首页|An improved typhoon monitoring model based on precipitable water vapor and pressure

An improved typhoon monitoring model based on precipitable water vapor and pressure

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
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.

TyphoonGNSS/ERA5 PWVPressureMonitoringImproved model

Junyu Li、Haojie Li、Lilong Liu、Jiaqing Chen、Yibin Yao、Mingyun Hu、Liangke Huang、Fade Chen、Tengxu Zhang、Lv Zhou

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College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541006,China

Guangxi Key Laboratory of Spatial Information and Geomatics,Guilin 541006,China

Qinzhou Institute of Surveying and Mapping for Housing and Urban-Rural Development Co.,Ltd.,Qinzhou 535000,China

School of Geodesy and Geomatics,Wuhan University,Wuhan 430079,China

School of Resources and Environmental Science and Engineering,Hubei University of Science and Technology,Xianning 437100,China

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Guangxi Natural Science Foundation of ChinaGuangxi Natural Science Foundation of ChinaFoundation of Guilin University of TechnologyGuangxi Key Laboratory of Spatial Information and GeomaticsNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaInnovative Training Program FoundationInnovative Training Program FoundationOpen Fund of Hubei Luojia LaboratoryOpen Fund of Hubei Luojia Laboratory

2020GXNSFBA297145GuikeAD23026177GUTQDJJ661603221-238-21-0542064002420040254207403542204006202210596015202210596402230100020230100019

2024

10.1016/j.geog.2023.10.002

大地测量与地球动力学(英文版)
中国地震局地震研究所

大地测量与地球动力学(英文版)

EI
影响因子：0.568
ISSN：1674-9847
年,卷(期)：2024.15(3)
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