The More Rain, the Better the Model Performs—The Dependency of Quantitative Precipitation Forecast Skill on Rainfall Amount for Typhoons in Taiwan

Abstract

A strong dependency of model performance in quantitative precipitation forecasts (QPFs) as measured by scores such as the threat score (TS) on rainfall amount (i.e., the better the model performs when there is more rain), is demonstrated through real-time forecasts by the 2.5-km Cloud-Resolving Storm Simulator (CReSS) for 15 typhoons in Taiwan in 2010-12. Implied simply from the positive correlation between rain-area sizes and scores, this dependency is expected to exist in all regions, models, and rainfall regimes, while for typhoon QPFs in Taiwan it is also attributed to the model's capability to properly handle (within 72 h) the processes leading to more rain, which are largely controlled by the typhoon's track, size, structure, and environment, and the island's topography. Because of this dependency, the performance of model QPFs for extreme events can be assessed accurately only when forecasts targeted for periods of comparable rainfall magnitude are included for averaging. For the most-rainy 24 h of the top-5 typhoons, the 0-24-h QPFs by CReSS have mean TS of 0.67, 0.67, 0.58, 0.51, and 0.32 at thresholds of 25, 50, 130, 200, and 350 mm, and 0.64, 0.57, 0.37, 0.33, and 0.22 from 48-72-h QPFs, respectively, suggesting superior performance even 2-2.5 days in advance. These scores are strikingly high, precisely because Taiwan can receive extreme rainfall from typhoons. For smaller (nonhazardous) events, the mean scores are progressively lower, but also unimportant and less representative statistically. Therefore, it is inappropriate to average scores over multiple forecasts as those for less-rainy periods would contaminate the result for key periods. The implication for forecasters is also discussed.

Regionalizing Rainfall at Very High Resolution over La Réunion Island: A Case Study for Tropical Cyclone Ando

“…Thus, in such cases, even poorly simulated TC structures can induce realistic rainfall amounts and distribution over the island due to the better representation of topography in high-resolution simulations. This point, which is consistent with recent studies conducted over Taiwan by Wang (2015) and Wang et al (2016), is particularly meaningful for operational forecasts and shows that realistic local rainfall estimates could be obtained despite the partly biased TC life cycle. Conversely, over complex terrain, reliable local estimates of severe weather events require very high-resolution grids so as to properly take into account both orographic effects and finescale processes modulated by the surface conditions.…”

A numerical study of back-building process in a quasistationary rainband with extreme rainfall over northern Taiwan during 11–12 June 2012

“…Sub-grid-scale processes parameterized include turbulent mixing in the planetary boundary layer, radiation, and surface momentum and energy fluxes (Kondo, 1976;Louis et al, 1981;Segami et al, 1989). With a single domain (no nesting), this model has been used to study a number of heavy rainfall events around Taiwan during the meiyu season (e.g., C.-C. Wang et al, , 2011Wang et al, , 2014a) as well as for real-time forecasts (e.g., Wang et al, 2013Wang et al, , 2016aWang, 2015Wang, , 2016. The CReSS model is open to the research community upon request, and further details can be found in the works referenced above and at http://www.rain.hyarc.…”

Study of Recent Literature on Weather Monitoring Systems

“…There are various communication's channels used in different field of embedded systems recently based on GSM based [34], GPRS [34], WSN network, etc. [19], [20], [21], [22], [23], [24] Climate prediction correctness has been difficult to address. Fault prediction occurs due to climate changes.…”

“…representation blunder representation utilizing either 2) stochastic active soul backscatter or 3) stochastically bothered parameterization propensities [21]. Multi-physics and a stochastic active fundamental backscatter arrangement are utilized in a similar system to speak to model instability in a meso-scale troupe conjecture framework utilizing the Weather Investigation and Forecasting model [22].…”