The influence of the Arctic Oscillation on winter temperatures in Iran

Summary The impact of the Arctic Oscillation (AO) on the winter surface air temperature (SAT) over Iran is demonstrated. Winter SAT data for 50 years (1951–2000) are analyzed for the negative and the positive AO phases. Using the Median Sequential Correlation Analysis (MSCA) technique it is shown that the winter SAT is negatively correlated to the winter AO index for most parts of Iran. The winter AO index accounts for about 14% to 46% of the winter SAT variance. The positive (negative) SAT anomaly is found to be associated with the onset of the negative (positive) phase. The overall probability of below long-term mean temperature during the positive and the negative phases are estimated to be around 70% and 25%, respectively. For the negative phase, westerly winds that originate from the warm Atlantic regions increase over Iran and consequently positive temperature anomalies are found across the country. The positive AO phase is accompanied by northerly winds that allow continental polar and arctic air masses to move into Iran, producing below normal temperatures. The summer AO is found to explain about 25–32% of the winter SAT variance in Iran. The reason for this is explained by the significant correlation (+0.38) between the summer and the following winter AO indices. These results indicate that the summer climate is linked to changes in atmospheric circulation which persist through to the following autumn and winter.     

Indicators of Climate Change for the Russian Federation

Observed climate changes over the Russian Federation (RF) territory are considered. Several indicators based on monthly mean temperature and precipitation station data are used to quantify regional climate changes. Some of these are the components of two aggregated indices of climate change, suggested by Karl et al. (1996): the Climate Extremes Index (CEI) and the Greenhouse Climate Response Index (GCRI). For the RF territory as a whole, and for its western part, the "Russian Permafrost Free (RPF) territory" in particular, changes in surface air temperature are investigated, together with changes in precipitation and drought indices, and also the fraction of the Russian territory experiencing climatic anomalies below and/or above certain specified percentiles. Composite indices CEI-3 and GCRI-3 based on three parameters (air temperature, precipitation and drought indices) are examined, as well as the Climate Anomaly Index (CAI), known in Russia as Bagrov's coefficient of "anomality".It is shown, that over the area of the RPF as a whole, air temperature and the occurrence of drought has increased somewhat during the 20th century, while precipitation has decreased; these changes were non-uniform in space. The linear trend accounts for only a small fraction of the total variability, but the role of climate variations on decadal scales seems more substantial. The CEI, determined as the percentage of the area experiencing extreme anomalies (with a 10% or less frequency of occurrence) of either sign, increased for mean annual temperature, decreased for total precipitation and increased slightly for the occurrence of drought conditions; the aggregated index based on all three of these quantities increased slightly. There was also an increase in the GCRI-3 index, which is indicative of an agreement between the observed climate changes and the changes owing to the greenhouse effect as predicted by climatic models.The observed climate changes are too small to enable us confidently to reject a hypothesis that they are a reflection of the natural variability of climatic parameters within the context of a stationary climate. However, there is no doubt about the reality and importance of the observed changes.     

Impact of the Winter North Pacific Oscillation on the Surface Air Temperature over Eurasia and North America: Sensitivity to the Index Definition

This study analyzes the impact of the winter North Pacific Oscillation(NPO) on the surface air temperature(SAT)variations over Eurasia and North America based on six different NPO indices. Results show that the influences of the winter NPO on the SAT over Eurasia and North America are sensitive to the definition of the NPO index. The impact of the winter NPO on the SAT variations over Eurasia(North America) is significant(insignificant) when the anticyclonic anomaly associated with the NPO index over the North Pacific midlatitudes shifts westward and pronounced northerly wind anomalies appear around Lake Baikal. By contrast, the impact of the winter NPO on the SAT variations over Eurasia(North America)is insignificant(significant) when the anticyclonic anomaly over the North Pacific related to the NPO index shifts eastward and the associated northerly wind anomalies to its eastern flank extend to North America. The present study suggests that the NPO definition should be taken into account when analyzing the impact of the winter NPO on Eurasian and North American SAT variations.     

Climate change in the northeastern US: regional climate model validation and climate change projections

A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Different types of uncertainties in climate simulations are examined by driving the RCM with different boundary data, applying different emissions scenarios, and running an ensemble of simulations with different initial conditions. Empirical orthogonal functions analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature (SAT) and precipitation variability. The RCM simulations tend to overestimate SAT, especially over the northern part of the domain in winter and over the western part in summer. Statistically significant increases in seasonal SAT under both higher and lower emissions scenarios over the whole RCM domain suggest the robustness of future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, though the changes are not statistically significant. The greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change.     

An Approach to Quantify the Heat Wave Strength and Price a Heat Derivative for Risk Hedging

Mitigating the heat stress via a derivative policy is a vital financial option for agricultural producers and other business sectors to strategically adapt to the climate change scenario. This study has provided an approach to identifying heat stress events and pricing the heat stress weather derivative due to persistent days of high surface air temperature (SAT). Cooling degree days (CDD) are used as the weather index for trade. In this study, a call-option model was used as an example for calculating the price of the index. Two heat stress indices were developed to describe the severity and physical impact of heat waves. The daily Global Historical Climatology Network (GHCN-D) SAT data from 1901 to 2007 from the southern California, USA, were used. A major California heat wave that occurred 20-25 October 1965 was studied. The derivative price was calculated based on the call-option model for both long-term station data and the interpolated grid point data at a regular 0.1 ×0.1 latitude-longitude grid. The resulting comparison indicates that (a) the interpolated data can be used as reliable proxy to price the CDD and (b) a normal distribution model cannot always be used to reliably calculate the CDD price. In conclusion, the data, models, and procedures described in this study have potential application in hedging agricultural and other risks.     

Simple metrics for representing East Asian winter monsoon variability: Urals blocking and western Pacific teleconnection patterns

Instead of conventional East Asian winter monsoon indices(EAWMIs), we simply use two large-scale teleconnection patterns to represent long-term variations in the EAWM. First, the Urals blocking pattern index(UBI) is closely related to cold air advection from the high latitudes towards western Siberia, such that it shows an implicit linkage with the Siberian high intensity and the surface air temperature(SAT) variations north of 40?N in the EAWM region. Second, the well-known western Pacific teleconnection index(WPI) is connected with the meridional displacement of the East Asian jet stream and the East Asian trough. This is strongly related to the SAT variations in the coastal area south of 40?N in the EAWM region.The temperature variation in the EAWM region is also represented by the two dominant temperature modes, which are called the northern temperature mode(NTM) and the southern temperature mode(STM). Compared to 19 existing EAWMIs and other well-known teleconnection patterns, the UBI shows the strongest correlation with the NTM, while the WPI shows an equally strong correlation with the STM as four EAWMIs. The UBI–NTM and WPI–STM relationships are robust when the correlation analysis is repeated by(1) the 31-year running correlation and(2) the 8-year high-pass and low-pass filter. Hence,these results are useful for analyzing the large-scale teleconnections of the EAWM and for evaluating this issue in climate models. In particular, more studies should focus on the teleconnection patterns over extratropical Eurasia.     

Simulation of Climate and Weather Extreme Indices with the INM-CM5 Climate Model

The simulation of extreme weather indices with the INM-CM5 and INMCM4 climate models for modern climate which were developed in the Institute of Numerical Mathematics of Russian Academy of Sciences is considered. It is shown that the INM-CM5 model improved the simulation of almost all indices concerning temperature (especially to its minimum values) and precipitation (mean total precipitation, mean precipitation intensity) extremes and concerning consecutive dry days and consecutive wet days. At the same time, the simulation of indices connected with extreme heavy precipitation became worse. It was found that this shortcoming can be minimized by introducing the vertical mixing of horizontal wind for the large-scale condensation and deep convection.     

Monthly Changes in the Influence of the Arctic Oscillation on Surface Air Temperature over China

Partial Least Squares Regression （PLSR） is used to study monthly changes in the influence of the Arctic Oscillation （AO） on spring, summer and autumn air temperature over China with the January 500 hPa geopotential height data from 1951 to 2004 and monthly temperature data from January to November at 160 stations in China. Several AO indices have been defined with the 500-hPa geopotential data and the index defined as the first principal component of the normalized geopotential data is best to be used to study the influence of the AO on SAT （surface air temperature） in China. There are three modes through which the AO in winter influences SAT in China. The influence of the AO on SAT in China changes monthly and is stronger in spring and summer than in autumn. The main influenced regions are Northeast China and the Changjiang River drainage area.     

Construction and Application of a Climate Risk Index for China

In the context of global warming, China is facing with increasing climate risks. It is imperative to develop quantitative indices to reflect the climate risks caused by extreme weather/climate events and adverse climatic conditions in association with different industries. Based on the observations at 2288 meteorological stations in China and the meteorological disasters data, a set of indices are developed to measure climate risks due to water-logging, drought, high temperature, cryogenic freezing, and typhoon. A statistical method is then used to construct an overall climate risk index (CRI) for China from these individual indices. There is a good correspondence between these indices and historical climatic conditions. The CRI, the index of water-logging by rain, and the high temperature index increase at a rate of 0.28, 0.37, and 0.65 per decade, respectively, from 1961 to 2016. The cryogenic freezing index is closely related to changes in the consumer price index for food. The high temperature index is correlated with the consumption of energy and electricity. The correlation between the yearly growth in claims on household property insurance and the sum of the water-logging index and the typhoon index in the same year is as high as 0.70. Both the growth rate of claims on agricultural insurance and the annual growth rate of hospital inpatients are positively correlated with the CRI. The year-on-year growth in the number of domestic tourists is significantly negatively correlated with the CRI in the same year. More efforts are needed to develop regional CRIs.     

The nonlinear association between the Arctic Oscillation and North American winter climate

Nonlinear projections of the Arctic Oscillation (AO) index onto North American winter (December–March) 500-mb geopotential height (Z500) and surface air temperature (SAT) anomalies reveal a pronounced asymmetry in the atmospheric patterns associated with positive and negative phases of the AO. In a linear view, the Z500 anomaly field associated with positive AO resembles a positive North Atlantic Oscillation pattern with statistically significant positive and negative anomalies stretching zonally into central-eastern USA and Canada, respectively, resulting in a cold climate anomaly over northeastern and eastern Canada, Alaska and the west coast of USA, and a warm climate anomaly over the rest of the continent. By contrast, the nonlinear behavior, mainly a quadratic association with AO, which is most apparent when the amplitude of the AO index is large, has the same spatial pattern and sign for both positive and negative values of the index. The nonlinear pattern reveals negative Z500 anomalies over the west coast of USA and the North Atlantic and positive Z500 anomalies at higher latitudes centered over the Gulf of Alaska and northeastern Canada accompanied by cooler than normal climate over the USA and southwestern Canada and warmer than normal climate over other regions of the continent. A similar analysis is conducted on the data from the Canadian Center for Climate Modelling and Analysis second generation coupled general circulation model. The nonlinear patterns of North American Z500 and SAT anomalies associated with the AO in the model simulation are generally consistent with the observational results, thereby confirming the robustness of the nonlinear behavior of North American winter climate with respect to the AO in a climate simulation that is completely independent of the observations.     

1951-2005年中国区域气候变化与干旱化趋势

摘 要：利用1951-2006年中国区域160个站的月降水及月平均气温资料,对中国区域近56 a气候要素的变化及其与干旱化联系的事实进行了分析。结果表明：降水减少的地区主要位于我国北方的西北东部、华北及东北;在南方,西南的降水减少趋势与上述地区具有类似特征。气温基本为增温趋势,而西北东部及西南地区气温也在20世纪80年代发生转折性变化,由80年代中期以前的降温趋势转为其后的增温趋势。地表湿润指数分析的结果指出：我国西北东部、华北、东北及西南地区当前正处于一个干旱化过程,但不同地区干湿变化特征及干旱化的持续时间和位相却有差别。     

关于ENSO事件监测指数的改进方案

为了改进气象行业标准(国标)推荐的厄尔尼诺/拉尼娜事件监测指数所涉及的异常数据带有趋势、间隔10年的修订所可能引入的额外周期、指数一致性及气候标准值变动所引起的事件属性、强弱的变化等系列问题,本文基于一个可以消除一阶趋势并舍弃气候标准值的异常计算方法用以构建相关指数.结果表明,该方案所计算的指数与原指数具有较好的一致性...     

青藏高原与中国其他地区气候突变时间的比较

基于1961～2006年中国地面观测气温和降水资料,对青藏高原地区以及中国其他6个地区地表气温、降水的变化趋势和突变时间进行了检测和比较。结果发现,(1)地表气温:1961～2006年青藏高原地区年和四季的地表气温都呈增加趋势。年平均地表气温在20世纪80年代中期开始变暖,但显著快速增暖的突变发生在90年代中期,该时间比东北、华北、西北和淮河地区晚,与长江中下游和华南地区接近,不同季节青藏高原地区与其他地区变暖突变时间的差别也各有不同,但所有季节快速变暖突变的时间都比东北地区晚,中国东部陆地地区年和冬季平均地表气温表现出北早南晚的经向差异;(2)降水:1961～2006年青藏高原地区年降水量没有检测到显著的变化趋势,冬春降水量显著增加,而夏季降水有微弱的减少,秋季降水显著减少。降水突变的信号明显比温度突变的信号弱,年降水量和春季降水都没有检测到突变的发生,降水突变方向(增或减)和突变时间在区域与区域之间以及不同季节之间都存在较大差异。由上可见,青藏高原气候的显著快速变化比中国东部长江以北地区有明显的滞后现象,尤其是冬春温度变化,这可能是由于青藏高原地区积雪增加导致的反照率增加和冰川融化吸热对青藏高原变暖的减弱作用所致。     

高低层纬向风切变的年际变率及气候学意义

用1959～1998共40年全球格点风场资料计算了200 hPa与850 hPa的纬向风速差, 即对流层纬向风切变(简称TZWS),并在此基础上得到其距平值。为了全面考察对流层中环流异常的年际变率特征, 根据TZWS的标准差分布, 文中选出了7个TZWS标准差数值大于5 m/s的代表性区域。这7个区域分别位于赤道中太平洋、赤道东太平洋、北太平洋亚热带地区、南太平洋亚热带地区、赤道大西洋、亚洲西南部以及东北部。前5个分别位于赤道、亚热带太平洋和大西洋的区域TZWS指数, 其年际变率与ENSO循环有密切联系, 反映了热带海洋温度异常对低纬度地区对流层环流的影响; 后2个区域的TZWS指数反映的是亚洲西南部和东北部的气候统变率, 在年际时间尺度上与ENSO循环有着明显的区别。通过对全球陆地降水和温度场的分析, 比较了热带、副热带的TZWS指数以及北极涛动指数的异同, 发现后2个区域TZWS指数能很好且能独立反映出北半球中高纬度地区陆地降水及陆地温度的异常模态。     

气候变化的归因与预估模拟研究

本文总结了近五年来中国科学院大气物理研究所在气候变暖的归因模拟与预估研究上的主要进展。研究表明,利用海温、太阳辐射和温室气体等实际强迫因子驱动大气环流模式,能够较为合理地模拟全球平均地表气温在20世纪的演变,但是难以模拟出包括北大西洋涛动／北极涛动和南极涛动在内的高纬度环流的长期变化趋势。利用温室气体和硫酸盐气溶胶等“历史资料”驱动气候系统模式,能够较好地模拟出20世纪后期的全球增暖,但如果要再现20世纪前期(1940年代)的变暖,还需同时考虑太阳辐射等自然外强迫因子。20世纪中国气温演变的耦合模式模拟技巧,较之全球平均情况要低;中国气候在1920年代的变暖机理目前尚不清楚。对于近50年中国东部地区“南冷北暖”、“南涝北旱”的气候变化,基于大气环流模式特别是区域气候模式的数值试验表明,夏季硫酸盐气溶胶的负辐射效应超过了温室气体的增暖效应,从而对变冷产生贡献。但现有的数值模拟证据,不足以说明气溶胶增加对“南涝北旱”型降水异常有贡献。20世纪中期以来,青藏高原主体存在明显增温趋势,温室气体浓度的增加对这种增暖有显著贡献。多模式集合预估的未来气候变化表明,21世纪全球平均温度将继续增暖,增温幅度因不同排放情景而异;中国大陆年均表面气温的增暖与全球同步,但增幅在东北、西部和华中地区较大,冬季升温幅度高于夏季、日最低温度升幅要强于日最高温度;全球增暖有可能对我国中东部植被的地理分布产生影响。伴随温室气体增加所导致的夏季平均温度升高,极端温度事件增多;在更暖的气候背景下,中国大部分地区总降水将增多,极端降水强度加大且更频繁发生,极端降水占总降水的比例也将增大。全球增暖有可能令大洋热盐环流减弱,但是减弱的幅度因模式而异。全球增暖可能不是导致北太平洋副热带－热带经圈环流自20世纪70年代以来变弱的原因。文章同时指出了模式预估结果中存在的不确定性。     

Performance of Regional Integrated Environment Modeling System (RIEMS) in the Simulation of Surface Air Temperature over East Asia

Regional climate models (RCMs) have the potential for more detailed surface characteristic and mesoscale modeling results than general circulation models (GCMs).These advantages have drawn significant focus on RCM development in East Asia.The Regional Integrated Environment Modeling System,version 2.0 (RIEMS2.0),has been developed from an earlier RCM,RIEMS1.0,by the Key Laboratory of Regional ClimateEnvironment for Temperate East Asia (RCE-TEA) and Nanjing University.A numerical experiment covering 1979 to 2008 (simulation duration from 1 January 1978 to 31 December 2008) with a 50-km spatial resolution was performed to test the ability of RIEMS2.0 to simulate long-term climate and climate changes in East Asia and to provide a basis for further development and applications.The simulated surface air temperature (SAT) was compared with observed meteorological data.The results show that RIEMS2.0 simulation reproduced the SAT spatial distribution in East Asia but that it was underestimated.The simulated 30-year averaged SAT was approximately 2.0°C lower than the observed SAT.The annual and interannual variations in the averaged SAT and their anomalies were both well reproduced in the model.A further analysis of three sub-regions representing different longitudinal ranges showed that there is a good correlation and consistency between the simulated results and the observed data.The annual variations,interannual variations for the averaged SAT,and the anomalies in the three sub-regions were also captured well by the model.In summary,RIEMS2.0 shows stability and does well both in simulating the long-term SAT in East Asia and in expressing sub-regional characteristics.     

Aridity in Vojvodina, Serbia

For investigating aridity in Vojvodina, two parameters were used: the De Martonne aridity index and the Pinna combinative index. These indices were chosen as the most suitable for the analysis of climate in Vojvodina (a region in northern part of Serbia). Also, these indices were calculated from data obtained from 10 meteorological stations for the period from 1949 to 2006. The spatial distribution of the annual and seasonal De Martonne and the Pinna combinative indices as well as the mean monthly values of the De Martonne index and aridity trends of these indices are presented. There were two, four, and five types of climate on a yearly, seasonal, and monthly basis in Vojvodina, according to the De Martonne climate classification which consists of a total of seven types. In addition, semi-humid and humid climate types were represented in the region, on a yearly basis. The winter season was dominated by wetter types of climate, while the summer season was characterized by drier ones. During the spring and autumn seasons, there were types of climate which range between both aforementioned types. Two out of three climate types, which can be identified using the Pinna combinative index, were registered in Vojvodina region. The most dominant climate type was the semidry Mediterranean with formal Mediterranean vegetation, while the humid type was only identified in one small part of southwestern Vojvodina. The calculated values of both aridity indices showed that there were no annual trends. Therefore, it can be considered that there were no recent aridity changes during the observed period. For paleoclimate, the general story is more complex. The lack of aridity trends in the recent period from 1949 to 2006 supports the fact that Vojvodina has very well preserved loess–palaeosol sequences from the Middle and Late Pleistocene, which indicates that crucial point for their preservation was caused by the weak aridity variability in the region.     

Amplitude—Phase Characteristics of the Annual Cycle of Surface Air Temperature in the Northern Hemisphere

The amplitude-phase characteristics(APC)of surface air temperature(SAT)annual cycle(AC)in the Northern Hemisphere are analyzed.From meteorological observations for the 20th century and meteorological reanalyses for its second half,it is found that over land negative correlation of SAT ACamplitude with annual mean SAT dominates.Nevertheless,some exceptions exist.The positive correlationbetween these two variables is found over the two desert regions:in northern Africa and in Central America.Areas of positive correlations are also found for the northern Pacific and for the tropical Indian and PacificOceans.Southward of the characteristic annual mean snow-ice boundary (SIB) position,the shape ofthe SAT AC becomes more sinusoidal under climate warming.In contrast,northward of it,this shapebecomes less sinusoidal.The latter iS also found for the above-mentioned two desert regions.In theFar East(southward of about 50°N),the SAT AC shifts as a whole:here its spring and autumn phasesoccur earlier if the annual     

RECOGNISING THE UNCERTAINTY IN THE QUANTIFICATION OF THE EFFECTS OF CLIMATE CHANGE ON HYDROLOGICAL RESPONSE

A widely used method of evaluating effects of climate change on flow regime is to perturb the climate inputs to a rainfall–runoff model and examine the effect on a statistic of the modelled flows. Such studies require four elements: a method of perturbing the climate, a rainfall–runoff model, a study catchment and a flow index. In practice the direction and magnitude of the estimated effects depend on each of the four elements, leading to concern over the usefulness and generality of the results. To investigate these uncertainties two climate scenarios and eight climate sensitivity tests have been applied to three UK catchments using two conceptual rainfall–runoff models in order to quantify effects of climate change on three flow indices representing mean runoff, flood magnitudes and low flows. The sensitivity tests were found to be useful to assess the suitability of the models to simulate flows outside the conditions experienced in their calibration. Both models gave internally consistent results but, on close examination, one model was found inappropriate for this application. Results show that the effect of climate change on flow varies between catchments and that different flow response indices can change in opposite directions, e.g. floods increased in magnitude while low flows reduced. Contrasting results were obtained from the two climate scenarios.     

A review on aspects of climate simulation assessment

This paper reviews some aspects of evaluation of climate simulation, including the ITCZ, the surface air temperature (SAT), and the monsoon. A brief introduction of some recently proposed approaches in weather forecast verification is followed by a discussion on their possible application to evaluation of climate simulation. The authors suggest five strategies to extend the forecast verification methods to climate simulation evaluation regardless significant differences between the forecasts and climate simulations. It is argued that resolution, convection scheme, stratocumulus cloud cover, among other processes in the atmospheric general circulation model (AGCM) and the ocean-atmosphere feedback are the potential causes for the double ITCZ problem in coupled models and AGCM simulations, based on the system- and component-level evaluations as well as the downscaling strategies in some recent research. Evaluations of simulated SAT and monsoons suggest that both coupled models and AGCMs show good performance in representing the SAT evolution and its variability over the past century in terms of correlation and wavelet analysis but poor at reproducing rainfall, and in addition, the AGCM alone is not suitable for monsoon regions due to the lack of air-sea interactions.