Point verification and improved communication of the low‐to‐medium cloud cover forecasts

Abstract

The amount of sunshine weighs heavily in our perception of the weather. It is largely determined by cloud cover, especially that at the low‐to‐medium level. Therefore, when reviewing the Hong Kong Observatory's weather symbol forecasting product, verification on the low‐to‐medium cloud field is carried out against the synoptic observations at the Hong Kong International Airport. Several metrics are used to examine the different aspects of the forecasts, and consideration is given to the non‐Gaussian nature of the reported cloud amount for a fairer assessment. Based on the data from January to mid‐August 2015, the median of the forecasts from the European Centre for Medium‐Range Weather Forecasts Ensemble Prediction System is found to outperform the other model forecasts, particularly when the performance is examined by forecast day. This paper presents these results and also discusses the potential of using the field in deriving site‐specific weather symbol forecasts.

A Pilot Forecasting System for Epidemic Thunderstorm Asthma in Southeastern Australia

“…The forecasts were skillful according to the 3-category Gerrity score (GS) which rewards rare but correct (or close) forecasts and penalizes large categorical errors (Gandin andMurphy 1992, Jolliffe andStephenson 2012). The GS has not been used very widely; to put these values into some context, Tam and Wong (2017) reported GS values of 0.27-0.56 for 4-category forecasts of sky cover over Hong Kong from the ECMWF Ensemble Prediction System. Even though Table 8 shows no correct high risk forecasts, the GS values of 0.27 (day 2) to 0.36 (day 0) reflect the ability to predict moderate risk when moderate or high risk occurs (rarely).…”

Editorial: Recent developments and application examples on forecast verification

“…The overall aim is to design specific forecast advisories for when to avoid the application of either fertilizers or pesticides because rain is predicted with high probability. A system for evaluating a weather symbol forecasting product is introduced by Tam and Wong (2017). Cloud cover forecasts from ensemble predictions are evaluated at observation sites around Hong Kong to discuss the potential of deriving site‐specific weather symbol forecasts.…”