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In this study, an ensemble typhoon quantitative precipitation forecast (ETQPF) model was developed to provide typhoon rainfall forecasts for Taiwan. The ETQPF rainfall forecast is obtained by averaging the pick-out cases, which are screened using certain criterion based on given typhoon tracks from an ensemble prediction system (EPS). Therefore, the ETQPF model resembles a climatology model. However, the ETQPF model uses the quantitative precipitation forecasts (QPFs) from an EPS instead of historical rainfall observations. Two typhoon cases, Fanapi (2010) and Megi (2010), are used to evaluate the ETQPF model performance. The results show that the rainfall forecast from the ETQPF model, which is qualitatively compared and quantitatively verified, provides reasonable typhoon rainfall forecasts and is valuable for real-time operational applications. By applying the forecast track to the ETQPF model, better track forecasts lead to better ETQPF rainfall forecasts. Moreover, the ETQPF model provides the 'scenario' of the typhoon QPFs according to the uncertainty of the forecast tracks. Such a scenario analysis can provide valuable information for risk assessment and decision making in disaster prevention and reduction. Deficiencies of the ETQPF model are also presented, including that the average over the pick-out case usually offsets the extremes and reduces the maximum ETQPF rainfall, the underprediction is especially noticeable for weak phase-locked rainfall systems, and the ETQPF rainfall error is related to the model bias. Therefore, reducing model bias is an important issue in further improving the ETQPF model performance. [ABSTRACT FROM AUTHOR]

Operational monsoon moisture surveillance and severe weather prediction is essential for timely water resource management and disaster risk reduction. For these purposes, this study suggests a moisture indicator using the COSMIC-2/FORMOSAT-7 radio occultation (RO) observations and evaluates numerical model experiments with RO data assimilation. The RO data quality is validated by a comparison between sampled RO profiles and nearby radiosonde profiles around Taiwan prior to the experiments. The suggested moisture indicator accurately monitors daily moisture variations in the South China Sea and the Bay of Bengal throughout the 2020 monsoon rainy season. For the numerical model experiments, the statistics of 152 moisture and rainfall forecasts for the 2020 Meiyu season in Taiwan show a neutral to slightly positive impact brought by RO data assimilation. A forecast sample with the most significant improvement reveals that both thermodynamic and dynamic fields are appropriately adjusted by model integration posterior to data assimilation. The statistics of 17 track forecasts for typhoon Hagupit (2020) also show the positive effect of RO data assimilation. A forecast sample reveals that the member with RO data assimilation simulates better typhoon structure and intensity than the member without, and the effect can be larger and faster via multi-cycle RO data assimilation. [ABSTRACT FROM AUTHOR]

A pluvial flash flood is rapid flooding induced by intense rainfall associated with a severe weather system, such as thunderstorms or typhoons. Additionally, topography, ground cover, and soil conditions also account for the occurrence of pluvial flash floods. Pluvial flash floods are among the most devastating natural disasters that occur in Taiwan, and these floods always /occur within a few minutes or hours of excessive rainfall. Pluvial flash floods usually threaten large plain areas with high population densities; therefore, there is a great need to implement an operational high-performance forecasting system for pluvial flash flood mitigation and evacuation decisions. This study developed a high-performance two-dimensional hydrodynamic model based on the finite-element method and unstructured grids. The operational high-performance forecasting system is composed of the Weather Research and Forecasting (WRF) model, the Storm Water Management Model (SWMM), a two-dimensional hydrodynamic model, and a map-oriented visualization tool. The forecasting system employs digital elevation data with a 1-m resolution to simulate city-scale pluvial flash floods. The extent of flooding during historical inundation events derived from the forecasting system agrees well with the surveyed data for plain areas in southwestern Taiwan. The entire process of the operational high-performance forecasting system prediction of pluvial flash floods in the subsequent 24 h is accomplished within 8–10 min, and forecasts are updated every six hours. [ABSTRACT FROM AUTHOR]

Typhoon-induced storm surges are catastrophic disasters in coastal areas worldwide, although typhoon surges are not extremely high in Taiwan. However, the rising water level around an estuary could be a block that obstructs the flow of water away from the estuary and indirectly forms an overflow in the middle or lower reaches of a river if the occurrence of the highest storm surge (HSS) coincides with the highest astronomical tide (HAT). Therefore, assessing the highest storm tide (HST, a combination of the HSS and HAT) hazard level along the coast of Taiwan is particularly important to an early warning of riverine inundation. This study hindcasted the storm surges of 122 historical typhoon events from 1979 to 2018 using a high-resolution, unstructured-grid, surge-wave fully coupled model and a hybrid typhoon wind model. The long-term recording measurements at 28 tide-measuring stations around Taiwan were used to analyze the HAT characteristics. The hindcasted HSSs of each typhoon category (the Central Weather Bureau of Taiwan classified typhoon events into nine categories according to the typhoon's track) were extracted and superposed on the HATs to produce the individual potential HST hazard maps. Each map was classified into six hazard levels (I to VI). Finally, a comprehensive potential HST hazard map was created based on the superposition of the HSSs from 122 typhoon events and HATs. [ABSTRACT FROM AUTHOR]

In Taiwan, the coastal hazard from typhoon-induced storm waves poses a greater threat to human life and infrastructure than storm surges. Therefore, there has been increased interest in assessing the storm wave hazard levels for the nearshore waters of Taiwan. This study hindcasted the significant wave heights (SWHs) of 124 historical typhoon events from 1978 to 2017 using a fully coupled model and hybrid wind fields (a combination of the parametric typhoon model and reanalysis products). The maximum SWHs of each typhoon category were extracted to create individual storm wave hazard maps for the sea areas of the coastal zones (SACZs) in Taiwan. Each map was classified into five hazard levels (I to V) and used to generate a comprehensive storm wave hazard map. The results demonstrate that the northern and eastern nearshore waters of Taiwan are threatened by a hazard level IV (SWHs ranging from 9.0 to 12.0 m) over a SACZ of 510.0 km2 and a hazard level V (SWHs exceeding 12.0 m) over a SACZ of 2152.3 km2. The SACZs threatened by hazard levels I (SWHs less than 3.0 m), II (SWHs ranging from 3.0 to 6.0 m), and III (SWHs ranging from 6.0–9.0 m) are of 1045.2 km2, 1793.9 km2, and 616.1 km2, respectively, and are located in the western waters of Taiwan. [ABSTRACT FROM AUTHOR]