An improved typhoon monitoring model based on precipitable water vapor and pressureOAEI
An improved typhoon monitoring model based on precipitable water vapor and pressure
The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV)has been confirmed.However,monitoring the movement of typhoon is focused on PWV,making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy.Hence,based on PWV and meteorological data,we propose an improved typhoon monitoring mode.First,the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV(ERA5-PWV)and the Global Navigation Satellite System-derived PWV(GNSS-PWV)were compared with the reference radiosonde PWV(RS-PWV).Then,using the PWV and atmospheric parameters derived from ERA5,we discussed the anomalous variations of PWV,pressure(P),precipitation,and wind speed during different typhoons.Finally,we compiled a list of critical factors related to typhoon movement,PWV and P.We developed an improved multi-factor typhoon monitoring mode(IMTM)with different models(i.e.,IMTM-Ⅰ and IMTM-Ⅱ)in different cases with a higher density of GNSS observation or only Numerical Weather Prediction(NWP)data.The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network(CMOTN).The re-sults show that the root mean square(RMS)of the IMTM-Ⅰ is 1.26 km/h based on ERA5-P and ERA5-PWV,and the absolute bias values are mostly within 2 km/h.Compared with the models considering the single factor ERA5-P/ERA5-PWV,the RMS of the IMTM-Ⅰ is improved by 26.3%and 38.5%,respectively.The IMTM-Ⅱ model manifests a residual of only 0.35 km/h.Compared with the single-factor model based on GNSS-PWV/P,the residual of the IMTM-Ⅱ model is reduced by 90.8%and 84.1%,respectively.These re-sults propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.
Junyu Li;Lv Zhou;Haojie Li;Lilong Liu;Jiaqing Chen;Yibin Yao;Mingyun Hu;Liangke Huang;Fade Chen;Tengxu Zhang
College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541006,ChinaCollege of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541006,China||Guangxi Key Laboratory of Spatial Information and Geomatics,Guilin 541006,ChinaQinzhou Institute of Surveying and Mapping for Housing and Urban-Rural Development Co.,Ltd.,Qinzhou 535000,ChinaSchool of Geodesy and Geomatics,Wuhan University,Wuhan 430079,ChinaSchool of Resources and Environmental Science and Engineering,Hubei University of Science and Technology,Xianning 437100,China
TyphoonGNSS/ERA5 PWVPressureMonitoringImproved model
《大地测量与地球动力学(英文版)》 2024 (003)
276-290 / 15
This work was supported by the Guangxi Natural Science Foundation of China(2020GXNSFBA297145,GuikeAD23026177),the Foundation of Guilin University of Technology(GUTQDJJ6616032),Guangxi Key Laboratory of Spatial Information and Geomatics(21-238-21-05),the National Natural Science Foundation of China(42064002,42004025,42074035,42204006),the Innovative Training Program Foundation(202210596015,202210596402),and the Open Fund of Hubei Luojia Laboratory(gran 230100020,230100019).
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