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1.
利用1957年9月—2002年8月ECMWF和NCEP/NCAR月平均再分析资料,分别讨论了冬季和夏季SLP(sea level pressure,海平面气压)、500hPa高度、200hPa纬向风和850hPa经向风年际变率的潜在可预报性特征。结果表明:热带地区的潜在可预报性较高,尤其是赤道中东太平洋地区,而中高纬地区的潜在可预报性则较低。比较两套资料潜在可预报性的异同后发现:南半球的差异均明显大于北半球,特别是南极地区;低层变量的差异均大于中高层变量;东亚大陆在冬、夏季均具有一定的潜在可预报性;冬季各变量均表现出东亚冬季风具有较高的年际变率潜在可预报性,且两套资料的差异较小;500hPa位势高度表现的东亚夏季风潜在可预报性在两套资料中较一致,而低层变量(SLP和850hPa经向风)表现的东亚夏季风年际变率潜在可预报性在两套资料中存在较大差异。 相似文献
2.
2001年北半球大气环流特征及其对中国气候异常的影响 总被引：3，自引：0，他引：3
2001年受前期赤道东太平洋海温长期冷水位相的影响，北半球大气环流的主要特征表现为：500hPa西太平洋副热带高压冬春季偏强，夏季秋偏弱；欧亚地区夏季500hPa位势高度距平场上中高纬从西到东呈现为“－＋－”分布形式，贝加尔湖地区为正距平中心；东亚冬、夏季风偏弱；7月赤道辐合带异常偏强、偏北等。在上述大气环流的影响下，我国的天气气候发生了异常。 相似文献
3.
基于动力气候模式进行月一季尺度预报的“两步法”思想,提出一种新的预报海温场统计模型,并以该统计模型预报的海温场驱动NCAR CAM3.1模式对1981-2000年月时间尺度的东亚500 hPa高度距平场进行客观回报试验;在此基础上,提出了对预报结果的订正方法。结果表明:统计预报海温模型的预报海温场能够反映出全球海温空间分布的基本特征,并对表征ENSO事件的Ni?o3.4区海温变化的预报能力较强。该统计模型预报的海温场驱动的CAM3.1模式可以较好地预报出东亚500 hPa环流的主要分布特征,试验表明:适当的统计订正方法可以在一定程度上提高CAM3.1模式对东亚夏季500 hPa环流背景的预报技巧。 相似文献
4.
利用山西省58个台站1960-2009年有观测记录的50年夏季降水资料和NCEP/NCAR再分析逐月位势高度场和海温场资料,研究了山西省旱、涝年大气环流特征差异,并进一步讨论了山西省夏季降水异常与赤道东太平洋（Nino区）海温异常的关系。研究结果表明：山西省夏季降水异常年从前期春季到同期夏季,欧亚中高纬度500hPa位势高度的大气环流存在异常,尤其是乌拉尔山高压脊、贝加尔湖低槽及西太平洋副热带高压等大尺度环流系统都有明显的变化;850hPa风场上蒙古气旋南部纬向风的异常,以及我国东部到华北地区经向风（东亚夏季风）的异常,是直接影响山西省夏季降水的重要环流因子;赤道东太平洋秘鲁冷水舌和太平洋东岸暖水舌均是山西省夏季降水的敏感区,其中Nino区域前期春季海温异常对山西省夏季降水的环流系统有显著的影响,即Nino区域前期海温偏低有利于山西省夏季降水偏多。 相似文献
5.
山西省夏季降水与赤道东太平洋海温关系初探 总被引：2，自引：0，他引：2
利用山西省58个台站1960-2009年有观测记录的50a夏季降水资料和NCEP／NCAR逐月再分析位势高度场、NOAA逐月海温场资料,研究了山西省旱、涝年大气环流特征差异,并进一步讨论了山西省夏季降水异常与赤道东太平洋（Nino区）海温异常的关系。研究结果表明：山西省夏季降水异常年从前期春季到同期夏季,欧亚中高纬度500hPa位势高度的大气环流存在异常,尤其是乌拉尔山高压脊、贝加尔湖低槽及西太平洋副热带高压等大尺度环流系统都有明显的变化;850hPa风场上蒙古气旋南部纬向风的异常,以及我国东部到华北地区经向风（东亚夏季风）的异常,是直接影响山西省夏季降水的重要环流因子;赤道东太平洋秘鲁冷水舌和太平洋东岸暖水舌均是山西省夏季降水的敏感区,Nino区域前期海温异常对山西省夏季降水有显著的影响,即Nino区域前期海温偏低有利于山西省夏季降水偏多。 相似文献
6.
中国南方多雪年环流特征及对关键区海温的响应 总被引：6，自引：3，他引：3
根据NECP/NCAR月平均再分析资料,采用回归分析、合成分析等方法,探讨了La Nia（El Nio）气候背景下,大气外强迫因子北大西洋中纬度（45°N,30°W）、赤道印度洋、我国南海和东海海域海温异常对亚洲环流及我国南方降雪多寡的影响。分析发现,La Nia气候背景下,北大西洋中纬（45°N,30°W）海温为正异常,有利于500 hPa高度场亚洲中高纬叶尼塞地区（50°N, 90°E）位势高度偏高并出现阻塞型,也有利于东亚冬季风环流加强;赤道印度洋、我国南海和东海附近海温出现负异常,850 hPa高度东亚大陆沿海低纬地区风距平场出现偏北风距平,我国南方多雪,温度相对偏低。El Nio背景下,北大西洋中纬度（45°N,30°W）海温为负异常,亚洲中高纬叶尼塞地区位势高度偏低,东亚冬季风环流偏弱;赤道印度洋、我国南海和东海附近海温出现正异常,850 hPa高度东亚大陆沿海低纬风距平场出现偏南风距平,我国南方多雪,温度相对偏高。回归分析指出,冬季500 hPa亚洲中高纬叶尼塞地区（90°E附近）的位势高度正（负）异常与北大西洋中纬度（45°N,30°W）附近海温正（负）异常有关;冬季850 hPa东亚大陆沿海低纬地区偏南（北）风距平与赤道印度洋、我国南海和东海地区的海温正（负）异常有关。La Nia气候背景下的2008年1月我国南方低温、雨雪、冰冻极端灾害事件的发生可能与北大西洋中纬度（45°N,30°W）附近以及赤道印度洋、我国南海和东海海温都出现正异常有关。 相似文献
7.
北半球夏季位势高度场遥相关型的观测研究 总被引：3，自引：0，他引：3
本文利用点相关普查和经验正交函数展开分析了北半球夏季500hPa位势高度场的年际变化特征,指出在北半球夏季主要存在4种遥相关型,它们分别被称作亚洲/北美型、欧亚型、东北太平洋型和北美/西欧型.其中前两种遥相关型和东亚夏季大气环流年际异常有直接的联系.北半球夏季遥相关型的揭示对于研究东亚大气环流年际变异的机理及其预报有参考价值. 相似文献
8.
北太平洋次表层海温异常对中国夏季降水影响的可能途径 总被引：2，自引：0，他引：2
利用Godas月平均次表层海温资料, 分析了冬、春季和夏季北太平洋次表层海温层际相似性特征, 据此对次表层海温进行分层。在此基础上研究了500 hPa位势高度场、北太平洋次表层海温、中国夏季降水三者之间的时滞相关关系, 发现春季北太平洋次表层海温场是联系前、后期大气环流的关键因素。前期冬季大气环流对春季北太平洋次表层海温场影响最显著, 春季北太平洋次表层海温场又持续影响同期及后期夏季大气环流异常。异常的夏季大气环流与同期表层、次表层海温相互作用, 共同造成夏季长江流域与华北、华南降水出现相反异常的分布型式。 相似文献
9.
10.
本文对2013年海洋和大气环流异常特征进行分析,讨论这些异常特征对中国气温和降水的主要影响。结果表明：2012/2013年冬季,北极涛动持续维持负位相,500 hPa位势高度场上,欧亚大陆中高纬环流呈“两槽一脊”的环流形势,乌拉尔山的高压脊持续偏强,而东亚槽也异常偏强,导致全国平均气温较常年同期偏低。季内,西伯利亚高压强度变化显著,与之相对应,我国气温季内阶段性变化大,前冬冷、后冬暖。进一步研究表明,前秋北极海冰的大幅偏少是造成东亚冬季风偏强的重要原因。2013年冬季至夏季,赤道中东太平洋海温异常偏低而海洋性大陆至西太平洋海温异常偏高,受此影响,夏季西太平洋副热带高压位置明显偏北,导致我国北方夏季多雨。与此同时,受西太平洋副热带高压下沉气流的控制,我国南方大部高温持续。2013年南海夏季风爆发偏早两候,结束偏晚4候,强度偏弱。 相似文献
11.
基于NCEP/NCAR再分析资料,利用信噪比(SNR)方法研究了南海夏季风强度潜在可预报性的年代际变化,结果表明:南海夏季风强度潜在可预报性在20世纪80年代出现了由潜在可预报性偏低位相向偏高位相的年代际转折。进一步的研究发现,南海夏季风强度潜在可预报性和东印度洋—西太平洋(EIOWP)的海表温度(SST)存在明显的正相关。当EIOWP区域SST年际变率较大时,对南海夏季风影响较强,使得南海夏季风的外部信号增强,从而提高了潜在可预报性;当EIOWP区域SST年际变率较小时,对南海夏季风影响较弱,南海夏季风的外部信号进而减弱,潜在可预报性降低。 相似文献
12.
土壤湿度对东亚夏季气候潜在可预报性影响的数值模拟 总被引：5，自引：0，他引：5
利用全球大气环流模式NCARCAM3进行了在给定的观测海温条件下的22a（1979—2000年）5—8月的2组集合试验。运用方差分析方法,分析了在气候态和年际变化的表层土壤湿度情况下,CAM3模式模拟的东亚夏季气候潜在可预报性及其差异。结果表明：在给定的观测海温条件下,采用气候态的土壤湿度时,CAM3模式模拟的东亚夏季气候的潜在可预报性偏低;而采用年际变化的土壤湿度时,模拟的夏季气候潜在可预报性有所提高,尤其是在中国西北地区;后者模拟的中国西北地区夏季降水和气温的潜在可预报性比前者的模拟结果提高0．1以上。其原因可能是：采用年际变化的土壤湿度时,模式可以更好地模拟出中国西北地区的地表蒸发量和湍流热通量的年际变化,进而使得模式对该地区夏季气候的预报技巧得到提高。 相似文献
13.
Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3 总被引：2，自引：1，他引：1
Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice?Cocean?Cterrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1?year. In all regimes, ice thickness has high potential predictability for at least 2?years. 相似文献
14.
Gill M.MARTIN Amulya CHEVUTURI Ruth E.COMER Nick J.DUNSTONE Adam A.SCAIFE Daquan ZHANG 《大气科学进展》2019,36(3):253-260
Predicting monsoon onset is crucial for agriculture and socioeconomic planning in countries where millions rely on the timely arrival of monsoon rains for their livelihoods. In this study we demonstrate useful skill in predicting year-to-year variations in South China Sea summer monsoon onset at up to a three-month lead time using the GloSea5 seasonal forecasting system. The main source of predictability comes from skillful prediction of Pacific sea surface temperatures associated with El NiÑo and La NiÑa. The South China Sea summer monsoon onset is a known indicator of the broadscale seasonal transition that represents the first stage of the onset of the Asian summer monsoon as a whole. Subsequent development of rainfall across East Asia is influenced by subseasonal variability and synoptic events that reduce predictability, but interannual variability in the broadscale monsoon onset for East Asian summer monsoon still provides potentially useful information for users about possible delays or early occurrence of the onset of rainfall over East Asia. 相似文献
15.
The interannual variation of East Asia summer monsoon (EASM) rainfall exhibits considerable differences between early summer [May–June (MJ)] and peak summer [July–August (JA)]. The present study focuses on peak summer. During JA, the mean ridge line of the western Pacific subtropical High (WPSH) divides EASM domain into two sub-domains: the tropical EA (5°N–26.5°N) and subtropical-extratropical EA (26.5°N–50°N). Since the major variability patterns in the two sub-domains and their origins are substantially different, the Part I of this study concentrates on the tropical EA or Southeast Asia (SEA). We apply the predictable mode analysis approach to explore the predictability and prediction of the SEA peak summer rainfall. Four principal modes of interannual rainfall variability during 1979–2013 are identified by EOF analysis: (1) the WPSH-dipole sea surface temperature (SST) feedback mode in the Northern Indo-western Pacific warm pool associated with the decay of eastern Pacific El Niño/Southern Oscillation (ENSO), (2) the central Pacific-ENSO mode, (3) the Maritime continent SST-Australian High coupled mode, which is sustained by a positive feedback between anomalous Australian high and sea surface temperature anomalies (SSTA) over Indian Ocean, and (4) the ENSO developing mode. Based on understanding of the sources of the predictability for each mode, a set of physics-based empirical (P-E) models is established for prediction of the first four leading principal components (PCs). All predictors are selected from either persistent atmospheric lower boundary anomalies from March to June or the tendency from spring to early summer. We show that these four modes can be predicted reasonably well by the P-E models, thus they are identified as the predictable modes. Using the predicted PCs and the corresponding observed spatial patterns, we have made a 35-year cross-validated hindcast, setting up a bench mark for dynamic models’ predictions. The P-E hindcast prediction skill represented by domain-averaged temporal correlation coefficient is 0.44, which is twice higher than the skill of the current dynamical hindcast, suggesting that the dynamical models have large rooms to improve. The maximum potential attainable prediction skills for the peak summer SEA rainfall is also estimated and discussed by using the PMA. High predictability regions are found over several climatological rainfall centers like Indo-China peninsula, southern coast of China, southeastern SCS, and Philippine Sea. 相似文献
16.
东亚季风指数及其与大尺度热力环流年际变化关系 总被引：24，自引：1，他引：23
将东西向海平面气压差与低纬度高、低层纬向风切变相结合 ,定义了东亚季风指数 ,该季风指数较好地反映了东亚冬、夏季风变化。其中 ,夏季风指数年际异常对西太平洋副热带高压南北位置变化和长江中下游旱涝具有较强的反映能力。分析表明 :东亚夏季风年际变化与印度洋 -西太平洋上空反 Walker环流及夏季越赤道南北半球间的季风环流呈显著正相关关系。在强、弱异常东亚夏季风年份 ,异常的 Walker环流在西太平洋上的辐合 (辐散 )中心在垂直方向不重合 ,高层 ( 2 0 0 h Pa)速度势与东亚夏季风显著相关区域位于西北太平洋上 ,该异常环流的高层的辐合 (辐散 )通过改变低层空气质量而影响夏季 50 0 h Pa西北太平洋副热带高压。采用 SVD分析进一步发现 :与海温耦合的异常 Walker环流在西太平洋上空的上升支表现出南北半球关于赤道非对称结构 ,亚澳季风区受该异常 Walker环流控制。因而 ,东亚季风与热带海气相互作用可直接通过这种纬向非对称的 Walker环流发生联系。 相似文献
17.
NUMERICAL SIMULATIONS ON INFLUENCES OF VARIATION OF SEA ICE THICKNESS AND EXTENT ON ATMOSPHERIC CIRCULATION* 
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下载免费PDF全文 By using a 2-layer AGCM designed by Institute of Atmospheric Physics,Chinese Academy of Sciences.this paper investigates influences of thickness and extent variations in Arctic sea ice on the atmosphere circulation,particularly on climate variations in East Asia.The simulation results have indicated that sea ice thickness variation in the Arctic exhibits significant influences on simulation results,particularly on East Asian monsoon.A nearly reasonable distribution of sea ice thickness in the model leads directly to stronger winter and summer monsoon over East Asia.and improves the model's simulation results for Siberia high and Icelandic low in winter.On the other hand,sea ice thickness variation can excite a teleconnection wave train across Asian Continent,and in low latitudes,the wave propagates from the western Pacific across the equator to the eastern Pacific.In addition,the variation of sea ice thickness also influences summer convective activitiesover the low latitudes including South China Sea and around the Philippines.Effects of winter sea ice extents in the Barents Sea on atmospheric circulation in the following spring and summer are also significant.The simulation result shows that when winter sea ice extent in the target region is larger (smaller) than normal.(1)in the following spring (averaged from April to June).positive (negative) SLP anomalies occupy the northern central Pacific.which leads directly to weakened (deepened)Aleutian low.and further favors the light (heavy) sea ice condition in the Bering Sea:(2)in the following summer,thermal depression in Asian Continent is deepened (weakened).and the subtropical high in the northwestern Pacific shifts northward(southward) from its normal position and to be strengthened (weakened). 相似文献
18.
By using a 2-layer AGCM designed by Institute of Atmospheric Physics,Chinese Academy ofSciences.this paper investigates influences of thickness and extent variations in Arctic sea ice onthe atmosphere circulation,particularly on climate variations in East Asia.The simulation resuhshave indicated that sea ice thickness variation in the Arctic exhibits significant influences onsimulation results,particularly on East Asian monsoon.A nearly reasonable distribution of sea icethickness in the model leads directly to stronger winter and summer monsoon over East Asia.andimproves the model's simulation results for Siberia high and Icelandic low in winter.On the otherhand,sea ice thickness variation can excite a teleconnection wave train across Asian Continent,andin low latitudes,the wave propagates from the western Pacific across the equator to the easternPacific.In addition,the variation of sea ice thickness also influences summer convective activitiesover the low latitudes including South China Sea and around the Philippines.Effects of winter sea ice extents in the Barents Sea on atmospheric circulation in the followingspring and summer are also significant.The simulation result shows that when winter sea iceextent in the target region is larger (smaller) than normal.(1)in the following spring (averagedfrom April to June).positive (negative) SLP anomalies occupy the northern central Pacific.whichleads directly to weakened (deepened)Aleutian low.and further favors the light (heavy) sea icecondition in the Bering Sea:(2)in the following summer,thermal depression in Asian Continent isdeepened (weakened).and the subtropical high in the northwestern Pacific shifts northward(southward) from its normal position and to be strengthened (weakened). 相似文献
19.
Interannual predictability of Arctic sea ice in a global climate model: regional contrasts and temporal evolution 总被引：1，自引：1，他引：0
Agathe Germe Matthieu Chevallier David Salas y Mélia Emilia Sanchez-Gomez Christophe Cassou 《Climate Dynamics》2014,43(9-10):2519-2538
The predictability of the Arctic sea ice is investigated at the interannual time scale using decadal experiments performed within the framework of the fifth phase of the Coupled Model Intercomparison Project with the CNRM-CM5.1 coupled atmosphere–ocean global climate model. The predictability of summer Arctic sea ice extent is found to be weak and not to exceed 2 years. In contrast, robust prognostic potential predictability (PPP) up to several years is found for winter sea ice extent and volume. This predictability is regionally contrasted. The marginal seas in the Atlantic sector and the central Arctic show the highest potential predictability, while the marginal seas in the Pacific sector are barely predictable. The PPP is shown to decrease drastically in the more recent period. Regarding sea ice extent, this decrease is explained by a strong reduction of its natural variability in the Greenland–Iceland–Norwegian Seas due to the quasi-disappearance of the marginal ice zone in the center of the Greenland Sea. In contrast, the decrease of predictability of sea ice volume arises from the combined effect of a reduction of its natural variability and an increase in its chaotic nature. The latter is attributed to a thinning of sea ice cover over the whole Arctic, making it more sensitive to atmospheric fluctuations. In contrast to the PPP assessment, the prediction skill as measured by the anomaly correlation coefficient is found to be mostly due to external forcing. Yet, in agreement with the PPP assessment, a weak added value of the initialization is found in the Atlantic sector. Nevertheless, the trend-independent component of this skill is not statistically significant beyond the forecast range of 3 months. These contrasted findings regarding potential predictability and prediction skill arising from the initialization suggest that substantial improvements can be made in order to enhance the prediction skill. 相似文献