Addressing spatial uncertainty of convection in thunderstorm forecast verification

Terminal aerodrome forecast (TAF) is a standard ICAO product used for flight planning purposes worldwide. It is created by forecasters and states forecasted weather conditions significant for aviation and their changes for the airport in the next 24 hours. TAF Verification in Croatia control follows the approach proposed by Mahringer (2008).

Forecasting of convection is challenging and nowadays mostly leans on ingredients-based methodology. Ingredients for deep moist convection are never ideally known–especially mesoscale lift–so uncertainty in local initiation is always present. On the other hand, the standard reference area for thunderstorm (TS) forecast in TAF is a 16 km diameter circle around the airport. The commonly used procedure of verifying TS in TAFs is against observed TS stated in standard reports for the airport (METAR) where a thunderstorm is observed in the same area. But is this enough and fair considering the inherent spatial uncertainty of convection initiation?

For example, the forecaster predicts conditions for TS at the airport for an afternoon with a probability of 40%, and TS was observed 40km away. There is no doubt that it was a  miss event for the (small) airport area but still, TAF had some value. On the other hand, when TS is forecast with high probability and it was not observed within 200km of the airport it is apparently a false alarm. 

To do a fairer TAF verification we used lighting data network (LINET) data and adapted it for several diameters around airports: 16, 30, 50, 100, 150, and 200 km. Hourly series with observed thunderstorms were derived from raw data and verified with forecasted ones from TAFs. We also tried to investigate differences in using this TAF verification method on the homogeneous mainland of Croatia, at the coast, or on complex topography near mountains.

Our results reflect the inherent spatial uncertainty of convection and could be used in analyzing and diagnosing where more improvements could be made in local thunderstorm forecasting.