Ozone Regression Calculator

Introduction : This calculator demonstrates an example of a simple regression model for predicting ozone levels, given basic meteorological data. In this calculator, you have seven input values, or predictors:
  1. the maximum surface temperature in degrees F (Tmax)
  2. the minimum surface temperature in degrees F (Tmin)
  3. Fraction of Cloud Cover between 1600-1800 UTC (TSKC)
  4. Surface Wind Speed (knots) at 0900 UTC (WS)
  5. 950-mb temperature (degrees C) at 1200 UTC (T950)
  6. 850-mb wind speed (meters/sec) at 1200 UTC (WS850)
  7. Daily solar angle in degrees (SZ)

Once entered, the calculator then performs a "best-fit" statistical regression to predict the one-hour ozone level for that day.

The parameters found in this particular equation are generated through a statistical analysis of data over many years. One of the criticisms of this method is that once the parameters are determined, they are "fixed" for all future calculations, and are not subject to refinement.

This particular regression calculator was created for Baltimore Maryland. Mathematically, the regression equation is as follows:

O3 (1-hour ppb) = 1.671Tmax - 1.1163Tmin-1.750TSKC-0.786WS+3.048T950-1.457WS850-1.075SZ +16.15

Once the 1-hour ozone concentration is determined, we use another regression equation to calculate the 8-hour ozone concentration:

O3 (8-hour ppb) = 0.8857(1-hour ozone) + 0.2325

Ozone Forecast Regression Calculator

Input Values:

Maximum Surface temperature (Tmax, degrees F)
Minimum Surface temperature (Tmin, degrees F)
Fraction of Cloud Cover (TSKC, 1600-1800 UTC)
Surface Wind Speed (WS, knots) at 0900 UTC
950-mb temperature (T950, degrees C) at 1200 UTC
850-mb wind speed (WS850, meters/sec) at 1200 UTC
Daily solar zenith angle (SZ, degrees)

Results:

One-hour ozone level (ppb) Eight-hour ozone level (ppb)