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下投式探空资料对数值预报初始场影响的个例分析 被引量:8
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作者 曲晓波 julian heming 《气象与环境学报》 2006年第2期34-37,共4页
通过对2000年8月加勒比海地区飓风Debby活动期间,连续2个时次中使用下投式探空资料同化分析后,利用英国气象局全球数值预报系统的数值预报分析场和背景场的对比分析,阐明了由于下投式探空资料的引入,较好地描述了实际大气的情况,为数值... 通过对2000年8月加勒比海地区飓风Debby活动期间,连续2个时次中使用下投式探空资料同化分析后,利用英国气象局全球数值预报系统的数值预报分析场和背景场的对比分析,阐明了由于下投式探空资料的引入,较好地描述了实际大气的情况,为数值预报提供了较为接近实际的初始场,从而提高了数值预报的精度。其中以湿度场和风场的贡献为最大。 展开更多
关键词 下投式探空资料 初始场 影响 个例分析
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A review of recent advances(2018–2021)on tropical cyclone intensity change from operational perspectives,part 2:Forecasts by operational centers 被引量:1
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作者 Weiguo Wang Zhan Zhang +18 位作者 John P.Cangialosi Michael Brennan Levi Cowan Peter Clegg Hosomi Takuya Ikegami Masaaki Ananda Kumar Das Mrutyunjay Mohapatra Monica Sharma John A.Knaff John Kaplan Thomas Birchard James D.Doyle julian heming Jonathan Moskaitis Suhong Ma Charles Sampson Liguang Wu Eric Blake 《Tropical Cyclone Research and Review》 2023年第1期50-63,共14页
This paper summarizes the progress and activities of tropical cyclone(TC)operational forecast centers during the last four years(2018–2021).It is part II of the review on TC intensity change from the operational pers... This paper summarizes the progress and activities of tropical cyclone(TC)operational forecast centers during the last four years(2018–2021).It is part II of the review on TC intensity change from the operational perspective in the rapporteur report presented to the 10th International Workshop on TCs(IWTC)held in Bali,Indonesia,from Dec.5–9,2022.Part I of the review has focused on the progress of dynamical model forecast guidance.This part discusses the performance of TC intensity and rapid intensification forecasts from several operational centers.It is shown that the TC intensity forecast errors have continued to decrease since the 9th IWTC held in 2018.In particular,the improvement of rapid intensification forecasts has accelerated,compared with years before 2018.Consensus models,operational procedures,tools and techniques,as well as recent challenging cases from 2018 to 2021 identified by operational forecast centers are described.Research needs and recommendations are also discussed.©2023 The Shanghai Typhoon Institute of China Meteorological Administration.Publishing services by Elsevier B.V.on behalf of KeAi Communication Co.Ltd.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/). 展开更多
关键词 Forecast error Intensity forecast Operational forecasts Tropical cyclone
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A review of recent advances(2018–2021)on tropical cyclone intensity change from operational perspectives,part 1:Dynamical model guidance
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作者 Zhan Zhang Weiguo Wang +19 位作者 James D.Doyle Jonathan Moskaitis William A.Komaromi julian heming Linus Magnusson John P.Cangialosi Levi Cowan Michael Brennan Suhong Ma Ananda Kumar Das Hosomi Takuya Peter Clegg Thomas Birchard John A.Knaff John Kaplan Mrutyunjay Mohapatra Monica Sharma Ikegami Masaaki Liguang Wu Eric Blake 《Tropical Cyclone Research and Review》 2023年第1期30-49,共20页
This review summarizes the rapporteur report on tropical cyclone(TC)intensity change from the operational perspective,as presented to the 10th International Workshop on TCs(IWTC-10)held in Bali,Indonesia,from Dec.5–9... This review summarizes the rapporteur report on tropical cyclone(TC)intensity change from the operational perspective,as presented to the 10th International Workshop on TCs(IWTC-10)held in Bali,Indonesia,from Dec.5–9,2022.The accuracy of TC intensity forecasts issued by operational forecast centers depends on three aspects:real-time observations,TC dynamical model forecast guidance,and techniques and methods used by forecasters.The rapporteur report covers the progress made over the past four years(2018–2021)in all three aspects.This review focuses on the progress of dynamical model forecast guidance.The companion paper(Part II)summarizes the advance from operational centers.The dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity forecasts.Here,we describe recent advances and developments of major operational regional dynamical TC models and their intensity forecast performance,including HWRF,HMON,COAMPS-TC,Met Office Regional Model,CMA-TYM,and newly developed HAFS.The performance of global dynamical models,including NOAA's GFS,Met Office Global Model(MOGM),JMA's GSM,and IFS(ECMWF),has also been improved in recent years due to their increased horizontal and vertical resolution as well as improved data assimilation systems.Recent challenging cases of rapid intensification are presented and discussed. 展开更多
关键词 Dynamical models Intensity forecast Operational forecasts Tropical cyclone
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Remote sensing and analysis of tropical cyclones:Current and emerging satellite sensors
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作者 Lucrezia Ricciardulli Brian Howell +14 位作者 Christopher R.Jackson Jeff Hawkins Joe Courtney Ad Stoffelen Sebastian Langlade Chris Fogarty Alexis Mouche William Blackwell Thomas Meissner julian heming Brett Candy Tony McNally Masahiro Kazumori Chinmay Khadke Maria Ana Glaiza Escullar 《Tropical Cyclone Research and Review》 2023年第4期267-293,共27页
This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Orga... This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Organization(WMO)report prepared for the 10th International Workshop on Tropical Cyclones(IWTC),held in Bali in December 2022,and its objective is to present updates in TC research and operation every four years.Here we focus on updates regarding the most recent space-based TC observations,and we cover new methodologies and techniques using polar orbiting sensors,such as C-band synthetic aperture radars(SARs),L-band and combined C/X-band radiometers,scatterometers,and microwave imagers/sounders.We additionally address progress made with the new generation of geostationary and small satellites,and discuss future sensors planned to be launched in the next years.We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research,and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future. 展开更多
关键词 Tropical cyclones Surface wind Satellite sensors Operations
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Unusual tracks:Statistical,controlling factors and model prediction
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作者 Ying Li julian heming +3 位作者 Ryan D.Torn Shaojun Lai Yinglong Xu Xiaomeng Chen 《Tropical Cyclone Research and Review》 2023年第4期309-322,共14页
The progress of research and forecast techniques for tropical cyclone(TC)unusual tracks(UTs)in recent years is reviewed.A major research focus has been understanding which processes contribute to the evolution of the ... The progress of research and forecast techniques for tropical cyclone(TC)unusual tracks(UTs)in recent years is reviewed.A major research focus has been understanding which processes contribute to the evolution of the TC and steering flow over time,especially the reasons for the sharp changes in TC motion over a short period of time.When TCs are located in the vicinity of monsoon gyres,TC track forecast become more difficult to forecast due to the complex interaction between the TCs and the gyres.Moreover,the convection and latent heat can also feed back into the synoptic-scale features and in turn modify the steering flow.In this report,two cases with UTs are examined,along with an assessment of numerical model forecasts.Advances in numerical modelling and in particular the development of ensemble forecasting systems have proved beneficial in the prediction of such TCs.There are still great challenges in operational track forecasts and warnings,such as the initial TC track forecast,which is based on a poor pre-genesis analysis,TC track forecasts during interaction between two or more TCs and track predictions after landfall.Recently,artificial intelligence(AI)methods such as machine learning or deep learning have been widely applied in the field of TC forecasting.For TC track forecasting,a more effective method of center location is obtained by combining data from various sources and fully exploring the potential of AI,which provides more possibilities for improving TC prediction. 展开更多
关键词 Unusual TC tracks Track controlling factors Track predictions Track forecast errors
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