网络环境下的前兆数据自动编排管理系统

通过在Intemet和局域网下开发的程序,实现了安徽省地震前兆数据自动编排管理。该网络程序可以自动检索和收集各地方台站上报的数据,然后将其按照规定的格式编排,通过纠错子系统检查无误后传至中国地震局数据中心。本系统可以将数据自动分类管理并做好备份,最大的优点是速度快、准确性高、操作方便。     

逆断层地震近场地震动影响场和地表形变模拟

本文设计了一个MW7.0级地震的简单的逆断层有限移动源破裂模型,计算了断层周围64个观测点的加速度、速度和位移时程及峰值,简单讨论了近场地震动峰值、断层附近地表永久位移(或地表形变)的分布特点,并讨论了永久位移和地面运动速度大脉冲的关系。重点研究了断层附近三分量的永久位移(或地表形变)大小、方向和地震动作用特点。     

超高强混凝土短柱抗震性能的试验研究

通过对12根剪跨比λ=2．0的超高强混凝土短柱在低周反复荷载下抗震性能的试验研究,分析了其破坏形态,并研究了轴压比和配箍率对试件滞回特性和抗震延性的影响,提出了满足一定延性要求（μ△≥3．0）超高强混凝土短柱的轴压比限值和箍筋加密区的最小配箍特征值的建议值。该值可为现行规范的修订提供参考。     

Early solar system aqueous activity: K isotope evidence from Allende

The alkali element K is moderately volatile and fluid mobile; thus, it can be influenced by both primary processes (evaporation and recondensation) in the solar nebula and secondary processes (thermal and aqueous alteration) in the parent body. Since these primary and secondary processes would induce different isotopic fractionations, K isotopes could become a potential tracer to distinguish them. Using recently developed methods with improved precision (0.05‰, 95% confidence interval), we systematically measured the K isotopic compositions and major/trace elemental compositions of chondritic components (18 chondrules, 3 CAIs, 2 matrices, and 5 bulks) in the carbonaceous chondrite fall Allende. Among all the components analyzed in this study, CAIs, which formed initially under high‐temperature conditions in the solar nebula and were dominated by nominally K‐free refractory minerals, have the highest K₂O content (average 0.53 wt%) and have K isotope compositions most enriched in heavy isotopes (δ⁴¹K: ?0.30 to ?0.25‰). Such an observation is consistent with previous petrologic studies that show CAIs in Allende have undergone alkali enrichment during metasomatism. In contrast, chondrules contain lower K₂O content (0.003–0.17 wt%) and generally lighter K isotope compositions (δ⁴¹K: ?0.87‰ to ?0.24‰). The matrix and bulks are nearly identical in K₂O content and K isotope compositions (0.02–0.05 wt%; δ⁴¹K: ?0.62 to ? 0.46‰), which are, as expected, right in the middle of CAIs and chondrules. This strongly indicates that most of the chondritic components of Allende suffered aqueous alteration and their K isotopic compositions are the ramification of Allende parent‐body processing instead of primary nebular signatures. Nevertheless, we propose the small K isotope fractionations observed (< 1‰) among Allende components are likely similar to the overall range of K isotopic fractionation that occurred in nebular environment. Furthermore, the K isotope compositions seen in the components of Allende in this study are consistent with MC‐ICP‐MS analyses of the components in ordinary chondrites, which also show an absence of large (10‰) isotope fractionations. This is not expected as evaporation experiments in nebular conditions suggest there should be large K isotopic fractionations. Nevertheless, possible nebular processes such as chondrules back exchanging with ambient gas when they formed could explain this lack of large K isotopic variation.     

南极中山站全天信息采集系统

南极高原拥有独特的天文观测优势,为了对南极中山站夜天文观测条件进行实测研究,中国科学院云南天文台专门研制了一套具有耐低温、自动除雪除霜等适应南极气候特征的全自动全天信息采集系统,该系统可以提供实时的全天云量、天光背景和全天图像,并将信息推送到网页实时显示。介绍了系统的研制及为适应南极气候进行的耐低温实验,统计分析了中山站2016~2017年的全天信息数据,结果显示,中山站2016和2017年的可观测时间为772.21 h和437.38 h,可观测夜数为93 d和51 d,天光背景最大真实值为22.05 Mag/arcsec 2,年平均气温为-10.6℃,最高气温19.1℃,最低气温为-44℃,2016年平均相对湿度为55.2%。     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

SMAP卫星海表盐度产品的检验与校正

In this study, sea surface salinity(SSS) Level 3(L3) daily product derived from soil moisture active passive(SMAP)during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity(SMOS) and in-situ measurements. Generally, the root mean square error(RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature(SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.     

2017年春夏季西北太平洋浮游植物的区域差异及其与不同水团的关系

The West Pacific Ocean is considered as the provenance center of global marine life and has the highest species diversity of numerous marine taxa. The phytoplankton, as the primary producer at the base of the food chain,effects on climate change, fish resources as well as the entire ecosystem. However, there are few large-scale surveys covering several currents with different hydrographic characteristics. This study aimed to explore the relationships between the spatio-temporal variation in phytoplankton community structure and different water masses. A total of 630 water samples and 90 net samples of phytoplankton were collected at 45 stations in the Northwest Pacific Ocean(21.0°–42.0°N, 118.0°–156.0°E) during spring and summer 2017. A total of 281 phytoplankton taxa(5 μm) belonging to 61 genera were identified in the study area. The distribution pattern of the phytoplankton community differed significantly both spatially and temporally. The average abundances of phytoplankton in spring and summer were 797.07×10~2 cells/L and 84.94×10~2 cells/L, respectively. Whether in spring or summer, the maximum abundance always appeared in the northern transition region affected by the Oyashio Current, where nutrients were abundant and diatoms dominated the phytoplankton community;whereas the phytoplankton abundance was very low in the oligotrophic Kuroshio region, and the proportion of dinoflagellates in total abundance increased significantly. The horizontal distribution of phytoplankton abundance increased from low to high latitudes, which was consistent with the trend of nutrient distributions, but contrary to that of water temperature and salinity. In the northern area affected by the Oyashio Current, the phytoplankton abundance was mainly concentrated in the upper 30 m of water column, while the maximum abundance often occurred at depths of 50–75 m in the south-central area affected by the Kuroshio Current.Pearson correlation and redundancy analysis(RDA) showed that phytoplankton abundance was significant negatively correlated with temperature and salinity, but positively correlated with nutrient concentration. The phytoplankton community structure was mainly determined by nutrient availability, especially the N:P ratio.     

2018?2019年舟山近海浮游动物群落结构春季年际变化及其与水团的关系

根据2018?2019年春季两个航次在舟山近海进行的浮游生物调查结果,对舟山近海的浮游动物群落结构(类群组成、优势种数量)年际变化进行了研究,利用典范对应分析(Canonical Correspondence Analysis, CCA)研究了两年春季浮游动物类群组成差异、优势种变化的原因,初步探讨了春季浮游动物群落结构动态变化的机制。结果表明:根据表层温度(Sea Surface Temperature,SST)、表层盐度(Sea Surface Salinity,SSS)的聚类分析,将该区域分为3个水团:杭州湾内水团(I区)、舟山本岛上升流水团II区)、舟山近海水团(III区)。不同水团对浮游动物类群组成影响显著,引起2018年和2019年春季3个水团区差异的主要贡献种(贡献率>10%)均为中华哲水蚤,同一水团两年间年际差异的贡献种如下:I区为捷氏歪水蚤(56.91%)和真刺唇角水蚤(12.34%);II区为中华哲水蚤(72.64%)、五角水母(13.35%);III区为中华哲水蚤(41.93%)、夜光虫(22.94%)。CCA分析表明,第1 CCA轴(CCA1)和第2 CCA轴(CCA2)共解释了两年春季浮游动物优势种累计方差的46.14%和物种?环境累计方差的97.82%。CCA1主要反映了空间(近海水团和湾内水团)的差异。CCA2主要反映了2018年和2019年站位的年际差异。盐度是影响春季浮游动物群落结构空间差异的主要因素,而温度、叶绿素a浓度是春季浮游动物群落结构年际差异的主要因素。     

发展广东省空间天气轨道的思考

根据中国气象发展战略研究成果中8条业务轨道对空间天气轨道的要求,通过对空间天气和空间天气学的描述,分析广东省气象部门空间天气发展的可行性与必要性,结合广东省气象局业务体制改革,对发展广东省空间天气业务提出一些建议。