Tools · Weather · Method

HOW THE FORECAST WORKS

The Quota 4000 dropzone weather forecast combines 4 numerical weather prediction (NWP) models from different meteorological centres, computes their spread to estimate confidence, and applies skydiving-specific operational thresholds instead of the usual "sunny / cloudy" labels. It is not a wrapper around a single provider — it is a proprietary ensemble tuned to skydiving ops.

The 4 models we combine

For the first 24 hours (where accuracy matters most — the window where you decide whether tomorrow you drive to the DZ) we query all 4 models simultaneously and show the median. For hours 24–168 we use the model auto-selected for the area (best_match), because beyond that the inter-model spread becomes noise.

ICON-EUDWD · German weather service
📐 3.3 km🌍 Europe🔄 Every 6h

Best for central-north Italy — high spatial resolution over the Po valley and eastern Alps.

ECMWF IFSECMWF · European Centre for Medium-Range Weather Forecasts
📐 9 km🌍 Global🔄 Every 12h

The "gold standard" of global forecasting. Lower resolution than ICON-EU but excellent physics on synoptic-scale dynamics (fronts, depressions).

AROME France HDMétéo-France
📐 1.3 km🌍 France + NW Italy + Western Alps🔄 Every 6h

Finest resolution available at 1.3 km. Convection-permitting model: it explicitly represents cumulus and storm cells rather than parametrising them. Best over alpine orography.

GFSNOAA · NCEP USA
📐 13 km🌍 Global🔄 Every 6h

Global reference baseline, free and frequently updated. On its own it never beats ECMWF, but in an ensemble it acts as an "independent vote" that catches scenarios the other 3 miss.

All 4 models are queried via Open-Meteo (open-source / free tier for non-commercial use), which acts as the aggregator: a single HTTP call returns the 4 models' outputs aligned on the same hourly grid.

Confidence indicator

For every hour in the next 24h we compute the standard deviation (σ) of wind, gust and precipitation across the 4 models. If models agree, σ is low: the forecast is "robust", confidence is high. If models diverge, σ is high: scenario likely ill-defined, exercise caution.

●●●High confidenceσ vento < 1.5 m/s · σ pioggia < 0.3 mm
●●○Mediumσ vento 1.5–3 m/s · σ pioggia 0.3–1 mm
●○○Lowσ vento > 3 m/s · σ pioggia > 1 mm

Jumpability score · how it's computed

The score starts at 100 and applies non-linear penalties for each condition outside operating limits. Logic mirrors a jumpmaster, not a meteorologist: surface wind and gusts dominate, clouds are weighted against the dropzone-specific exit altitude, storms and rain in the next 2h are hard stops.

ConditionPenalty
Gust > 13 m/s−100 · Hard stop everyone
Gust 10–13 m/s−35 · No students
Surface wind > 12 m/s−80 · No-go everyone
Surface wind 8–12 m/s−30 · No students
Upper wind 80m > 18 m/s−25 · Heavy drift on opening
Cloud base < 600 m−100 · Below VFR minimums
Cloud base < DZ exit altitude−60 · No visual exit
Cloud base < exit + 500 m−20 · Tight margin
CAPE > 1500 J/kg or rain 2h > 1 mm−100 · Storms or incoming rain
Rain probability > 60%−40 · Rain likely
Visibility < 5 km−80 · Low-vis landing

The final score is clamped to 0–100. Green ≥ 70 (jumpable), yellow 40–69 (borderline), red < 40 (no-go). Cloud base is derived locally from the Espy formula: cloudBaseM ≈ 125 × (T − Td), where T is temperature and Td is dewpoint — Open-Meteo doesn't expose cloud base directly, but the estimate is conservative when low clouds actually exist.

List score vs detail score

The list shows a single number: a weighted average of the score across the next 36 operating hours (08:00–19:00, weight 0 for night hours). When you open a DZ detail, you see the score hour-by-hour. A DZ can appear yellow (e.g. 55/100) in the list and then show a 0/100 hour in the detail: it means some hours are outside range but others over the next 1–2 days recover. Open the detail to see where the usable window falls.

Known limits

Sources and attribution

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