No abstract

Typhoon Morakot produced record-breaking accumulated rainfall over southern Taiwan in August 2009. The combination of several factors resulted in this extreme weather event: the steep terrain in Taiwan, the prevailing south-westerly flow in the monsoon trough, Typhoon Goni over the northern South China Sea, and the slow translation speed of Morakot itself over Taiwan. In this study, the influence of the translation speed is particularly emphasized. Based on the EnKF data assimilation, an innovative method is applied to perform ensemble simulations with several designated translation speeds of Morakot using the WRF model. Thus the influence of the translation speed on the amount of accumulated rainfall over Taiwan can be quantitatively evaluated. In the control simulation with observed translation speed, the maximum amount and geographic pattern of accumulated rainfall during the landfall period of Morakot are generally consistent with the observations, though the detailed overall distributions of accumulated rainfall is mostly underestimated, resulting in the low bias of the frequency distribution of the accumulated rainfall. In a simulation with nearly-doubled translation speed of Morakot, the maximum accumulated rainfall is decreased by 33% than that in the control simulation, while the rainfall distribution over Taiwan remains similar. In addition, the 28 ensemble members can further provide additional information in terms of their spread and other statistics. The results from ensemble members reveal the usefulness of ensemble simulations for the quantitative precipitation forecast.

This study investigates the statistical characteristics of extreme hourly precipitation over Taiwan during 2003–12 that exceeds the 5-, 10-, and 20-yr return values and 100 mm h−1. All the extreme precipitation records are classified into four types according to the synoptic situations under which they occur: tropical cyclones (TCs), fronts, weak-synoptic forcing, and vortex/shear line types. The TC type accounts for over three-quarters of the total records, while the front type and weak-synoptic forcing type are comparable (9%–13%). Extreme hourly precipitation is mostly caused by mei-yu fronts during May–mid-June and by TCs during July–October. The TC type tends to have a long duration time (>12 h) with a symmetrical evolution of hourly rainfall intensity, while the front type and weak-synoptic forcing type mainly occur over a short period (<6 h) with a slightly asymmetrical evolution pattern. The TC type is further divided into seven subtypes according to the location of the TC center relative to the island. When the TC center is over the island or near the coastline (distance <100 km), the spatial distribution of subtypes I–IV is largely determined by the interaction between the TC circulation and topography when a TC center is over the northwest, south, east, or northeast portion of Taiwan, respectively. When the TC center is far away (distance >100 km) from the island, the strength of the environmental southwesterly or northeasterly winds and the impingement of TC circulation on the east side of the Central Mountain Range are also key factors determining the spatial distribution of subtypes V–VII.

This study utilizes data compiled over 21 years (1993–2013) from the Central Weather Bureau of Taiwan to investigate the statistical characteristics of typhoon-induced rainfall for 53 typhoons that have impacted Taiwan. In this work the data are grouped into two datasets: one includes 21 selected conventional weather stations (referred to as Con-ST), and the other contains all the available rain gauges (250–500 gauges, mostly automatic ones; referred to as All-ST). The primary aim of this study is to understand the potential impacts of the different gauge distributions between All-ST and Con-ST on the statistical characteristics of typhoon-induced rainfall. The analyses indicate that although the average rainfall amount calculated with Con-ST is statistically similar to that with All-ST, the former cannot identify the precipitation extremes and rainfall distribution appropriately, especially in mountainous areas. Because very few conventional stations are located over the mountainous regions, the cumulative frequency obtained solely from Con-ST is not representative. As compared to the results from All-ST, the extreme rainfall assessed from Con-ST is, on average, underestimated by 23%–44% for typhoons approaching different portions of Taiwan. The uneven distribution of Con-ST, with only three stations located in the mountains higher than 1000 m, is likely to cause significant biases in the interpretation of rainfall patterns. This study illustrates the importance of the increase in the number of available stations in assessing the long-term rainfall characteristic of typhoon-associated heavy rainfall in Taiwan.

Using special data from the field campaign of 2008 and an ensemble Kalman filter-based vortex initialization method, this study explores the impact of different track clusters categorized under the ensemble simulations of Typhoon Sinlaku (2008) on the associated precipitation. In particular, the distinct pattern of cumulative frequencies in the 28 members is identified to correspond to three types of track clusters. The simulation integrated from the initial ensemble mean slightly underestimates the maximum amount of the observed rainfall in central Taiwan by about 30%. The quantitative evaluation based on the equitable threat score indicates that members with tracks close to the best track produce more consistent rainfall distribution in northern Taiwan although their cumulative frequencies are underestimated. For members with southwestward-biased tracks, although the cumulative frequencies are closer to the observation, the simulated rainfall pattern is less consistent with the observation in northern Taiwan and the maximum rainfall amount is overestimated. The comparison of rainfall simulation during landfall between two representative members shows that the distinct differences in the rainfall amount and distribution are primarily associated with the track differences on the windward side of the mountain. With a finer horizontal grid resolution, the rainfall accumulation becomes greater as a result of the enhancement of updraft from the better-resolved topography, yet the cumulative frequency stays nearly unchanged. Based on ensemble simulations, this study highlights that the uncertainties in rainfall patterns and amounts can be assessed from ensemble track variations, thus providing better insights into the rainfall predictability associated with typhoons near Taiwan.

Using special data from the field program of "Impact of Typhoons on the Ocean in the Pacific" (2010) and an ensemble Kalman filter-based vortex initialization method, this study explores the impact of the Taiwan terrain on the uncertainty in forecasting track, intensity and rainfall of Typhoon Fanapi (2010) based on ensemble simulations. The results show that the presence of Taiwan topography leads to rapid growths of the simulation uncertainty in track and intensity during the landfall period, in particular at the earlier landfall period. The fast moving ensemble members show an earlier southward track deflection as well as the weakening of intensity, resulting in a sudden increase of standard deviation in track and intensity. During the period of offshore departure from Taiwan, our analysis suggests that the latitudinal location of the long-lasting and elongated rainband to the south of tropical cyclone (TC) center has a strong dependence on the latitude of the TC center. In addition, the rainfall uncertainty in southern Taiwan is dominated by the uncertainty of simulated TC rainband, and the latitude of TC track can be regarded as a good predictor of the rainband's location at departure time. It is also found that the rainband develop farther to the south as the topography is elevated. Considering the fact that the rainband impinging the high mountains in the southern Central Mountain Range generates the greatest accumulated rainfall, positions where the rainband associated circulation and its interaction with topography appear to offer an explanation on the uncertainty of the simulated rainfall.