2007-2017年中国沙尘气溶胶的三维分布特征及输送过程

利用最新发布的CALIPSO产品，构建了2007-2017年中国沙尘气溶胶的三维分布，并结合HYSPLIT-4模式和再分析数据，探讨了沙尘的三维输送过程。结果表明：中国的沙尘排放源区主要是塔克拉玛干沙漠和巴丹吉林沙漠，沙尘气溶胶出现频率分别为60%和35%。塔克拉玛干沙漠排放的沙尘主要（50%~70%）停留在源地0~6 000 m高度，少部分向东输送至甘肃和内蒙古；巴丹吉林沙漠排放的沙尘则主要向东输送。中国沙尘排放量在春季最大，向东输送最强；夏季，东亚夏季风限制了沙尘向东输送；秋季，沙尘排放减弱，输送强度和夏季相当；沙尘排放量在冬季最小，输送最弱。夏季，沙尘在输送过程中可被抬升至高度5 000 m以上，春季次之，秋、冬季的沙尘主要在低层大气输送。沙尘在向东输送的过程中被抬升并和当地人为污染物混合变为污染性沙尘，华北地区污染性沙尘出现频率高达30%；输送到海洋的沙尘也会与洋面上（0~3 000 m高度）的海盐气溶胶混合，出现频率约为10%。     

Solar GLAO and TAO:performance comparisons

Multi-conjugate adaptive optics(MCAO),consisting of several deformable mirrors(DMs),can significantly increase the adaptive optics(AO)correction field of view.Current MCAO can be realized by either star-oriented or layer-oriented approaches.For solar AO,ground-layer adaptive optics(GLAO)can be viewed as an extreme case of layer-oriented MCAO in which the DM is conjugated to the ground,while solar tomography adaptive optics(TAO)that we proposed recently can be viewed as star-oriented MCAO with only one DM.Solar GLAO and TAO use the same hardware as conventional solar AO,and therefore it will be important to see which method can deliver better performance.In this article,we compare the performance of solar GLAO and TAO by using end-to-end numerical simulation software.Numerical simulations of TAO and GLAO with different numbers of guide stars are conducted.Our results show that TAO and GLAO produce the same performance if the DM is conjugated to the ground,but TAO can only generate better performance when the DM is conjugated to the best height.This result has important application in existing one-DM solar AO systems.     

基于连续帧间差分的抛弃式探头三维下沉运动处理方法研究

抛弃式探头由无人机装载,能够在较远目标区域和危险海域开展海洋水文环境剖面参数的测量。通过安装不同传感器,可以实现对温度、盐度的剖面测量,其深度的测量采用数学方法计算得到。针对双摄像机水箱实验获得的5个不同攻角实验结果,分析了常用的运动目标的检测方法,最终选择基于连续帧间差分法,确定探头的三维坐标位置,进而得到探头下沉运动的三维运动轨迹和速度曲线等信息。探头从水面释放后攻角在下沉过程中不断调整,改变运动姿态,同时伴随自身的旋转,抵消水平方向阻力作用,初始攻角产生的深度测量误差主要体现在加速过程,探头达到匀速运动后测量误差不变,在不考虑横流的情况下,探头最后以匀速垂直下落运动。     

An Early Cretaceous slab window beneath central Tibet,SW China: Evidence from OIB‐like alkaline gabbros in the Duolong area

The geodynamic mechanism of the late Early Cretaceous magmatic flare‐up in the collisional zone between the Lhasa and Qiangtang terranes in Tibet is controversial because of a scarcity of robust evidence. To address this problem, we report geochronological, geochemical and Hf isotopic data for the newly discovered Gufeng gabbros from the Duolong Cu–Au mineral district of the western Bangong–Nujiang Suture Zone (BNSZ). The gabbro samples, dated at 126.3 ± 1.8 Ma, show geochemical similarities to typical ocean island basalt (OIB) and have positive εHf(t) values of +3.3 to +6.9. The gabbros were generated by decompression melting of deep upwelling asthenosphere. This event is best explained by slab break‐off and the resultant development of a slab window beneath central Tibet.     

基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

Variations in glacier volume and snow cover and their impact on lake storage in the Paiku Co Basin,in the Central Himalayas

Glaciers and snow cover are important constituents of the surface of the Tibetan Plateau. The responses of these phenomena to global environmental changes are sensitive, rapid and intensive due to the high altitudes and arid cold climate of the Tibetan Plateau. Based on multisource remote sensing data, including Landsat images, MOD10A2 snow product, ICESat, Cryosat-2 altimetry data and long-term ground climate observations, we analysed the dynamic changes of glaciers, snow melting and lake in the Paiku Co basin using extraction methods for glaciers and lake, the degree-day model and the ice and lake volume method. The interaction among the climate, ice-snow and the hydrological elements in Paiku Co is revealed. From 2000 to 2018, the basin tended to be drier, and rainfall decreased at a rate of −3.07 mm/a. The seasonal temperature difference in the basin increased, the maximum temperature increased at a rate of 0.02°C/a and the minimum temperature decreased at a rate of −0.06°C/a, which accelerated the melting from glaciers and snow at rates of 0.55 × 10⁷ m³/a and 0.29 × 10⁷ m³/a, respectively. The rate of contribution to the lake from rainfall, snow and glacier melted water was 55.6, 27.7 and 16.7%, respectively. In the past 18 years, the warmer and drier climate has caused the lake to shrink. The water level of the lake continued to decline at a rate of −0.02 m/a, and the lake water volume decreased by 4.85 × 10⁸ m³ at a rate of −0.27 × 10⁸ m³/a from 2000 to 2018. This evaluation is important for understanding how the snow and ice melting in the central Himalayas affect the regional water cycle.     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

毛乌素沙区1961-2016年降水特征

基于毛乌素沙区10个气象站1961-2016年观测资料，应用Mann-Kendall方法和t检验法对各气象站年降水量进行了突变检验，借助小波分析讨论了各气象站年降水量的周期特征，根据降水量等值线划分结果对整个研究区分区分析了年、季、月和日尺度上的降水变化特征，并在两个时段上分析了季节性降水的差异。结果表明：毛乌素沙区年降水量空间特征差异明显，东部亚区呈上升趋势，中西部亚区呈下降趋势，但变化趋势不显著且无突变发生；降水年内分配不均，干湿季分明，降水集中在5-9月，夏秋季降水占全年降水比重大，季、月和日尺度降水量存在梯度递减变化；年降水量的年际变化过程存在多重时间尺度的自相似结构；近26年的冬春季降水增加显著，但降水波动幅度小于前30年。     

Classification of stellar spectra with SVM based on within-class scatter and between-class scatter

Support Vector Machine (SVM) is a popular data mining technique, and it has been widely applied in astronomical tasks, especially in stellar spectra classification. Since SVM doesn’t take the data distribution into consideration, and therefore, its classification efficiencies can’t be greatly improved. Meanwhile, SVM ignores the internal information of the training dataset, such as the within-class structure and between-class structure. In view of this, we propose a new classification algorithm-SVM based on Within-Class Scatter and Between-Class Scatter (WBS-SVM) in this paper. WBS-SVM tries to find an optimal hyperplane to separate two classes. The difference is that it incorporates minimum within-class scatter and maximum between-class scatter in Linear Discriminant Analysis (LDA) into SVM. These two scatters represent the distributions of the training dataset, and the optimization of WBS-SVM ensures the samples in the same class are as close as possible and the samples in different classes are as far as possible. Experiments on the K-, F-, G-type stellar spectra from Sloan Digital Sky Survey (SDSS), Data Release 8 show that our proposed WBS-SVM can greatly improve the classification accuracies.     

张掖盆地地下水硝酸盐污染与人体健康风险评价

地下水是张掖盆地的重要水资源，其硝酸盐污染尚未得到足够重视。对张掖盆地2004、2015年地下水硝酸盐浓度进行了系统分析，并采用美国环境保护署（USEPA）推荐的健康风险评价模型评估了地下水硝酸盐的健康风险。结果表明：自2004年以来张掖盆地地下水硝酸盐污染日趋严重。2015年硝酸盐浓度最高已达到283.32 mg·L^-1，17.61%的采样点硝酸盐氮浓度超过GB5749-2006《生活饮用水卫生标准》中饮用地下水限量值（20 mg·L^-1）。研究区人群经皮肤接触途径摄入硝酸盐的健康风险在可接受水平，而饮水摄入硝酸盐的健康风险较高，总风险中饮水途径引起健康风险的贡献率占99.40%，远大于皮肤接触途径。儿童经饮水摄入和皮肤接触两种途径的健康风险均显著高于成人，分别为成人的1.544倍和1.039倍。32.39%的采样点地下水硝酸盐对儿童的健康风险超出了可接受水平，14.79%的采样点地下水硝酸盐对成人的健康风险不可接受。甘州区城区、临泽县北部边缘及高台县城区周围硝酸盐浓度最高，这些区域内所有人群都面临硝酸盐引发的高健康风险，其余区域硝酸盐引发的健康风险相对较低。