In the world of meteorology, a data point without a height reference is like a map without a scale. When you access weather variables through Visual Crossing, you are using a sophisticated blend of physical observations from multiple sources and reanalysis models.
To ensure your modeling is accurate, it is vital to distinguish between what is physically measured by a sensor at a specific height and what is derived or calculated to fill the gaps between stations.
Section 1: The Observed Layer – Ground to 10 Meters
This layer is the “anchor” of any weather model, relying on direct physical observations from global weather stations.
- Atmospheric (Ambient) | 2 Meters (6.5 ft):
- Variables: Air Temperature, Humidity, and Pressure.
- Data Type: Measured. Sensors are placed at “head height” to capture the environment humans and crops actually inhabit. Pressure is a critical anchor variable used to stabilize the entire global model.
- Surface Wind | 10 Meters (33 ft):
- Variables: Wind Speed, Direction, and Gust.
- Data Type: Measured. This is the global meteorological standard. Sensors at 10m are high enough to avoid “surface roughness” (friction from grass and small buildings), providing a clean baseline.
- Ground Precipitation | 0 Meters (Surface):
- Variables: Rain and Snow Accumulation.
- Data Type: Measured. Physical tipping-bucket gauges record accumulation exactly where it hits the earth.
Section 2: The Sky & Radiation Layer
This is where data moves from direct hardware measurements to derived and calculated values.
- Solar GHI (Global Horizontal Irradiation):
- Data Type: Derived. Physical sensors called pyranometers measure solar radiation. These are specialized “light meters” set up by national weather services and research institutions. Because they are expensive and rare, GHI for most locations is derived via a radiative transfer model. It starts with the sun’s angle and “subtracts” energy based on modeled cloud density and aerosols.
- Sky Conditions (Cloud Cover & Visibility):
- Cloud Cover: Satellite-Derived. Measured by infrared and visible sensors on satellites orbiting at roughly 36,000 km. The “height” of the cloud itself is calculated based on the temperature of the cloud top compared to the known atmospheric temperature at various altitudes.
- Visibility: Calculated. While airports use scatterometers at the surface, global visibility is a calculation based on measured humidity and particulate matter. If humidity is high and particulates are present, the model “calculates” a reduction in visual range.
Section 3: The Precipitation Options – Radar vs. Station
Precipitation is the only variable we track at two distinct heights to ensure accuracy in remote areas. While we always prefer the gold standard accuracy of rain gauges at observational stations, sometimes we need to lean on the technology of radar to determine values at great distance from stations. In addition to precipitation measurements, we also get tremendous value from radar to tell us the when, where and intensity of storms prior to logging an event.
- Radar Precipitation | ~500m to 3,000m+:
- Data Type: Estimated/Remote Sensed. Weather radar (like NEXRAD) scans the sky at various “tilt” angles. Because the earth curves, the radar beam gets higher the further it travels.
- Why it’s better: If you are more than 20–30 miles from a station, a localized storm might miss the physical gauge entirely. Radar “sees” the entire area from above, providing a better spatial estimate of where the rain is actually falling.
Section 4: The Modeled Frontier – Energy & Soil
These values are provided for specialized industries and rely on mathematical physics to move beyond the 10m standard.
- Extended Wind | 50m, 80m, 100m:
- Data Type: Extrapolated. Using the 10m measured wind as a base, we apply the Logarithmic Wind Profile to estimate how much the wind speeds up as you move away from ground-level friction.
- Sub-Surface Soil | 4 distinct levels from 0cm to 2m:
- Data Type: Modeled. It begins with the Skin Temperature (measured at the top micron of soil). The model then uses heat diffusion equations to “sink” that energy into lower layers, calculating the temp and moisture levels for the root zone.
Technical Summary: The Vertical Weather Spectrum
| Weather Category | Specific Variables | Height / Depth | Data Method |
| Atmospheric | Temp, Humidity, Pressure | 2 Meters | Measured |
| Surface Wind | Speed, Direction, Gust | 10 Meters | Measured |
| Ground Precip | Rain, Snow Accumulation | 0 Meters | Measured (Gauge) |
| Radar Precip | Rainfall intensity | 500m – 3km+ | Estimated (Radar) |
| Energy Wind | Hub-Height Wind | 50m, 80m, 100m | Extrapolated |
| Solar (GHI) | Solar Radiation | Surface | Derived (Model) |
| Sky Condition | Cloud Cover | Cloud Top | Satellite-Derived |
| Sky Condition | Visibility | 2 Meters | Calculated |
| Sub-Surface | Soil Temp & Moisture | 4 levels: 0cm to 2m | Modeled |
Conclusion
Precision in weather data requires an understanding of where a number comes from. By distinguishing between 2m measurements and radar estimations, Visual Crossing provides the transparency needed for high-stakes decision-making.
Ready for professional-grade precision? Explore our Advanced Data Packages at www.visualcrossing.com today which are included at no additional cost in our Corporate and Enterprise licenses.