Lapse Rate Environmental
Fit measured environmental temperature profile and expose extrapolated-height predictions, retaining inversion sign; not a prescribed constant atmosphere or pressure/altitude conversion.
Description
An environmental lapse rate describes how observed temperature changes with height.
An environmental lapse rate describes how observed temperature changes with height. A straight-line fit averages the trend across the supplied profile; a negative lapse rate indicates warming with height over that fitted range.1
Fit measured environmental temperature profile and expose extrapolated-height predictions, retaining inversion sign; not a prescribed constant atmosphere or pressure/altitude conversion.
When to use Lapse Rate Environmental
Use this tool to fit measured environmental temperature profile and expose extrapolated-height predictions, retaining inversion sign; not a prescribed constant atmosphere or pressure/altitude conversion.
Prepare the climate observations and any independently chosen thresholds or model parameters. Confirm units, daily coverage, time order and the intended seasonal window.
How to use Lapse Rate Environmental and understand its results
- Prepare the climate observations and any independently chosen thresholds or model parameters. Confirm units, daily coverage, time order and the intended seasonal window.
- Enter observedHeightsM, observedTemperaturesC, predictionHeightM using the field table and calculation rules, then run the tool.
- Read fittedEnvironmentalLapseCPerKm, predictedProfileTemperatureC, predictionOutsideObservedHeightRange. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| observedHeightsM | Observed heights m | list of number | Required |
| observedTemperaturesC | Observed temperatures c | list of number | Required |
| predictionHeightM | Prediction height m | number | Required |
Enter at least two strictly increasing heights in m, aligned temperatures in °C and a prediction height in m. The tool performs an ordinary least-squares line fit and reports its slope as a °C/km lapse rate using the displayed sign convention. It also evaluates the fitted temperature at the requested height and flags whether that height lies outside the observed height range.
Paired lists must be nonempty and have equal lengths. Each sequence checked for increasing order must contain at least two strictly increasing values. The least-squares fit needs at least two aligned observations and a varying independent variable; a constant dependent variable has reported R² of 1.
T(z) = intercept + slope × z; lapse rate = −1000 × slope Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| fittedEnvironmentalLapseCPerKm | Fitted environmental lapse c per km | number |
| predictedProfileTemperatureC | Predicted profile temperature c | number |
| predictionOutsideObservedHeightRange | Prediction outside observed height range | boolean |
{
"input": {
"observedHeightsM": [
0,
1000,
2000
],
"observedTemperaturesC": [
20,
14,
8
],
"predictionHeightM": 3000
},
"output": {
"fittedEnvironmentalLapseCPerKm": 6,
"predictedProfileTemperatureC": 2,
"predictionOutsideObservedHeightRange": true
}
}Limitations and assumptions
The fitted rate need not equal a dry or moist adiabatic lapse rate. A linear fit can conceal multiple layers and inversions. Extrapolated temperatures are returned with a flag rather than rejected; judge their physical plausibility separately.
Numeric inputs and returned numeric values must be finite; an unrepresentable returned value produces an error. Numeric lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.
Alternative or Complementary methods
Use Sen Slope Estimator: Estimate Sen median of all pairwise slopes on actual irregular observation years; distinct from OLS regression and no independence-adjusted interval or extrapolation. For a complementary task, use Showalter Index: Estimate Showalter 850-hPa-origin parcel index via explicit supplied LCL and caller piecewise dry/moist lapse approximation; differs from supplied surface-parcel lifted index, not a full pseudoadiabatic solver or validated thunder forecast.
References
-
Lapse Rate Environmental — tool.io
Similar or alternative tools
- Sen Slope Estimator
Estimate Sen median of all pairwise slopes on actual irregular observation years; distinct from OLS regression and no independence-adjusted interval or extrapolation.
- Showalter Index
Estimate Showalter 850-hPa-origin parcel index via explicit supplied LCL and caller piecewise dry/moist lapse approximation; differs from supplied surface-parcel lifted index, not a full pseudoadiabatic solver or validated thunder forecast.