土壤湿度年际变化对中国区域极端气候事件模拟的影响研究Ⅱ.敏感性试验分析

利用NCARCAM3.1大气环流模式,设计了有、无土壤湿度年际异常的两组数值试验,探讨了土壤湿度年际异常对极端气候事件模拟的可能影响。结果表明,模式模拟的极端气候事件对土壤湿度异常十分敏感,土壤湿度异常对极端气候指标的多年平均空间分布、年际变率以及年际变化均具有重要影响。当不考虑土壤湿度的年际异常时:(1)模拟的暖夜日数、暖昼日数和热浪持续指数的发生频次在全国范围内均明显减少,而霜冻日数则明显增加。极端降水指标的响应表现出明显的空间差异,极端降水频次在江淮流域明显减小,而极端降水强度则表现为东北减弱、长江流域增强;中雨日数和持续湿期在我国大部分地区减少。(2)极端气温指标的年际变率在我国大部分地区呈减小趋势;而极端降水事件的变化则较为复杂,极端降水频次和极端降水强度的年际变率在长江以南有所增强,而北方地区则有所减弱。中雨日数和持续湿期的年际变率在我国呈现出较为一致的减少趋势。(3)模式对暖夜日数、霜冻日数的年际变化的模拟能力明显下降,并对4个极端降水指标的年际变化的模拟能力在全国多数区域均有不同程度的下降。     

年际气候变率的数值模拟

本文利用IAP GCM 20年的模式输出结果，计算了海平面气压、表面气温和降水的年际气候变率，并与观测资料作了对比分析，以考察模式模拟年际变率的能力。结果表明，模式成功地再现了观测变率地理分布的基本特征，这说明大气内部动力-物理相互作用过程对年际变率有重要影响，而模拟值的偏低则显示了模式中未包括的某些外界强迫因子如海温和海冰年际变化的潜在作用。     

Sea ice in the Barents Sea: seasonal to interannual variability and climate feedbacks in a global coupled model

Sea ice variability in the Barents Sea and its impact on climate are analyzed using a 465-year control integration of a global coupled atmosphere–ocean–sea ice model. Sensitivity simulations are performed to investigate the response to an isolated sea ice anomaly in the Barents Sea. The interannual variability of sea ice volume in the Barents Sea is mainly determined by variations in sea ice import into Barents Sea from the Central Arctic. This import is primarily driven by the local wind field. Horizontal oceanic heat transport into the Barents Sea is of minor importance for interannual sea ice variations but is important on longer time scales. Events with strong positive sea ice anomalies in the Barents Sea are due to accumulation of sea ice by enhanced sea ice imports and related NAO-like pressure conditions in the years before the event. Sea ice volume and concentration stay above normal in the Barents Sea for about 2 years after an event. This strongly increases the albedo and reduces the ocean heat release to the atmosphere. Consequently, air temperature is much colder than usual in the Barents Sea and surrounding areas. Precipitation is decreased and sea level pressure in the Barents Sea is anomalously high. The large-scale atmospheric response is limited with the main impact being a reduced pressure over Scandinavia in the year after a large ice volume occurs in the Barents Sea. Furthermore, high sea ice volume in the Barents Sea leads to increased sea ice melting and hence reduced surface salinity. Generally, the climate response is smallest in summer and largest in winter and spring.     

Potential impacts of East Asian winter monsoon on climate variability and predictability in the Australian summer monsoon region

This study explores potential impacts of the East Asian winter monsoon (EAWM) on summer climate variability and predictability in the Australia–Asian region through Australia–Asia (A-A) monsoon interactions. Observational analysis is conducted for the period of 1959 to 2001 using ERA-40 wind reanalysis and Climate Research Unit rainfall and surface temperature monthly datasets. Statistically significant correlations are established between the Australian summer monsoon and its rainfall variations with cross-equatorial flows penetrating from South China Sea region and northerly flow in the EAWM. The underlying mechanism for such connections is the response of the position and intensity of Hardley circulation to strong/weak EAWM. A strong EAWM is associated with an enhanced cross-equatorial flow crossing the maritime continent and a strengthened Australia summer monsoon westerlies which affect rainfall and temperature variations in northern and eastern part of the Australian continent. Furthermore, partial correlation analysis, which largely excludes El Niño-Southern Oscillation (ENSO) effects, suggests that these connections are the inherent features in the monsoon system. This is further supported by analyzing a global model experiment using persistent sea surface temperatures (SSTs) which, without any SST interannual variations, shows similar patterns as in the observational analysis. Furthermore, such interaction could potentially affect climate predictability in the region, as shown by some statistically significant lag correlations at monthly time scale. Such results are attributed to the impacts of EAWM on regional SST variations and its linkage to surface conditions in the Eurasian continent. Finally, such impacts under global warmed climate are discussed by analyzing ten IPCC AR4 models and results suggest they still exist in the warmed climate even though the EAWM tends to be weaker.     

The influence of the North Atlantic on climate variations in the Barents Sea and their predictability

The effects of Atlantic water inflow on the climate variability in the Barents Sea are studied. Initial data are the series of water temperature at the Kola meridian cross-section, monthly values of ice extent, air temperature at the stations, sea level pressure from the reanalysis data, and sea surface temperature. The methods of multivariate correlation, spectral, and factor analysis and EOF decomposition are used. It was found that variations in the Atlantic water inflow define the main part of interannual variability of sea ice extent, water temperature, and air temperature in the Barents Sea in the cold season. The influence of regional atmospheric circulation on the interannual variability of these parameters is small. The effects that water temperature anomalies in the area of Newfoundland and in the equatorial part of the North Atlantic have on climate parameters in the Barents Sea are discovered. The response of these parameters lags behind the respective anomalies by 9-58 months. The high correlation between them makes it possible to develop the method of statistical forecasting of sea ice extent and water temperature in the Barents Sea with the lead time up to 4 years.     

土壤湿度年际异常对中国春、夏季气候模拟的影响

基于NCAR大气模式CAM3.1模式,设计了有、无土壤湿度年际异常两组试验对中国区域近40a(1961-2000年)气候进行了模拟。从气候态和年际变率的角度,通过分析两组试验的差值场来探讨土壤湿度年际异常对气候模拟的影响,并初步探讨了影响的可能机制。结果表明:模式模拟的温度和降水对土壤湿度的年际异常非常敏感,土壤湿度的年际变化对中国春夏季气候及其年际变率均有显著影响。当不考虑土壤湿度年际异常时,模式模拟的春夏季平均温度、最高温度、最低温度在我国大范围内降低,春夏季降水在东部大部分地区明显减少,西部增加。而模式模拟的春夏季温度、降水年际变率在中国大部分地区减弱。但当考虑土壤湿度的年际变化,则能在一定程度上提高模式对气候年际变率的模拟能力。在进一步分析表明土壤湿度年际异常时,主要通过改变地表能量通量和环流场,对温度、降水产生影响。当不考虑土壤湿度年际异常时,地表净辐射通量减少,地表温度降低,感热通量减少。感热通量差值场的空间变化和温度差值场的空间变化一致,感热通量对温度有一定影响。而潜热通量差值场的空间变化和降水的差值场的空间变化一致,可见降水受地表潜热通量的影响。土壤湿度年际异常引起的环流场的变化也是导致气候变化的原因之一,地表能量和环流场年际变率的改变对春夏季气候年际变率存在一定影响。     

Observed dependence of the water vapor and clear-sky greenhouse effect on sea surface temperature: comparison with climate warming experiments

This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.     

全球海温异常年代际分量的方差贡献及其与中国气候异常的相关

将全球海洋海表温度异常 (SSTA) 分解为年代际、年际变化两部分, 用方差分析法给出年代际变化分量显著的洋区及其季节变化, 用奇异值分解 (SVD) 方法分析了它与中国冬温 (冬季平均气温)、夏雨 (夏季总降水量) 年代际异常分量的同期和时滞相关联系的时空结构。结果表明, 无论冬、夏, SSTA的方差构成中, 年代际变化分量方差均较年际变化分量显著; SSTA年代际分量正异常时, 中国 (以北方和东部为主) 易出现一致的冬温正异常, 长江流域、华南夏雨易出现正异常, 而华北夏雨易出现负异常; 反之亦然。     

全球气温与ENSO多年际耦合振荡关系的初步研究

借助于最优分割法和多通道奇异谱分析（MSSA）等方法对全球气候变化背景场阶段性变化及其与ENSO振荡信号的相互关系作了详细的诊断分析。结果表明：（1）全球近百年气温长期变化阶段性明显，各阶段之间的气候变率特征差异较大；（2）全球气温变化背景场的阶段性对ENSO的年际及年代际准周期振荡有较为明显的影响；（3）全球气温与Nino区海温的年际变率存在着准4年和准2年的显著耦合振荡。     

Cloudiness over the Black Sea region in 1985–2009 from satellite data

The seasonal and interannual variability ofcloud fraction over the Black Sea region for the period of1985-2009 is analyzed using the CM SAF dataset obtained from the satellite measurements of a high-resolution AVHRR instrument. The features of geographic distribution and seasonal variations in cloudiness are investigated. The causes for its spatial inhomogeneity in different months are analyzed. It is demonstrated using the long-term dataset that the dramatic decrease in the amount of cloudiness occurred over the Black Sea region from 67% in 1985 to 54% in 2008. The value of the trend is -0.4% per year. Both the trends and the features of interannual variability of cloudiness, in particular, strongly pronounced four-year cycles, are in antiphase with variations in sea surface temperature. The cloudiness reduction accompanied by the increase in the influx of short-wave radiation may be the basic reason for the warming and sea surface temperature variations in the Black Sea region.     

Climate Variability-Observations, Reconstructions, and Model Simulations for the Atlantic-European and Alpine Region from 1500-2100 AD

A detailed analysis is undertaken of the Atlantic-European climate using data from 500-year-long proxy-based climate reconstructions, a long climate simulation with perpetual 1990 forcing, as well as two global and one regional climate change scenarios. The observed and simulated interannual variability and teleconnectivity are compared and interpreted in order to improve the understanding of natural climate variability on interannual to decadal time scales for the late Holocene. The focus is set on the Atlantic-European and Alpine regions during the winter and summer seasons, using temperature, precipitation, and 500 hPa geopotential height fields. The climate reconstruction shows pronounced interdecadal variations that appear to “lock” the atmospheric circulation in quasi-steady long-term patterns over multi-decadal periods controlling at least part of the temperature and precipitation variability. Different circulation patterns are persistent over several decades for the period 1500 to 1900. The 500-year-long simulation with perpetual 1990 forcing shows some substantial differences, with a more unsteady teleconnectivity behaviour. Two global scenario simulations indicate a transition towards more stable teleconnectivity for the next 100 years. Time series of reconstructed and simulated temperature and precipitation over the Alpine region show comparatively small changes in interannual variability within the time frame considered, with the exception of the summer season, where a substantial increase in interannual variability is simulated by regional climate models.     

Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model

The results are analyzed of the ensemble forecast of temperature and precipitation extremes on the territory of Siberia by the middle of the 21st century based on the regional climate model of the Main Geophysical Observatory (MGO) with the resolution of 25 km. The results of computation of oceanic components of CMIP3 coupled models are used as the boundary conditions on the sea surface. It is demonstrated that the high resolution of the regional model enables to simulate the observed climate variability in a more realistic way as compared to the low-resolution models. The analysis of the signal-to-noise ratio for future climate changes made it possible to determine to which degree its internal variability for various time scales (from interannual to interdecennial one) bounds the potential of the ensemble to compute the statistically significant anthropogenic changes of extremes. A comparative analysis of variations of extreme and average seasonal characteristics of the Siberian climate is carried out.     

土壤湿度年际变化对中国区域极端气候事件模拟的影响研究 I. 基于CAM3.1的模式评估

利用NCAR大气模式CAM3.1对中国区域近40年的极端气候事件进行了模拟试验;在此基础上, 利用1961～2000年中国区域452站的逐日最高、最低气温和降水资料, 从气候平均、年际变化和长期变化趋势等方面全面评估了该模式对中国极端气候事件的模拟能力。结果表明:(1)模式对中国区域极端气候指数气候平均态的大尺度空间分布特征具有一定的模拟能力;模式对极端降水指标空间分布的模拟能力较好, 而对极端气温指标的模拟较差;模式对极端气候指标的模拟存在系统性的偏差, 模拟的极端降水的系统性偏差要远大于对极端温度的模拟。(2)模式对极端气温指数的年际变化特征具有较强的模拟能力, 而对极端降水指数的年际变化基本没有模拟能力;模式模拟的各极端降水指标的年际变幅与观测存在较大的偏差。(3)模式较好地模拟出了暖夜和暖昼指数在中国大部分区域的增加趋势, 但变幅较实测偏小;模式对热浪持续指数长期趋势的模拟则相对略差。模式对极端气温指标长期趋势的模拟能力总体优于对极端降水指标的模拟。模式对极端降水频次和中雨日数长期趋势的模拟尚可, 但对持续湿期长期趋势的空间分布模拟较差。研究结果可为该模式用于极端气候的模拟研究提供一定参考。     

Modelling the dominant climate signals around southern Africa

In this study, statistical techniques are employed to decompose climate signals around southern Africa into the dominant temporal frequencies, with the aim of modelling and predicting area-averaged rainfall. In the rainfall time series over the period 1900–1999, the annual cycle accounts for 83% of variance. Residual spectral energy cascades from biennial (42%) to interannual (20%) to decadal bands (3%). Regional climate signals are revealed through a multi-taper singular value decomposition analysis of sea surface temperature and sea level pressure fields over the Atlantic and Indian Oceans, in conjunction with southern Africa rainfall. Rossby wave action in the South Indian Ocean dominates the biennial scale variability. El Niño-Southern Oscillation (ENSO) and related Indian Ocean dipole patterns are important for interannual variability. Significant sea temperature and pressure fluctuations occurring 6–12 months prior to rainfall contribute biennial and interannual indices to a multi-variate model that demonstrates useful predictive skill.     

冬季和春季印度洋海温异常年际变率模态对中国东部夏季降水的可能影响过程

印度洋热力状况是影响全球气候变化和亚洲季风变异的一个重要的因素,但以往研究更多关注热带印度洋海温的变化,对南印度洋中高纬地区海温变化关注不够,由此限制了我们对印度洋的全面认识.本文研究了年际尺度上整个印度洋海温异常主导模态的特征及其对我国东部地区夏季降水的可能影响过程,以期望为气候变异研究及预测提供理论依据.研究结果表明:全印度洋海温异常年际变率的主导模态特征是在南印度洋副热带地区海温异常呈现西南—东北反向变化的偶极子模态,西极子位于马达加斯加以东南洋面,东极子位于澳大利亚以西洋面;同时,热带印度洋海温异常与东极子一致.当西极子为正的海温异常,东极子、热带印度洋为负异常时定义为正的印度洋海温异常年际变率模态;反之,则为负的印度洋海温异常年际变率模态.从冬至春,印度洋海温异常年际变率模态具有较好的季节持续性;与我国长江中游地区夏季降水显著负相关,而与我国华南地区夏季降水显著正相关.其可能的影响过程为:对于正的冬、春季印度洋海温异常年际变率模态事件,印度洋地区异常纬向风的经向大气遥相关使得热带印度洋盛行西风异常,导致春、夏季海洋性大陆对流减弱,使夏季西太平洋副热带高压强度偏弱、位置偏东偏北,造成华南地区夏季降水增多,长江中游地区降水减少;反之亦然.同时,印度洋海温异常年际变率模态可通过改变印度洋和孟加拉湾向长江中游地区的水汽输送而影响其夏季降水.     

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。     

Dominant Modes of Interannual Variability in Atmospheric Water Vapor Content over East Asia during Winter and Their Associated Mechanisms

Atmospheric water vapor content(WVC) is a critical factor for East Asian winter precipitation. This study investigates the dominant modes of interannual variability in WVC over East Asia during winter and their underlying mechanisms.Based on the empirical orthogonal function(EOF) method, the leading mode(EOF1, R~2 = 28.9%) of the interannual variability in the East Asian winter WVC exhibits a meridional dipole pattern characterized by opposite WVC anomalies over northeastern China and eastern China; the second mode(EOF2, R~2 = 24.3%) of the interannual variability in the East Asian winter WVC exhibits a monopole pattern characterized by consistent WVC anomalies over eastern China. EOF1 is mainly modulated by two anomalous zonal water vapor transport(WVT) branches over northeastern China and eastern China, which are associated with an anomalous atmospheric wave train over Eurasia affected by sea ice cover in the Kara Sea-Barents Sea(SIC-KSBS) area in the preceding October-November(ON). EOF2 is mainly modulated by an anomalous westerly WVT branch over eastern China, which is associated with a circumglobal atmospheric zonal wave train in the Northern Hemisphere. This circumglobal zonal wave train is modulated by concurrent central and eastern tropical Pacific sea surface temperature anomalies. The SIC-KSBS anomalies in ON and the concurrent SST anomalies over tropical Pacific may partially account for the interannual variability of EOF1 and EOF2 winter WVC, and thus may provide a theoretical basis for improving the prediction of winter climate over East Asia.     

Relevance of soil moisture for seasonal atmospheric predictions: is it an initial value problem?

Ensembles of boreal summer atmospheric simulations, spanning a 15-year period (1979–1993), are performed with the ARPEGE climate model to investigate the influence of soil moisture on climate variability and potential predictability. All experiments are forced with observed monthly mean sea surface temperatures. In addition to a control experiment with interactive soil moisture boundary conditions, two sensitivity experiments are performed. In the first, the interannual variability of the deep soil moisture is removed during the whole season, through a relaxation toward the monthly mean model climatology. In the second, only the variability of the initial soil moisture conditions is suppressed. While it is shown that soil moisture strongly contributes to the climate variability simulated in the control experiment, an analysis of variance indicates that soil moisture does not represent a significant source of predictability in most continental areas. The main exception is the North American continent, where climate predictability is clearly reduced through the use of climatological initial conditions. Using climatological soil moisture boundary conditions does not lead to strong and homogeneous impacts on potential predictability, thereby suggesting that the climate signals driven by the sea surface temperature variability are not generally amplified by interactive soil moisture and that the relevance of soil moisture for seasonal forecasting is mainly an initial value problem.     

Assessment of the Capability of ENSEMBLES Hindcasts in Predicting Spring Climate in China

Using the hindcasts provided by the Ensemble-Based Predictions of Climate Changes and Their Impacts(ENSEMBLES) project for the period of 1980–2005, the forecast capability of spring climate in China is assessed mainly from the aspects of precipitation, 2-m air temperature, and atmospheric circulations. The ENSEMBELS can reproduce the climatology and dominant empirical orthogonal function(EOF) modes of precipitation and 2-m air temperature, with some differences arising from different initialization months. The multi-model ensemble(MME) forecast of interannual variability is of good performance in some regions such as eastern China with February initialization.The spatial patterns of the MME interannual and inter-member spreads for precipitation and 2-m air temperature are consistent with those of the observed interannual spread, indicating that internal dynamic processes have major impacts on the interannual anomaly of spring climate in China. We have identified two coupled modes between intermember anomalies of the 850-hPa vorticity in spring and sea surface temperature(SST) both in spring and at a lead of 2 months, of which the first mode shows a significant impact on the spring climate in China, with an anomalous anticyclone located over Northwest Pacific and positive precipitation and southwesterly anomalies in eastern China.Our results also suggest that the SST at a lead of two months may be a predictor for the spring climate in eastern China. A better representation of the ocean–atmosphere interaction over the tropical Pacific, Northwest Pacific, and Indian Ocean can improve the forecast skill of the spring climate in eastern China.     

Regional features of long-term variability of the Black Sea surface temperature

The regional features oflong-term variability ofsea surface temperature (SST) in the Black Sea are analyzed using the satellite data for 1982-2014. It is demonstrated that the maximum intraannual and interannual variability of SST is registered on the northwestern shelf of the Black Sea. The high level of interannual variability of SST and maximum linear trends are observed in the northeastern part of the sea. The qualitative connection is revealed between the long-term variability of SST and the variations in the intensity of the Black Sea Rim Current in the long-term seasonal cycle. An increase in the level of interannual variability of SST is observed in summer, when the Black Sea Rim Current weakens. The significant negative correlation is revealed between the interannual anomalies of SST and the NAO index. The highest correlation coefficients are obtained for the eastern part of the Black Sea and near the Crimean coast.