming?
Weather, soil health and varietal selection are three vital and inextricably interwoven variables that affect crop yields and quality. Of those, weather is by far the least controllable and most influential over otherwise best laid plans. Regarding weather, there are short-term extreme events (flash flood, frost, hail, extreme heat) that can have season impacts in a single day, but for the most part, crops react to aggregated periods of weather: accumulated rain across a growth stage or accumulated heat units or growing degree days. For example, a half-inch rain event that arrives a day late or a day that is a few degrees cooler or warmer than expected has little effect in isolation.
The same criteria holds for observation accuracy. While a few millimeters of rain or a couple of degrees difference on a given day will not likely affect a farming decision, accumulations over one-to-two weeks will. That is why we quantify and pay attention to both daily and accumulated accuracies.
Validating Our Data
The real question to ask of any weather values reported by aWhere or any system is "How well do the reported values reflect what is happening on my field?" At aWhere, the values we return for your field are always generated from multiple sources and we use the same algorithms to test the values we report to give you statistical confidence for daily and accumulated values.
aWhere breaks the world into 22 agronomic zones and statistically cross validates our estimates against each ground observation station with that station removed. As an example, we perform this value validation across each of more than 450 stations in the corn belt which provides statistical confidence in what values we would provide for any arbitrary field location if you were to place a ground station on that field.
Learn more about weather accuracy and how we provide best-in-class agricultural weather data in this whitepaper.