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The 2022 extreme Heatwave in Shanghai,Lower Reaches of the Yangtze River Valley:Combined Influences of Multiscale Variabilities

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Advances in Atmospheric Sciences 2024年第4期41卷 593-607页

作者： Ping LIANG Zhiqi ZHANG Yihui DING Zeng-Zhen HU Qi CHeN Key Laboratory of Cities’Mitigation and Adaptation to Climate Change in Shanghai Shanghai Regional Climate CenterChina Meteorological AdministrationShanghai 200030China National Climate Center China Meteorological AdministrationBeijing 100081China Climate Prediction Center NCEP/NWS/NOAACollege ParkMD 20740USA

In the summer of 2022,China(especially the Yangtze River Valley,YRV)suffered its strongest heatwave(HW)event since *** this study,we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV,focusing on the city of *** found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global *** mid-summer of 2022,an enhanced western Pacific subtropical high(WPSH)and anomalous double blockings over the Ural Mountains and Sea of Okhotsk,respectively,were associated with the persistently anomalous high pressure over the YRV,leading to the extreme *** Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time ***,the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking *** warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong *** the subseasonal time scale,the anomalously frequent phases 2-5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden-Julian Oscillation suppressed the convection over the YRV and also contributed to the ***,the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air-sea interaction at multiple time scales.

关键词： extreme heatwave multiscale variability air-sea interaction warming trend Yangtze River Valley Shanghai

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Assimilation of GOeS-R Geostationary Lightning Mapper Flash extent Density Data in GSI 3DVar, enKF, and Hybrid en3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

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Advances in Atmospheric Sciences 2024年第2期41卷 263-277页

作者： Rong KONG Ming XUe edward R.MANSeLL Chengsi LIU Alexandre O.FIeRRO Center for Analysis and Prediction of Storms Norman Oklahoma 73072U.S.A University of Oklahoma Norman Oklahoma 73072U.S.A noaa/National Severe Storms Laboratory NormanOklahoma 73072U.S A.4Zentralanstalt für Meteorologie und Geodynamik Department of Forecasting Models-ZAMGVienna 1190Austria

Capabilities to assimilate Geostationary Operational environmental Satellite “R-series ”(GOeS-R) Geostationary Lightning Mapper(GLM) flash extent density(FeD) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter(GSI-enKF) framework were previously developed and tested with a mesoscale convective system(MCS) case. In this study, such capabilities are further developed to assimilate GOeS GLM FeD data within the GSI ensemble-variational(enVar) hybrid data assimilation(DA) framework. The results of assimilating the GLM FeD data using 3DVar, and pure en3DVar(Pen3DVar, using 100% ensemble covariance and no static covariance) are compared with those of enKF/DfenKF for a supercell storm case. The focus of this study is to validate the correctness and evaluate the performance of the new implementation rather than comparing the performance of FeD DA among different DA schemes. Only the results of 3DVar and pen3DVar are examined and compared with enKF/DfenKF. Assimilation of a single FeD observation shows that the magnitude and horizontal extent of the analysis increments from Pen3DVar are generally larger than from enKF, which is mainly caused by using different localization strategies in enFK/DfenKF and Pen3DVar as well as the integration limits of the graupel mass in the observation operator. Overall, the forecast performance of Pen3DVar is comparable to enKF/DfenKF, suggesting correct implementation.

关键词： GOeS-R lightning data assimilation enKF enVar

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Internal solitary waves in the east China Sea

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Acta Oceanologica Sinica 2008年第3期27卷 51-59页

作者： LI Xiaofeng ZHAO Zhongxiang HAN Zhen XU Liuxiong Joint Center for Ocean Remote Sensing and Living Marine Resources Management Shanghai Fisheries University Shanghai 200090 China noaa e/ra3 WWBG Camp Springs MD 20746 USA Applied Physics Laboratory University of Washington Seattle WA 98105 USA

A european Space Agency＇ s eNVISAT advanced synthetic aperture radar （ASAR） image covering Zhejiang coastal water in the east China Sea （eCS） was acquired on 1 August 2007. This image shows that there are about 20 coherent internal solitary wave （ISW） packets propagating southwestward toward Zhejiang coast. These ISW packets are separated by about 10 kin, suggesting that these ISWs are tide-generated waves. each ISW packet contains 5-15 wave crests. The wavelengths of the wave crests within the ISW packets are about 300 m. The lengths of the leading wave crests are about 50 km. The ISW amplitude is estimated from solving KdV equation in an ideal two-layer ocean model. It is found that the ISW amplitudes is about 8 m. Further analysis of the ASAR image and ocean stratification profiles show that the observed ISWs are depression waves. Analyzing the tidal current finds that these waves are locally generated. The wavelength and amplitude of the eCS ISW are much smaller than their counter- parts in the South China Sea （SCS）. The propagation speed of the eCS ISW is also an order of magnitude smaller than that of the SCS ISW. The observed ISWs in the eCS happened during a spring tide period.

关键词： SAR Internal wave east China Sea

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Atmospheric frontal gravity waves observed in satellite SAR images of the Bohai Sea and Huanghai Sea

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Acta Oceanologica Sinica 2010年第5期29卷 35-43页

作者： LIU Shuming LI Ziwei YANG Xiaofeng Pichel William G YU Yang ZHeNG Quanan LI Xiaofeng The First Institute of Oceanography State Oceanic Administration Qingdao 266061 China National Marine Data and Information Service Tianjin 300171 China Institute of Remote Sensing Applications Chinese Academy of Science Beijing 100101 China noaa/NeSDIS Center for Satellite Applications and Research Camp Springs MD 20746-4304 USA Department of Atmospheric and Oceanic Science University of Maryland Maryland 20742-2425 USA IMSG at noaa/NeSDIS NOAA E/RA3 WWBG Room 102 5200 Auth Road Camp Springs MD 20746-4304 USA.

In the satellite synthetic aperture radar（SAR） images of the Bohai Sea and Huanghai Sea,the authors observe sea surface imprints of wave-like patterns with an average wavelength of 3.8 *** SAR observations with sea surface wind fields and surface weather maps,the authors find that the occurrence of the wave-like phenomena is associated with the passing of atmospheric *** authors define the waves as atmospheric frontal gravity *** dynamical parameters of the wave packets are derived from statistics of 9 satellite SAR images obtained from 2002 to 2008.A two-dimensional linear physical wave model is used to analyze the generation mechanism of the *** atmospheric frontal wave induced wind variation across the frontal wave packet is compared with wind retrievals from the SAR *** CMOD-5（C-band scatterometer ocean geophysical model function） is used for SAR wind retrievals VV（transmitted vertical and received vertical） for eNVISAT and HH（transmitted horizontally and received horizontally） for raDARSAT-1.A reasonable agreement between the analytical solution and the SAR observation is *** new SAR frontal wave observation adds to the school of SAR observations of sea surface imprints of AGWs including island lee waves,coastal lee waves,and upstream Atmospheric Gravity Waves（AGW）.

关键词： Atmospheric gravity waves atmospheric front generation mechanism synthetic aperture radar

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大洋钻探有什么惊人发现

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十万个为什么（探索版） 2024年第7期 12-17页

作者：李阳阳无同济大学海洋与地球科学学院 IODP noaa NASA 维基百科视觉中国

如果你目赌过大洋钻探过去50余年在全球海域的钻孔位置图,便会发现这些钻孔星罗棋布!4000多口井,获取的岩芯总长40多万米,比1000个东方明珠电视塔高度加起来还长。这些岩芯可不一般,它们就像历史书一样记载了千万年来地球海陆变迁的历... 详细信息

如果你目赌过大洋钻探过去50余年在全球海域的钻孔位置图,便会发现这些钻孔星罗棋布!4000多口井,获取的岩芯总长40多万米,比1000个东方明珠电视塔高度加起来还长。这些岩芯可不一般,它们就像历史书一样记载了千万年来地球海陆变迁的历史。而大洋钻探把这些埋没在海底的“史书”捞了上来,其中有什么惊人发现呢?

关键词：东方明珠电视塔钻孔位置海陆变迁全球海域岩芯历史

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Scientific Advances and Weather Services of the China Meteorological Administration’s National Forecasting Systems during the Beijing 2022 Winter Olympics

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Advances in Atmospheric Sciences 2024年第5期41卷 767-776页

作者： Guo DeNG Xueshun SHeN Jun DU Jiandong GONG Hua TONG Liantang DeNG Zhifang XU Jing CHeN Jian SUN Yong WANG Jiangkai HU Jianjie WANG Mingxuan CHeN Huiling YUAN Yutao ZHANG Hongqi LI Yuanzhe WANG Li GAO Li SHeNG Da LI Li LI Hao WANG Ying ZHAO Yinglin LI Zhili LIU Wenhua GUO China Meteorological Administration earth System Modeling and Prediction Centre Beijing 100081China State Key Laboratory of Severe Weather China Meteorological AdministrationBeijing 100081China Key Laboratory of earth System Modeling and Prediction China Meteorological AdministrationBeijing 100081China National Meteorological Center China Meteorological AdministrationBeijing 100081China environmental Modeling Center/NCeP/NWS/noaa College ParkMD 20740USA Nanjing University of Information Science and Technology Nanjing 210044China Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China School of Atmospheric Sciences and Key Laboratory of Mesoscale Severe Weather/Ministry of education Nanjing UniversityNanjing 210023China Tsinghua University Beijing 100084China

Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and *** made providing meteorological services for this event particularly *** China Meteorological Administration(CMA)earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical *** key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was *** of these advancements represent the highest level of capabilities currently available in *** meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and *** included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 *** 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting *** accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the *** program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(ra)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather

关键词： Beijing Winter Olympic Games CMA national forecasting system data assimilation ensemble forecast bias correction and downscaling machine learning-based fusion methods

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Virus-Host Interactions Drive Contrasting Bacterial Diel Dynamics in the Ocean

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Research 2024年第2期6卷 389-399页

作者： Xiaowei Chen Chen Hu Wei Wei Yunlan Yang Markus G.Weinbauer Hongbo Li Shiying Ren Ruije Ma YVibin Huang Tingwei Luo Nianzhi Jiao Rui Zhang State Key Laboratory of Marine environmental Science College of Ocean and Earth SciencesFujian Key Laboratory of Marine Carbon SequestrationXiamen UniversityXiamen 361102PR China College of the environment and ecology Xiamen UniversityXiamen 361102PR China Research Center for environmental ecology and engineering School of Environmental Ecology and Biological EngineeringWuhan Institute of TechnologyWuhan 430205PR China Sorbonne Universités UPMCUniversitéParis 06CNRSLaboratoire d'Oceanographie de Villefranche(LOV)Villefranche-sur-Mer 06230France National Marine environmental Monitoring Center Ministry of Ecological EnvironmentDalian 116023PR China Department of Ocean Sciences University of CaliforniaSanta CruzCAUSA noaa/OAR Pacific Marine environmental Laboratory SeattleWAUSA Institute for Advanced Study Shenzhen UniversityShenzhen 518055PR China

Marine organisms perform a sea of diel *** diel dynamics have been shown to be driven by light,energy resources,circadian rhythms,and the coordinated coupling of photoautotrophs and heterotrophic ***,we explore the diel fluctuation of viral production and decay and their impact on the total and active bacterial community in the coastal and open seawaters of the South China *** results showed that the night-production diel pattern of lytic viral production was concurrent with the lower viral decay at night,contributing to the accumulation of the viral population size during the night for surface *** diel variations in bacterial activity,community composition,and diversity were found highly affected by viral *** was revealed by the finding that bacterial community diversity was positively correlated to lytic viral production in the euphotic zone of the open ocean but was negatively related to lysogenic viral production in the coastal *** distinct but contrasting correlations suggest that viral life strategies can not only contribute to diversifying bacterial community but also potentially piggyback their host to dominate bacterial community,suggesting the tightly synchronized depth-dependent and habitat-specific diel patterns of virus-host *** further implies that viruses serve as an ecologically important driver of bacterial diel dynamics across the ocean,highlighting the viral roles in bacterial ecological and biogeochemical processes in the ocean.

关键词： coastal ocean Marine

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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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Tropical Cyclone Research and Review 2023年第1期12卷 30-49页

作者： Zhan Zhang Weiguo Wang 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 noaa/NWS/NCeP environmental Modeling Center USA SAIC@noaa/NWS/NCeP environmental Modeling Center USA Naval Research Laboratory USA Met Office UK eCMWF ReadingUK noaa/NWS/NCeP National Hurricane Center USA Joint Typhoon Warning Center USA China Meteorological Administration China Indian Meteorological Department India Japan Meteorological Agency Japan Bureau of Meteorology Australia Central Pacific Hurricane Center USA noaa Center for Satellite Applications and Research USA noaa/AOML Hurricane Research Division USA Fudan University ShanghaiChina IMSG@noaa/NWS/OSTI USA

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,*** 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 *** rapporteur report covers the progress made over the past four years(2018–2021)in all three *** review focuses on the progress of dynamical model forecast *** companion paper(Part II)summarizes the advance from operational *** dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity ***,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 *** 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 *** challenging cases of rapid intensification are presented and discussed.

关键词： Dynamical models 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 2:Forecasts by operational centers

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Tropical Cyclone Research and Review 2023年第1期12卷 50-63页

作者： Weiguo Wang Zhan Zhang 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 noaa/NWS/NCeP environmental Modeling Center USA noaa/NWS/NCeP National Hurricane Center USA Joint Typhoon Warning Center USA Bureau of Meteorology Australia Japan Meteorological Agency Japan Indian Meteorological Department India noaa Center for Satellite Applications and Research USA noaa/AOML Hurricane Research Division USA Central Pacific Hurricane Center USA Naval Research Laboratory USA Met Office UK China Meteorological Administration China Fudan University ShanghaiChina IMSG@noaa/NWS/OSTI USA

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,*** I of the review has focused on the progress of dynamical model forecast *** part discusses the performance of TC intensity and rapid intensification forecasts from several operational *** is shown that the TC intensity forecast errors have continued to decrease since the 9th IWTC held in *** particular,the improvement of rapid intensification forecasts has accelerated,compared with years before *** models,operational procedures,tools and techniques,as well as recent challenging cases from 2018 to 2021 identified by operational forecast centers are *** needs and recommendations are also discussed.©2023 The Shanghai Typhoon Institute of China Meteorological *** services by elsevier *** behalf of KeAi Communication *** is an open access article under the CC BY-NC-ND license(http://***/licenses/by-nc-nd/4.0/).

关键词： Forecast error Intensity forecast Operational forecasts Tropical cyclone

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Calibration of Gridded Wind Speed Forecasts Based on Deep Learning

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Journal of Meteorological Research 2023年第6期37卷 757-774页

作者： Xuan YANG Kan DAI Yuejian ZHU National Meteorological Centre Beijing100081China noaa/NWS/NCeP/environmental Modeling Center College ParkMaryland20740USA

The challenges of applying deep learning(DL) to correct deterministic numerical weather prediction(NWP) biases with non-Gaussian distributions are discussed in this *** is known that the DL UNet model is incapable of correcting the bias of strong winds with the traditional loss functions such as the MSe(mean square error),MAe(mean absolute error),and WMAe(weighted mean absolute error).To solve this,a new loss function embedded with a physical constraint called MAe_MR(miss ratio) is *** performance of the UNet model with MAe_MR is compared to UNet traditional loss functions,and statistical post-processing methods like Kalman filter(KF) and the machine learning methods like random forest(RF) in correcting wind speed biases in gridded forecasts from the eCMWF high-resolution model(HReS) in east China for lead times of 1–7 *** addition to MAe for full wind speed,wind force scales based on the Beaufort scale are derived and *** to raw HReS winds,the MAe of winds corrected by UNet(MAe_MR) improves by 22.8% on average at 24–168 h,while UNet(MAe),UNet(WMAe),UNet(MSe),RF,and KF improve by 18.9%,18.9%,17.9%,13.8%,and 4.3%,*** with MSe,MAe,and WMAe shows good correction for wind forces 1–3 and 4,but negative correction for 6 or ***(MAe_MR) overcomes this,improving accuracy for forces 1–3,4,5,and 6 or higher by 11.7%,16.9%,11.6%,and 6.4% over HReS.A case study of a strong wind event further shows UNet(MAe_MR) outperforms traditional post-processing in correcting strong wind biases.

关键词： deep learning wind speed grid forecasting loss function statistical post-processing

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