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Quantitative estimation of global mean precipitation throughout the Phanerozoic era

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Science China Earth Sciences 2024年第5期67卷 1616-1624页

作者： Xiujuan BAO Yongyun HU Laboratory for Climate and Ocean-atmospheric Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China

Quantitatively estimating the global mean precipitation(GMP)throughout Earth's history is crucial for enhancing our understanding of long-term climate evolution and the hydrological ***,currently there is no established methodology for estimating global mean ***,we present the first study that estimates GMP in the Phanerozoic *** relationship between GMP and global mean surface temperature(GMST)is investigated by analyzing data from 23 models in the Coupled Model Intercomparison Project phase 6(CMIP6).The result reveals consistent and significant impact of temperature on precipitation,with a sensitivity range of 2–3%K^(-1).Additionally,we propose a method for accessing latitudinal variations in precipitation caused by land area distributions and paleo-Koppen climatic *** climatic belts are determined based on geological indicators such as coals,evaporites,and glacial *** GMP is thus quantitatively estimated by combining variations in GMST,land area distributions,and paleo-koppen climatic belts,spanning from 540 Ma to the present *** quantitative GMP curve demonstrates fluctuations in GMP about 500 mm yr^(-1),with values ranging from 948 to1442 mm yr-1over the Phanerozoic *** curve aligns closely with findings derived from numerical *** presented paleoprecipitation variations facilitate a more comprehensive understanding of the interconnected geological and paleoclimatic developments.

关键词： Paleoprecipitation Paleoclimate K?ppen climatic belts Global mean precipitation Hydrological cycle

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

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)

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

A deep learning-based global tropical cyclogenesis prediction model and its interpretability analysis

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Science China Earth Sciences 2024年

作者： Bin MU Xin WANG Shijin YUAN Yuxuan CHEN Guansong WANG Bo QIN Guanbo ZHOU School of Software Engineering Tongji University Department of atmospheric and oceanic Sciences & Institute of atmospheric Sciences Fudan University national Meteorological Center Shanghai Typhoon Institute China Meteorological Administration

Tropical cloud clusters (TCCs) can potentially develop into tropical cyclones (TCs),leading to significant casualties and economic *** prediction of tropical cyclogenesis (TCG) is crucial for early *** traditional deep learning methods applied to TCG prediction rely on predictors from a single time point,neglect the ocean-atmosphere interactions,and exhibit low model *** study proposes the Tropical Cyclogenesis Prediction-Net (TCGP-Net) based on the Swin Transformer,which leverages convolutional operations and attention mechanisms to encode spatiotemporal features and capture the temporal evolution of *** model incorporates the coupled ocean-atmosphere interactions,including multiple variables such as sea surface ***,causal inference and integrated gradients are employed to validate the effectiveness of the predictors and provide an interpretability analysis of the model’s decision-making *** model is trained using GridSat satellite data and ERA5 reanalysis *** results demonstrate that TCGP-Net achieves high accuracy and stability,with a detection rate of 97.9%and a false alarm rate of 2.2%for predicting TCG 24 hours in advance,significantly outperforming existing *** indicates that TCGP-Net is a reliable tool for tropical cyclogenesis prediction.

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A Tri-mode of Mock-Walker Cells

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Advances in atmospheric Sciences 2024年第4期41卷 671-679页

作者： Han QIN Ji NIE Zhiyong MENG Laboratory for Climate and Ocean-Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China China Meteorological administration Tornado Key Laboratory Foshan 528061China

This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a single peak of precipitation over the SST maximum(mode 1),symmetric double peaks of precipitation straddling the SST maximum(mode 2),and a single peak of precipitation on one side of the SST maximum(mode 3).The three modes are caused by three distinct convective activity center migration *** indicate that the virtual effect of water vapor plays an important role in differentiating the three *** the SST gradient is large,the virtual effect may be strong enough to overcome the temperature effect,generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the *** results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.

关键词： Walker circulation cloud-resolving simulation virtual effect

Roles of Upper-Level Descending Inflow in Moat Development in Simulated Tropical Cyclones with Secondary Eyewall Formation

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Advances in atmospheric Sciences 2024年第6期41卷 1100-1114页

作者： Nannan QIN Liguang WU Nanjing Joint Institute for atmospheric Sciences Nanjing 210041China Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030China Department of atmospheric and oceanic Sciences and Institute of atmospheric Sciences Fudan UniversityShanghai 200438China Innovation Center of Ocean and Atmosphere System Zhuhai Fudan Innovation Research InstituteZhuhai 518057China

This study investigated the effects of upper-level descending inflow(ULDI)associated with inner-eyewall convection on the formation of the moat in tropical cyclones(TCs)with secondary eyewall formation(SEF).In our numerical experiments,a clear moat with SEF occurred in TCs with a significant ULDI,while no SEF occurred in TCs without a significant *** eyewall convection developed more vigorously in the control run.A ULDI occurred outside the inner-eyewall convection,where it was symmetrically *** ULDI was initially triggered by the diabatic warming released by the inner eyewall and later enhanced by the cooling below the anvil *** ULDI penetrated the outer edge of the inner eyewall with relatively dry air and prevented excessive solid-phase hydrometeors from being advected further *** produced extensive sublimation cooling of falling hydrometeors between the eyewall and the outer *** sublimation cooling resulted in negative buoyancy and further induced strong subsidence between the eyewall and the outer *** a result,a clear moat was *** of the moat in the ongoing SEF prevented the outer rainband from moving farther inward,helping the outer rainband to symmetrize into an outer *** the sensitivity experiment,no significant ULDI formed since the eyewall convection was weaker,and the eyewall anvil developed relatively lower,meaning the formation of a moat and thus an outer eyewall was less *** study suggests that a better-represented simulation of inner-eyewall convective structures and distribution of the solid-phase hydrometeors is important to the prediction of SEF.

关键词： tropical cyclone secondary eyewall formation upper-level descending inflow eyewall convection

Improving the Forecasts of Coastal Wind Speeds in Tianjin,China Based on the WRF Model with Machine Learning Algorithms

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Journal of Meteorological Research 2024年第3期38卷 570-585页

作者： Weihang ZHANG Meng TIAN Shangfei HAI Fei WANG Xiadong AN Wanju LI Xiaodong LI Lifang SHENG College of oceanic and atmospheric Sciences Ocean University of ChinaQingdao266100China Tianjin Key Laboratory for oceanic Meteorology Tianjin Institute of Meteorological ScienceTianjin300074China CMA Earth System Modeling and Prediction Centre China Meteorological Administration(CMA)Beijing100081China Qingdao Meteorological Bureau Qingdao266003China

Characterized by sudden changes in strength,complex influencing factors,and significant impacts,the wind speed in the circum-Bohai Sea area is relatively challenging to *** the western side of Bohai Bay,as the economic center of the circum-Bohai Sea,Tianjin exhibits a high demand for accurate wind *** this study,three machine learning algorithms were employed and compared as post-processing methods to correct wind speed forecasts by the Weather Research and Forecast(WRF)model for *** results showed that the random forest(RF)achieved better performance in improving the forecasts because it substantially reduced the model bias at a lower computing cost,while the support vector machine(SVM)performed slightly worse(especially for stronger winds),but it required an approximately 15 times longer computing *** back propagation(BP)neural network produced an average forecast significantly closer to the observed forecast but insufficiently reduced the *** regard to wind speed frequency forecasting,the RF method commendably corrected the forecasts of the frequency of moderate(force 3)wind speeds,while the BP method showed a desirable capability for correcting the forecasts of stronger(force>6)*** addition,the 10-m u and v components of wind(u_(10)and v_(10)),2-m relative humidity(RH_(2))and temperature(T_(2)),925-hPa u(u925),sea level pressure(SLP),and 500-hPa temperature(T_(500))were identified as the main factors leading to bias in wind speed forecasting by the WRF model in Tianjin,indicating the importance of local dynamical/thermodynamic processes in regulating the wind *** study demonstrates that the combination of numerical models and machine learning techniques has important implications for refined local wind forecasting.

关键词： machine learning Weather Research and Forecast(WRF)model wind speed forecasting coastal region

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