The Relationship between Siberian High Anomaly and SSTA

By using the monthly average dataset of NCEP/NCAR reanalysis and the monthly average ocean temperature data of NOAA satellite center,we analyzed and probed into the relationship between Siberian high anomaly and SSTA,and found that the sea area anomaly is a bigger area,which have greater effect on the variation of Siberian high.The results indicated that there was a wonderful contemporaneously correlation between the area and intensity index of Siberian high and ocean temperature.The correlation type of the synchronous correlative areas between the central intensity index of Siberian high and ocean temperature have structural similarities with the correlative field's structure of area index,but the positive correlative regions expanded,and the intensity of negative correlative regions weakened significantly.The correlation among the area index of Siberian high and the central intensity index,as well as the ocean temperature anomaly of the North Atlantic during spring,autumn and summer of the same year was remarkable.The area index and the central intensity index of Siberian high anomaly have obvious correlation with the ocean temperature anomaly of Southwest Atlantic Ocean during spring,summer and autumn,however,they have apparent seasonal differences with the prominent negative correlative areas of subtropical South Indian Ocean and tropical South Pacific Ocean as well as Southwest Atlantic Ocean.The correlative index of area anomaly is greater than those of intensity anomaly.Larger impact on the variability of Siberian high anomaly are the SSTA of subtropical South Indian Ocean,mid and high latitudes of North Pacific Ocean,North Atlantic,tropical South Pacific Ocean,Southwest Atlantic Ocean,etc.several areas.

Possible Impacts of Winter Arctic Oscillation on Siberian High, the East Asian Winter Monsoon and Sea-Ice Extent

Using the NCEP/ NCAR reanalysis dataset covering a 40-year period from January 1958 to December 1997, sea surface temperature (1950-1992), and monthly sea-ice concentration dataset for the period from 1953 to 1995, we investigate connections between winter Arctic Oscillation (AO) and Siberian high (SH), the East Asian winter monsoon (EAWM), and winter sea-ice extent in the Barents Sea. The results indicate that winter AO not only influences climate variations in the Arctic and the North Atlantic sector, but also shows possible effects on winter SH, and further influences EAWM, When winter AO is in its positive phase, both of winter SH and the EAWM are weaker than normal, and air temperature from near the surface to the middle troposphere is about 0.5-2degreesC higher than normal in the southeastern Siberia and the East Asian coast, including eastern China, Korea, and Japan. When AO reaches its negative phase, an opposite scenario can be observed. The results also indicate that winter SH has no significant effects on climate variations in Arctic and the North Atlantic sector. Its influence intensity and extent are obviously weaker than AO, exhibiting a 'local, feature in contrast to AO. This study further reveals the possible mechanism of how the winter AO is related to winter SH. It is found that winter SH variation is closely related to both dynamic processes and air temperature variations from the surface to the middle troposphere. The western SH variation mainly depends on dynamic processes, while its eastern part is more closely related to air temperature variation. The maintaining of winter SH mainly depends on downward motion of airflow of the nearly entire troposphere. The airflow originates from the North Atlantic sector, whose variation is influenced by the AO. When AO is in its positive (negative) phase, downward motion remarkably weakened (strengthened), which further influences winter SH. In addition, winter AO exhibits significant influences on the simultaneous sea-ice extent in the Barents Sea.

The Project Siberian High in CMIP5 Models

The Siberian high(SH)experienced a decline from the 1970s to 1990s and a recovery in recent years.The evolution of the SH under global warming is unclear.In this study,41 Coupled Model Intercomparison Project Phase 5(CMIP5)climate models are evaluated in terms of their ability to simulate the temporal evolution of the SH in the 19th and 20th centuries and the spatial pattern of the SH during 1981–2005.The results show that 12models can capture the temporal evolution of the SH center intensity(SHCI)for 1872–2005.The linear correlation coefficient between the SHCI from the Twentieth Century Reanalysis and the simulated SHCI from the multi-model ensemble(MME)of the 12 models is 0.3 on annual and inter-annual scales(above the 99%confidence level).On decadal and multi-decadal time scales,the MME also captures the pronounced reduction(between 1981–2000and 1881–1900 period)and the recovery(during1991–2005)of the SH intensity.Finally,the future evolution of the SH is investigated using the MME of the 12models under the+4.5 and+8.5 W m-2 Representative Concentration Pathway(RCP)scenarios(RCP4.5 and RCP8.5).It is shown that the SHCI,similar to the SHCI in the 20th century,has no significant long-term trend in the 21st century under global warming(RCP8.5 scenario).At the end of 21st century(2081–2100),the SH shows stronger interannual variability than the SH at the end of20th century(1981–2000).The increased interannual variability likely favors the increased interannual variability in winter air temperature over midlatitude Eurasia at the end of 21st century.

Study of the climatic teleconnection between the Siberian high and maritime continent warm pool

This paper attempts to establish a method for analysing the relationship between the polar and equatorial climate of the Northern Hemisphere. The Arctic Oscillation （AO） is known to have no direct relationship with the monsoon over the Maritime Continent （MC）. Thus, an index called the Siberian High（SH^Maritime Continent（MC） Index （SHMCI） is developed to represent the mean sea level pressure difference between the SH and the warm pool over the MC. This index indicates a strong link with the monsoon circulation. A positive （strong） value of the SHMCI is associated with strong meridional winds and intense and frequent cold surge events over the South China Sea. The correlation between the AO index and the SHMCI is -0.39, which is medium but statistically significant; however, it is not sufficiently conclusive to infer direct correlation. Nevertheless, the SHMCI can be used as a tool to relate the AO with the monsoon over the MC because of the influence demonstrated by the AO towards the SH. Further analysis on the convergence and divergence anomalies over the MC reveals an impact discernible only from the SHMCI. This implies that the SHMCI manifests clearly the relationship between the Arctic and equatorial climate.

Impacts of the Autumn Arctic Sea Ice on the Intraseasonal Reversal of the Winter Siberian High

During 1979–2015, the intensity of the Siberian high(SH) in November and December–January(DJ) is frequently shown to have an out-of-phase relationship, which is accompanied by opposite surface air temperature and circulation anomalies.Further analyses indicate that the autumn Arctic sea ice is important for the phase reversal of the SH. There is a significantly positive(negative) correlation between the November(DJ) SH and the September sea ice area(SIA) anomalies. It is suggested that the reduction of autumn SIA induces anomalous upward surface turbulent heat flux(SHF), which can persist into November, especially over the Barents Sea. Consequently, the enhanced eddy energy and wave activity flux are transported to mid and high latitudes. This will then benefit the development of the storm track in northeastern Europe. Conversely, when downward SHF anomalies prevail in DJ, the decreased heat flux and suppressed eddy energy hinder the growth of the storm track during DJ over the Barents Sea and Europe. Through the eddy–mean flow interaction, the strengthened(weakened)storm track activities induce decreased(increased) Ural blockings and accelerated(decelerated) westerlies, which makes the cold air from the Arctic inhibited(transported) over the Siberian area. Therefore, a weaker(stronger) SH in November(DJ) occurs downstream. Moreover, anomalously large snowfall may intensify the SH in DJ rather than in November. The ensemble-mean results from the CMIP5 historical simulations further confirm these connections. The different responses to Arctic sea ice anomalies in early and middle winter set this study apart from earlier ones.

Enhancement of Winter Arctic Warming by the Siberian High over the Past Decade

In recent decades the Arctic surface air temperature(SAT) in autumn has been increasing steadily. In winter, however, instead of a linear trend, the Arctic SAT shows an abrupt change that occurred in 2004. During the years from 1979 to 2003, the first principle component(PC1) of winter Arctic SAT remains stable, and no significant increasing trend is detected. However, the PC1 changes abruptly from negative to positive phase in the winter of 2004. The enhanced Siberian high may have contributed to this abrupt change because the temporal evolution of Arctic temperature correlates significantly with sea level pressure variation in the northern Eurasian continent, and the atmospheric circulation anomaly related to the Siberian high from 2004 to 2013 favors a warmer Arctic. With the help of the meridional wind anomaly around the Siberian high, warmer air is transported to the high latitudes and therefore increases the Arctic temperature.

Precursory atmospheric teleconnection patterns for strong Siberian High events

本文利用日本55年逐日再分析资料,发现在SH异常增强前,有三种不同的大气遥相关型前兆信号,即斯堪的纳维亚(SCA)型,西太平洋(WP)型,极地-欧亚(POL)型据此,本文将异常增强的SH分为对应的三类事件.合成结果表明,三类事件在典型环流特征和对东亚气温的影响上存在着明显的不同.具体而言,SCA类事件主要表现为在欧亚中高纬度上自西向东的波列异常,WP类事件表现为环流异常自下游太平洋/俄罗斯远东地区向西发展的特征,POL型事件的显著信号则来源于自极区向南移动的反气旋式环流异常.在对东亚地表气温的影响上,SCA类与POL类事件类似,它们均可造成大范围的低温异常.而WP类仅在我国北方和东部地区造成强度较弱的地表气温异常,但该异常的持续性特征较明显。

Effects of autumn-winter Arctic sea ice on winter Siberian High

The intensity of the winter Siberian High has significantly negative correlations with Arctic sea ice concentration anomalies from the previous autumn to winter seasons in the Eastern Arctic Ocean and Siberian marginal seas. Our results indicate that autumn-winter Arctic sea ice concentration and concurrent sea surface temperature anomalies are responsible for the winter Siberian High and surface air temperature anomalies over the mid-high latitudes of Eurasia and East Asia. Numerical experiments also support this conclusion, and consistently show that the low sea ice concentration causes negative surface air temperature anomalies over the mid-high latitudes of Eurasia. A mechanism is proposed to explain the association between autumn-winter sea ice concentration and winter Siberian High. Our results also show that September sea ice concentration provides a potential precursor for winter Siberian High that cannot be predicted using only tropical sea surface temperatures. In the last two decades (1990–2009), a strengthening trend of winter Siberian High along with a decline trend in surface air temperature in the mid-high latitudes of the Asian Continent have favored the recent frequent cold winters over East Asia. The reason for these short-term trends in winter Siberian High and surface air temperature are discussed.

冬季亚洲两种大气环流型对云南低温事件的影响

利用1961—2022年云南125个国家气象站冬季逐日平均气温观测资料、NCAR/NCEP大气环流再分析资料,分析了冬季亚洲环流变化的主要类型及其对云南低温事件的影响,发现冬季亚洲500hPa大气环流存在纬向型和经向型两种环流类型,并对云南低温事件产生明显不同的影响。纬向型环流时,冷空气从贝加尔湖直接南下,主要影响东亚东部,云南低温事件也主要发生在东部地区,此时的低温过程与乌拉尔山高压和西伯利亚高压加强、欧亚中高纬度波列的活动密切联系;而经向型时,冷空气伴随贝加尔湖地区的异常反气旋东侧偏北气流沿着东亚大陆东部沿岸南下,并在中低纬度地区以回流的形式向东南推进,活动位置偏南偏西,使得云南全省、青藏高原和东南亚低纬度地区气温偏低,此时的低温过程主要与副热带波列的活动和青藏高原海平面气压(Surface level Pressure,SLP)的正距平加强有关,与乌拉尔山和西伯利亚地区的高压加强关系不密切。

东亚大槽和西伯利亚高压的季节内变率对冬季东亚气温的影响

基于气候态定义了西伯利亚高压指数(SH index)、东亚大槽指数(ET index)和高低压系统间的东亚经向风指数(V index),使用回归分析探究西伯利亚高压和东亚大槽在季节内尺度上对东亚地区冬季温度的影响机理,构建线性模型对冬季华南地区季节内尺度温度进行延伸期预报。结果表明:西伯利亚高压和东亚大槽系统变化中最显著的是季节内尺度信号;季节内尺度SH index和ET index对V index的贡献分别为82.6%和42.2%;3个指数的回归模态在对流层中层对应西北-东南向低频罗斯贝波列缓慢东南传播,低层水汽、近地面层环流、降水及2 m温度场配置良好,当西伯利亚高压深厚或东亚大槽发展时,经向风关键区北风强盛,有利于冬季高纬度地区干冷空气向东亚输送;V index对华南地区冬季季节内尺度2 m气温的有效预报时效达25 d。

近40年中国冬季寒潮的气候特征及大气环流异常

利用1980—2023年高分辨率中国气象站观测数据,根据寒潮标准及强度指数,对中国寒潮事件的强度及影响区域进行客观分类,探讨全国性、区域性寒潮事件的时空变化特征和环流演变。结果表明:近40年我国冬季寒潮频次呈显著减少趋势,其影响范围扩大,而强寒潮的强度呈显著增加趋势,且年际变化幅度明显增大。中国寒潮冷空气主要来源于新地岛东南地区,路径因寒潮类型而异。分析全国型、东北华北型和西北华北型寒潮前期和同期大气环流异常特征发现:格陵兰岛的异常深厚暖高压是全国型寒潮的重要前兆,欧亚大陆对流层中高层纬向波列是其爆发的显著特征;东北华北型寒潮与冷涡在中低纬度异常高压系统阻挡下的东移有关;西北华北型寒潮与东欧平原上空暖性高压脊的发展及欧亚大陆两脊一槽的形势密切相关。所有类型寒潮爆发前均有乌拉尔阻塞高压的维持和西伯利亚地区冷空气的堆积。

我国南方两次低温雨雪天气成因对比分析

2018年末和2021年末我国南方分别发生了一次大范围的低温雨雪天气,通过对比分析两次低温雨雪天气成因,结果表明:两次过程期间,对流层中层中高纬阻塞流场显著,阻高位于贝加尔湖西侧,脊前偏北气流在下游横槽后部堆积,使得西伯利亚高压强度增强。东传的Rossby波在阻高区域发生能量频散,利于阻高减弱、崩溃,横槽转竖引导槽后冷空气南下,导致地面强烈降温,同时在西伯利亚高压东侧和南侧,低频风温度平流是造成强降温的主要原因。低纬南支槽活跃,向北的暖湿空气与中高纬南下的冷空气汇合,造成我国南方大范围的低温雨雪、冻雨天气。与2018年过程相比,2021年过程持续时间较短,降水范围小,关键区域降温幅度更大,是因为2021年过程期间Rossby波能量频散更快,阻高维持时间较短,冷空气从中高纬地区直接南下侵袭我国,而2018年冷空气在贝加尔湖附近发生堆积、西折,向南渗透时势力减弱。

不同强度冷空气事件特征及对中国冬季温度的影响

利用1979-2019年美国国家环境预报中心-国家大气研究中心再分析资料,采用冷空气爆发指数和二维阻塞高压指数,筛选出3类不同强度的冷空气事件:高-中纬(H-M)、高-低纬(H-L)、中-低纬(M-L)事件和乌拉尔山阻塞高压(UBH)事件,分析冬季3类冷空气事件的演变特征、UBH背景下冷事件的基本特征及其对中国的降温效果.结果表明,H-M和M-L事件的频次在2000年前呈下降趋势,M-L事件的强度总体上呈减小趋势.UBH背景下,66.1%的冷空气事件强度较强(冷空气爆发指数≥2),46.4%的冷空气事件持续时间为1 d,H-L事件的平均持续时间最长(3.4 d).3类事件的冷空气通量在高纬欧亚大陆上空表现为由西伯利亚反气旋和东亚北部气旋组成的偶极型分布;阻塞高压影响下,偏北风加强,冷空气南下入口处的冷气团总量距平在事件开始前后最强达到110 hPa以上,50°N的温度负异常也受影响变得更加深厚,可以延伸到500 hPa以上;强的负热含量距平与强的地面温度异常对应,尤其在冷事件开始当天,50°N的负热含量距平远大于30°N.3类事件发生时,降温主要集中在中国北部和东部地区,H-L事件的降温效果最强,容易形成高纬至华南的穿透性冷空气事件.

中国沿海风能年际变化的区域性特征成因及其预测

基于ERA5的逐小时100m风场数据,利用时间序列K-means聚类方法,将中国沿海冬季风能年际变化划分为四个区域,分别为北中国海(NorthChina Sea,NCS)、东海(East China Sea,ECS)、南海北部(Northern South China Sea,NSCS)及南海南部(SouthernSouthChinaSea,SSCS)。四个区域风能的年际变化受不同气候模态的影响,其中NCS风能的年际变化与北极涛动(ArcticOscillation,AO)有关;ECS风能的年际变化与中部型ENSO及西伯利亚高压有关;SSCS和NSCS的年际变化则和东部型ENSO及大陆高压的南北位置存在联系。鉴于影响各区域风能年际变化的气候模态具有较高的可预测性,进一步评估了多个气候模式对中国沿海风能年际变化的预测技巧。结果表明,气候模式对南中国海的风能年际变化预测技巧更高,这与气候模式对ENSO的高预测技巧有关。气候模式对北方海域风能年际变化的预测技巧较差,这和气候模式不能较好地预测AO和西伯利亚高压有关。

Predominant types of regional cold waves in North China and their historical changes

寒潮事件对东亚地区的社会经济,生态系统和人体健康影响巨大.根据1980-2019年间10月至次年3月的每日寒潮记录和K-means聚类,本文识别出了中国两种不同类型的区域性寒潮(T1和T2). T1区域性寒潮主要影响东北地区,T2区域性寒潮则主要影响华北和东部地区.与T1区域性寒潮相比, T2区域性寒潮强度更强,持续时间更长,影响范围更广. 1980–2019年期间, T1区域性寒潮的频率显著增加,而T2区域性寒潮的频率则没有趋势变化. T1和T2区域性寒潮事件均与西伯利亚高压增强有关,然而与它们相关的对流层中层波列明显不同.在T1区域性寒潮事件发生期间,西伯利亚-蒙古上空出现负-正模态的500-hPa位势高度异常波列,削弱了东亚大槽,导致西伯利亚冷空气东移.T1区域寒潮频次增加趋势可能与全球变暖引起的500-hPa位势高度的线性趋势变化有关.与T2区域寒潮事件相关的波列则在乌拉尔山脉,蒙古和华北地区形成了脊-槽-脊环流异常,导致冷空气向东南方向入侵.本文得出结论,由于两类区域寒潮影响不同,西伯利亚高压增强和对流层中层波列模态在我国区域性寒潮事件的预报中应综合考虑.

Interdecadal changes in the frequency of winter extreme cold events in North China during 1989–2021

全球变暖背景下,极端天气气候事件的变化受到关注.本文研究发现, 1989-2021年期间,华北地区极端冷日数在2003和2013年发生了年代际变化.极端冷日数先增加后减少. 2003-2012年,西伯利亚-乌拉尔高压偏强,极地西风急流偏弱,有利于冷空气南下入侵华北地区,华北极端冷日数偏多.而在1989-2002年和2013-2021年,情况相反.虽然三个时段华北极端冷日的强度没有显著差异,但与其相联系的冷空气强度变得更强, 2013-2021年冷空气中心区域往西北扩张到了贝加尔湖以西地区.

西伯利亚高压对亚洲大陆的气候影响分析

西伯利亚高压是冬季影响亚洲大陆地区的重要环流因子 ,本文用冬季 (1～ 3月 ) 70°～ 12 0°E ,40°～ 6 0°N区域平均海平面气压值代表其强度 ,分析其变化特征。结果表明 ,从 192 2年到 1970年代中期 ,西伯利亚高压略有增强趋势 ,但并不显著。但近 2 0多年来的显著减弱非常突出。用NCAR资料计算的线性趋势是 - 1.78hPa/ 10a(1976— 2 0 0 0年 ) ,用CRU气压资料计算的趋势是 - 2 .15hPa/ 10a(1976— 1995年 )。西伯利亚高压对中高纬亚洲大陆平均 (30°～ 140°E ,30°～ 70°N)温度和降水都有显著影响 ,与两个要素的相关系数分别达到 - 0 .5 8和 - 0 .44。如果同时考虑其他的影响因子 (如北极涛动、欧亚遥相关型等 ) ,72 %的温度变化及 2 6 %的降水变化能得到解释。其中北极涛动对亚洲大陆的温度贡献最高达到 30 % ,西伯利亚高压的贡献为 2 4%。而区域平均降水变化的 9.

东亚2005年和2006年冬季风异常及其与准定常行星波活动的关系

利用NCEP/NCAR再分析资料系统地分析了2005年与2006年冬季欧亚大陆的气温和东亚冬季风的差别及其与北半球准定常波活动的关系。分析结果表明:2005年冬季欧亚大陆中、高纬度地区气温偏低,东亚冬季风偏强;而2006年冬季欧亚大陆中、高纬度地区气温偏高,出现暖冬,东亚冬季风偏弱。分析结果还表明,这两年冬季东亚冬季风的差别不仅是由于西伯利亚高压和阿留申低压的变异所造成,而且是由于北极涛动(北半球环状模)的变化所造成。并且,作者还从这两年冬季北半球准定常行星波活动的差异,在动力理论上进一步讨论了这两年冬季北半球气候和东亚冬季风差异的机理。结果表明:2005年冬季北半球行星波活动为低指数,准定常行星波在高纬度往平流层传播加强,而往低纬度对流层上层传播减弱,造成了行星波E-P通量在高纬度地区对流层中、上层辐合加强,而在副热带地区对流层中、上层辐散加强,引起了北半球高纬度地区极锋急流减弱,而副热带急流加强,这有利于西伯利亚高压的发展,从而引起了东亚冬季风增强;相反,2006年冬季北半球行星波活动为高指数,准定常行星波在高纬度往平流层传播减弱,而往低纬度对流层上层传播加强,造成了行星波E-P通量在高纬度地区对流层中、上层辐散加强,而在副热带地区对流层中、上层辐合加强,引起了北半球高纬度地区极锋急流加强,而副热带急流减弱,这不利于西伯利亚高压的发展,从而引起了东亚冬季风减弱。

气候因子对渤海冰情影响的统计分析

运用相关分析、偏相关分析等统计分析方法研究了北极涛动、北极海冰和西伯利亚高压等气候因子对渤海海冰年际变化的影响。统计表明西伯利亚高压是影响渤海海冰年际变化最重要的因子。秋季北极海冰密集度、冬季北极涛动与渤海冰情显著相关,它们可能通过影响西伯利亚高压的强度,从而影响渤海海冰的严重程度。利用回归分析得到渤海冰情等级与西伯利亚高压、西太平洋副高之间的统计关系,回归结果较好的反映了渤海冰情年际变化。

影响我国冬季温度的若干气候因子

综合分析了西伯利亚高压、北极涛动、ENSO和西太平洋遥相关型(WP)在年际和年代际时间尺度上对中国冬季温度的影响,结果表明在年际尺度上,WP和西伯利亚高压都对温度有显著影响,WP的影响主要存在于中国东部从东北南部至广东沿海一带大陆边缘区,而西伯利亚高压的影响范围则大得多,几乎涵盖了除黄河长江上游部分地区外的整个中国。在年代际尺度上,北极涛动和ENSO都与东亚冬季风有关联,北极涛动比ENSO的影响范围大,除长江上游沿江地区外的其他地区基本上都是关联区,ENSO与温度的关联区位于35°N以北的整个北方及长江中下游地区。