Typhoon Rainfall Research Articles

Genetic diagnosis for heavy typhoon rainfall attenuated by Fujian landfall

This study used the dynamic synthetic analysis method to analyze the causes of attenuated heavy rainfall from a westward moving typhoon after landfall over Fujian by focusing on the genetic diagrgnosis of the strongest 12 h rainstorms based on typhoon data obtained from the Shanghai Typhoon Institute, precipitation data from Fujian Province, and NCEP reanalysis data from the United States. The results showed that: (1) the environmental field of the westward moving typhoon benefits the long-term maintenance of convergence in coastal areas, which provides synoptic scale forcing for rainstorm intensification along the southeastern coast; (2) the southwest jet in the boundary layer transports warm water vapor from low latitudes into the eastern circulation of typhoon; the water vapor peak occurs 6 h before the strongest rainstorm and can be used as a reference index to predict heavy rainstorms; (3) the high altitude strong divergence center is located at 100–150 hPa, and the strong convergence center is located near 925–950 hPa in the boundary layer, which is higher (lower) than the 200 hPa divergence layer (850 hPa convergence layer) commonly used in professional work; (4) warm and wet advection in the boundary layer transports unstable energy and weak cold air southward, strengthens the baroclinic pressure, increases the latent heat flux on the sea surface, and plays a significant role in triggering and developing mesoscale convective clouds along the southeast coast.

Evaluation of the WRF physical parameterisations for Typhoon rainstorm simulation in southeast coast of China

Due to easily causing severe disasters in mountainous areas, typhoon rainfall forecast with numerical weather prediction (NWP) system plays an important role for meteorological and hydrological use. In order to investigate the applicability of physical parameterisations for typhoon rainstorms, thirty-six physical parameterisation combinations are designed by three microphysics (Lin, WSM6 and WDM6), three pairs of longwave/shortwave radiations (RRTM/Dudhia, RRTMG/RRTMG and CAM/CAM) and four cumulus parameterisations (KF, BMJ, GD and Grell 3D). The Weather Research and Forecasting (WRF) model is used to simulate the three representative typhoon storm events occurred in southeast coast of China and the rainfall simulations in Meixi catchment are evaluated. Not only for the individual parameterisation but also for the parameterisation combination, WSM6, RRTMG/RRTMG and KF outperform the other physical parameterisation as a whole. The WRF model has poor capability in simulating the rainfall caused by strong convection, and the storm events with uneven distributed rainfall tend to have worse rainfall simulation in space and time dimensions. The findings provide references for choosing the physical parameterisation, which can help to obtain relatively reliable typhoon rainfall forecast and flood warning in catchment scale. The shortage of the NWP system and the solution for improve the rainfall simulation are also put forward.

Characteristics of environmental factors associated with typhoon Kongrey (1825) over the Eastern Coastal Region of Korea

In this study, the characteristics of environmental factors associated with typhoon Kongrey were examined using radiosonde, wind-profiler, radar, and Automated Surface Observing System (ASOS) data in Uljin, which is located the eastern coast of Korea. The radiosonde data were obtained from intensive observation between 1500 LST 5 to 0000 LST 7 October 2018. Environmental factors such as Total Precipitable Water (TPW) and Strom Relative Environmental Helicity (SREH) were selected to examine their relations to typhoon-accompanied precipitation. The TPW peak with 60.54 mm appeared at 1200 LST 6 October, which is 6 h after the peak of typhoon precipitation. It was found that the TPW variation is largely associated with the effect of water vapor supply from the typhoon with nearest proximity to Uljin at 1500 LST 6 October. Mean SREH, which indicates mechanical instability, was 761 m2 s⁻2 during the period in which typhoon precipitation occurred. These environments would provide a good condition for the development of super-cell storms, causing heavy precipitation associated with typhoon. In addition, it was found that the correlation coefficient between SREH and typhoon rainfall is 0.8 (p-value = 0.02).

Basin-wide responses of the South China Sea environment to Super Typhoon Mangkhut (2018)

Relative to the open Northwest Pacific, the basin-scale South China Sea (SCS) is smaller and semi-enclosed, and the impacts of frequent super typhoons on the entire SCS basin have yet to be fully understood. Using multi-satellite observations and reanalysis data, this study explored biophysical responses of the upper ocean of the SCS induced by a typical super typhoon, Mangkhut (2018), and their regional differences with potential mechanisms. There were three different significant-response regions in the whole SCS, as follows: (1) In the ocean area around the typhoon path, strong vertical mixing, upwelling and cooling were induced, resulting in the surface chlorophyll-a (chl-a) concentration enhancing markedly (three-fold). Particularly, asymmetric distribution of typhoon rainfall induced asymmetric sea surface salinity change over along the path the nearshore. Diurnal peak of chl-a concentration increased obviously, and the daily growth rate of chl-a sped up considerably in non-shore areas after Mangkhut's passage. (2) In the Beibu Gulf (BBG), the peripheral winds of Mangkhut caused a change in direction of the sea surface flow field, transporting the high-temperature and high-salinity surface seawater from the southeastern area to the BBG. This induced dramatic increases in sea surface temperature, salinity and height, and a decrease in chl-a, in most areas of BBG. (3) In the southwest SCS, the southwest monsoon–induced eastward offshore upwelling jet was weakened by the opposite large-scale peripheral wind vector of Mangkhut and gradually disappeared, resulting in accumulation and enhancement of chl-a in the nearshore. In addition, Mangkhut peripheral winds also intensified (weakened), shifting the cold (warm) eddy to the north (south) and blocking the horizontal eastward transport belt of the high-concentration chl-a. In general, our present work sheds light on the new evidence that a supper typhoon can cause basin-wide anomalies in the SCS, which has broad implications for marine biophysical environment.

Rainstorm Magnitude Likely Regulates Event Water Fraction and Its Transit Time in Mesoscale Mountainous Catchments: Implication for Modelling Parameterization

Event water transit time estimation has rarely been done for violent rainstorms (e.g., typhoons) in steep and fractured mountainous catchments where the range of transit time, potential controlling factors, and the validity of time-invariant parametrization are unclear. Characterized by steep landscape and torrential typhoon rainfall, Taiwan provides great opportunities for inquiring into the above questions. In this study, the hydrometrics and δ18O in rainwater and streamwater were sampled with a ~3-h interval for six typhoon events in two mesoscale catchments. The TRANSEP (transfer function hydrograph separation) model and global sensitivity analysis were applied for estimating mean transit time (MTTew) and fraction (Few) of event water and identifying the chronosequent parameter sensitivity. Results showed that the MTTew and Few varied from 2.0 to 11.0 h and from 0.2 to 0.8, respectively. Our MTTew in the mesoscale catchments is comparable with that in microscale catchments, showing a fast rainfall-runoff transfer in our steep catchments. The average rainfall intensity is a predominant indicator, which negatively affects the MTTew and positively affects the Few, likely activating preferential flow-paths and quickly transferring event water to the stream. Sensitivity analysis among inter- and intra-events demonstrates that parameter sensitivity is event-dependent and time-variant. A quick and massive subsurface flow without distinct mixing with groundwater would be triggered during large rainstorms, suggesting that time-variant parameterization should be particularly considered when estimating the MTTew in steep and fractured catchments at rainstorm scale.

Estimation of Hourly Rainfall during Typhoons Using Radar Mosaic-Based Convolutional Neural Networks

Taiwan is located at the junction of the tropical and subtropical climate zones adjacent to the Eurasian continent and Pacific Ocean. The island frequently experiences typhoons that engender severe natural disasters and damage. Therefore, efficiently estimating typhoon rainfall in Taiwan is essential. This study examined the efficacy of typhoon rainfall estimation. Radar images released by the Central Weather Bureau were used to estimate instantaneous rainfall. Additionally, two proposed neural network-based architectures, namely a radar mosaic-based convolutional neural network (RMCNN) and a radar mosaic-based multilayer perceptron (RMMLP), were used to estimate typhoon rainfall, and the commonly applied Marshall–Palmer Z-R relationship (Z-R_MP) and a reformulated Z-R relationship at each site (Z-R_station) were adopted to construct benchmark models. Monitoring stations in Hualien, Sun Moon Lake, and Taichung were selected as the experimental stations in Eastern, Central, and Western Taiwan, respectively. This study compared the performance of the models in predicting rainfall at the three stations, and the results are outlined as follows: at the Hualien station, the estimations of the RMCNN, RMMLP, Z-R_MP, and Z-R_station models were mostly identical to the observed rainfall, and all models estimated an increase during peak rainfall on the hyetographs, but the peak values were underestimated. At the Sun Moon Lake and Taichung stations, however, the estimations of the four models were considerably inconsistent in terms of overall rainfall rates, peak rainfall, and peak rainfall arrival times on the hyetographs. The relative root mean squared error for overall rainfall rates of all stations was smallest when computed using RMCNN (0.713), followed by those computed using RMMLP (0.848), Z-R_MP (1.030), and Z-R_station (1.392). Moreover, RMCNN yielded the smallest relative error for peak rainfall (0.316), followed by RMMLP (0.379), Z-R_MP (0.402), and Z-R_station (0.688). RMCNN computed the smallest relative error for the peak rainfall arrival time (1.507 h), followed by RMMLP (2.673 h), Z-R_MP (2.917 h), and Z-R_station (3.250 h). The results revealed that the RMCNN model in combination with radar images could efficiently estimate typhoon rainfall.

Improvement of typhoon rainfall prediction based on optimization of the Kain-Fritsch convection parameterization scheme using a micro-genetic algorithm

Inclusion of cloud processes is essential for precipitation prediction with a numerical weather prediction model. However, convective parameterization contains numerous parameters whose values are in large uncertainties. In particular, it is still not clear how the parameters of a sub-grid-scale convection scheme can be modified to improve high-resolution precipitation prediction. To address these issues, a micro-genetic (micro-GA) algorithm is coupled to the Kain-Fritsch (KF) convective parameterization scheme (CPS) in the WRF to improve the quantitative precipitation forecast (QPF). The optimization focuses on two parameters in the KF scheme: the convective time scale and the conversion rate. The optimizing process is controlled by the micro-GA using a QPF skill score as the fitness function. Two heavy rainfall events related to typhoons that made landfall over the south-east coastal region of China are selected, and for each case the parameter values are adjusted to achieve the best QPF skill. Significant improvements in QPF are evident with an increase in the average equitable threat score (ETS) by 5.8% for the first case, and by 18.4% for the second case. The results demonstrate that the micro-GAKF coupling system is effective in optimizing the parameter values, which affect the applicability of CPS in a high-resolution model, and therefore improves the rainfall prediction in both ETS and spatial distribution.

A hybrid approach of artificial neural network and multiple regression to forecast typhoon rainfall and groundwater-level change

ABSTRACT A forecasting model is developed using a hybrid approach of artificial neural network (ANN) and multiple regression analysis (MRA) to predict the total typhoon rainfall and groundwater-level change in the Zhuoshui River basin. We used information from the raingauge stations in eastern Taiwan and open source typhoon data to build the ANN model for forecasting the total rainfall and the groundwater level during a typhoon event; then we revised the predictive values using MRA. As a result, the average accuracy improved up to 80% when the hybrid model of ANN and MRA was applied, even where insufficient data were available for model training. The outcome of this research can be applied to forecasts of total rainfall and groundwater-level change before a typhoon event reaches the Zhuoshui River basin once the typhoon has made landfall on the east coast of Taiwan.

Raindrop Size Distribution Characteristics for Tropical Cyclones and Meiyu-Baiu Fronts Impacting Tokyo, Japan

Tropical cyclones and meiyu-baiu fronts, as the two main synoptic systems over East Asia, bring heavy rain during summers, but their long-term and vertical raindrop size distribution (RSD) features over the midlatitude Japan Islands are limited. Radar-based quantitative precipitation estimation (QPE) techniques require RSD observations. In this study, five-year observations from Tokyo with a ground-based impact Joss-Waldvogel disdrometer (JWD) and a vertically pointing micro rain radar (MRR) with a vertical range of 0.2–6.0 km were used to study the vertical structures of RSD and QPE parameters. The results showed that the convective rain associated with tropical cyclones had a maritime nature, while the rain associated with the meiyu-baiu front had a continental nature. The rain associated with tropical cyclones had a relatively higher concentration of raindrops and a larger average raindrop diameter than the rain associated with the meiyu-baiu front. The Z–R (radar reflectivity-rain rate) relationships (Z = ARb) based on the JWD data for tropical cyclones, the meiyu-baiu front and total summer rainfall in Tokyo were Z = 189 R1.38, Z = 214 R1.35 and Z = 212 R1.33, respectively. When the Z–R relationships obtained in this study were used to replace the operational relationship of Z = 300 R1.4, the standard deviation of the rain rate was reduced from 5.50 mm/h (2.34 mm/h) to 2.34 mm/h (1.32 mm/h) for typhoon (meiyu-baiu front) rainfall, although the change for total summer rainfall was small. In addition, with increasing height below 4 km, the value of A and b decreased.

Impact of Sea Surface Temperature and Surface Air Temperature on Maximizing Typhoon Rainfall: Focusing on Typhoon Maemi in Korea

In this study, the effects of surface air temperature (SAT) and sea surface temperature (SST) changes on typhoon rainfall maximization are analysed. Based on the numerically reproduced Typhoon Maemi, this study tried to maximize the typhoon-induced rainfall by increasing the amount of saturated water vapour in the atmosphere and the amount of water vapour entering the typhoon. Using the Weather Research and Forecasting (WRF) model, which is one of the regional climate models (RCMs), the rainfall simulated by WRF while increasing the SAT and SST to various sizes at initial conditions and boundary conditions of the model was analysed. As a result of the simulated typhoon rainfall, the spatial distribution of total rainfall depth on the land due to the increase combination of SAT and SST showed a wide variety without showing a certain pattern. This is attributed to the geographical location of the Korean peninsula, which is a peninsula between the continent and the ocean. In other words, under certain conditions, typhoons may drop most of the rainfall on the southern sea of the peninsula before landing on the peninsula. For instance, the 6-hour duration maximum precipitation (MP) in Busan Metropolitan City was 472.1 mm when the SST increased by 2.0°C. However, when the SST increased by 4.0°C, the MP was found to be 395.3 mm, despite the further increase in SST. This indicates that the MP at a particular area and the increase in temperature do not have a linear relationship. Therefore, in order to maximize typhoon rainfall, it is necessary to repeat the numerical experiment on various conditions and search for the combination of SAT and SST increase which is most suitable for the target typhoon.

How much of Typhoon Morakot's extreme rainfall is attributable to anthropogenic climate change?

Typhoon Morakot (2009), which made landfall in Taiwan during August 7–9, 2009, produced the highest rainfall and became the deadliest typhoon ever recorded in Taiwan since 1958. To assess the role of anthropogenic climate change in the typhoon‐related torrent, we compare the water budget between a pair of cloud‐resolving sensitivity experiments. The pair consists of a control simulation that reproduces Typhoon Morakot (2009) in current climate and a sensitivity simulation in which the same storm is placed in a slightly different climate background where the late 20th century anthropogenic climate change signal is removed. The anthropogenic signal is estimated with the CMIP5 experiments of 18 models for the period of 1985–2005, during which the global warming trend is discernible. In climate states that differ merely by a 20‐year mean anthropogenic change, Morakot (2009) yields 3.4–3.6% more total rainfall in the control experiment than its sensitivity counterpart within a radius of 300–500 km from the storm centre. Water budget analysis indicates that the increase in typhoon rainfall is mainly resulted from the enhanced convergence of vapour flux. The enhancement is, in turn, contributed by the increased tropospheric moisture due to global warming and, to a lesser extent, by a more active secondary circulation in the storm that is associated with the anthropogenic climate change.

Stable isotope ratios of typhoon rains in Fuzhou, Southeast China, during 2013–2017

Stable isotope ratios (δ2H and δ18O) in precipitation not only show a certain response to climate change at different time scales, but also have strong linkages to extreme weather events such as tropical cyclones (hurricanes/typhoons). Typhoon activity in the coastal region of Southeast China is quite intense, bringing huge amounts of moisture; thus, contributing to extreme rainfall in this region. The existing isotope data in Southeast China is available on a monthly or daily temporal resolution, which is inadequate to study 1–2-day-long typhoon rainfall events at a particular location. In this study, hourly rainfall δ2H and δ18O data are collected for eight typhoon events from 2013 to 2017 in Fuzhou, Southeast China. The total correlation between δ2H and δ18O is obtained as δ2H = 7.41 δ18O + 0.81 (R2 = 0.96, N = 220). All the eight typhoon events reveal a similar variability pattern in δ18O values which can be divided into three stages. More positive δ18O values occur in the first and third stages, while the second stage is dominated by most negative δ18O values, exhibiting an inverted U-shaped pattern. The positive δ18O values during the first and third stages are governed by re-evaporation. The precipitation during the second stage has distinctly lower δ18O values than the weighted average δ18O of summer precipitation in Fuzhou. Some of these values are slightly lower than those of the water vapor over the Pacific Ocean’s surface. No significant relationship is observed between precipitation δ18O and temperature as well as the amount of precipitation during the second stage. We hypothesize that the significant 18O-depletion is mainly caused by the ‘rain shield effect’, which refers to combination of large-scale convection, high condensation efficiency, and recycling of isotopically depleted vapor in rain shield areas leading to very negative δ18O values during typhoon system. These findings suggest the use of stable isotope ratios as important tracers of typhoon water.

Effect of Sea Surface Temperature on Maximizing Typhoon Rainfall Depth

Effect of Sea Surface Temperature on Maximizing Typhoon Rainfall Depth

Typhoon Rainfall Forecasting by Means of Ensemble Numerical Weather Predictions with a GA-Based Integration Strategy

Rainfall during typhoons is one of the most important water resources in Taiwan, but heavy typhoon rainfall often leads to serious disasters and consequently results in loss of lives and property. Hence, accurate forecasts of typhoon rainfall are always required as important information for water resources management and rainfall-induced disaster warning system. In this study, a methodology is proposed for providing quantitative forecasts of 24 h cumulative rainfall during typhoons. Firstly, ensemble forecasts of typhoon rainfall are obtained from an ensemble numerical weather prediction (NWP) system. Then, an evolutionary algorithm, i.e., genetic algorithm (GA), is adopted to real-time decide the weights for optimally combining these ensemble forecasts. That is, the novelty of this proposed methodology is the effective integration of the NWP-based ensemble forecasts through an evolutionary algorithm-based strategy. An actual application is conducted to verify the forecasts resulting from the proposed methodology, namely NWP-based ensemble forecasts with a GA-based integration strategy. The results confirm that the forecasts from the proposed methodology are in good agreement with observations. Besides, the results from the GA-based strategy are more accurate as compared to those by simply averaging all ensemble forecasts. On average, the root mean square error decreases about 7%. In conclusion, more accurate typhoon rainfall forecasts are obtained by the proposed methodology, and they are expected to be useful for disaster warning system and water resources management during typhoons.

Predictor selection method for the construction of support vector machine (SVM)‐based typhoon rainfall forecasting models using a non‐dominated sorting genetic algorithm

This study proposes a predictor selection method for constructing a support vector machine (SVM)‐based typhoon rainfall forecasting models using a fast elitist Non‐dominated Sorting Genetic Algorithm II (NSGA‐II). Based on SVMs, four rainfall forecasting models with different combinations of the three types of input variables (i.e. antecedent rainfalls, typhoon characteristics and local weather factors) were constructed for 1–6 hr‐ahead forecasting. An application to three rain gauge stations in the Yilan River basin, northeastern Taiwan, was conducted to demonstrate the superiority of the proposed predictor selection method. The results showed that the optimal combination of predictors for each SVM‐based rainfall forecasting model can be automatically and effectively determined by the proposed predictor selection method. The rainfall forecasting model using all three types of input variables performed better than the other three models, especially for long lead‐time forecasting. The construction of rainfall forecasting models is helpful to extend the lead time of flood forecasting. The optimal rainfall forecasting model can be further integrated with river hydraulic models or flood inundation models for flood forecasting to assist floodplain managers to take suitable precautionary measures during typhoon landfall.

A Study on Estimation Equation for Damage and Recovery Costs Considering Human Losses Focused on Natural Disasters in the Republic of Korea

In this study, we conduct an estimation study of the damage costs, recovery costs, and human losses in the case of natural disasters in the Republic of Korea. This research method analyzed human losses, damage costs, and recovery costs caused by natural disasters that swept across the Republic of Korea over the past 16 years, from 2000 to 2015, including extreme wind, heavy snowfall, typhoon, wind wave, and heavy rainfall. Damage status and trend of occurrence were reviewed for each year’s human losses, damage costs, and recovery costs. We propose a calculating equation of the linear regression equation that estimates damage costs and recovery costs considering human losses. The correlation coefficient was 0.898 for the estimation of human losses and damage costs, and 0.889 for the estimation of human losses and recovery costs. In addition, the correlation of both equations was found to be 166% of damage costs when calculating recovery costs. The results of this study can be used as descriptive statistical data to estimate damage costs and recovery costs according to human losses in case of natural disasters.

Complex networks for tracking extreme rainfall during typhoons.

Reconciling the paths of extreme rainfall with those of typhoons remains difficult despite advanced forecasting techniques. We use complex networks defined by a nonlinear synchronization measure termed event synchronization to track extreme rainfall over the Japanese islands. Directed networks objectively record patterns of heavy rain brought by frontal storms and typhoons but mask out contributions of local convective storms. We propose a radial rank method to show that paths of extreme rainfall in the typhoon season (August-November, ASON) follow the overall southwest-northeast motion of typhoons and mean rainfall gradient of Japan. The associated eye-of-the-typhoon tracks deviate notably and may thus distort estimates of heavy typhoon rainfall. We mainly found that the lower spread of rainfall tracks in ASON may enable better hindcasting than for westerly-fed frontal storms in June and July.

Drop Size Distribution Characteristics of Seven Typhoons in China

AbstractThis study is the first attempt to investigate the characteristics of the drop size distribution (DSD) and drop shape relation (DSR) of seven typhoons after making landfall in China. Four typhoons were sampled by a C‐band polarimetric radar (CPOL) and a two‐dimensional video disdrometer (2DVD) in Jiangsu Province (East China) while three typhoons were sampled by two 2DVDs in Guangdong Province (south China). Although the DSD and DSR are different in individual typhoons, the computed DSD parameters in these two groups of typhoons possess similar characteristics. The DSR is more spherical, and the shape‐slope (μ‐Λ) relation has a significantly lower value of μ for a given Λ than that in typhoons in the Taiwan area, indicating different microphysical processes of typhoons between continental China and other regions (western Pacific and Atlantic). The convective precipitation of typhoons contains higher raindrop concentration and lower raindrop diameter than that of the maritime convection. A Z (reflectivity factor)‐R (rain rate) relationship, Z = 147.28R1.38, is derived for typhoons over land in China. The contoured frequency by altitude diagrams of CPOL polarimeteric parameters and the vertical distributions of hydrometeors and retrieved DSD parameters are further investigated to better reveal the microphysical processes of two typhoons (Matmo and Soudelor). Despite the differences in DSDs and polarimetric parameters, microphysical characteristics in both typhoons are similar. The CPOL‐derived microphysical properties, in conjunction with high freezing level, suggest that warm rain accretion processes dominate typhoon rainfall after landfall in China.

Effect of Improvement of Initial and Boundary Conditions in WRF Model on Simulating Typhoon Rainfall

In this study, it is analyzed that the influence of the improvement of the initial and boundary conditions in Weather Research and Forecast (WRF) model on reproducing typhoon rainfall. After WRF model for typhoon MAEMI is constructed and its initial and boundary conditions are improved by various methods, the results of the typhoon rainfall simulation by each improvement method are compared. The application of the typhoon initialization technique had the greatest effect on the reproduction of the typhoon path. In the sense of the accumulated rainfall depth, the application of the typhoon initialization technique had a lot of influence on the spacial distribution. In addition, the adjustment of the relative humidity among various boundary conditions had the greatest effect on the cumulative rainfall depth, and building a WRF model including the regional data in addition to the global data significantly contributed to the reproduction of the local rainfall field. When all the improvement methods were applied, it could be said that the spatially averaged hourly rainfall pattern of the typhoon MAEMI was better reproduced. Keywords: Initial and Boundary Condition, Typhoon MAEMI, Typhoon Rainfall, WRF Model

Effective Use of Ensemble Numerical Weather Predictions in Taiwan by Means of a SOM-Based Cluster Analysis Technique

Typhoon rainfall is one of the most important water resources in Taiwan. However, heavy rainfall during typhoons often leads to serious disasters. Therefore, accurate typhoon rainfall forecasts are always desired for water resources managers and disaster warning systems. In this study, the quantitative rainfall forecasts from an ensemble numerical weather prediction system in Taiwan are used. Furthermore, a novel strategy, which is based on the use of a self-organizing map (SOM) based cluster analysis technique, is proposed to integrate these ensemble forecasts. By means of the SOM-based cluster analysis technique, ensemble forecasts that have similar features are clustered. That is helpful for users to effectively combine these ensemble forecasts for providing better typhoon rainfall forecasts. To clearly demonstrate the advantage of the proposed strategy, actual application is conducted during five typhoon events. The results indicate that the ensemble rainfall forecasts from numerical weather prediction models are well categorized by the SOM-based cluster analysis technique. Moreover, the integrated typhoon rainfall forecasts resulting from the proposed strategy are more accurate when compared to those from the conventional method (i.e., the ensemble mean of all forecasts). In conclusion, the proposed strategy provides improved forecasts of typhoon rainfall. The improved quantitative rainfall forecasts are expected to be useful to support disaster warning systems as well as water resources management systems during typhoons.