Mean Sea Level Trend MM Year Calculator
OLS actual mean-level/mm versus decimal-year trend, no forecast/uncertainty from a short record, seasonal/varying datum excluded externally. Caller independently establishes units, regime, calibration and applicability; this does not establish design-code compliance, authenticity, operational safety, treatment efficacy or a validated forecast.
Description
A sea-level trend summarizes change over the observed record in a chosen vertical datum.
A sea-level trend summarizes change over the observed record in a chosen vertical datum.1
Fitting decimal years and millimetres produces a signed slope in millimetres per year.
When to use Mean Sea Level Trend MM Year Calculator
Use this tool to calculate or review the supplied observations under the stated rules. Match the observation interval, units, datum, coordinate signs and model regime.
How to use Mean Sea Level Trend MM Year Calculator and understand its results
- Match the observation interval, units, datum, coordinate signs and model regime.
- Enter observedEpochDecimalYears, observedMeanSeaLevelMm, using the field meanings and rules below, then run the tool.
- Read observedSeaLevelTrendMmYear, seaLevelTrendRSquared. Inspect nested result fields where present, and review unknown records separately from known matches.
- Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| observedEpochDecimalYears | Observed epoch decimal years | list of number | Required |
| observedMeanSeaLevelMm | Observed mean sea level mm | list of number | Required |
Supply at least two aligned finite decimal-year and mean-level samples with nonzero year variance. Fit ordinary least squares with a free intercept and return the slope and R². No seasonal correction, confidence interval or forecast is added.
The regression helper accepts 2–10000 aligned finite pairs with nonzero predictor variance. It uses ordinary least squares with a free intercept and shifted coordinates. Samples need not be sorted unless this tool adds that requirement. R² is clamped to [0,1], with constant responses assigned one. A fit summary does not add an uncertainty estimate or an unlisted output.
trend=Σ(x−x̄)(y−ȳ)/Σ(x−x̄)² Use the matching field units and the exact boundary, ordering and reference rules above.
| Output field | Meaning | Value type |
|---|---|---|
| observedSeaLevelTrendMmYear | Observed sea level trend mm year | number |
| seaLevelTrendRSquared | Sea level trend r squared | number |
{
"input": {
"observedEpochDecimalYears": [
2000,
2001,
2003
],
"observedMeanSeaLevelMm": [
0,
2,
6
]
},
"output": {
"observedSeaLevelTrendMmYear": 2,
"seaLevelTrendRSquared": 1
}
}Limitations and assumptions
The stated observation or model covers only the supplied record and reference regime. It does not fill missing measurements, supply uncertainty estimates or produce a validated forecast.
Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.
Alternative or Complementary methods
For a related step, use Local vs Global Sea Level Split Calculator: Relative sea level combines ocean-level change and vertical land movement. For a complementary comparison, use Atlantic Multidecadal Window Average Calculator: A multidecadal index average depends on the anomaly baseline and the amount of time actually observed.
References
-
Mean Sea Level Trend MM Year Calculator — tool.io
Similar or alternative tools
- Local vs Global Sea Level Split Calculator
Relative sea level combines ocean-level change and vertical land movement.
- Atlantic Multidecadal Window Average Calculator
A multidecadal index average depends on the anomaly baseline and the amount of time actually observed.