Cloud-resolving time-lagged rainfall ensemble forecasts for typhoons in Taiwan: Examples of Saola (2012), Soulik (2013), and Soudelor (2015)

As high resolution is required for numerical models to adequately simulate convective storms and thus produce quantitative precipitation forecasts (QPFs), a time-lagged ensemble out to 8 days at 6-h intervals using a 2.5-km cloud-resolving model is applied to three rainy typhoons that made landfall in Taiwan in recent years: Saola (2012), Soulik (2013), and Soudelor (2015), following an earlier study. For the three typhoons where the worst-case rainfall scenario turned out to happen in Taiwan, the system was able to predict this particular scenario with high accuracy (with a rainfall pattern similar to the observed) at an earliest lead time of about 162 h, 79 h, and 164 h before landfall, and thus provided key information for early preparation. Within the short range (≤72 h), as the predicted tracks converged toward the best track, high-quality QPFs were consistently generated starting at about 36 h, 55 h, and 80 h prior to landfall, respectively, with derived probabilities in good to excellent agreement with the observations, even at extreme thresholds (≥500 and 700 mm in 24 h). Leading up to the track convergence, the probabilities across various rainfall thresholds increased markedly, so their time evolution also provided useful information for decision makers and hazard preparation. The underlying reason behind our results is the high predictability of topographic rainfall in Taiwan produced by the typhoon circulation, which cannot be properly captured without high model resolution. Thus, without compromising the resolution, we demonstrate the advantages of the time-lagged strategy for ensemble forecasting, assuming QPF as the key target forecast parameter.