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Another Record: Ocean Warming Continues through 2.2. despite La Nina Conditions

Advances in atmospheric sciences 2022年第3期39卷 373-385页

作者： Lijing CHENG John ABRAHAM kevin ETRENBERTH John FASULLO Tim BOYER Michael EMANN Jiang zhu {2. wang Ricardo LOCARNINI Yuanlong LI Bin ZHANG Zhetao TAN Fujiang YU Liying WAN Xingrong CHEN Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Viktor GOURETSKI Gengxin CHEN Alexey MISHONOV Jim REAGAN international center for Climate and Environment {2. Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China University of St.Thomas School of EngineeringMinnesota 55105USA National center for atmospheric {2. BoulderColorado 80307USA National Oceanic and atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA Department of Meteorology&atmospheric Science The Pennsylvania State UniversityUniversity ParkPennsylvania 16802USA institute of Oceanology Chinese Academy of SciencesQingdao 266071China National Marine Environmental Forecasting center Ministry of Natural Resources of ChinaBeijing 100081China College of Oceanography Hohai UniversityNanjing 210098China National Marine Data and Information Service Tianjin 300171China Italian National Agency for New Technologies Energy and Sustainable Economic DevelopmentS.Teresa Research CenterLerici 19032Italy Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South china Sea institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMD 20742USA

The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate system and increases ocean heat content(OHC). Here, we provide the first analysis of recent OHC changes through 2.2. from two international groups. The world ocean, in 2.2., was the hottest ever recorded by humans, and the 2.2. annual OHC value is even higher than last year’s record value by 14 ± 11 ZJ(1 zetta J = 102. J) using the IAP/CAS dataset and by16 ± 10 ZJ using NCEI/NOAA dataset. The long-term ocean warming is larger in the Atlantic and Southern Oceans than in other regions and is mainly attributed, via climate model simulations, to an increase in anthropogenic greenhouse gas concentrations. The year-to-year variation of OHC is primarily tied to the El Nino-Southern Oscillation(ENSO). In the seven maritime domains of the Indian, Tropical Atlantic, North Atlantic, Northwest Pacific, North Pacific, Southern oceans,and the Mediterranean Sea, robust warming is observed but with distinct inter-annual to decadal variability. Four out of seven domains showed record-high heat content in 2.2.. The anomalous global and regional ocean warming established in this study should be incorporated into climate risk assessments, adaptation, and mitigation.

关键词： La Nina ocean heat ocean warming attribution observation

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基于年际增量方法的云南省普洱雨季开始期气候预测

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大气科学学报 2019年第6期42卷 801-813页

作者：王秀英田宝强范可普洱市气象局云南普洱665000 中国科学院大气物理研究所竺可桢-南森国际研究中心北京100029 南京信息工程大学气象灾害预报预警与评估协同创新中心江苏南京210044 中国科学院大学北京100049

基于普洱雨季开始期年际增量变化规律和影响雨季开始期的环流形势及物理过程,采用年际增量方法和多元线性回归分析方法,选取5个具有物理意义的预测因子(包括前期1月南半球绕极环流、前期2.南太平洋高压、前期4月孟加拉湾至南海海平面... 详细信息

基于普洱雨季开始期年际增量变化规律和影响雨季开始期的环流形势及物理过程,采用年际增量方法和多元线性回归分析方法,选取5个具有物理意义的预测因子(包括前期1月南半球绕极环流、前期2.南太平洋高压、前期4月孟加拉湾至南海海平面气压、前期冬季加拿大北部海冰和前期冬季伊朗高原积雪深度),建立了普洱雨季开始期的预测模型,并对预测模型进行1967-2.17年的交叉检验和1998-2.17年的逐年独立样本检验。交叉检验中,雨季开始期预测值和观测值年际增量的相关系数为0.84,相对均方根误差为2.%;独立样本检验中,雨季开始期年际增量的相对均方根误差为15%,模型对雨季开始期异常年份的预测误差小于7 d,表明该预测模型能很好再现1967-2.17年雨季开始期的变化趋势。

关键词：年际增量方法云南普洱雨季开始期气候预测

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Another Year of Record Heat for the Oceans

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Advances in atmospheric sciences 2023年第6期40卷 963-974页

作者： Lijing CHENG John ABRAHAM kevin ETRENBERTH John FASULLO Tim BOYER Michael EMANN Jiang zhu {2. wang Ricardo LOCARNINI Yuanlong LI Bin ZHANG Fujiang YU Liying WAN Xingrong CHEN Licheng Feng Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Viktor GOURETSKI Gengxin CHEN Alexey MISHONOV Jim REAGAN Guancheng LI international center for Climate and Environment {2. Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China University of St.Thomas School of EngineeringMinnesota 55105USA National center for atmospheric {2. BoulderColorado 80307USA University of Auckland AucklandNew Zealand National Oceanic and atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA Department of Earth and Environmental Science University of PennsylvaniaPhiladelphiaPennsylvania 19104USA institute of Oceanology Chinese Academy of SciencesQingdao 266071China National Marine Environmental Forecasting center Ministry of Natural Resources of ChinaBeijing 100081China College of Oceanography Hohai UniversityNanjing 210098China National Marine Data and Information Service Tianjin 300171China Italian National Agency for New Technologies Energy and Sustainable Economic DevelopmentS.Teresa Research CenterLerici 19032Italy Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South china Sea institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMDCollege ParkMaryland 20740USA Eco-Environmental Monitoring and research center Pearl River Valley and South China Sea Ecology and Environment AdministrationMinistry of Ecology and EnvironmentPRCGuangzhou 510611China

Changes in ocean heat content(OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2.2., the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2.2. record *** to IAP/CAS data, the 0–2.00 m OHC in 2.2. exceeded that of 2.2. by 10.9 ± 8.3 ZJ(1 Zetta Joules = 102.Joules);and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins(the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier–fresh gets fresher” pattern, also reached its highest level on record in 2.2.,implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2.2. were dominated by a strong La Ni?a event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2.2..

关键词： ocean heat content salinity stratification global warming climate

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滑坡泥石流大尺度统计预报模型的实时检验

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大气科学学报 2019年第1期42卷 78-92页

作者：何爽爽汪君王会军中国科学院大气物理研究所竺可桢-南森国际研究中心北京100029 中国科学院大学北京100049 南京信息工程大学气象灾害预报预警与评估协同创新中心江苏南京210044 南京信息工程大学气象灾害教育部重点实验室江苏南京210044

利用滑坡敏感性分布和降雨阈值公式建立了一个滑坡泥石流统计模型,该模型可以用于中国大尺度范围内的滑坡泥石流预警。使用CMORPH卫星降水驱动该统计模型,对2.16—2.17年的106起滑坡泥石流事件进行了验证分析。结果表明,该模型能较好地... 详细信息

利用滑坡敏感性分布和降雨阈值公式建立了一个滑坡泥石流统计模型,该模型可以用于中国大尺度范围内的滑坡泥石流预警。使用CMORPH卫星降水驱动该统计模型,对2.16—2.17年的106起滑坡泥石流事件进行了验证分析。结果表明,该模型能较好地预警大多数滑坡泥石流事件,其中对72. 1%的雨季滑坡泥石流事件能较好预警,但对非雨季的事件只有35%能较好预警,对雨季的预警效果明显优于非雨季。由于滑坡泥石流主要发生在雨季,因此该模型总体上具有较好的效能。该模型对于强降雨引发的快速滑坡事件具有较好的预警能力,但对于由强度较小、持续时间较长的降雨引发的慢过程滑坡事件的预警效果有待提升。利用该统计模型以及CMORPH实时卫星降水产品,可以建立滑坡泥石流大尺度实时预警系统,对滑坡泥石流减灾防灾具有一定意义。

关键词：滑坡泥石流统计模型 CMOPRH卫星降水

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太平洋年代际振荡的年代际预测方法

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气象学报 2020年第2期78卷 177-186页

作者：黄艳艳王会军南京信息工程大学气象灾害预报预警与评估协同创新中心南京210044 中国科学院大气物理研究所竺可桢-南森国际研究中心北京100029

太平洋年代际振荡(PDO)是北太平洋海表温度年代际变率的主模态。由于太平洋年代际振荡对区域乃至全球气候的显著影响,其合理的预测结果可以带来多方面收益。然而,针对太平洋年代际振荡及其有关的海表温度的年代际预测,目前气候模式的预... 详细信息

太平洋年代际振荡(PDO)是北太平洋海表温度年代际变率的主模态。由于太平洋年代际振荡对区域乃至全球气候的显著影响,其合理的预测结果可以带来多方面收益。然而,针对太平洋年代际振荡及其有关的海表温度的年代际预测,目前气候模式的预测水平还十分有限,因此,提出了一个新的增量方法。一系列的验证结果表明,增量方法可以有效预测太平洋年代际振荡,其中包括成功预测出其振荡的年代际转折。增量方法的预测过程主要包括3个步骤:(1)采用5 a滑动平均得到太平洋年代际振荡的年代际变率;(2.利用3 a增量形式的预测因子构建预测模型,预测3 a增量的太平洋年代际振荡(DI_PDO);(3)将预测得到的DI_PDO加上3 a前的观测PDO,得到最后预测的PDO。增量方法亦可以应用到气候系统年代际内部变率的其他模态(如:北大西洋年代际振荡)和其他气候变量的年代际预测(如:海表温度)。

关键词：太平洋年代际振荡年代际预测增量方法

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2.00年后中国北方东部地区夏季极端降水减少及水汽输送特征

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大气科学 2019年第5期43卷 1109-1124页

作者：李湘瑞范可徐志清中国科学院大气物理研究所竺可桢—南森国际研究中心北京100029 中国科学院大学北京100049

本文研究了1961~2.16年中国北方东部地区夏季极端降水日数和极端降水贡献率的年代际变化特征,并进一步分析了该地区极端降水和普通降水的大气环流和水汽输送的差异。主要的研究结果表明:1961~2.16年中国北方东部地区夏季极端降水日数和... 详细信息

本文研究了1961~2.16年中国北方东部地区夏季极端降水日数和极端降水贡献率的年代际变化特征,并进一步分析了该地区极端降水和普通降水的大气环流和水汽输送的差异。主要的研究结果表明:1961~2.16年中国北方东部地区夏季极端降水日数和极端降水贡献率在2.00年前后发生显著年代际变化,2.00年后夏季极端降水天数和极端降水贡献率显著减少。与1984~1999年相比,2.00~2.16年在对流层高层从欧洲大陆、中亚到东北—蒙古地区,位势高度异常呈现出'正—负—正'的大气波列,从而造成北方东部地区上空为正压的位势高度正异常控制,伴随着下沉运动,大气层结趋于稳定,这些环流条件不利于极端降水发生。2.00年后负位相的太平洋年代际振荡(PDO)和正位相的北大西洋多年代际振荡(AMO)共同加强了北方东部地区上空的正位势高度异常。进一步研究表明,极端降水与普通降水的水汽输送和收支以及关键的局地大气系统存在着显著差异,较普通降水而言,极端降水在南北向水汽输送和收支上更强;北方东部地区低空为较强的闭合低压控制,并不断受到高层高位涡空气下传的影响。

关键词：中国北方东部极端降水日数极端降水贡献率水汽输送年代际变化

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Homogenization of the Daily Land Surface Temperature over the Mainland of china from 1960 through 2.17

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Advances in atmospheric sciences 2021年第11期38卷 1811-1822页

作者： Dan wang Aihui wang Xianghui KONG nansen-zhu {2. {2. center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of chinese academy of sciences Beijing 100029China

Land surface temperature(LST)is one of the most important factors in the land-atmosphere interaction *** measured LSTs may contain biases due to instrument replacement,changes in recording procedures,and other non-climatic *** study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over china using 2.60 stations from 1960 through *** high-quality land surface air temperature(LSAT)dataset is used to correct the LST warming biases especially evident during cold months in regions north of 40ºN due to the replacement of observation instruments around ***,the Multiple Analysis of Series for Homogenization(MASH)method is adopted to detect and then adjust the daily observed LST *** total,3.68×10^(3) effective breakpoints in 1.65×106 monthly records(about 2.%)are detected.A large number of these effective breakpoints are located over large parts of the Sichuan Basin and southern *** the MASH procedure,LSTs at more than 80%of the breakpoints are adjusted within+/-0.5℃,and of the remaining breakpoints,only 10%are adjusted over 1.5℃.Compared to the raw LST dataset over the whole domain,the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most ***,we perform preliminary analysis upon the homogenized LST and find that the annual mean LST averaged across china shows a significant warming trend[0.2.℃(10 yr)^(-1)].The homogenized LST dataset can be further adapted for a variety of applications(e.g.,model evaluation and extreme event characterization).

关键词： land surface temperature(LST) daily observation homogenization MASH method variability

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Assessment of Temperature Extremes in china Using RegCM4 and WRF

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Advances in atmospheric sciences 2019年第4期36卷 363-377页

作者： Xianghui KONG Aihui wang Xunqiang BI Dan wang nansen-zhu {2. {2. Centre Institute of Atmospheric PhysicsChinese Academy of Sciences Climate Change research center Institute of Atmospheric PhysicsChinese Academy of Sciences

This study assesses the performance of temperature extremes over china in two regional climate models(RCMs),RegCM4 and WRF, driven by the ECMWF's 2. th century reanalysis. Based on the advice of the Expert Team on Climate Change Detection and Indices(ETCCDI), 12.extreme temperature indices(i.e., TXx, TXn, TNx, TNn, TX90 p, TN90 p,TX10 p, TN10 p WSDI, ID, FD, and CSDI) are derived from the simulations of two RCMs and compared with those from the daily station-based observational data for the period 1981–2.10. Overall, the two RCMs demonstrate satisfactory capability in representing the spatiotemporal distribution of the extreme indices over most regions. RegCM performs better than WRF in reproducing the mean temperature extremes, especially over the Tibetan Plateau(TP). Moreover, both models capture well the decreasing trends in ID, FD, CSDI, TX10 p, and TN10 p, and the increasing trends in TXx, TXn, TNx, TNn, WSDI, TX90 p,and TN90 p, over china. Compared with observation, RegCM tends to underestimate the trends of temperature extremes,while WRF tends to overestimate them over the TP. For instance, the linear trends of TXx over the TP from observation,RegCM, and WRF are 0.53?C(10 yr)^(-1), 0.44?C(10 yr)^(-1), and 0.75?C(10 yr)^(-1), respectively. However, WRF performs better than RegCM in reproducing the interannual variability of the extreme-temperature indices. Our findings are helpful towards improving our understanding of the physical realism of RCMs in terms of different time scales, thus enabling us in future work to address the sources of model biases.

关键词： dynamical downscaling extreme-temperature index observation RegCM WRF

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Seasonal variation of the temperature profile and its characteristics within urban roughness sublayer

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chinese Science Bulletin 2009年第3期54卷 468-473页

作者： wang XiQuan wang ZiFa GUO HU nansen-zhu {2. {2. center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Beijing Meteorological Bureau Beijing 100089 China

By using conventional micro-meteorological observation data of Beijing Yuetan Park Tower (180 m), the temperature profile of urban boundary layer (UBL), its characteristics and seasonal variation are analyzed. The main results are as follows: (1) In winter, the interdiurnal surface air temperature varia- tion at the surface is not synchronized with that of the upper levels, other than in summer and other seasons, which illuminates the impacts of Beijing’s geographical location, sky view factor and stably stratified nocturnal inversion. (2. Except that the stratification is unstable around noon, the stratifica- tion in the roof layer or above-roof layer is of seasonal variability, which is weak unstable or weak sta- ble in winter or summer respectively. This weak stable stratification possibly inhibits urban pollutant dispersion upwards in summer season. (3) The effect of urban building rooftop on the UBL thermal state has seasonal difference, that is, the rooftop plays the role of heating or cooling the urban roughness sublayer, in summer or winter respectively, which is similar to the effects of the Qing- hai-Tibet Plateau on the atmospheric thermal state.

关键词：城市边界层温度季节变更北京

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Comparison of Ten Potential Evapotranspiration Models and Their Attribution Analyses for Ten chinese Drainage Basins

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Advances in atmospheric sciences 2020年第9期37卷 959-974页

作者： Ruiheng XIE Aihui wang School of atmospheric sciences Chengdu University of Information TechnologyChengdu 610225China nansen-zhu {2. {2. center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Potential evapotranspiration(EPET)is usually calculated by empirical methods from surface meteorological variables,such as temperature,radiation and wind *** in-situ measured pan evaporation(ETpan)can also be used as a proxy for *** this study,EPET values computed from ten models are compared with observed ETpan data in ten chinese river basins for the period 1961−*** daily observed meteorological variables at 2.67 stations are used as the input to those models,and a ranking scheme is applied to rank the statistical quantities(ratio of standard deviations,correlation coefficient,and ratio of trends)between ETpan and modeled EPET in different river *** are large deviations between the modeled EPET and the ETpan in both the magnitude and the annual trend at most *** eight of the basins(except for Southeast and Southwest china),ETpan shows decreasing trends with magnitudes ranging between−0.01 mm d−1 yr−1 and−0.03 mm d−1 yr−1,while the decreasing trends in modeled EPET are less than−0.01 mm d−1 yr−*** comparisons among different models in different river basins suggest that PETHam1 is the best model in the Pearl River basin,PETHam2.outperforms other models in the Huaihe River,Yangtze River and Yellow River basins,and PETFAO is the best model for the remaining *** analyses reveal that wind speed and sunshine duration are two important factors for decreasing EPET in most basins except in Southeast and Southwest *** increasing EPET trend in Southeast china is mainly attributed to the reduced relative humidity.

关键词： potential evapotranspiration model pan evaporation model comparison sensitivity analysis china

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