黔北务-正-道铝土矿床矿物学特征研究

黔北务—正—道铝土矿集区为黔中—渝南铝土矿成矿带的重要组成部分,是贵州省主要的铝土矿成矿区带之一。含矿岩系为中二叠统梁山组,矿床成因属古风化壳沉积型。矿石化学成分分析显示,土状、碎屑状铝土矿中Al2O3含量较高,Al2O3/ SiO2值大,质量好,而豆鲕状、致密块状铝土矿中Al2O3含量较低,Al2O3/ SiO2值小,质量较差。显微观察、粉晶衍射和电子探针分析表明,铝土矿石中主要矿物为一水硬铝石、勃姆石和粘土矿物,其中一水硬铝石多为短柱、半自形-自形晶体,呈集合体分布,粘土矿物以高岭石为主,呈孤岛、残留环状产出,其次见伊利石、蒙托石、绿泥石等,副矿物有黄铁矿、磁铁矿、长石、石英、金红石、锆石、锐钛矿、方解石和白云石等。铝土岩中主要矿物为粘土矿物,以高岭石为主,其它矿物和铝土矿相似。铝土矿石的主要元素Al2O3、SiO2、TFe2O3 和TiO2含量之和大于83%,烧失量小于14%,而铝土岩的Al2O3、SiO2、TFe2O3 和TiO2含量之和小于80%,烧失量大于15%。可见铝土矿和铝土岩在主要矿物组成和主要组分总量上具有明显差异。结合以往研究资料,本文解析铝土矿形成过程为韩家店组砂页岩(成矿母岩)在适宜的气候条件下,经风化、淋滤等作用,形成富集Al、Ti等惰性元素的风化残积物和以高岭石为主的粘土矿物,随后被迁移、搬运至河湖盆地环境中,在沉积分过程中粘土矿物不断脱硅、去铁、富铝,形成铝土岩层,经埋深压实、成岩成矿作用后进一步脱硅、去铁、富铝,最终在中二叠世形成以一水硬铝石为主的铝土矿工业矿体。     

A new insight into the contribution of environmental conditions to tropical cyclone activities

The changes of tropical cyclone (TC) activities in response to influencing environmental conditions have been paid more and more attention to in recent years. The potential contributions of single and multivariate environmental variables to annual TC frequency and intensity from 1970 to 2009 are investigated in this study. Instead of using correlation coefficient that assumes a set of samples satisfying the normal distribution, a quantitative measurement is formulated based on the information theory. The results show that dynamic environmental variables play an important role in variations of TC activities over the western North Pacific, North Atlantic, and eastern Pacific. These dynamic factors include wind shear between 850 and 200 hPa and 850-hPa relative vorticity. However, the effects of thermal factors on TC activities are distinct over different basins. The thermal environmental variables only have significant contributions to TC frequency and intensity over the eastern Pacific as well as to TC frequency over the North Atlantic. It is found that the primary factors influencing TC activities are indeed not the same over different basins because of the differences in atmospheric conditions and their changes across different areas. The effects of dynamic variables should be considered more in the regions such as the western North Pacific where the thermal conditions are always satisfied.     

Diagnostics of subseasonal prediction biases of the Asian summer monsoon by the NCEP climate forecast system

Biases of subseasonal prediction of the Asian summer monsoon are diagnosed using daily data from the hindcasts of 45-day integrations by the National Centers for Environmental Prediction Climate Forecast System version 2. The retrospective forecasts often show apparent systematic biases, which are mostly represented by the underestimation of the whole Asian monsoon. Biases depend not only on lead time, but also on the stage of monsoon evolution. An abrupt turning point of bias development appears around late June and early July, when ensemble spread and bias growth of winds and precipitation show a significant change over the northwestern Pacific (NWP) and the South Asian summer monsoon (SASM) region. The abrupt turning of bias development of winds, precipitation, and surface temperature is also captured by the first two modes of multivariate empirical orthogonal function analysis. Several features appear associated with the abrupt change in bias development: the western Pacific subtropical high (WPSH) begins its first northward jump and the surface temperature over the Tibetan Plateau commences a transition from warm bias to cold bias, and a reversal of surface temperature biases occurs in the eastern tropical Indian Ocean and the SASM region. The shift of WPSH position and the transition of surface thermal bias show close relationships with the formation of bias centers in winds and precipitation. The rapid growth in bias due to the strong internal atmospheric variability during short leads seems to mainly account for the weak WPSH and SASM in the model. However, at certain stages, particularly for longer-lead predictions, the biases of slowly varying components may also play an important role in bias development of winds and precipitation.     

Influence of springtime North Atlantic Oscillation on crops yields in Northeast China

Forecasting grain production is of strategic importance in considerations of climate change and growing population. Here we show that the springtime North Atlantic Oscillation (NAO) is significantly correlated to the year-to-year increment of maize and rice yield in Northeast China (NEC). The physical mechanism for this relationship was investigated. Springtime NAO can induce sea surface temperature anomalies (SSTAs) in the North Atlantic, which display a tripole pattern and are similar to the empirical mode pattern in spring. The spring Atlantic SSTA pattern that could persists to summer, can trigger a high-level tropospheric Rossby wave response in the Eurasia continent, resulting in atmospheric circulation anomalies over the Siberia-Mongolia region, which is unfavorable (favorable) for cold surges that affect NEC. Weaker (stronger) cold surges can accordingly reduce (increase) cloud amount, resulting in an increase (a decrease) in daily maximum temperature and a decrease (an increase) in daily minimum temperature, thereby leading to an increase (a decrease) in diurnal temperature range. And summer-mean daily minimum temperature and diurnal temperature range are most significantly related to the NEC crop yields.     

A note on climate change adaptation for seaports: a challenge for global ports, a challenge for global society

With 80 % of world trade carried by sea, seaports provide crucial linkages in global supply-chains and are essential for the ability of all countries to access global markets. Seaports are likely to be affected directly and indirectly by climatic changes, with broader implications for international trade and development. Due to their coastal location, seaports are particularly vulnerable to extreme weather events associated with increasing sea levels and tropical storm activity, as illustrated by hurricane “Sandy”. In view of their strategic role as part of the globalized trading system, adapting ports in different parts of the world to the impacts of climate change is of considerable importance. Reflecting the views of a diverse group of stakeholders with expertise in climate science, engineering, economics, policy, and port management, this essay highlights the climate change challenge for ports and suggests a way forward through the adoption of some initial measures. These include both “soft” and “hard” adaptations that may be spearheaded by individual port entities, but will require collaboration and support from a broad range of public and private sector stakeholders and from society at large. In particular, the essay highlights a need to shift to more holistic planning, investment and operation.     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.     

不同参数化方案对风预报效果影响个例研究

中尺度气象模式对风场的预报效果与参数化方案的适应性紧密相关.以内蒙古高原丘陵地形、江苏平缓的海陆交界地形2种典型下垫面试验风电场为模拟区域,分别用WRFV3.2 （Weather Research and Forecast Model）模式自带的6种物理过程参数化组合方案预报了2010年1月和7月两个风电场区域的风速和风向,对比分析了参数化组合方案差异对风场预报的影响.结果表明：①内蒙古试验区,边界层MRF方案描述的边界层结构较MYJ方案合理;微物理方案WSM3在夏季的风速预报能力优于WSM6,而冬季相反;复杂地形区域的风场预报需考虑陆面过程参数化方案,尤其是夏季降水发生后,陆面过程对于边界层结构的影响增大,选用Noah优于无陆面过程.②江苏试验区,边界层MRF方案描述的边界层结构较MYJ方案合理;1月陆面过程RUC方案优于陆面热量扩散和Noah;7月陆面热量扩散方案优于RUC和Noah.③风向预报6个方案的预报风向统计与实际记录风向统计有较好的一致性,风向概率分布相似,盛行风向一致且稳定.     

基于中尺度模式与神经网络的风电功率预测

将中尺度数值天气预报模式与BP神经网络模型相结合用于风电功率预测,以WRF模式回算了2008年6月至2009年6月试验风电场的气象要素,精度检验结果显示风速预报值与对应实测值之间的相关系数达到0.72,风向、气温、湿度、气压的预报也比较准确,满足建立BP神经网络预报模型的需要.逐一建立试验风电场40台风电机组输出功率的BP神经网络预报模型,分析了数据标准化方法、隐含层神经元数对预报精度的影响.进行了26天实效为24 h的逐10 min预报试验,并以独立样本进行预报精度检验,结果显示单台风电机组输出功率相对均方根误差在24.8％～32.6％之间,预报值与实测值之间的相关系数现在0.45～0.68之间;风电场整体相对均方根误差为19.5％,预报值与实测值之间的相关系数为0.74.研究结果表明该方法可以用于实际的风电功率预测.