我国冬季气温的年际变化及其与大气环流和海温异常的关系

利用我国160个台站49个冬季（1951/1952～1999/2000年）的气温资料和NCEP/NCAR再分析资料,通过波谱分析的方法提取变量的年际变化分量（周期小于8年部分）进行分析,结果发现：在年际变化的时间尺度上,我国冬季气温表现为全国一致变化型（EOF1）和南北反相变化型（EOF2）两个主要模态,并可以解释总方差60％以上的变化。进一步分析表明,在年际变化尺度上,与气温全国一致变化型相联系的大气环流表现出海陆气压差的改变以及与此相关的东亚大槽强度的变化和东亚高空急流位置的南北移动;赤道中东太平洋的异常海温对这一模态的出现有一定的预示意义,而中国近海的海温则更多的是被动地随气温改变。与南北反相变化型相联系的大气环流表现出显著的北极涛动特征,这一模态的出现会使得次年春季的西北太平洋海温呈现以30°N为界南北反相变化的形态;而北太平洋的海温异常可能对这一模态的形成有一定的作用。这两个模态的空间分布虽然与年代际尺度上的分布非常相似,但它们的相对强弱和对应的环流却有很大的差异。分析显示,全国一致变化型可能更多地表现出年代际变化的特征,而南北反相变化型更多地表现出年际变化的特征;结果还表明,我国冬季气温的变化在不同的时间尺度上是受不同因子影响的。因此,在研究我国冬季气温变化时,将不同的时间尺度分开考虑是十分必要的。     

Interannual Variability of Sea Surface Temperature in the Northern Indian Ocean Associated with ENSO and IOD

The Northern Indian Ocean(NIO) sea surface temperature(SST) warming,associated with the El Ni o/Southern Oscillations(ENSO) and the Indian Ocean Dipole(IOD) mode,is investigated using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) monthly data for the period 1979 2010.Statistical analyses are used to identify respective contribution from ENSO and IOD.The results indicate that the first NIO SST warming in September November is associated with an IOD event,while the second NIO SST warming in spring-summer following the mature phase of ENSO is associated with an ENSO event.In the year that IOD co-occurred with ENSO,NIO SST warms twice,rising in the ENSO developing year and decay year.Both shortwave radiation and latent heat flux contribute to the NIO SST variation.The change in shortwave radiation is due to the change in cloudiness.A cloud-SST feedback plays an important role in NIO SST warming.The latent heat flux is related to the change in monsoonal wind.In the first NIO warming,the SST anomaly is mainly due to the change in the latent heat flux.In the second NIO warming,both factors are important.     

三种方法统计的广东省霾日时空变化特征比较分析

根据广东省86个气象观测站1980—2013年的能见度、相对湿度和天气现象等资料,采用人工观测法、日均值法和14时值法对广东省霾日特征进行了对比分析。结果表明,三种方法统计的全省霾日数、霾日变化速率、全省排名前10位的站点均不尽相同,甚至差异较大。全省年平均霾日是日均值法统计结果 人工观测法的14时值法的,大致比例是1∶0.59∶0.49。人工观测法统计的广东省霾日变化速率最大,达2.1天/a,是日均值法的1.85倍,14时值法的3.34倍。人工观测法统计的霾日全省排名前10位的站点与日均值法、14时值法的都有7个相同、3个不同。三种方法统计的全省霾日长期变化趋势、季节变化特点和空间分布特征基本一致,三种方法均较适用于分析区域长时间序列的霾日变化特征。综合考虑霾日长期变化趋势、季节变化特点、空间分布特征和前人研究结果,日均值法统计的霾日更能反映广东省的实际变化特征。     

基于东亚冬季风指数的安徽省冬季霾预测研究

东亚冬季风强度与中国中东部冬季霾日数的变化在年际尺度上密切相关,这为霾的短期气候预测提供了可能的物理因子。利用NCEP/NCAR再分析资料和安徽省1980-2016年气象观测数据,采用统计分析方法研究安徽省1月霾日数与同期不同东亚季风指数的关系,确定了安徽省不同区域冬季霾的主要季风指数预测因子,建立安徽省冬季霾的月尺度预测模型,并进行了验证。结果表明:(1)1月气候霾日数与6类东亚冬季风指数均呈反相关关系,其中淮河以北、江淮之间两个区东亚大槽强度指数与气候霾日数的相关系数在各项指数中最高,沿江江南为西伯利亚高压强度指数与气候霾日数的相关系数在各项指数中最高。(2)不同分区建立的1月气候霾日数的预测模型均通过了α=0. 01的显著性水平检,验证结果表明,霾日数预测等级与实况等级基本一致,各区均未出现预测错误的情况,表明模型具有较好的预测表现。(3)在安徽省冬季霾实际预测业务中,相比NCEPCFS2模式输出的环流预报场,ECMWFSYSTEM4模式输出环流预报场的预测效果更好。     

不同年代际背景下AO与冬季中国东北气温的关系

采用1951—2006年北极涛动指数序列、NCEP/NCAR再分析资料和我国160站气温资料,利用滑动相关分析研究了不同年代际背景下北极涛动与冬季中国东北气温年际异常关系的变化情况。结果表明,两者的关系在20世纪60年代中后期显著增强,在80年代中后期减弱。不同年代际背景下,与AO相关联的中高纬度大气环流异常发生的明显改变是AO与东北冬季气温关系发生年代际变化的原因。强相关年代,西伯利亚高压与阿留申低压均明显减弱,东亚冬季风偏弱,对流层中下层异常东南风控制东北地区,对流层中层东亚大槽明显减弱,环流的经向性减弱,使该地区冬季气温偏高;相关较弱的年代则以上表现不明显。     

Interdecadal Change in the Interannual Variability of South China Sea Summer Monsoon Intensity

The interdecadal change in the interannual variability of the South China Sea summer monsoon(SCSSM) intensity and its mechanism are investigated in this study. The interannual variability of the low-level circulation of the SCSSM has experienced a significant interdecadal enhancement around the end of the 1980s, which may be attributed to the interdecadal changes in the evolution of the tropical Indo-Pacific sea surface temperature(SST) anomalies and their impacts on the SCSSM. From 1961 to 1989...     

春季欧亚大陆地表气温变化特征的气候意义

研究了春季欧亚大陆地表气温的年际变化及其相联系的环流场特征,发现春季欧亚大陆地表气温年际变化呈现为大陆尺度的南北跷跷板式的空间分布特征, 即当中高纬度地表气温为正距平时,副热带地区则为负距平,反之亦然。这种空间分布型代表了欧亚大陆中高纬度地表气温年际变化的主要特征。进一步的研究表明,这种变化与前期冬季北大西洋涛动（NAO）有着显著的正相关,而与同期的NAO无关。同时,欧亚大陆地表气温异常存在着明显的从冬到夏的持续性。与东亚初夏气候变化关系的研究表明,春季欧亚大陆地表气温的变化通过影响鄂霍次克高压的变化进一步影响初夏梅雨的变化。当春季欧亚大陆中高纬度地表气温为正距平时,鄂霍次克高压偏强,初夏梅雨较活跃,反之亦然。     

四川盆地冬季霾日数的分布特征及其与气象条件和海温关系

利用四川盆地气象站点资料和NCEP/NCAR再分析资料,结合四川盆地冬季霾日数的时空变化特征,分析了影响盆地冬季霾日数的气象条件,探讨了海温异常对冬季霾日数的可能影响,基于海温关键区建立冬季霾日数预测模型,并检验了模型的预测能力.研究表明,四川盆地冬季霾日数呈弱增加趋势;四川盆地三大城市群为冬季霾多发区;四川盆地冬季霾...     

中国冬季气温的年际变化

利用中国160站1951-2000年的冬季月平均气温资料，用EOF分析、小波分析和合成分析等方法对中国近50年来的冬季气温的年际变化和时空分布特征进行研究。结果表明：中国冬季气温50年来有显著的增暖趋势，在70年代后期增暖幅度开始加大，年际变化以6～9年周期为主。中国冬季气温的空间变化有很好的一致性，全国绝大部分区域呈整体变暖或变冷的趋势，并且气温变化南北有别，从南向北幅度逐渐变大。另一种模态是当东北、华北和西北地区冬季气温较高时，其它地区则偏冷；反之亦然。     

ENSO and Sea Surface Temperature Anomalies in Association with Canadian Wheat Yield Variability

Interannual variations of spring wheat yields in Canadian agricultural regions are analyzed, together with the associated sea surface temperature (SST) anomalies in the northern hemisphere tropics and extratropics, from 1961 to 2015. The cubic trend is calculated and used to represent the trend related to advances in agricultural technology over this time period. The correlations between Canadian wheat yields at regional scales and the tropical El Niño–Southern Oscillation (ENSO) variability are not robust at any stage of the evolution of ENSO. Based on the power spectrum and cross-spectrum analysis, the most prominent yield variance is found in the Canadian Prairies, with a significant power peak of 4.5 years but does not co-vary significantly with interannual ENSO variability. ENSO weakly affects temperature and precipitation anomalies in the Canadian Prairie Region in summer—two important agroclimatic conditions for crop growth—and hence insignificantly impacts wheat yields. This indicates that there would be little benefit to including tropical ENSO indices in the operational wheat yield forecasting system. For Canadian wheat yield forecasting, attention should be paid to the preceding winter and spring SST anomalies in the northern extratropics. The SST anomalies associated with yields in the Canadian Prairie region and Central Region are generally stronger than those associated with yields in the Canadian Pacific Coast Region and eastern Maritime Region. In association with the Prairie Region and Central Region yields, SST shows pronounced anomalies in the mid-high latitudes of the North Pacific from winter to summer. The non-linearity of the SST anomalies associated with the Canadian yields is also clearly evident. Stronger (weaker) SST anomalies in the extratropical North Pacific correspond to low wheat yields in the Prairie (Central) Region, while weaker (stronger) SST anomalies correspond to high yields in the Prairie (Central) Region.     

热带海洋变异对东亚季风的影响

季风主要是由于海陆热力差异随季节的变化所造成。热带海洋温度具有显著的年际异常，热带海温的变异不仅可以通过改变海陆热力差异，而且也通过热带地区强烈的海气相互作用，对季风系统产生重要影响，造成季风区天气和气候的异常。回顾了发生在热带东太平洋(ENSO现象)、热带西太平洋暖池和热带印度洋海温的变异对东亚季风的影响及其影响的物理过程，并指出东亚季风与这些热带区域的海温变异是一个有机的整体，只有对它们进行综合的研究，才能真正认识它们之中任一部分的变化。     

山东冬季气温年际变化及大气环流特征

采用经验正交函数(EOF)方法分析山东省43年(1961—2003年)冬季气温变化，结果表明，第1模态几乎反映了整个温度场的时空变化特征，冬季气温年际变化明显，增温显著；采用NCEP／NCAR月平均大气环流再分析资料(1961—2003年)，分析表明，冷、暖冬大气环流差异明显，冷冬年500hPa高度距平场呈北高南低的特征，西伯利亚高压加强，东亚大槽偏西加深，亚洲地区维持稳定的经向环流，利于冷空气南下，易造成冷冬；暖冬年呈相反特征。     

Diversity on the Interannual Variations of Spring Monthly Precipitation in Southern China and the Associated Tropical Sea Surface Temperature Anomalies

There is a continuous and relatively stable rainy period every spring in southern China (SC). This spring precipitation process is a unique weather and climate phenomenon in East Asia. Previously, the variation characteristics and associated mechanisms of this precipitation process have been mostly discussed from the perspective of seasonal mean. Based on the observed and reanalysis datasets from 1982 to 2021, this study investigates the diversity of the interannual variations of monthly precipitation in spring in SC, and focuses on the potential influence of the tropical sea surface temperature (SST) anomalies. The results show that the interannual variations of monthly precipitation in spring in SC have significant differences, and the correlations between each two months are very weak. All the interannual variations of precipitation in three months are related to a similar western North Pacific anomalous anticyclone (WNPAC), and the southwesterlies at the western flank of WNPAC bring abundant water vapor for the precipitation in SC. However, the WNPAC is influenced by tropical SST anomalies in different regions each month. The interannual variation of precipitation in March in SC is mainly influenced by the signal of El Ni?o-Southern Oscillation, and the associated SST anomalies in the equatorial central-eastern Pacific regulate the WNPAC through the Pacific-East Asia (PEA) tele-connection. In contrast, the WNPAC associated with the interannual variation of precipitation in April can be affected by the SST anomalies in the northwestern equatorial Pacific through a thermally induced Rossby wave response. The interannual variation of precipitation in May is regulated by the SST anomalies around the western Maritime Continent, which stimulates the development of low-level anomalous anticyclones over the South China Sea and east of the Philippine Sea by driving anomalous meridional vertical circulation.     

1961—2012年中国冬半年霾日数的变化特征及气候成因分析

利用全国664站1961—2012年逐日霾观测资料、降水量、平均风速和最大风速资料,分析中国霾日数变化特征及其气候成因。结果表明：我国年霾日数分布呈明显东多西少特征,中东部大部地区年霾日数在5～30 d,部分地区超过30 d,西部地区基本在5 d以下。霾日数主要集中在冬半年,冬季最多,秋季和春季次之,夏季最少,12月是霾日数最多的月份,约占全年霾日数的2成。我国中东部地区冬半年平均霾日数呈显著的增加趋势（1.7 d/10a）,霾日数显著增加时段主要在1960年代、1970年代和21世纪初,在1970年代初和21世纪初发生了明显均值突变。从区域分布来看,华南、长江中下游、华北等地霾日数呈增加趋势,而东北、西北东部、西南东部霾日数呈减少趋势。持续性霾过程增加,持续时间越长的霾过程比持续时间短的霾过程增加更为明显。不利的气候条件加剧了霾的出现。霾日数与降水日数在中东部地区基本以负相关为主,中东部冬半年降水日数呈减少趋势（-4 d/10a）,表明降水日数的减少导致大气对污染物的沉降能力减弱。另一方面,霾日数与平均风速和大风日数以负相关为主,而与静风日数则以正相关为主,冬半年平均风速和大风日数减小,静风日数增加,表明风速减小导致空气中污染物不易扩散,从而更易形成霾天气。     

东亚冬季风年际变化的ENSO信息 I.模拟资料分析

系统分析了观测海温强迫９层大气环流模式的模拟资料,结果表明该大气环流模式能够对与ＥｌＮｉｎｏ、ＬａＮｉｎａ事件爆发有关的赤道太平洋异常纬向风和对流活动有很好的模拟;模拟中的东亚冬季风具有明显的年际变化特征,这种变化与观测结果有很好的一致性,而且进一步分析发现这种年际变化具有显著的２～７年的周期,即东亚冬季风异常与ＥＮＳＯ密切相关。     

江苏秋季霾的年代际变化特征及其影响因素分析

利用1961-2010年江苏地级市气象站资料分析了近50年江苏秋季霾的年代际变化特征,并从气候背景的影响方面探讨其形成变化的特点：少霾期,大气环流以及水汽输送特征都有利于污染物的输送和稀释;而在调整期,气象条件有所调整,但不显著;在显著上升期,气候背景场对霾的发生起到十分积极的作用。另外,1961-2010年大气净化次数显著减少。海温与霾的年代际变化存在密切关系,当霾日数不断上升时,印度洋到南海海域的海温升高,引起低层风场的辐合,并通过类似于Hadley环流形式使得东亚同经度的中纬度地区低层辐散,利于水汽通道转换,进而有利于霾天气的发生。     

The Impacts of the Interannual Variability of Vegetation on the Interannual Variability of Global Evapotranspiration: A Modeling Study

The impact of the interannual variability (IAV) of vegetation on the IAV of evapotranspiration is investigated with the Community Land Model (CLM3.0) and modified Dynamic Global Vegetation Model (DGVM). Two sets of 50-year off-line simulations are used in this study. The simulations begin with the same initial surface-water and heat states and are driven by the same atmospheric forcing data. The vegetation exhibits interannual variability in one simulation but not in the other simulation. However, the climatological means for the vegetation are the same. The IAV of the 50-year annual total evapotranspiration and its three partitions (ground evaporation, canopy evaporation, and transpiration) are analyzed. The global distribution of the evapotranspiration IAV and the statistics of evapotranspiration and its components in different ecosystems show that the IAV of ground evaporation is generally large in areas dominated by grass and deciduous trees, whereas the IAV of canopy evaporation and transpiration is large in areas dominated by bare soil and shrubs. For ground evaporation, canopy evaporation, and transpiration, the changes in IAV are larger than the mean state over most grasslands and shrublands. The study of two sites with the same IAV in the leaf area index (LAI) shows that the component with the smaller contribution to the total evapotranspiration is more sensitive to the IAV of vegetation. The IAV of the three components of evapotranspiration increases with the IAV of the fractional coverage (FC) and the LAI. The ground evaporation IAV shows the greatest increase, whereas the canopy evaporation shows the smallest increase.     

The 30–60-day Intraseasonal Variability of Sea Surface Temperature in the South China Sea during May–September

This study investigates the structure and propagation of intraseasonal sea surface temperature(SST) variability in the South China Sea(SCS) on the 30–60-day timescale during boreal summer(May–September). TRMM-based SST, GODAS oceanic reanalysis and ERA-Interim atmospheric reanalysis datasets from 1998 to 2013 are used to examine quantitatively the atmospheric thermodynamic and oceanic dynamic mechanisms responsible for its formation. Power spectra show that the 30–60-day SST variability is predominant, accounting for 60% of the variance of the 10–90-day variability over most of the SCS. Composite analyses demonstrate that the 30–60-day SST variability is characterized by the alternate occurrence of basin-wide positive and negative SST anomalies in the SCS, with positive(negative) SST anomalies accompanied by anomalous northeasterlies(southwesterlies). The transition and expansion of SST anomalies are driven by the monsoonal trough–ridge seesaw pattern that migrates northward from the equator to the northern SCS. Quantitative diagnosis of the composite mixed-layer heat budgets shows that, within a strong 30–60-day cycle, the atmospheric thermal forcing is indeed a dominant factor, with the mixed-layer net heat flux(MNHF) contributing around 60% of the total SST tendency, while vertical entrainment contributes more than 30%. However, the entrainment-induced SST tendency is sometimes as large as the MNHF-induced component, implying that ocean processes are sometimes as important as surface fluxes in generating the30–60-day SST variability in the SCS.     

SVD分析揭示的澳大利亚高压年际变化对中国夏季气温的可能影响

利用澳大利亚海平面气压和中国夏季气温站点资料,使用SVD和线性回归方法揭示了澳大利亚高压（以下简称澳高）的年际变化与中国夏季气温异常的联系。结果表明,SVD的第一模态（简称SVD1）时间系数与通常使用澳高指数相关可达到0．97。SVD1表示出澳大利亚高压的年际变化与中国江南地区夏季气温存在密切联系。澳高增强（减弱）时,江南地区夏季气温偏低（偏高）。整层垂直积分大气加热场、海平面气压场、500hPa的高度场变化以及降水和总云量的变化都对夏季气温的形成有一定作用。澳高对中国夏季气温的可能影响途径为：澳高强（弱）年时,澳大利亚地区低层的异常辐散风场在菲律宾东侧的暖池附近产生辐合（辐散）,引起正（负）涡度源,激发P-J型波列,伴随着在南海-西太平洋地区产生副高正异常（负异常）,导致副高偏西（偏东）,进而增强（减弱）来自孟加拉湾的水汽输送,同时江南地区水汽和异常风场辐合（辐散）,有利于（不利于）该地区降水异常的发生和维持,有益于气温降低（升高）。     

近50年中国霾年代际特征及气象成因

根据1961-2013年全国745个国家基准站的长期观测资料,分析中国霾日数年代际变化特征及可能的气象成因。结果表明:近50年来,中国霾天气主要集中在东部从华南到华北的大部分地区,霾日数呈增加趋势。秋冬两季是霾天气发生最频繁、变化最明显的两个季节。中国东部淮河以南地区秋冬两季霾日数在2000年前呈增加趋势,其后增加趋势变得较为平缓,20世纪90年代前霾日数与近地面风速呈显著负相关关系,90年代后则与大气相对湿度呈显著负相关关系,随着90年代前近地面风速减小和90年代后大气相对湿度降低,该区域霾日数表现出明显的增加趋势。中国东部从淮河到华北大部分地区秋冬两季霾日数1980年后增加趋势变得不明显,这可能与该区域近地面风速和大气相对湿度的变化趋势较为平缓有关。