| --- |
| license: mit |
| tags: |
| - weather |
| - forecasting |
| - baseline |
| --- |
| |
| # Persistence baseline |
|
|
| A reference forecast for 2 metre temperature: the analysis at T+0, carried |
| forward unchanged to every lead hour. |
|
|
| Persistence is the standard trivial reference in weather forecasting. It has no |
| parameters and no training data. Its purpose is comparison — a forecast system |
| is only demonstrating skill once it beats persistence, and the margin by which |
| it does so at each lead time is a more meaningful number than an error score |
| quoted on its own. |
|
|
| ## Behaviour |
|
|
| Skill decays in a predictable way, which is what makes it useful as a control: |
|
|
| | Lead | Typical behaviour | |
| |---|---| |
| | +6 h | Hard to beat by much — the atmosphere is strongly autocorrelated at this range | |
| | +24 h | Clearly beaten by any competent forecast | |
| | +120 h | Error approaches that of climatology | |
|
|
| Error that does **not** grow with lead time indicates a problem in the |
| evaluation, not in the forecast. |
|
|
| ## Inputs |
|
|
| Reads `2m_temperature` from a gridded analysis in netCDF, with dimensions |
| `(time, latitude, longitude)`, latitude descending from +90 to −90, and |
| longitude ascending on a 0–360 convention. It uses the most recent timestep. |
|
|
| ## Outputs |
|
|
| `temperature_2m` with dimensions `(lead_hour, latitude, longitude)` on the input |
| grid, in Kelvin (the unit of the source field). |
|
|
| ## Files |
|
|
| - `predict.py` — the model |
| - `earthboi.yaml` — declared variables, lead hours and grid |
|
|
| ## Licence |
|
|
| MIT. |
|
|
