Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

大气环流的季节突变与季风的建立Ⅰ.基本理论方法和气候场分析

将曾庆存等提出的大气环流的季节划分和计算季风的理论方法作了改进,使之更便于研究季风的建立过程.该理论方法将环流突变和季风建立时段,其"变差度"和与其前和其后场的"相似度"等由空间场的泛函随时间的变化(即数学名词上的"流"[flow])一起求出来.研究Ⅰ先分析气候平均场,Ⅱ分析各个别年份的情况及年际变化.研究Ⅰ的结果表明:(1)该方法可以客观定量地定出"突变"时段的关键日期;与季风建立过程联系,即是季风建立的"预兆日期",它比人们用天气-气候学方法(甚至用别的气象要素)定出的可以明显感觉到的或有明显实用价值的"季风来临日期"要早2至4天.(2)在北半球亚澳季风系统区域,夏季风的来临在许多关键地区伴有明显的环流突变,建立和推进者很快,但也有许多区域不表现为当地环流的突变,推进速度也慢.(3)北半球亚澳季风系统低空的热带季风分支,在6月中以前可明确区分为3个子系统,(a)西太平洋暖池和邻近低纬区域,4月中下旬建立;(b)热带东北印度洋(北界与孟加拉湾相邻,但不包括其在内)及索马里东边海洋,4月末至5月初建立;和(c)南海区域,5月上旬从南到5月下旬到北部.南海夏季风向北推进最快,于5月末候即可达北回归线附近,然后与暖池西北区域风场的突变一起,于6月中旬影响到东亚30°N区域;印度洋季风于6月初到达印度半岛东南端,然后逐渐推向印-巴次大陆.7月中以后,热带季风才连成一片,由非洲东岸直至长江下游和菲律宾附近.副热带季风分支于6月中旬可以感到其影响,于7、8月盛行于东亚和西太平洋区域,且结构和演变都比较复杂;6～7月间只表现为在(5～20°N,120～150°E)区域有强的环流突变(与副高增强并北移对应),7月中至8月底,则在上述区域和沿30°N的长江下游和日本以南的洋面上有3个强的环流突变中心(对应于副高又一次增强北移和西伸).这里暂不讨论温寒带季风分支.(4)季风具有鲜明的三度空间斜压结构,尤其是在低空季风"爆发"之前,平流层早已有强的环流突变,季节调整完成,然后突变向下延伸(虽然强度大减),跟着就有当地的低空季风"爆发"(建立).平流层和对流层环流的相互作用及其与季风建立的关系很值得进一步研究.     

东北地区汛期降水异常的大气环流特征分析

针对东北地区汛期(7~8月)的情况,分析了造成汛期降水异常的大气环流特征,结果表明:汛期多(少)雨年,低层850 hPa蒙古东南的气旋(反气旋)式距平环流、我国大陆东部的西南风(东北风)距平气流及日本南面的反气旋(气旋)式距平环流的共同作用加强(减弱)了低层西南暖湿气流在东北地区的辐合;多(少)雨年,中层500 hPa中高纬西风带经向运动加强(减弱),从贝加尔湖以北的高纬地区到日本附近的高度场呈 - (- -)的波列分布。8月的环流形势比7月更容易造成严重旱涝,下游鄂霍茨克海和日本海阻塞高压的发展和减弱是造成8月降水异常的重要因子。考虑7月旱涝流型演变时,应着重关注南北向 - 的“波列”;而考虑8月旱涝流型演变时,则更应着重关注东西向- - -的“波列”配置。多、少雨年,高、低层的散度场、垂直速度场及水汽条件等物理量场都有明显的差异。     

中国大陆GNSS连续站观测噪声的时空分布

为了全面分析我国大陆及其周边GNSS连续站噪声的空间分布规律,该文基于陆态网络260个GNSS连续站和周边区域10个IGS站的观测数据,利用GAMIT/GLOBK软件进行解算,得到各站的坐标值及其N、E、U 3分量误差值,制定筛选标准,依据该标准剔除质量差的测站,剔除异常值;利用Matlab软件,按照东向(E分量)、北向(N分量)、垂向(U分量)3个方向进行拟合,并提取各测站单日解的最大误差值出现的年积日,绘制其在我国大陆的空间分布图,得到中国大陆GNSS连续站最大单日误差值的时空分布特性图。发现大部分GNSS连续站单日最大误差值集中在夏季(7月居多)并分析了原因。     

近50年黄河上游径流量与气候变化特征研究

根据1956-2010年唐乃亥水文站逐月径流量资料和1961-2009年黄河上游兴海、泽库、玛沁、达日、久治、玛多6个代表站的降水量、气温资料,分析了唐乃亥站径流量与黄河上游地区降水和气温的气候变化特征及其关系.结果表明:春、夏、秋、冬季的径流量分别占年径流量的14.9%、2.9%、34.7%、7.5%;唐乃亥站年和四...     

Partitioning of heavy metals on soil samples from column tests

In this study, column tests were used to determine the retention capability of three types of estuarine alluvia collected adjacent to landfill sites in South Wales. Selective sequential extraction (SSE) was used to study the retention mechanisms of heavy metals in the soil columns obtained from leaching experiments. Acid digestion was later used to check the validity of the SSE results. Breakthrough curves show good retention of heavy metal ions (Pb, Cu, and Zn) by all soils, where almost 99% of heavy metals were retained with the C_e/C_o values in the order of 10⁻³. The retention strength of these soils was observed to be constant up to five pore volumes (PV). This corresponds with the pH of the effluents and pore water of soil slices, which also show good buffering capacity against very acidic leachate up to 5PV. The heavy metal extraction profiles from SSE show very similar trends with the retention profiles from the leaching experiments, where heavy metals were retained mainly at the top part where the leachate entered the column. SSE indicates qualitatively that heavy metals precipitated with carbonates and amorphous materials (oxides/hydroxides) are higher than heavy metal retention via exchangeable mechanisms. The mass balance calculation gives range of deviation of 1–16% of the total soil extraction. The distribution of the heavy metals with various soil constituents are ranked in the following order: Carbonates>Amorphous oxides hydroxides>Organic matter>Exchangeable phases.     

2016年夏季DOGRAFS系统站点24h降水量级预报检验

随着精细化降水预报的要求和发展,模式对站点定量降水预报已成为天气预报业务的主要参考依据之一。本文对乌鲁木齐区域数值天气预报系统DOGRAFS v1.0在2016年夏季全疆105个站点的24h累积降水量的预报性能进行统计检验。结果表明：(1)除山区外,全疆晴天预报准确率达到85%以上,其中南疆盆地、吐鄯托盆地晴天预报准确率达到95%以上。(2)对于小雨出现较多的站点,预报准确率达到55%以上、部分站点达到70%,同时上述区域存在15%左右的报强率;对于降水较少的南疆盆地和吐鄯托盆地整体以漏报为主,漏报率在80%以上。(3)北疆大部分地区和南疆西部山区的中雨预报准确率整体在30%左右;中雨日数较多的中天山及其两侧预报准确率约60%,该区域也存在20%左右的报强率;其他地区预报降水较实况以偏弱为主。(4)大雨及以上量级降水,模式预报整体表现为偏弱,对于大降水出现较多的地区预报平均准确率为25-30%。     

Paleoclimatic implications of the spatial patterns of modern and LGM European land-snail shell δO

The oxygen isotopic composition of land-snail shells may provide insight into the source region and trajectory of precipitation. Last glacial maximum (LGM) gastropod shells were sampled from loess from Belgium to Serbia and modern land-snail shells both record δ¹⁸O values between 0‰ and − 5‰. There are significant differences in mean fossil shell δ¹⁸O between sites but not among genera at a single location. Therefore, we group δ¹⁸O values from different genera together to map the spatial distribution of δ¹⁸O in shell carbonate. Shell δ¹⁸O values reflect the spatial variation in the isotopic composition of precipitation and incorporate the snails' preferential sampling of precipitation during the warm season. Modern shell δ¹⁸O decreases in Europe along a N-S gradient from the North Sea inland toward the Alps. Modern observed data of isotopes in precipitation (GNIP) demonstrate a similar trend for low-altitude sites. LGM shell δ¹⁸O data show a different gradient with δ¹⁸O declining toward the ENE, implying a mid-Atlantic source due to increased sea ice and a possible southern displacement of the westerly jet stream. Balkan LGM samples show the influence of a Mediterranean source, with δ¹⁸O values decreasing northward.     

Study of occurrence states and precipitation mechanism of tellurium in Huangtun Au -Cu -bearing breccia pipe in Luzong Basin,Anhui, eastern ChinaSCIEI北大核心CSCD

隐爆角砾岩筒型金(铜)矿床作为重要的金矿床类型,常伴生关键金属碲的矿化,然而对于此类矿床中碲的分布、分配特征及沉淀机制研究仍较为薄弱。黄屯矿床是长江中下游成矿带近年来发现的最为典型的隐爆角砾岩筒型金铜矿床,伴生有大量的碲化物产出。本文在详细的野外地质工作和岩相学观察基础上,发现碲在矿床中发生了显著富集。通过对黄屯矿床不同蚀变类型矿石及主要富碲矿物开展全岩及微区地球化学分析,明确了碲的分布、分配特征以及初步讨论了碲的沉淀机制。黄屯矿床成矿阶段从早到晚可划分为钠钙硅酸盐、钾硅酸盐、绿泥石-碳酸盐和伊利石-蒙脱石阶段,在不同深度形成了相应的蚀变带,并发育有不同强度的金铜矿化。黄屯矿床伴生的碲储量约有118.71t,平均品位为5.3g/t,达到中型规模,具备重要的综合利用价值。钾硅酸盐蚀变带碲的分布比例最高,占总储量约92.37%,平均品位约为9.6g/t。钾硅酸盐蚀变带内约有89%~99%的碲呈独立矿物,主要以微米级、纳米级的碲铋矿包体的形式分布在黄铁矿中,剩余部分则以类质同象的形式赋存在黄铁矿和黄铜矿内。减压沸腾引起流体温度骤降导致硫化物沉淀,和沸腾过程中释放大量气相H_(2)S,共同导致流体的f(Te_(2))/f(S_(2))比值升高,可能是黄屯矿床中碲沉淀富集的主要机制。     

复杂地形下C波段雷达定量降水估计算法

C波段雷达定量降水估计(QPE)精度受到很多因素的影响,主要包括:(1)雷达标定,(2)非气象回波的干扰,(3)降水物垂直空间变化,(4)地形或地物的严重遮挡,(5)Z-R关系的代表性,(6)雷达拼图的质量,(7)雷达观测回波衰减等.文中雷达定量降水估计算法基于陕西省C波段天气雷达展开,从雷达探测数据质量控制、地形遮挡...