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

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## Abstract

**:**

## 1. Introduction

## 2. Ensemble Numerical Weather Prediction System in Taiwan

## 3. The Artificial Neural Network (ANN)-Based Integration Strategy

#### 3.1. Self-Organizing Map-Based Cluster Analysis Technique

#### 3.2. Strategy for Effective Combination of Ensemble Numerical Weather Predictions

## 4. Study Cases

## 5. Results of the SOM-Based Cluster Analysis Technique

## 6. Results and Discussion

#### 6.1. Potential of the Ensemble Mean of Each Cluster

#### 6.2. Evaluation of the Performance of the Proposed ANN-Based Integration Strategy

## 7. Summary and Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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**Figure 1.**An example of ensemble 24-h typhoon track forecasts and 24-h rainfall forecasts (28 August 2013–29 August 2013) of TTFRI-EPS.

**Figure 3.**Illustration of the proposed artificial neural networks (ANN)-based strategy for effective use of ensemble forecasts.

**Figure 4.**Observed 24-h rainfall of (

**a**) Saola; (

**b**) Kong-Rey; (

**c**) Fung-Wong; (

**d**) Soudelor; and, (

**e**) Megi.

**Figure 7.**The observation and the ensemble means of corresponding clusters as well as all members, (

**a**) Typhoon Saola; (

**b**) Typhoon Kong-Rey; (

**c**) Typhoon Fung-Wong; (

**d**) Typhoon Soudelor; (

**e**) Typhoon Megi.

**Figure 8.**Performance measures of ensemble mean corresponding to each cluster and to all of the members, (

**a**) CC; (

**b**) RMSE; (

**c**) AEV; (

**d**) AEP.

**Figure 9.**Performance measures of the proposed and the conventional strategies for five typhoons, (

**a**) CC; (

**b**) RMSE; (

**c**) AEV; (

**d**) AEP.

**Table 1.**Physical parameterization schemes of Taiwan Typhoon and Flood Research Institute (TTFRI)-ensemble prediction system (EPS) ensemble members.

NWMs | Cumulus Schemes | Microphysics Schemes | Planetary Boundary Layer Schemes |
---|---|---|---|

WRF | Grell-Devenyi, Grell 3D, Betts-Miller-Janjic, Kain-Fritsch | Goddard | Yonsei University |

HWRF | Simplified Arakawa & Schubert | Ferrier | NCEP GFS |

MM5 | Grell | WRF Single-Moment 5-class | Medium-Range Forecast nonlocal boundary layer |

CReSS | ---- | Cold rain | Mellor & Yamada |

No. | Rainfall Period (yyyy/mm/dd/hh) | Maximum 24-h Rainfall (mm) | Remark |
---|---|---|---|

1 | 2012/08/01/00~2012/08/02/00 | 1024 | Typhoon Saola |

2 | 2013/08/28/18~2013/08/29/18 | 722 | Typhoon Kong-Rey |

3 | 2014/09/20/18~2014/09/21/18 | 761 | Typhoon Fung-Wong |

4 | 2015/08/07/12~2015/08/08/12 | 1042 | Typhoon Soudelor |

5 | 2016/09/26/18~2016/09/27/18 | 943 | Typhoon Megi |

Measures | Performance Measures of 5 Typhoons | Improvement | |
---|---|---|---|

Conventional | Proposed | ||

CC | 0.753 | 0.779 | 3.5% |

RMSE (mm) | 93.13 | 89.10 | −4.3% * |

AEV (%) | 19.85 | 19.05 | −4.0% * |

AEP (%) | 40.52 | 38.82 | −4.2% * |

**Table 4.**Comparison between the proposed and the conventional strategies under different levels of rainfall.

Data Used | CC | RMSE (mm) | ||||
---|---|---|---|---|---|---|

Conventional | Proposed | Improvement | Conventional | Proposed | Improvement | |

10% | 0.375 | 0.441 | 17.5% | 202.451 | 191.900 | −5.2% |

20% | 0.433 | 0.488 | 12.8% | 160.195 | 152.293 | −4.9% |

30% | 0.513 | 0.557 | 8.7% | 138.016 | 131.581 | −4.7% |

40% | 0.573 | 0.614 | 7.0% | 123.026 | 117.294 | −4.7% |

50% | 0.605 | 0.645 | 6.5% | 114.129 | 108.869 | −4.6% |

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**MDPI and ACS Style**

Wu, M.-C.; Hong, J.-S.; Hsiao, L.-F.; Hsu, L.-H.; Wang, C.-J.
Effective Use of Ensemble Numerical Weather Predictions in Taiwan by Means of a SOM-Based Cluster Analysis Technique. *Water* **2017**, *9*, 836.
https://doi.org/10.3390/w9110836

**AMA Style**

Wu M-C, Hong J-S, Hsiao L-F, Hsu L-H, Wang C-J.
Effective Use of Ensemble Numerical Weather Predictions in Taiwan by Means of a SOM-Based Cluster Analysis Technique. *Water*. 2017; 9(11):836.
https://doi.org/10.3390/w9110836

**Chicago/Turabian Style**

Wu, Ming-Chang, Jing-Shan Hong, Ling-Feng Hsiao, Li-Huan Hsu, and Chieh-Ju Wang.
2017. "Effective Use of Ensemble Numerical Weather Predictions in Taiwan by Means of a SOM-Based Cluster Analysis Technique" *Water* 9, no. 11: 836.
https://doi.org/10.3390/w9110836