Study on the Uncertainty of Ensemble Forecasting of Tropical Cyclone

Zhang, Qing‐Hong; Zhu, Xiaodong; Zhongfeng, Zhang; Wan, Qilin

doi:10.1002/cjg2.1074

Cited by 2 publications

(2 citation statements)

References 20 publications

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“…In recent years, quantitative precipitation forecast (QPF) techniques based on ensemble techniques have been developed rapidly (Ebert, 2001;Clark et al, 2017;Sofiati and Nurlatifah, 2019), and have also been applied to LTC precipitation forecasts Zhang et al, 2007;Chen et al, 2016). Among the various ensemble prediction methods, an important class is the integration of ensemble members or multi-model predictions, including the probability matching mean (PM) (Clark et al, 2012;Fang et al, 2013;Surcel et al, 2014), multi-model similar integration (Chen et al, 2005;Lin et al, 2013), optimal percentile (Dai et al, 2016), and ensemble pseudo-bias-corrected QPF (Novak et al, 2014;Alexander et al, 2019;Binh et al, 2020) methods, which yield the most possible single-value forecast by extracting or overlaying valid information.…”

Section: Introductionmentioning

confidence: 99%

上陸台風の降水量予測に向けた力学的-統計的-アナログ予報モデルのアンサンブル手法改善

Ren

Ding

et al. 2022

Journal of the Meteorological Society of Japan

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The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling typhoon precipitation (the DSAEF_LTP model) identifies tropical cyclones (TCs) from history data that are similar to a target TC, and then assembles the precipitation amounts and distributions of those identified to obtain those of the target TC. Two original ensemble methods in the DSAEF_LTP model, mean and maximum, tend to under-and over-forecast TC precipitation, respectively.In addition, these two methods are unable to forecast precipitation at stations beyond their maxima. To overcome the shortcomings and improve the forecast performance of the DSAEF_LTP model, the following five new ensemble methods are incorporated: optimal percentile, fuse, probability matching mean, equal difference-weighted mean, and TSAI (Tropical cyclone track Similarity Area Index)-weighted mean. Then, model experiments for landfalling TCs over China in 2018 are conducted to evaluate the forecast performance of the DSAEF_LTP model with the new ensemble methods. Results show that the overall performance of the optimal percentile (the 90th percentile) ensemble method is superior, with the false alarm rate lower than that of the original ensemble methods. As compared to five operational numerical weather prediction models, the improved DSAEF_LTP model shows advantages in predicting accumulated rainfall, especially with the rainfall of over 250 mm. When implementing the experiments, above results, however, it is found that the model forecast performance varies, depending on the type of TC tracks. 3That is, the accumulated rainfall forecast for westbound TCs is significantly better than that of northbound TCs. To address this issue, different schemes are used to forecast the accumulated rainfall of TCs with the two different track types. The precipitation forecast performance for westbound and northbound TCs, using the 90th percentile and the probability-matched ensemble mean ensemble method, respectively, is much better than that using a single ensemble method for all the TCs.

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Section: Introductionmentioning

confidence: 99%

上陸台風の降水量予測に向けた力学的-統計的-アナログ予報モデルのアンサンブル手法改善

Ren

Ding

et al. 2022

Journal of the Meteorological Society of Japan

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“…Numerical modeling study is an important approach for TC simulation and TC track forecast (Zhang et al, 2007;Han et al, 2008;Guan et al, 2011). Various physical parameterization schemes in numerical models have great impacts on the simulation of TC development and movement.…”

Section: Introductionmentioning

confidence: 99%

Mechanism Analysis for the Difference in Simulated Track of Tropical Cyclone Megi (2010) With Two Planetary Boundary Layer Schemes

Wang

Zhong

Sun

et al. 2017

Chinese J of Geophysics

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The WRF model was employed to simulate super typhoon Megi (2010) with the YSU and MYJ planetary boundary layer (PBL) schemes respectively. The sensitivity of the simulated tropical cyclone (TC) track to the PBL scheme was investigated, and the mechanism for the impact of the PBL scheme on TC track simulation was analyzed from the perspective of TC size. The results show that the description of the vertical mixing process with different schemes is the primary reason for the difference in the simulated lower‐level vertical transport of water vapor. Compared to the MYJ scheme, which could well reproduce Megi's track, the simulation with the YSU scheme produced more active outer spiral rainbands and larger TC size. Accordingly, the increased pressure gradient and radial wind led to more air mass transport from the western Pacific subtropical high (WPSH) to TC, resulting in a weakened WPSH and the large scale steering flow was changed subsequently. As a result, the simulated TC with the YSU scheme turned northward earlier than observation.

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Study on the Uncertainty of Ensemble Forecasting of Tropical Cyclone

Cited by 2 publications

References 20 publications

上陸台風の降水量予測に向けた力学的-統計的-アナログ予報モデルのアンサンブル手法改善

上陸台風の降水量予測に向けた力学的-統計的-アナログ予報モデルのアンサンブル手法改善

Mechanism Analysis for the Difference in Simulated Track of Tropical Cyclone Megi (2010) With Two Planetary Boundary Layer Schemes

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