Wind gust warning verification

Cristina Primo

doi:10.5194/asr-13-113-2016

Abstract

Abstract. Operational meteorological centres around the world increasingly include warnings as one of their regular forecast products. Warnings are issued to warn the public about extreme weather situations that might occur leading to damages and losses. In forecasting these extreme events, meteorological centres help their potential users in preventing the damage or losses they might suffer. However, verifying these warnings requires specific methods. This is due not only to the fact that they happen rarely, but also because a new temporal dimension is added when defining a warning, namely the time window of the forecasted event. This paper analyses the issues that might appear when dealing with warning verification. It also proposes some new verification approaches that can be applied to wind warnings. These new techniques are later applied to a real life example, the verification of wind gust warnings at the German Meteorological Centre ("Deutscher Wetterdienst"). Finally, the results obtained from the latter are discussed.

Highlights

Forecasting extreme events helps the public take action to prevent losses or disasters
Warnings have become a standard product in meteorological centres since they help the public prevent major disasters and minimize costs or losses
Need to adapt to the fact that warnings forecast rare events and they are given for a time window rather than for a particular time unit

Summary

Introduction

Forecasting extreme events helps the public take action to prevent losses or disasters. Different warning systems or extreme event forecast strategies are currently implemented in many weather centers around the world To improve these warnings systems and satisfy public demands there is a need to develop appropriate warning verification methods. A verification study should give information about the performance of these relevant aspects, i.e. lead time, intensity, correct timing and correct area In verifying the latter aspects, two properties have to be considered: accuracy (did the warning predict the event in the right place, at the right time and with the right intensity?) and timeliness The results obtained for differentiating the performance of competing forecast systems for extreme events seem to be good, yet these scores have not been widely tested Another aspect to take into consideration is that many verification studies do not consider how much in advance the warning was issued.

Matching forecast and observations

Hourly verification

Event-based verification

Discussion and future work