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Predictability of the 7·20 extreme rainstorm in Zhengzhou in stochastic kinetic-energy backscatter ensembles

Science China Earth Sciences 2024年第7期67卷 2226-2241页

作者： Min YANG Peilong YU Lifeng ZHANG Xiaobing PAN Quanjia ZHONG Yunying LI College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Key Laboratory of high impact weather(Special) China Meteorological AdministrationChangsha 410073China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjing 210044China department of Ocean Science Hong Kong University of Science and TechnologyHong Kong 999077China

The scale-dependent predictability of the devastating 7·20 extreme rainstorm in Zhengzhou,China in 2021 was investigated via ensemble experiments,which were perturbed on different scales using the stochastic kinetic-energy backscatter(SKEB)scheme in the WRF model,with the innermost domain having a 3-km grid *** daily rainfall(RAIN24h)and the cloudburst during 1600-1700 LST(RAIN1h)were *** demonstrated that with larger perturbation scales,the ensemble spread for the rainfall maximum widens and rainfall forecasts become closer to the *** ensembles with mesoscale or convective-scale perturbations,RAIN1h loses predictability at scales smaller than 20 km and RAIN24h is predictable for all *** in ensembles with synoptic-scale perturbations,the largest scale of predictability loss extends to 60 km for both RAIN1h and ***,the average positional error in forecasting the heaviest rainfall for RAIN24h(RAIN1h)was 400 km(50-60)*** southerly low-level jet near Zhengzhou was assumed to be directly responsible for the forecast uncertainty of *** rapid intensification in low-level cyclonic vorticity,mid-level divergence,and upward motion concomitant with the jet dynamically facilitated the *** analysis of the divergent,rotational and vertical kinetic spectra and the corresponding error spectra showed that the error kinetic energy at smaller scales grows faster than that at larger scales and saturates more quickly in all ***-scale perturbations not only boost larger-scale error growth but are also conducive to error growth at all scales through a downscale cascade,which indicates that improving the accuracy of larger-scale flow forecast may discernibly contributes to the forecast of cloudburst intensity and position.

关键词： Stochastic kinetic-energy backscatter(SKEB) Extreme rainfall Ensemble forecast Predictability

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An Evaluation of Tropical Cyclone Genesis Forecast over the Western North Pacific and the South China Sea from the CMA-TRAMS

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Journal of Tropical Meteorology 2024年第1期30卷 20-28页

作者：李梦婕陈子通戴光丰田群梁卓轩林青张艳霞 Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical weather Prediction CMAGuangzhou 510641 China State Key Laboratory of Severe weather Chinese Academy of Meteorological SciencesBeijing 100081 China Guangdong Meteorological Observatory Guangzhou 510641 China

Tropical cyclone(TC) genesis forecasting is essential for daily operational practices during the typhoon *** updated version of the Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS) offers forecasters reliable numerical weather prediction(NWP) products with improved configurations and fine resolution. While traditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesis forecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims to evaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South China Sea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has been proposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, predicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 h in advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors of operational models according to the annual evaluation. The study also briefly investigated the forecast of Noul(2011). The forecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, consistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized threedimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis,fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.

关键词： CMA-TRAMS cyclogenesis numerical weather prediction tropical cyclone

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Cloud Microphysical Characteristics of Typhoon Meranti(2016)during Its Rapid Intensification:Model Validation and SST Sensitivity Experiments

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Journal of Meteorological research 2024年第3期38卷 542-557页

作者： Rui WANG Yihong DUAN Jianing FENG department of Atmospheric and Oceanic Sciences&Institute of Atmospheric Sciences Fudan UniversityShanghai200438China State Key Laboratory of Severe weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing100081China

Cloud microphysics plays an important role in determining the intensity and precipitation of tropical cyclones(TCs).In this study,a high-resolution numerical simulation by WRF(version 4.2)of Typhoon Meranti(2016)during its rapid intensification(RI)period was conducted and validated by multi-source observations including Cloud-Sat and Global Precipitation Mission satellite *** snow and ice particles content were found to increase most rapidly compared with other hydrometeors during the RI *** all hydrometeors continued to *** graupel content only increased in the initial RI stage,and then decreased afterwards due to precipitation during the RI *** addition,sea surface temperature(SST)sensitivity experiments showed that,although the intensity of the TC increased with a higher SST,not all hydrometeors *** graupel content continued to increase with the increase in SST,mainly due to the accumulation of more lower-temperature supercooled water vapor at the corresponding *** content of snow decreased with the increase in SST because stronger vertical motion at the corresponding height affected the aggregation of ice crystals.

关键词： tropical cyclone rapid intensification cloud microphysical characteristics sea surface temperature(SST)

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Synergistic Effects of Bay of Bengal Tropical Cyclones and Tibetan Plateau Vortices on Water Vapor Transport over the Tibetan Plateau in Early Summer

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Journal of Meteorological research 2024年第2期38卷 383-398页

作者： Jialu LIN Ying LI Beiyao LIU Pengchao AN State Key Laboratory of Severe weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 University of Chinese Academy of Sciences Beijing 100049 department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200433

The Bay of Bengal(BoB)tropical cyclones(TCs)and the Tibetan Plateau vortices(TPVs)are two crucial weather systems influencing the Tibetan Plateau(TP).Their synergistic effects can lead to widespread heavy precipitation events on the *** this study,we employ the Hybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT)model to track the trajectory of water vapor transport during three large-scale precipitation events on the TP under the combined influence of BoB TCs and *** results indicate that low-level water vapor from the BoB under the influence of BoB TCs was cyclonically entangled into the cyclonic circulation,lifted and transported northward by southwesterly flow to the southeastern part of the TP,which contributes to the moistening of the entire troposphere ***,convergence of the cyclonic circulation of the TPVs on the northern TP further transports water vapor collected in the southeastern TP northward,conducive to the maintenance and development of precipitation systems,thus inducing widespread heavy precipitation events over the TP.

关键词： Bay of Bengal(BoB) tropical cyclones(TCs) Tibetan Plateau vortices(TPVs) trajectory tracing water vapor transport

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Physical mechanism of the rapid increase in intense and long-lived extreme heatwaves in the Northern Hemisphere since 1980

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Science China Earth Sciences 2024年第7期67卷 2103-2121页

作者： Yuqing WANG Wen ZHOU Chunzai WANG Key Laboratory of Polar Atmosphere-ocean-ice System for weather and Climate of the MOE Department of Atmospheric and Oceanic Sciences&Institute of Atmospheric SciencesFudan UniversityShanghai 200438China Key Laboratory for Polar Science of the MNR Polar Research Institute of ChinaShanghai 201209China State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China Global Ocean and Climate research Center South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China

Since 1980,both the intensity and duration of summer heatwaves in the middle and high latitudes of the Northern Hemisphere have significantly increased,leading this region to become a critical area for a significant increase in the frequency of intense and long-lived extreme *** found that stronger and more persistent high-pressure systems and lower soil moisture before the events were the main drivers of intense and long-lived extreme heatwaves in western Europe and the middle and high latitudes of North ***,in eastern Europe and Siberia,lower cloud cover before events is also a main driver of this type of extreme heatwave,in addition to the above *** factors are coupled with each other and can change heatwave intensity and duration by influencing surface radiation processes during *** the self-organizing map classification method,we found that 6 weather patterns with increased frequency,intensity,and duration were the main dynamic reasons leading to the increase in intense and long-lived extreme heatwaves after *** addition,the decrease in summer average soil moisture in most areas of the mid-high latitudes of the Northern Hemisphere and the decrease in average cloud cover in eastern Europe and Siberia are found to be the main thermodynamic reasons leading to the increase in these extreme heatwaves.

关键词： high intensity Long duration Extreme heatwaves high pressure system Soil moisture Cloud cover

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Anomalies of Precipitation over China on Days with Tropical Cyclone Activity over the Bay of Bengal: Role of Moisture Transport

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Journal of Meteorological research 2024年第2期38卷 368-382页

作者： Na WEI Ying LI Xiaoting FAN Nanjing Joint Institute for Atmospheric Sciences Nanjing 210041 State Key Laboratory of Severe weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200433

Tropical cyclones over the Bay of Bengal(BoBTC)affect the precipitation over China,with distinct seasonal and daily *** study quantitatively examines the daily standardized precipitation anomalies(SPAs)over China on the days with BoBTC activities(storm-days)and related circulations,based on rainfall measurements at surface meteorological stations and ECMWF reanalysis data on a 0.25°×0.25°resolution during *** positive SPA is found over the stations in the two adjacent regions around BoB(Southwest China in May/November and southern Tibetan Plateau in October)and three distant regions(Southeast China and the northeastern boundary of the Qinghai-Tibet Plateau in May,and central North China in October).The SPA distributions are remarkably consistent with the integrated water vapor transport(IVT)*** IVT is found associated with the interaction between southwesterly(southerly)of the BoBTC circulation and low-level monsoonal flow in May(midlevel westerly in winter months).The probabilities of extreme precipitation(EP)occurrences over the above regions all increase on *** adjacent regions,EP is significantly correlated with the northward IVT anomalies to the east of BoBTC circulation,which strengthen the water vapor input through the southern *** IVT anomalies are stronger in May,benefited by the deep monsoonal southwesterlies than those in *** distant regions,EP is more closely related to the IVT anomaly extending back from *** moisture from BoB concentrates along a local low-level convergence line over Southeast China,being further facilitated by coexistence of the BoBTC depression and midlevel westerly trough in *** results highlight the interactions between BoBTCs and local weather systems that influence the general precipitation anomalies and occurrence of EP over China,especially over distant regions.

关键词： tropical cyclone Bay of Bengal precipitation anomaly moisture transport

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A Physics-informed Deep-learning Intensity Prediction Scheme for Tropical Cyclones over the Western North Pacific

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Advances in Atmospheric Sciences 2024年第7期41卷 1391-1402页

作者： Yitian ZHOU Ruifen ZHAN Yuqing WANG Peiyan CHEN Zhemin TAN Zhipeng XIE Xiuwen NIE department of Atmospheric and Oceanic Sciences&Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China Shanghai Typhoon Institute of China Meteorological Administration Shanghai 200030China department of Atmospheric Sciences and International Pacific research Center University of Hawaii at ManoaHonolulu 96822USA Key Laboratory of Mesoscale Severe weather/MOE and School of the Atmospheric SciencesNanjing UniversityNanjing 210023China School of Computer Science Fudan UniversityShanghai 200438China

Accurate prediction of tropical cyclone(TC)intensity is challenging due to the complex physical processes ***,we introduce a new TC intensity prediction scheme for the western North Pacific(WNP)based on a time-dependent theory of TC intensification,termed the energetically based dynamical system(EBDS)model,together with the use of a long short-term memory(LSTM)neural *** time-dependent theory,TC intensity change is controlled by both the internal dynamics of the TC system and various environmental factors,expressed as environmental dynamical *** LSTM neural network is used to predict the environmental dynamical efficiency in the EBDS model trained using besttrack TC data and global reanalysis data during 1982–*** transfer learning and ensemble methods are used to retrain the scheme using the environmental factors predicted by the Global Forecast System(GFS)of the National Centers for Environmental Prediction during 2017–*** predicted environmental dynamical efficiency is finally iterated into the EBDS equations to predict TC *** new scheme is evaluated for TC intensity prediction using both reanalysis data and the GFS prediction *** intensity prediction by the new scheme shows better skill than the official prediction from the China Meteorological Administration(CMA)and those by other state-of-art statistical and dynamical forecast systems,except for the 72-h *** at the longer lead times of 96 h and 120 h,the new scheme has smaller forecast errors,with a more than 30%improvement over the official forecasts.

关键词： tropical cyclones western North Pacific intensity prediction EBDS LSTM

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Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

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Advances in Atmospheric Sciences 2024年第8期41卷 1539-1558页

作者： Yanxin ZHENG Shuanglin LI Noel KEENLYSIDE Shengping HE Lingling SUO department of Atmospheric Science CMA-CUG Joint Centre for Severe Weather and Climate and Hydro-geological HazardsChina University of GeosciencesWuhan 430074China Institute of Atmospheric Physics and Climate Change research Center Chinese Academy of SciencesBeijing 100029China Three Gorges National Climatological Observatory Yichang 443099China Geophysical Institute University of Bergen and Bjerknes Centre for Climate ResearchBergen 5007Norway Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate research Bergen 5007Norway Nansen-Zhu International research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(weather research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

关键词： triple-nested downscaling Three Gorges Reservoir area consecutive rainfall events geological hazards projection

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Improved forecasting via physics-guided machine learning as exemplified using“21·7”extreme rainfall event in Henan

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Science China Earth Sciences 2024年第5期67卷 1652-1674页

作者： Qi ZHONG Zhicha ZHANG Xiuping YAO Shaoyu HOU Shenming FU Yong CAO Linguo JING China Meteorological Administration Training Center Beijing 100081China State Key Laboratory of Severe weather Chinese Academy of Meteorological SciencesBeijing 100081China Zhejiang Meteorological Observatory Hangzhou 310017China Hebei Provincial weather Modification Center Shijiazhuang 050020China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China National Meteorological Center Beijing 100081China School of Computer Science Chengdu University of Information TechnologyChengdu 610225China

As a natural disaster,extreme precipitation is among the most destructive and influential,but predicting its occurrence and evolution accurately is very challenging because of its rarity and *** the example of the“21·7”extreme precipitation event(17–21 July 2021)in Henan Province,this study explores the potential of using physics-guided machine learning to improve the accuracy of forecasting the intensity and location of extreme *** physics-guided ways of embedding physical features,fusing physical model forecasts and revised loss function are used,i.e.,(1)analyzing the anomalous circulation and thermodynamical factors,(2)analyzing the multi-model forecast bias and the associated underlying reasons for it,and(3)using professional forecasting knowledge to design the loss function,and the corresponding results are used as input for machine learning to improve the forecasting *** results indicate that by learning the relationship between anomalous physical features and heavy precipitation,the forecasting of precipitation intensity is improved significantly,but the location is rarely adjusted and more false alarms *** reasons for this are as *** anomalous features used here mainly contain information about large-scale systems and factors which are consistent with the model precipitation deviation;moreover,the samples of extreme precipitation are sparse and so the algorithm used here is ***,by combining“good and different”multi models with machine learning,the advantages of each model are extracted and then the location of the precipitation center in the forecast is improved ***,by combining the appropriate anomalous features with multi-model fusion,an integrated improvement of the forecast of the rainfall intensity and location is ***,this study is a novel exploration to improve the refined forecasting of heavy precipitation with extreme intensity and high variability,

关键词： Extreme precipitation event Refined assessment Anomalous physical features Multi-model fusion Machine learning

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The Observed Near-Surface Energy Exchange Processes over Arctic Glacier in Summer

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Journal of Meteorological research 2024年第3期38卷 600-607页

作者： Libo ZHOU Jinhuan ZHU Linlin KONG Peng LI Shupo MA Fei LI Han ZOU Meigen ZHANG Irina REPINA department of Lower Atmospheric Observation and research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China department of weather Forecast Aviation Meteorological Centre of Air Traffic Management BureauCivil Aviation Administration of ChinaBeijing100015China A.M.Obukhov Institute of Atmospheric Physics Russian Academy of Sciences(RAS)Moscow119017Russian Federation

Under Arctic warming,near-surface energy transfers have significantly changed,but few studies have focused on energy exchange over Arctic glacier due to limitations in available *** this study,the atmospheric energy exchange processes over the Arctic glacier surface were analyzed by using observational data obtained in summer 2019 in comparison with those over the Arctic tundra *** energy budget over the glacier greatly differed from that over the tundra,characterized by less net shortwave radiation and downward sensible heat flux,due to the high albedo and icy *** of the incoming solar radiation was injected into the glacier in summer,leading to snow ice *** the observation period,strong daily variations in near-surface heat transfer occurred over the Arctic glacier,with the maximum downward and upward heat fluxes occurring on 2 and 6 July 2019,*** analyses suggested that the maximum downward heat flux is mainly caused by the strong local thermal contrast above the glacier surface,while the maximum upward heat transfer cannot be explained by the classical turbulent heat transfer theory,possibly caused by countergradient heat *** results indicated that the near-surface energy exchange processes over Arctic glacier may be strongly related to local forcings,but a more in-depth investigation will be needed in the future when more observational data become available.

关键词： Arctic glacier tundra energy exchange processes

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