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Impacts of the SSTs over Equatorial Central–Eastern Pacific and Southeastern Indian Ocean on the Cold and Rainy/Snowy/Icy Weather in Southern China

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Journal of Meteorological Research 2023年第2期37卷 248-261页

作者： Zhuolei QIAN jiehua ma Zhicong YIN Shaoxing Meteorological Office Shaoxing312000 Key Laboratory of Meteorological Disaster(KLME) Ministry of Education&Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044 Climate Change Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029 Nansen–Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029 Southern marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai519000

Low temperature together with snow/freezing rain is disastrous in winter over southern *** studies suggest that this is related to the sea surface temperature(SST)anomalies,especially La Nina conditions,over the equatorial central–eastern Pacific Ocean(EP).In reality,however,La Nina episodes are not always accompanied by rainy/snowy/icy(CRSI)days in southern China,such as the case in winter 2020/*** there any other factor that works jointly with the EP SST to affect the winter CRSI weather in southern China?To address this question,CRSI days are defined and calculated based on station observation data,and the related SST anomalies and atmospheric circulations are examined based on the Hadley Centre SST data and the NCEP/NCAR reanalysis data for winters of1978/1979–2017/*** results indicate that the CRSI weather with more CRSI days is featured with both decreased temperature and increased winter precipitation over southern *** SSTs over both the EP and the southeastern Indian Ocean(SIO)are closely related to the CRSI days in southern China with correlation coefficients of-0.29 and 0.39,significant at the 90%and 95%confidence levels,*** SST over EP affects significantly air temperature,as revealed by previous studies,with cooler EP closely related to the deepened East Asian trough,which benefits stronger East Asian winter monsoon(EAWM)and lower air temperature in southern ***,this paper discovers that the SST over SIO affects precipitation of southern China,with a correlation coefficient of 0.42,significant at the 99%confidence level,with warmer SIO correlated with deepened southern branch trough(SBT)and strengthened western North Pacific anomalous anticyclone(WNPAC),favoring more water vapor convergence and enhanced precipitation in southern *** presence of La Ni?a in both winters,compared to the winter of 2020/2021,the winter of 2021/2022 witnessed more CRSI days,perhaps due to the warmer SIO.

关键词： the cold and rainy/snowy/icy(CRSI)days sea surface temperature(SST)anomalies equatorial central–eastern Pacific Ocean(EP) southeastern Indian Ocean(SIO)

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Influence of Internal Decadal Variability on the Summer Rainfall in Eastern China as Simulated by CCSM4

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Advances in Atmospheric Sciences 2016年第6期33卷 706-714页

作者： Yali ZHU Tao WANG jiehua ma Nansen-Zhu International Research Centre Chinese Academy of Sciences Climate Change Research Centre Chinese Academy of Sciences

The combined impact of the Pacific Decadal Oscillation （PDO） and Atlantic Multidecadal Oscillation （AMO） on the summer rainfall in eastern China was investigated using CCSM4. The strongest signals occur with the combination of a positive PDO and a negative AMO （＋PDO- AMO）, as well as a negative PDO and a positive AMO （-PDO ＋ AMO）. For the ＋PDO- AMO set, significant positive rainfall anomalies occur over the lower reaches of the Yangtze River valley （YR）, when the East Asian summer monsoon becomes weaker, while the East Asian westerly jet stream becomes stronger, and ascending motion over the YR becomes enhanced due to the jet-related secondary circulation. Contrary anomalies occur over East Asia for the -PDO ＋ AMO set. The influence of these two combinations of PDO and AMO on the summer rainfall in eastern China can also be observed in the two interdecadal rainfall changes in eastern China in the late 1970s and late 1990s.

关键词： Pacific Decadal Oscillation Atlantic Multidecadal Oscillation eastern China summer rainfall CCSM4

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Dynamic Downscaling of Summer Precipitation Prediction over China in 1998 Using WRF and CCSM4

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Advances in Atmospheric Sciences 2015年第5期32卷 577-584页

作者： ma jiehua WANG Huijun FAN Ke Climate Change Research Center Chinese Academy of Sciences Nansen-Zhu International Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science & Technology

To study the prediction of the anomalous precipitation and general circulation for the summer（June–July–August） of1998, the Community Climate System Model Version 4.0（CCSM4.0） integrations were used to drive version 3.2 of the Weather Research and Forecasting（WRF3.2） regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model,but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.

关键词： seasonal climate prediction dynamic downscaling summer precipitation CCSM4 WRF

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Will boreal winter precipitation over China increase in the future? An AGCM simulation under summer “ice-free Arctic” conditions

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Chinese Science Bulletin 2012年第8期57卷 921-926页

作者： ma jiehua WANG HuiJun ZHANG Yin Nansen-Zhu International Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Climate Change Research Center Chinese Academy of SciencesBeijing 100029China Graduate University of Chinese Academy of Sciences Beijing 100049China

Frequent winter snowstorms have recently caused large economic losses and attracted wide *** snowstorms have raised an important scientific *** scenarios of future global warming,will winter precipitation in China increase significantly and produce more snow in the north? Using Coupled Model Intercomparison Project phase 3 (CMIP 3) model projections under the Special Report on Emissions Scenario A1B scenario,we generated a possible future Arctic condition,the summer (September) "ice-free Arctic" *** then used corresponding monthly sea surface temperature (SST) values and a set of CO 2 concentrations to drive an atmospheric general circulation model (AGCM),for simulating East Asian climate *** experimental results show that during the boreal winter (December-January-February;DJF),global surface air temperature would increase significantly under this scenario,producing substantial warming in Arctic regions and at high latitudes in Asia and North *** Siberian High,Aleutian Low and East Asian winter monsoon would all ***,because of increased transport of water vapor to China from the north,winter precipitation would increase from south to *** addition,the significant increase in winter temperature might cause fewer cold surges.

关键词：大气环流模式冬季降水中国北方北极地区模式模拟夏季东亚冬季风二氧化碳浓度

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Possible contribution of Arctic sea ice decline to intense warming over Siberia in June

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Atmospheric and Oceanic Science Letters 2022年第2期15卷 59-64页

作者： Ying Zhang Mengqi Zhang jiehua ma Dong Chen Tao Wang Climate Change Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina Nansen-Zhu International Research Center Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science&TechnologyNanjingChina

Siberia experienced intense heat waves in 2020,and this unusual warming may have caused more wildfires and losses of permafrost than normal,both of which can be devastating to *** on observational data,this paper shows that there was an intense warming trend over Siberia(60°–75°N,70°–130°E)in June during 1979–*** linear trend of the June surface air temperature is 0.90℃/10 yr over Siberia,which is much larger than the area with the same latitudes(60°–75°N,0°–360°,trend of 0.46℃/10 yr).The warming over Siberia extends from the surface to about 300 h *** geopotential height in the mid-to-upper troposphere plays an important role in shaping the Siberian warming,which favors more shortwave radiation reaching the surface and further heating the overlying atmosphere via upward turbulent heat flux and longwave *** Siberian warming is closely related to Arctic sea-ice decline,especially the sea ice over northern Barents Sea and Kara *** experiments carried out using and atmospheric general circulation model(IAP-AGCM4.1)confirmed the contribution of the Arctic sea-ice decline to the Siberian warming and the related changes in circulations and surface fluxes.

关键词： Intense Siberian warming Arctic sea ice decline Surface radiation flux Turbulent heat flux

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Design and testing of a global climate prediction system based on a coupled climate model

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Science China Earth Sciences 2014年第8期57卷 2417-2427页

作者： ma jiehua WANG HuiJun Climate Change Research Center Chinese Academy of Sciences Nansen-Zhu International Research Center Institute of Atmospheric Physics Chinese Academy of Sciences

A global climate prediction system （PCCSM4） was developed based on the Community Climate System Model, version 4.0, developed by the National Center for Atmospheric Research （NCAR）, and an initialization scheme was designed by our group. Thirty-year （1981-2010） one-month-lead retrospective summer climate ensemble predictions were carded out and analyzed. The results showed that PCCSM4 can efficiently capture the main characteristics of JJA mean sea surface temperature （SST）, sea level pressure （SLP）, and precipitation. The prediction skill for SST is high, especially over the central and eastern Pacific where the influence of E1 Nino-Southem Oscillation （ENSO） is dominant. Temporal correlation coefficients between the pre- dicted Nino3.4 index and observed Nino3.4 index over the 30 years reach 0.7, exceeding the 99% statistical significance level. The prediction of 500-hPa geopotential height, 850-hPa zonal wind and SLP shows greater skill than for precipitation. Overall, the predictability in PCCSM4 is much higher in the tropics than in global terms, or over East Asia. Furthermore, PCCSM4 can simulate the summer climate in typical ENSO years and the interannual variability of the Asian summer monsoon well. These preliminary results suggest that PCCSM4 can be applied to real-time prediction after further testing and improvement.

关键词： climate model climate prediction ENSO monsoon

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Predicting climate anomalies:A real challenge

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Atmospheric and Oceanic Science Letters 2022年第1期15卷 2-11页

作者： Huijun Wang Yongjiu Dai Song Yang Tim Li Jingjia Luo Bo Sun Mingkeng Duan jiehua ma Zhicong Yin Yanyan Huang Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of EducationNanjing University of Information Science and TechnologyNanjingChina School of Atmospheric Sciences Sun Yat-sen University&Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)ZhuhaiChina International Pacific Research Center and Department of Atmospheric Sciences School of Ocean and Earth Science and TechnologyUniversity of Hawaii at ManoaHonoluluUSA Nansen‐Zhu International Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina Climate Change Research Center Chinese Academy of SciencesBeijingChina

In recent decades,the damage and economic losses caused by climate change and extreme climate events have been increasing *** scientists all over the world have made great efforts to understand and predict climatic variations,there are still several major problems for improving climate *** 2020,the Center for Climate System Prediction Research(CCSP) was established with support from the National Natural Science Foundation of *** aims to tackle three scientific problems related to climate prediction—namely,El Ni?o-Southern Oscillation(ENSO) prediction,extended-range weather forecasting,and interannual-to-decadal climate prediction—and hence provide a solid scientific basis for more reliable climate predictions and disaster *** this paper,the major objectives and scientific challenges of CCSP are reported,along with related achievements of its research groups in monsoon dynamics,land-atmosphere interaction and model development,ENSO variability,intraseasonal oscillation,and climate *** will endeavor to tackle key scientific problems in these areas.

关键词： Center for climate system prediction research(CCSP) Monsoon dynamics Land surface model ENSO dynamics Extended-range forecasting Interannual-to-decadal prediction

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The China Multi-Model Ensemble Prediction System and Its Application to Flood-Season Prediction in 2018

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Journal of Meteorological Research 2019年第3期33卷 540-552页

作者： Hong-Li REN Yujie WU Qing BAO jiehua ma Changzheng LIU Jianghua WAN Qiaoping LI Xiaofei WU Ying LIU Ben TIAN Joshua-Xiouhua FU Jianqi SUN Laboratory for Climate Studies & China Meteorological Administration-Nanjing University Joint Laboratory for Climate Prediction Studies National Climate Center China Meteorological Administration Beijing 100081 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 National Climate Center China Meteorological Administration Beijing 100081 School of Atmospheric Sciences/Plateau Atmosphere and Environment Key Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu 610225 Institute of Atmospheric Sciences Fudan University Shanghai 200433

Multi-model ensemble prediction is an effective approach for improving the prediction skill short-term climate prediction and evaluating related uncertainties. Based on a combination of localized operation outputs of Chinese climate models and imported forecast data of some international operational models, the National Climate Center of the China Meteorological Administration has established the China multi-model ensemble prediction system version 1.0 (CMMEv1.0) for monthly-seasonal prediction of primary climate variability modes and climate elements. We verified the real-time forecasts of CMMEv1.0 for the 2018 flood season (June-August) starting from march 2018 and evaluated the 1991-2016 hindcasts of CMMEv1.0. The results show that CMMEv1.0 has a significantly high prediction skill for global sea surface temperature (SST) anomalies, especially for the El Nino-Southern Oscillation (ENSO) in the tropical central-eastern Pacific. Additionally, its prediction skill for the North Atlantic SST triple (NAST) mode is high, but is relatively low for the Indian Ocean Dipole (IOD) mode. Moreover, CMMEv1.0 has high skills in predicting the western Pacific subtropical high (WPSH) and East Asian summer monsoon (EASM) in the June-July-August (JJA) season. The JJA air temperature in the CMMEv1.0 is predicted with a fairly high skill in most regions of China, while the JJA precipitation exhibits some skills only in northwestern and eastern China. For real-time forecasts in march-August 2018, CMMEv1.0 has accurately predicted the ENSO phase transition from cold to neutral in the tropical central-eastern Pacific and captures evolutions of the NAST and IOD indices in general. The system has also captured the main features of the summer WPSH and EASM indices in 2018, except that the predicted EASM is slightly weaker than the observed. Furthermore, CMMEv1.0 has also successfully predicted warmer air temperatures in northern China and captured the primary rainbelt over northern China,

关键词： multi-model ensemble China multi-model ensemble prediction system (CMME) real-time forecast skill assessment

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清末四川新式高等体育教育研究

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成都体育学院学报 2024年第3期50卷 118-126页

作者：马杰华成都体育学院体育教育学院四川成都610041

清末四川新式高等体育教育展示了封闭的中国西部内陆省份教育走向近代化转型的一个“面相”。文章对清末四川教育转型之高等体育教育的兴起与发展进行考证研究,有助于拓展我国体育学的研究深度与广度。研究得出清末四川高等学堂(校)办... 详细信息

清末四川新式高等体育教育展示了封闭的中国西部内陆省份教育走向近代化转型的一个“面相”。文章对清末四川教育转型之高等体育教育的兴起与发展进行考证研究,有助于拓展我国体育学的研究深度与广度。研究得出清末四川高等学堂(校)办学性质多元;新式高等学堂(校)无论是在数量上还是体育的开办时间上都走在了同时期全国的前列;近代四川高等体育教育始于1896年创办的官立新式学堂—四川中西学堂,之后其他高等学堂普遍开始实行普通体操与兵式体操教育;1906年四川开办了培养体育专门人才的体育科,制定了专门的体育教育规范与以西方分科知识为基础的体育课程体系,该体育学堂培养了开国元勋朱德总司令等一批优秀学生;同时期四川还有一所直接由西方人创办的华西协合大学,该校于创办之初的1910年便开设了体育课程,其校园体育文化特色引领了中国西部近代体育之风尚,在全国享有较高的知名度。

关键词：清末四川高等学堂高等教育体育教育体育活动

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Can Eurasia Experience a Cold Winter under a Third-Year La Nina in 2022/23?

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Advances in Atmospheric Sciences 2023年第4期40卷 541-548页

作者： Fei ZHENG Bo WU Lin WANG Jingbei PENG Yao YAO Haifeng ZONG Qing BAO jiehua ma Shuai HU Haolan REN Tingwei CAO Renping LIN Xianghui FANG Lingjiang TAO Tianjun ZHOU Jiang ZHU International Center for Climate and Environment Science(ICCES) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Center for Monsoon System Research(CMSR) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China CAS Key Lab of Regional Climate-Environment for Temperate East Asia(RCE-TEA) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Nansen-Zhu International Research Centre(NZC) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Cma Earth System Modeling and Prediction Center Beijing 100081China Department of Atmospheric and Oceanic Sciences&Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China

The Northern Hemisphere(NH)often experiences frequent cold air outbreaks and heavy snowfalls during La Nina *** 2022,a third-year La Nina event has exceeded both the oceanic and atmospheric thresholds since spring and is predicted to reach its mature phase in December *** such a significant global climate signal,whether the Eurasian Continent will experience a tough cold winter should not be assumed,despite the direct influence of mid-to high-latitude,large-scale atmospheric circulations upon frequent Eurasian cold extremes,whose teleconnection physically operates by favoring Arctic air invasions into Eurasia as a consequence of the reduction of the meridional background temperature gradient in the *** the 2022/23 winter,as indicated by the seasonal predictions from various climate models and statistical approaches developed at the Institute of Atmospheric Physics,abnormal warming will very likely cover most parts of Europe under the control of the North Atlantic Oscillation and the anomalous anticyclone near the Ural Mountains,despite the cooling effects of La *** the same time,the possibility of frequent cold conditions in mid-latitude Asia is also recognized for this upcoming winter,in accordance with the tendency for cold air invasions to be triggered by the synergistic effect of a warm Arctic and a cold tropical Pacific on the hemispheric ***,how the future climate will evolve in the 2022/23 winter is still subject to some uncertainty,mostly in terms of unpredictable internal atmospheric ***,the status of the mid-to high-latitude atmospheric circulation should be timely updated by medium-term numerical weather forecasts and sub-seasonal-to-seasonal prediction for the necessary date information and early warnings.

关键词： Eurasian climate seasonal forecast La Nina winter cold climate

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