复杂条件下煤田三维地震勘探应用实例

勘探区地处毛乌素沙漠西南边缘,表层多为干燥疏松的沙丘和黄土;浅层为沙土、卵石、砾石层,大部分地段不含水,均为松散沉积物。区内断层和褶皱发育,煤层埋藏深度与产状变化较大。针对该区表、浅层和深层复杂的地震地质条件,通过不断优化三维地震勘探设计,最终确定了野外数据采集观测系统及激发与接收参数,并在数据处理中,选择了合适的处理技术、处理参数及处理流程,获得了信噪比与分辨率较高的三维数据体,较好的完成了地质勘探任务。     

三种非线性回归逐时气温预报比较订正

选取ECMWF和T639的2013年1月至2014年12月的数值预报场构造预报因子,基于神经网络、支持向量机和构造函数的非线性方法,预报地面逐时气温。试验结果显示,在单个方法预报误差较大时,3种方法的偏差订正集成方法更利于减小误差,通过偏差订正,3种非线性方法预报效果良好,平均绝对误差减小了0.5 ℃。在近1年独立样本的预报检验中,集成方法、神经网络、支持向量机和构造函数预报的平均绝对误差分别为1.5 ℃、1.7 ℃、1．8 ℃和1．4 ℃,总体上构造函数预报更为准确。     

利用ARGO资料改进海洋资料同化和海洋模式中的物理过程

国际ARGO计划的实施每年将可提供多达 10万个剖面 (0～ 2 0 0 0m水深 )的海水温度和盐度资料 ,这些资料的获取无疑将会大大促进海洋和大气科学的发展 ,使人们加深对海洋过程的了解 ,揭示海 气相互作用的机理 ,为长期天气预报和短期气候预测提供模式初始场 ,提高长期天气预报和短期气候预测的能力。如何利用这些资料开展研究工作以及在实际业务中应用这些资料是目前大气和海洋科学界的一个前沿课题。本研究将ARGO浮标资料引入了国家气候中心的NCC GODAS同化系统 ,结果分析表明 ,同化ARGO资料后所得到的海温场在三大洋中不仅在温度数值的大小 ,而且在分布形式方面都与观测场具有较好的一致性 ,可以很好地反映出观测到的冬季和夏季海温的分布形式以及海温的季节变化特征和异常特征。本研究还应用最新的ARGO海洋观测资料 ,通过建立新的热带西太平洋次表层海温参数化方案 ,改进了Zebiak Cane(1987)海洋模式 (ZC模式 ) ,克服了ZC模式几乎没有模拟赤道西太平洋表层和次表层海温变化能力的缺陷。在ZC模式中引用新的次表层海温参数化方案后 ,在赤道西太平洋不仅次表层海温的模拟得到了改善 ,对海面温度异常的模拟也有了较大的改进 ,不仅模拟出了赤道西太平洋表层和次表层海温异常的年际变化特征 ,也模拟出了与观     

Atmospheric Water Vapor Pressure over Land Surfaces: A Generic Algorithm with Data Input Limited to Air Temperature, Precipitation and Geographic Location

Summary A lack of information for surface water vapor pressure (WVP) represents a major impediment to model-assisted ecosystem analysis for understanding plant-environment interactions or for projecting biospheric responses to global climate change. This paper reports on a generic algorithm that captures global variation in monthly WVP. The algorithm solves WVP in terms of reduction from saturation WVP as a negative exponential function of potential evapotranspiration; the reduction rate per unit potential evapotranspiration in turn varies with monthly precipitation and a series of variables that distinguish local climate regimes. Data input to the algorithm is limited to monthly air temperature and precipitation, plus latitude, longitude and elevation. The algorithm is specified through regression fitting to monthly climate normal data from 852 stations around the world. It accounts for 96% of the variance in the WVP data, with a root mean square error of 0.17 kPa, or 12% of the data mean. The algorithm closely reproduces five-year sequential monthly WVP data for each of five selected United States locations representitative of diverse climate regimes: the average error generally falls within ±12% of the data mean, and the absolute error within ±0.2 kPa. Its projections also compare favorably against the WVP output from the General Circulation Models for temperature and precipitation conditions under the scenario of a doubled atmospheric carbon-dioxide concentration: the two fall within ±10% of each other for 75% of a total 264 data cases, or within ±20% for 94% of the cases. These statistics suggest that the spatially-based algorithm is useful for projecting temporal variation in WVP, and for extrapolative applications beyond the fluctuation range of present climate. Received March 4, 1999     

小白洋淀水-沉积物系统多环芳烃的分布、来源与生态风险

以端村小白洋淀为研究对象,利用GC-MS测定了6个样点水、悬浮物和沉积物中15种优控多环芳烃(PAHs)的含量,分析了其组成与来源特征,探讨了不同多环芳烃单体的生态风险,结果表明:(1)15种优控多环芳烃的总含量(PAH15),水相为40.1-74.0ng/L,算术均值51.0ng/L;悬浮物为2438.0-5927.0ng/g,算术均值4528ng/g;沉积物为466.9-1366.4ng/g,算术均值为755.6ng/g;与国内外有关研究相比,污染较轻,(2)三相中均以2、3环PAHs为主,其比例均高于80%;并且,从水相、悬浮物相到沉积物相,2环PAHs依次降低,3环、4环依次升高,高环检出率和含量也依次升高,(3)沉积物中多环芳烃的来源以生物质燃料(秸秆、薪材)和煤的燃烧为主,以液体化石燃料(汽油、柴油和原油)的燃烧为辅,(4)沉积物中的芴(FLO)、菲(PHE)含量在潜在生态风险效应区间低值(ERL)与中值(ERM)之间,其生态风险几率介于10%-50%之间;其他PAHs单体的含量均低于ERL,其生态风险几率均低于10%.     

A Case study of a snowstorm at the Great Wall Station,Antarctica

A case of a snowstorm at the Great Wall Station was studied using data of NCEP (National Centers for Environmental Prediction) analysis, in situ observations and surface weather charts. The storm occurred on August 29th,2006, and brought high winds and poor horizontal visibility to the region.It was found that the storm occurred under the synoptic situation of a high in the south and a low in the north. A low-level easterly jet from the Antarctic continent significantly decreased the air temperature and humidity.Warm air advection at high level brought sufficient vapor from lower latitudes for the snowstorm to develop.The dynamic factors relating to strong snowfall and even the developmentof a snowstorm were deep cyclonic vorticity at middle and low levels,the configuration of divergence at high level and convergence at low level, and strong verticaluplift. There was an inversion layer in the low-level atmosphere during the later phase of the storm.This vertical structure of cold air at low levels and warm air at high levels may have been important to the longevity of the snowstorm.     

Advances and Trends in Atmospheric Measurement by Smartphones*

With the development and popularization of smartphones and embedded sensors, a non-professional atmospheric measurement method by using smartphones carried by the public has been proposed recently. Without extra dedicated instrument, this method has many advantages, such as low hardware cost, high spatio-temporal resolution, and wide coverage, and it can supplement the professional atmospheric measurement methods, which has broad applications in the meteorological operation, scientific research, public service, and other fields. At present, the research on the non-professional atmospheric measurement in China is limited. In order to make full use of this method, this paper briefly outlined the states of existing smartphones and embedded sensors, highlighted the measurement of precipitation, air temperature, pressure, aerosols, and radiation by smartphones. To promote the development of smartphones for atmospheric measurement, future research should focus on mechanism study, available sources exploration, data quality control, big data processing, joining and matching with operation, research and service, etc.