Quantitative Precipitation Forecasts Using Numerical Models: The Example of Taiwan

Eight-Day Typhoon Quantitative Precipitation Forecasts in Taiwan by the 2.5 km CReSS Model, Part II: Reduced Control of Track Errors on Rainfall Prediction Quality for Typhoons Associated with Southwesterly Flow

“…On longer forecast ranges, however, northward biases occurred and were, in general, larger the longer the lead time (Figure 3b). As shown in earlier studies [35,[40][41][42] and reviewed in Section 1, the large spread in tracks from lagged runs at longer lead times due to higher forecast uncertainty, dictated by BCs from GFS forecasts, has the advantage to better ensure the coverage of the actual track. For TY Talim (2012), the QPF that had the highest SSS (=0.80) at ranges beyond 3 days was the one made on day 8, at 0000 UTC 14 August (Figure 4b), in which the track error on 21 August (at 1200 UTC) was 332 km and relatively large (also Table 2).…”

“…Thus far, the time-lagged runs have also been carried out at 6 h intervals (four times per day) for some typhoons and were shown to be capable of providing both high-quality QPFs within the short range as well as a wide range of rainfall scenarios in Taiwan associated with different TC tracks at longer lead times [35,40]. For some TCs where the worse-case scenario turned out to occur, such as typhoons (TYs) Saola (2012), Matmo (2014), and Soudelor (2015), the particular scenario was successfully predicted almost one week before landfall, providing long lead times for preparation [41,42]. However, decent QPFs were only obtainable within a short range in some other cases [5,43] because the predictability varies among different TC cases.…”