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

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.     

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

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).     

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

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.     

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

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.     

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

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.     

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.     

近54年阿勒泰地区夏季极端降水事件气候特征

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。     

加密探空资料在华东区域业务模式中的应用试验

采用中国气象局2014年6月1日—30日14时加密探空资料,利用华东区域中尺度数值预报业务系统比较同化加密探空观测资料前后模式预报结果的差异。研究表明,同化加密探空资料后,对模式初始时刻不同高度的位势高度、比湿、温度、风速等变量均有一定的影响;对位势高度、温度和风场的影响在高层100—150 h Pa比较显著,而对比湿的影响主要体现在低层700—750 h Pa。同化加密探空资料后模式初始场更接近实况。批量数值试验的统计检验表明,同化加密探空观测资料后对强降水及形势场预报均有不同程度改进,24 h暴雨和大暴雨量级降水的预报技巧分别提高了2.5%和8.1%。