Weather Footprints

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Thunder at the airport, or nearby?

Finished · 14 November 2026

The question. Should the thunder chance be for the spot, or for "somewhere within R km", and which R and which predictors give the most skill?

Why

A storm a few kilometres away is a storm for anyone planning a day, but a single airport only hears thunder within about 15 km; and a model at 0.5° cannot place showers to the town. So we tested defining the event as "thunder reported by any airport within R km" and forecasting it from the 3×3 neighbourhood of grid cells around the airport.

Data

Summer 2025, 101 airports, as in storm ingredients. Logistic regression, leave-one-week-out cross-validation, scored by Brier skill (BSS) against the event's base rate.

RadiusNeighbouring airports (median)Airports with noneBase rateThunder days
airport only––1.6 %142
30 km053 of 1012.4 %212
50 km221 of 1013.6 %317

Results (BSS, cross-validated)

Event, predictorsDay 0Day 3
Airport, member share of the rule+0.017+0.022
Airport, best LI + log rain+0.053−0.008
30 km, best LI + log rain+0.066−0.006
30 km, member share+0.031+0.035
50 km, best LI + log rain+0.079+0.007
50 km, member share+0.046+0.055
50 km, share + best LI + rain+0.077+0.030

What worked

  • 50 km. More events (317) and almost every airport with a neighbour, and the best skill at both leads.
  • Different predictors by lead. At day 0 the ensemble-mean lowest best lifted index and the log of the largest 6-hour rain carry the information; by day 3 those continuous fields are too noisy and the simple share of members meeting the rule is better.

What did not

  • 30 km: half the airports have no other airport that close, so the event is barely different from "at the airport".
  • Continuous predictors at day 3: best LI + rain had no skill (−0.008 to +0.007); adding them to the member share made day 3 worse.
  • Most-unstable CAPE as a third predictor added nothing to best LI + rain (+0.051 against +0.053 at the airport).

What we changed

The live thunder chance became "thunder within about 50 km", with day 0 calibrated on best LI + rain and day 3 (and later days) on the member share; the production fit (3×3 neighbourhood predictors) scored +0.082 and +0.053 on summer 2025. See three summers for what more data did.

Scripts: scripts/thunder/multi.py, scripts/thunder/area.py.