Arctic sea ice and Eurasian climate: A review

The Arctic plays a fundamental role in the climate system and has shown significant climate change in recent decades,including the Arctic warming and decline of Arctic sea-ice extent and thickness. In contrast to the Arctic warming and reduction of Arctic sea ice, Europe, East Asia and North America have experienced anomalously cold conditions, with record snowfall during recent years. In this paper, we review current understanding of the sea-ice impacts on the Eurasian climate.Paleo, observational and modelling studies are covered to summarize several major themes, including: the variability of Arctic sea ice and its controls; the likely causes and apparent impacts of the Arctic sea-ice decline during the satellite era,as well as past and projected future impacts and trends; the links and feedback mechanisms between the Arctic sea ice and the Arctic Oscillation/North Atlantic Oscillation, the recent Eurasian cooling, winter atmospheric circulation, summer precipitation in East Asia, spring snowfall over Eurasia, East Asian winter monsoon, and midlatitude extreme weather; and the remote climate response(e.g., atmospheric circulation, air temperature) to changes in Arctic sea ice. We conclude with a brief summary and suggestions for future research.     

Recent advances in monsoon studies in China

This review provides a synopsis of the major progress that has been made in monsoon studies in China and to further bridge the gap between the Chinese and international meteorological community. It consists of seven major sections. After the introduction, the second section begins with the global monsoon systems and their seasonal variation, based on some new methods proposed in recent years. Besides, some major intraseasonal features of East Asian monsoon, including the onset of South China Sea summer monsoon are discussed. In the third section, we review the interactions between ENSO and the East Asian monsoon, focusing in particular on the results of Chinese meteorologists that indicate the influence of ENSO on the East Asian summer monsoon(EASM) is obviously different from that on the tropical monsoon. Besides the tropical Pacific,other ocean basins, such as the Indian Ocean and the Atlantic Ocean, are also important to the East Asian monsoon, and this topic is discussed in the fourth section. In the fifth section, we address the role of land surface processes in East Asian monsoon. For example, we describe work that has shown more snow cover in spring on the Tibetan Plateau is followed by a weakened EASM and more summer rainfall in the Yangtze River valleys. The sixth section focuses on the influence of atmospheric circulation in the Southern Hemisphere(SH) on EASM, demonstrating how the signal from the SH is likely to provide new clues for the seasonal forecasting of summer rainfall in China. Finally, in the seventh section, we concentrate on the interdecadal variations of EASM. In particular, we look at a significant interdecadal variation that occurred at the end of the 1970 s, and how our understanding of this feature could affect forecasting ability.     

基于AHP的文物建筑防雷分类研究

通过对文物建筑雷电灾害规律的分析,提出将文物建筑的重要性、雷击密度、所处环境、服务设施、文物建筑高度、周围树木、自身结构、雷击史等作为文物建筑防雷分类的评估指标,采用层次分析法(AHP)确定指标权重。根据文物建筑保护等级、遭受雷灾规律、雷电活动情况以及现行国家标准将评估指标分类,参考里克特量表及等权指标体系对评估指标进行评价,建立了文物建筑防雷分类评估模型。     

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation （NPP） to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model （CanESM2） of the Canadian Centre for Climate Modelling and Analysis （CCCma）, which are part of the phase 5 of the Coupled Model Intercomparison Project （CMIP5）. The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m^-2 yr^-1 and-0.14 gC m^- 2 yr^-2, respec- tively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at -1.79 gC m^-2 yr^-2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m^-2 yr^-1 and 0.84 gC m^-2 yr^-2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m^2 yr^-1 and 0.83 gC m^2 yr^-2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of-0.39 kg m^-2 yr^-1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration （experiment M2）, and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-     

Oceanic origin of southeast tropical Atlantic biases

Most coupled general circulation models suffer from a prominent warm sea surface temperature bias in the southeast tropical Atlantic Ocean off the coast of Africa. The origin of the bias is not understood and remains highly controversial. Previous studies suggest that the origin of the bias stems from systematic errors of atmospheric models in simulating surface heat flux and coastal wind, or poorly simulated coastal upwelling. In this study, we show, using different reanalysis and observational data sets combined with a set of eddy-resolving regional ocean model simulations, that systematic errors in ocean models also make a significant contribution to the bias problem. In particular (1) the strong warm bias at the Angola-Benguela front that is maintained by the local wind and the convergence of Angola and Benguela Currents is caused by an overshooting of the Angola Current in ocean models and (2) the alongshore warm bias to the south of the front is caused by ocean model deficiencies in simulating the sharp thermocline along the Angola coast, which is linked to biases in the equatorial thermocline, and the complex circulation system within the Benguela upwelling zone.     

湿热力平流参数在一次华北暴雨模拟诊断中的应用研究

对2011年7月24~25日发生在华北地区的一次暴雨过程进行了分析,并以NCEP资料为初值场对此次暴雨过程进行了数值模拟,结合实况对模拟结果进行对比分析。分析表明:模式对本次华北暴雨的模拟比较成功,基本反映出了本次暴雨过程的降水分布特点。利用湿热力平流参数对本次华北地区的降水落区进行了诊断分析。分析指出,湿热力平流参数纬向平均的垂直剖面图上,湿热力平流参数的高值区及大值中心与地面的强降水雨区对应得较好,其梯度大小及向上延伸高度均可以定性地指示降水的强弱;垂直积分的湿热力平流参数与地面6 h强降水落区具有较好的对应关系,而在示踪弱降水区时效果并不是很好,其大值中心并不与强降水中心完全重叠,而是其梯度大值区与降水中心相对应;垂直积分的湿热力平流参数与6 h累积地面降水的空间分布特征和时间演变趋势比较相似,并且其变化趋势能反映降水的发展和消弱。     

A timescale decomposed threshold regression downscaling approach to forecasting South China early summer rainfall

A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.     

Factors controlling the interannual variations of MJO intensity

The interannual variations of intensity of the Madden-Julian Oscillation (MJO) during boreal winter are investigated by using the observed outgoing longwave radiation (OLR) and the reanalysis data of ECMWF and NCEP. The standard deviation of 20-80-day filtered OLR anomaly is used to measure the MJO intensity. The dominant spatial structure of the interannual variability is revealed by an EOF analysis of the MJO intensity field. It is found that the leading mode is associated with eastern Pacific type ENSO, whereas the second mode is related to central Pacific type ENSO. A simple atmospheric model is used to investigate the relative roles of background moisture and wind changes in affecting the overall strength of MJO. The numerical experiments indicate that the background moisture effect is dominant while the background wind change has a minor effect.