More than two hundred and fifty thousand spectroscopic binary or variable star candidates discovered by LAMOST     

Sheng-Bang Qian  Xiang-Dong Shi  Li-Ying Zhu  Lin-Jia Li  Jia Zhang  Er-Gang Zhao  Zhong-Tao Han  Xiao Zhou  Xiao-Hui Fang  Wen-Ping Liao 《天文和天体物理学研究(英文版)》2019,(5)

About 786.4 thousand stars were observed by LAMOST twice or more during the first stage of its spectroscopic survey. The radial velocity differences for about 256 thousand targets are larger than10 km s~(-1) and they are possible spectroscopic binary or variable candidates(SBVCs). It is shown that most SBVCs are slightly metal poorer than the Sun. There are two peaks in the temperature distribution of SBVCs around 5760 K and 4870 K, while there are three peaks in the distribution of the gravitational acceleration at 2.461, 4.171 and 4.621 cm s~(-2). The locations of SBVCs on the [Fe/H]-T, [Fe/H]-log g, log g-T and H-R diagrams are investigated. It is found that the detected SBVCs could be classified into four groups. The first group has higher log g～4.621 and lower T ～ 4870 K which are mainly cool red dwarf binaries. The second group of SBVCs has logg around 4.171 cm s~(-2) that includes binaries and pulsating stars such as δSet and γ Dor variables. The gravitational accelerations of the third group of SBVCs are higher and some of them are below the zero-age main sequence. They may be contact binaries in which the primary components are losing energy to the secondaries in the common envelopes and are at a special stellar evolutionary stage.The last group is composed of giants or supergiants with log g around 2.461 cm s~(-2) that may be evolved pulsating stars. One target(C134624.29+333921.2) is confirmed as an eclipsing binary with a period of 0.65 days. A preliminary analysis suggests that it is a detached binary with a mass ratio of 0.46. The primary fills its critical Roche lobe by about 89%, indicating that mass transfer will occur between the two components.  相似文献   

Particulate air pollution from wildfires in the Western US under climate change     

Jia Coco Liu  Loretta J. Mickley  Melissa P. Sulprizio  Francesca Dominici  Xu Yue  Keita Ebisu  Georgiana Brooke Anderson  Rafi F. A. Khan  Mercedes A. Bravo  Michelle L. Bell 《Climatic change》2016,135(3-4):655-668

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The spatial distribution characteristics of a comprehensive drought risk index in southwestern China and underlying causes   总被引：6，自引：1，他引：5  

Lanying Han  Qiang Zhang  Pengli Ma  Jianying Jia  Jinsong Wang 《Theoretical and Applied Climatology》2016,124(3-4):517-528

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Mesoscale numerical simulation study of warm fog dissipation by salt particles seeding     

Hui He  Xueliang Guo  Xiang’e Liu  Qian Gao  Xingcan Jia 《大气科学进展》2016,33(5):579-592

Based on the dynamic framework of WRF and Morrison 2-moment explicit cloud scheme, a salt-seeding scheme was developed and used to simulate the dissipation of a warm fog event during 6–7 November 2009 in the Beijing and Tianjin area. The seeding effect and its physical mechanism were studied. The results indicate that when seeding fog with salt particles sized 80 μm and at a quantity of 6 gm~(-2) at the fog top, the seeding effect near the ground surface layer is negative in the beginning period, and then a positive seeding effect begins to appear at 18 min, with the best effect appearing at 21 min after seeding operation. The positive effect can last about 35 min. The microphysical mechanism of the warm fog dissipation is because of the evaporation due to the water vapor condensation on the salt particles and coalescence with salt particles.The process of fog water coalescence with salt particles contributed mostly to this warm fog dissipation. Furthermore, two series of sensitivity experiments were performed to study the seeding effect under different seeding amounts and salt particles sizes. The results show that seeding fog with salt particles sized of 80 μm can have the best seeding effect, and the seeding effect is negative when the salt particle size is less than 10 μm. For salt particles sized 80 μm, the best seeding effect, with corresponding visibility of 380 m, can be achieved when the seeding amount is 30 g m~(-2).  相似文献   

Ensemble simulation of land evapotranspiration in China based on a multi-forcing and multi-model approach     

Jianguo Liu  Binghao Jia  Zhenghui Xie  Chunxiang Shi 《大气科学进展》2016,33(6):673-684

In order to reduce the uncertainty of offline land surface model(LSM) simulations of land evapotranspiration(ET), we used ensemble simulations based on three meteorological forcing datasets [Princeton, ITPCAS(Institute of Tibetan Plateau Research, Chinese Academy of Sciences), Qian] and four LSMs(BATS, VIC, CLM3.0 and CLM3.5), to explore the trends and spatiotemporal characteristics of ET, as well as the spatiotemporal pattern of ET in response to climate factors over mainland China during 1982–2007. The results showed that various simulations of each member and their arithmetic mean(Ens Mean) could capture the spatial distribution and seasonal pattern of ET sufficiently well, where they exhibited more significant spatial and seasonal variation in the ET compared with observation-based ET estimates(Obs MTE). For the mean annual ET, we found that the BATS forced by Princeton forcing overestimated the annual mean ET compared with Obs MTE for most of the basins in China, whereas the VIC forced by Princeton forcing showed underestimations. By contrast, the Ens Mean was closer to Obs MTE, although the results were underestimated over Southeast China. Furthermore, both the Obs MTE and Ens Mean exhibited a significant increasing trend during 1982–98; whereas after 1998, when the last big EI Ni ?no event occurred, the Ens Mean tended to decrease significantly between 1999 and 2007, although the change was not significant for Obs MTE. Changes in air temperature and shortwave radiation played key roles in the long-term variation in ET over the humid area of China, but precipitation mainly controlled the long-term variation in ET in arid and semi-arid areas of China.  相似文献   

Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon     

Yuanyuan Wang  Zhenghui Xie  Binghao Jia 《大气科学进展》2016,33(9):1047-1060

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.  相似文献   

Operational climate prediction in the era of big data in China: Reviews and prospects     

王昕  宋连春  王国复  任宏利  吴统文  贾小龙  吴焕萍  吴捷 《Acta Meteorologica Sinica》2016,30(3):444-456

Big data has emerged as the next technological revolution in IT industry after cloud computing and the Internet of Things. With the development of climate observing systems, particularly satellite meteorological observation and high-resolution climate models, and the rapid growth in the volume of climate data, climate prediction is now entering the era of big data. The application of big data will provide new ideas and methods for the continuous development of climate prediction. The rapid integration, cloud storage, cloud computing, and full-sample analysis of massive climate data makes it possible to understand climate states and their evolution more objectively, thus predicting the future climate more accurately. This paper describes the application status of big data in operational climate prediction in China; it analyzes the key big data technologies, discusses the future development of climate prediction operations from the perspective of big data, speculates on the prospects for applying climatic big data in cloud computing and data assimilation, and puts forward the notion of big data-based super-ensemble climate prediction methods and computerbased deep learning climate prediction methods.  相似文献   

Factors controlling the interannual variations of MJO intensity     

邓莉  李天明  刘佳 《Acta Meteorologica Sinica》2016,30(3):328-340

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.  相似文献   

2014—2016年超强厄尔尼诺事件的气候影响   总被引：7，自引：4，他引：3  

袁媛  高辉  贾小龙  万江华 《气象》2016,42(5):532-539

2014—2016年,赤道中东太平洋发生了一次超强厄尔尼诺事件,此次事件于2015年11月达到峰值,12月开始衰减。其峰值强度超过了1951年以来另外两次超强厄尔尼诺事件（1982/1983年和1997/1998年）的强度,成为了1951年以来最强的事件。截至2016年4月,事件已持续20个月,也成为了1951年以来持续时间最长的厄尔尼诺事件。在这次事件的发展过程中,热带太平洋至东亚副热带地区的大气环流表现出了显著的响应特征：赤道中东太平洋对流活动加强,异常上升运动发展,而赤道西太平洋对流活动受抑制,异常下沉运动控制;菲律宾附近异常反气旋生成并发展加强,西太平洋副热带高压强度偏强、西伸脊点异常偏西,尤其2015年冬季副热带高压强度为1980年以来最强。与此同时,2015年秋、冬季,我国长江以南大部降水偏多,尤其冬季华南地区（广东、广西、海南三省区）平均降水量达历史第一,较常年偏多1.6倍以上。近期,超强厄尔尼诺正处于衰减阶段,但是考虑到热带印度洋暖海温的“接力”作用,厄尔尼诺事件对2016年春、夏季我国气候异常的影响可能仍将持续。  相似文献   

近54年阿勒泰地区夏季极端降水事件气候特征     

博尔楠  恰里哈尔  阿依敏  别克达吾列提  宋佳 《沙漠与绿洲气象(新疆气象)》2016,10(4):39-46

本文采用阿勒泰地区7个国家级气象站近54a(1960～2013年)夏季(6～8月)的日有效降水量（20～20h降水量≥0.1mm）资料,用WMO推荐的百分位法计算了全地区过去54a夏季极端强降水的阈值、进一步分析了当地夏季时空分布特征及变化趋势,结果表明：阿勒泰地区夏季极端强降水阈值呈西部、南部小,北部、东部大,并且空间异常分布特征如下: 夏季以及夏季各月的极端强降水日数和强度均可总结出5种最主要模型;极端强降水量可总结出8种最主要模型;并且通过时间标准化序列分析各种模型都有对应的降水日数、量级、强度明显偏多（强）和偏少（弱）的时段。日数、量级、强度近54a来,除吉木乃略有下降以外,其余各县（市）均为增长趋势,尤其是北部、东部地区.同时上述三指标存在着显著的年代际和年纪尺度的周期变化,上世纪90年代和2010年至今为三个指标最多(强)的年代,而上世纪70年代为最少（最差）的年代.并通过周期分析（小波分析）可知,均有对应的显著变化周期。  相似文献