Remote Sensing (Oct 2022)
Time-Lagged Ensemble Quantitative Precipitation Forecasts for Three Landfalling Typhoons in the Philippines Using the CReSS Model, Part II: Verification Using Global Precipitation Measurement Retrievals
Abstract
In this study, high-resolution quantitative precipitation forecasts (QPFs) in lagged runs with a cloud-resolving model are evaluated for three typhoons in the Philippines: Mangkhut (2018), Koppu (2015), and Melor (2015), hitting northern Luzon, central Luzon, and the middle section of the Philippine archipelago, respectively. In Part I of this study, the QPFs were verified using 56 gauge observations on land over the Philippines. Here, in Part II, they are verified against the Global Precipitation Measurement (GPM) satellite estimates (also covering nearby oceans), using categorical scores in the same way. For each typhoon, rainfall valid at a selected 24 h period and the whole event (48 or 72 h) is examined. For 24 h rainfall inside the short range (lead time ≤ 72 h), good QPFs (with a threat score of ≥0.2) were produced for Koppu at 200 mm by almost all runs, and at 100 mm by all runs for Mangkhut, but only 22% of the runs for Melor. At longer lead times, good QPFs at 100 mm were also produced by all runs for Koppu, half of the runs for Mangkhut, and only 1 out of 16 runs for Melor. For whole events (48 or 72 h), the QPFs were similarly the best for Koppu, followed by Mangkhut, and least ideal for Melor. The quality of the GPM data during the three typhoons was found to be generally good and suitable for QPF verification, and the results were more stable and, thus, more reliable for the assessment of bias. However, the threat scores using the GPM dropped lower at high thresholds, and the results could become different from those obtained against the gauges (Part I), suggesting a much higher skill. Thus, verification using rain gauges is still needed toward high thresholds, especially over mountain regions where satellite estimates tend to exhibit larger errors.
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