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Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023? 被引量:2
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作者 Fei ZHENG Shuai HU +17 位作者 jiehua ma Lin WANG Kexin LI Bo WU Qing BAO Jingbei PENG Chaofan LI Haifeng ZONG Yao YAO Baoqiang TIAN Hong CHEN Xianmei LANG Fangxing FAN Xiao DONG Yanling ZHAN Tao ZHU Tianjun ZHOU Jiang ZHU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第4期581-586,共6页
In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how th... In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter.In this report,as shown in the multi-model ensemble mean(MME)prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences,a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months,which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection,thus serving to modulate the winter climate in East Asia and North America.Despite some uncertainty due to unpredictable internal atmospheric variability,the global mean surface temperature(GMST)in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend.Specifically,the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter,and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991.Moreover,the necessary early warnings are still reliable in the timely updated mediumterm numerical weather forecasts and sub-seasonal-to-seasonal prediction. 展开更多
关键词 winter climate El Niño seasonal forecast GMST
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Predicting climate anomalies:A real challenge 被引量:2
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作者 Huijun Wang Yongjiu Dai +7 位作者 Song Yang Tim Li Jingjia Luo Bo Sun Mingkeng Duan jiehua ma Zhicong Yin Yanyan Huang 《Atmospheric and Oceanic Science Letters》 CSCD 2022年第1期2-11,共10页
In recent decades,the damage and economic losses caused by climate change and extreme climate events have been increasing rapidly.Although scientists all over the world have made great efforts to understand and predic... In recent decades,the damage and economic losses caused by climate change and extreme climate events have been increasing rapidly.Although scientists all over the world have made great efforts to understand and predict climatic variations,there are still several major problems for improving climate prediction.In 2020,the Center for Climate System Prediction Research(CCSP) was established with support from the National Natural Science Foundation of China.CCSP 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 prevention.In 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 prediction.CCSP will endeavor to tackle key scientific problems in these areas. 展开更多
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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Can Eurasia Experience a Cold Winter under a Third-Year La Nina in 2022/23? 被引量:1
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作者 Fei ZHENG Bo WU +13 位作者 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 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2023年第4期541-548,共8页
The Northern Hemisphere(NH)often experiences frequent cold air outbreaks and heavy snowfalls during La Nina winters.In 2022,a third-year La Nina event has exceeded both the oceanic and atmospheric thresholds since spr... The Northern Hemisphere(NH)often experiences frequent cold air outbreaks and heavy snowfalls during La Nina winters.In 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 2022.Under 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 NH.In 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 Nina.At 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 scale.However,how the future climate will evolve in the 2022/23 winter is still subject to some uncertainty,mostly in terms of unpredictable internal atmospheric variability.Consequently,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. 展开更多
关键词 Eurasian climate seasonal forecast La Nina winter cold climate
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Influence of Internal Decadal Variability on the Summer Rainfall in Eastern China as Simulated by CCSM4 被引量:7
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作者 Yali ZHU Tao WANG jiehua ma 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2016年第6期706-714,共9页
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 c... 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. 展开更多
关键词 Pacific Decadal Oscillation Atlantic Multidecadal Oscillation eastern China summer rainfall CCSM4
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Possible contribution of Arctic sea ice decline to intense warming over Siberia in June
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作者 Ying Zhang Mengqi Zhang +2 位作者 jiehua ma Dong Chen Tao Wang 《Atmospheric and Oceanic Science Letters》 CSCD 2022年第2期59-64,共6页
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 ecosystems.Based on observational data,th... 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 ecosystems.Based on observational data,this paper shows that there was an intense warming trend over Siberia(60°–75°N,70°–130°E)in June during 1979–2020.The 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 Pa.Increased 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 radiation.The Siberian warming is closely related to Arctic sea-ice decline,especially the sea ice over northern Barents Sea and Kara Sea.Numerical 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. 展开更多
关键词 Intense Siberian warming Arctic sea ice decline Surface radiation flux Turbulent heat flux
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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 被引量:2
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作者 Zhuolei QIAN jiehua ma Zhicong YIN 《Journal of Meteorological Research》 SCIE CSCD 2023年第2期248-261,共14页
Low temperature together with snow/freezing rain is disastrous in winter over southern China.Previous studies suggest that this is related to the sea surface temperature(SST)anomalies,especially La Nina conditions,ove... Low temperature together with snow/freezing rain is disastrous in winter over southern China.Previous 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 2020/2021.Is 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 of1978/1979–2017/2018.The results indicate that the CRSI weather with more CRSI days is featured with both decreased temperature and increased winter precipitation over southern China.The 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,respectively.The 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 China.Nevertheless,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 China.Given 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. 展开更多
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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The China Multi-Model Ensemble Prediction System and Its Application to Flood-Season Prediction in 2018 被引量:21
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作者 Hong-Li REN Yujie WU +9 位作者 Qing BAO jiehua ma Changzheng LIU Jianghua WAN Qiaoping LI Xiaofei WU Ying LIU Ben TIAN Joshua-Xiouhua FU Jianqi SUN 《Journal of Meteorological Research》 SCIE CSCD 2019年第3期540-552,共13页
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 ... 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, except that it predicted much more precipitation in the middle and lower reaches of the Yangtze River than observation. 展开更多
关键词 MULTI-MODEL ENSEMBLE China MULTI-MODEL ENSEMBLE PREDICTION system (CMME) real-time FORECAST SKILL assessment
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