Chen Yu-xu, Jia Li, J. Zuo, Ding Chen-chen, Ren Fu-min, LI Guo-ping
{"title":"On the Improvement of the DSAEF_LTP Model to Heavy Precipitation Simulation of Landfalling Tropical Cyclones over China in 2018","authors":"Chen Yu-xu, Jia Li, J. Zuo, Ding Chen-chen, Ren Fu-min, LI Guo-ping","doi":"10.46267/J.1006-8775.2021.021","DOIUrl":null,"url":null,"abstract":"In this study, the Dynamical-Statistical-Analog Ensemble Forecast model(DSAEF_LTP model) for landfalling tropical cyclone(LTC) precipitation was employed to simulate the precipitation of 10 LTCs that occurred over China in 2018. With similarity region scheme(SRS) parameter values added and TC intensity introduced to the generalized initial value(GIV), four groups of precipitation simulation experiments were designed to verify the forecasting ability of the improved model for more TC samples. Results show that the simulation ability of the DSAEF_LTP model can be optimized regardless of whether adding SRS values only, or introducing TC intensity into GIV, while the experiment with both the two improvements shows a more prominent advantage in simulating the heavier precipitation of LTCs. Compared with four NWP models(i.e., ECMWF, GFS, GRAPES and SMS-WARMS), the overall forecasting performance of the DSAEF_LTP model achieves a better result in simulating precipitation at the thresholds over 250 mm and performs slightly better than NWP models at the thresholds over 100 mm.","PeriodicalId":17432,"journal":{"name":"热带气象学报","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"热带气象学报","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.46267/J.1006-8775.2021.021","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 1
Abstract
In this study, the Dynamical-Statistical-Analog Ensemble Forecast model(DSAEF_LTP model) for landfalling tropical cyclone(LTC) precipitation was employed to simulate the precipitation of 10 LTCs that occurred over China in 2018. With similarity region scheme(SRS) parameter values added and TC intensity introduced to the generalized initial value(GIV), four groups of precipitation simulation experiments were designed to verify the forecasting ability of the improved model for more TC samples. Results show that the simulation ability of the DSAEF_LTP model can be optimized regardless of whether adding SRS values only, or introducing TC intensity into GIV, while the experiment with both the two improvements shows a more prominent advantage in simulating the heavier precipitation of LTCs. Compared with four NWP models(i.e., ECMWF, GFS, GRAPES and SMS-WARMS), the overall forecasting performance of the DSAEF_LTP model achieves a better result in simulating precipitation at the thresholds over 250 mm and performs slightly better than NWP models at the thresholds over 100 mm.