Improvement of Statistical Typhoon Rainfall Forecasting with ANN-Based Southwest Monsoon Enhancement

Pan, Tsung-Yi; Yang, Yi-Ting; Kuo, Hung‐Chi; Tan, Yih–Chi; Lai, Jihn‐Sung; Chang, Tsang‐Jung; Lee, Cheng-Shang; Hsu, Kai-Chieh

doi:10.3319/tao.2011.07.04.01(tm)

Cited by 8 publications

(9 citation statements)

References 23 publications

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“…Warm ocean eddies in the vicinity of Morakot's path also are closely involved in the enhancement of local convection embedded in Morakot . On the other hand, the synoptic environments were also favorable for convective instability to occur; for example, our model results indicate that very large CAPE (up to 3000 J kg -1 ) existed over the oceanic region covering the Morakot spiral circulation and the southwesterly monsoon belt that both transported abundant water vapor to south Taiwan which is in agreement with the observational study (Pan et al 2011). The atmospheric flow in fact exhibited convective instability to a depth of about 10 km just west of south Taiwan.…”

Section: Discussionsupporting

confidence: 77%

Extreme Rainfall Mechanisms Exhibited by Typhoon Morakot (2009)

Huang¹,

Wong²,

Yeh³

2011

Terr. Atmos. Ocean. Sci.

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Moderate Typhoon Morakot (2009) became the most catastrophic typhoon in Taiwan on record. The MM5 numerical experiments with and without bogus data assimilation (BDA) were used to investigate the extreme rainfall mechanisms in Taiwan associated with the westbound typhoon. The BDA, based on 4DVAR, helps MM5 to maintain a more consolidated typhoon vortex and better predict the observed track after landfall, thus producing realistic extreme rainfall (about 2400 mm) at the southern and Central Mountain Range (CMR) of Taiwan. Severe rainfall in Taiwan is dominated by the CMR that hence modulates rainfall predictability.Model analyses indicate that the synoptic environment provides low-level preconditioning with large convective available energy (CAPE) in the southwest monsoon conveying belt in conjunction with the cyclonic Morakot. When Morakot passed slowly over north Taiwan, the developing Tropical Storm Goni, originating west of Hong Kong, facilitated the moist southwesterly flow to converge with the northerly cyclonic flow of Morakot. These processes contributed to enhanced rainfall in south Taiwan. In an experiment whereby the Goni vortex was initially deactivated by BDA, the southwesterly prevailing flow, southwest of Taiwan, weakened considerably and shifted southward at a later time, resulting in one-third reduction in total accumulated rainfall in south Taiwan. Conversely, total accumulated rainfall in Taiwan is greatly reduced when the initial Morakot vortex is deactivated. Removal of Taiwan topography results in a significant reduction in total accumulated rainfall by more than 50%, due to lack of orographic lift by the CMR.

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Section: Discussionsupporting

confidence: 77%

Extreme Rainfall Mechanisms Exhibited by Typhoon Morakot (2009)

Huang¹,

Wong²,

Yeh³

2011

Terr. Atmos. Ocean. Sci.

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“…Several studies have proposed several methods to forecast long-term or short-term precipitation patterns or classify the characteristics of typhoons, including machine learning methods that use artificial neural networks (ANN) or support vector machines (SVM) (French et al 1992;Kuligowski and Barros 1998;Lin and Chen 2005;Lin and Wu 2009;Pan et al 2011). In addition, ensemble meteorological models include perturbations in the initial conditions, data-analysis methods, and physical parameterizations to forecast typhoon rainfall (Hsiao et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Typhoon Type Index: A New Index for Understanding the Rain or Wind Characteristics of Typhoons and Its Application to Agricultural Losses and Crop Vulnerability

Lin

Wang

Lai

et al. 2020

Journal of Applied Meteorology and Climatology

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Heavy rainfall and strong wind are the two main sources of disasters that are caused by tropical cyclones (TCs), and typhoons with different characteristics may induce different agricultural losses. Traditionally, the classification of typhoon intensity has not considered the amount of rainfall. Here, we propose a novel approach to calculate the typhoon type index (TTI). A positive TTI represents a “wind type” typhoon, where the overall damage in a certain area from TCs is dominated by strong wind. On the other hand, a negative TTI represents a “rain type” typhoon, where the overall damage in a certain area from TCs is dominated by heavy rainfall. From the TTI, the vulnerability of crop losses from different types of typhoons can be compared and explored. For example, Typhoon Kalmaegi (2008) was classified as a rain-type typhoon (TTI = −1.22). The most affected crops were oriental melons and leafy vegetables. On the contrary, Typhoon Soudelor (2015) was classified as a significant wind-type typhoon in most of Taiwan (TTI = 1.83), and the damaged crops were mainly bananas, bamboo shoots, pomelos, and other crops that are easily blown off by strong winds. Through the method that is proposed in this study, we can understand the characteristics of each typhoon that deviate from the general situation and explore the damages that are mainly caused by strong winds or heavy rainfall at different locations. This approach can provide very useful information that is important for the disaster analysis of different agricultural products.

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“…Furthermore, Pan et al (2007) demonstrated that DLRNN (one type of SSNNs) only needs the current rainfall as the input to get a satisfactory hydrograph while an FNN, which has the same input and number of weights as the DLRNN, performs rainfall-runoff processes poorly. Pan et al (2011) used an ANN-based southwest monsoon rainfall enhancement (AME) to improve TRCM rainfall forecasting for two mountain stations Alishan and Yushan with cumulative rainfall over 400 mm. Their result suggested that AME improves TRCM rainfall predictions significantly in both mountain stations.…”

Section: Introductionmentioning

confidence: 99%