GFS模式2019 & 2020年NIO热带气旋路径及强度预测技术

IF 2.4 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Tropical Cyclone Research and Review Pub Date : 2022-03-01 DOI:10.1016/j.tcrr.2022.04.002
Ch. Sridevi , D.R. Pattanaik , A.K. Das , Akhil Srivastava , V.R. Durai , C.J. Johny , Medha Deshpande , P. Suneetha , Radhika Kanase
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引用次数: 3

摘要

利用不同的NWP模型进行热带气旋路径预测及其验证是提供模型误差先验知识的关键任务,这有利于基于模式指导的实时气旋预警。本研究试图验证全球预报系统(GFS)模型对2019年和2020年北印度洋(NIO)热带气旋路径和强度的预测。GFS是印度气象部门(IMD)的业务模式之一,提供长达10天的中期天气预报。利用地球物理流体动力学实验室(GFDL)研制的涡旋跟踪器获得了GFS预报的预测轨迹。本研究共考虑了北印度洋上形成的13个热带气旋,其中2019年有8个,2020年有5个。模式预报路径和强度的准确性以每隔6小时进行5天(120小时)预报验证;对航迹误差进行了直接定位误差(DPE)、沿航迹误差(ATE)和交叉航迹误差(CTE)的验证。2019年(51 ~ 331 km)的年平均DPE低于2020年(82 ~ 359 km), 2019年(66 h)和2020年(48 h)的DPE均小于150 km。正的ATE值(76 ~ 332 km)表明预测轨迹的移动速度快于观测轨迹。大多数预测提前期的正CTE值表明,在这两年中,预测轨迹都朝着观测轨迹的右侧。利用平均误差(ME)和均方根误差(RMSE)验证了最大持续风速(MaxWS)和中心平均海平面压力(MSLP)的气旋强度预报。这些误差与交货期无关。然而,在大多数情况下,该模型都低估了这两年的气旋强度。最后,从气旋到气旋,从孟加拉湾盆地到阿拉伯海盆地,在路径和强度误差上存在显著差异。
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Tropical cyclone track and intensity prediction skill of GFS model over NIO during 2019 & 2020

The Tropical Cyclone (TC) track prediction using different NWP models and its verification is the critical task to provide prior knowledge about the model errors, which is beneficial for giving the model guidance-based real-time cyclone warning advisories. This study has attempted to verify the Global Forecast System (GFS) model forecasted tropical cyclone track and intensity over the North Indian Ocean (NIO) for the years 2019 and 2020. GFS is one of the operational models in the India Meteorological Department (IMD), which provides the medium-range weather forecast up to 10 days. The forecasted tracks from the GFS forecast are obtained using a vortex tracker developed by Geophysical Fluid Dynamics Laboratory (GFDL). A total of 13 tropical cyclones formed over the North Indian Ocean, eight during 2019 and five in 2020 have been considered in this study. The accuracy of the model predicted tracks and intensity is verified for five days forecasts (120 h) at 6-h intervals; the track errors are verified in terms of Direct Position Error (DPE), Along Track Error (ATE) and Cross-Track Error (CTE). The annual mean DPE over NIO during 2019 (51–331 km) is lower than 2020 (82–359 km), and the DPE is less than 150 km up to 66 h during 2019 and 48 h during 2020. The positive ATE (76–332 km) indicates the predicted track movement is faster than the observed track during both years. The positive CTE values for most forecast lead times suggest that the predicted track is towards the right side of the observed track during both years. The cyclone Intensity forecast for the maximum sustained wind speed (MaxWS) and central mean sea level pressure (MSLP) are verified in terms of mean error (ME) and root mean square error (RMSE). The errors are lead time independent. However, most of the time model under-predicted the cyclone intensity during both years. Finally, there is a significant variance in track and intensity errors from the cyclone to cyclone and Bay of Bengal basin to the Arabian Sea basin.

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来源期刊
Tropical Cyclone Research and Review
Tropical Cyclone Research and Review METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
4.60
自引率
3.40%
发文量
184
审稿时长
30 weeks
期刊介绍: Tropical Cyclone Research and Review is an international journal focusing on tropical cyclone monitoring, forecasting, and research as well as associated hydrological effects and disaster risk reduction. This journal is edited and published by the ESCAP/WMO Typhoon Committee (TC) and the Shanghai Typhoon Institute of the China Meteorology Administration (STI/CMA). Contributions from all tropical cyclone basins are welcome. Scope of the journal includes: • Reviews of tropical cyclones exhibiting unusual characteristics or behavior or resulting in disastrous impacts on Typhoon Committee Members and other regional WMO bodies • Advances in applied and basic tropical cyclone research or technology to improve tropical cyclone forecasts and warnings • Basic theoretical studies of tropical cyclones • Event reports, compelling images, and topic review reports of tropical cyclones • Impacts, risk assessments, and risk management techniques related to tropical cyclones
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