近百年全球平均地面气温准周期信号及其长期演变特征的分析

应用奇异谱分析(SSA)方法,对全球及南北半球近100多年(1856～1997年)逐月地面气温距平序列的年际变化准周期性进行诊断分析,结果表明,全球平均气温序列中以准5～6年和准4年周期振荡最显著,其次是准两年周期振荡.各种准周期振荡年代际演变特征及其变率的阶段性,不但表现在振幅上,而且其波数亦很明显.上述特征在全球、南北半球都各有明显的差异.奇异交叉谱分析(SCSA)表明,全球平均地面气温的年际振荡与气候系统中其他各子系统所隐含的准周期信号具有各种耦合关系,尤其表现在与Nino区海温或南方涛动指数中的准周期信号的耦合关系上.     

Quaternary vertical offset and average slip rate of the Nojima Fault on Awaji Island, Japan

Abstract Drilling was carried out to penetrate the Nojima Fault where the surface rupture occurred associated with the 1995 Hyogo-ken Nanbu earthquake. Two 500 m boreholes were successfully drilled through the fault zone at a depth of 389.4 m. The drilling data show that the relative uplift of the south-east side of the Nojima Fault (south-west segment) was approximately 230 m. The Nojima branch fault, which branches from the Nojima Fault, is inferred to extend to the Asano Fault. From the structural contour map of basal unconformity of the Kobe Group, the vertical component of displacement of the Nojima branch–Asano Fault is estimated to be 260–310 m. Because the vertical component of displacement on the Nojima Fault of the north-east segment is a total of those of the Nojima Fault of the south-west segment and of the Nojima branch–Asano Fault, it is estimated to total to 490–540 m. From this, the average vertical component of the slip rate on the Nojima Fault is estimated to be 0.4–0.45 m/10³ years for the past 1.2 million years.     

脉冲电镀金刚石钻头试验研究

介绍脉冲电镀在人造金刚石孕镶钻头上的应用研究，探讨脉冲电镀机理，采用正交试验法优化脉冲电镀工艺参数；研制了脉冲电镀钻头，生产钻头周期缩短了３０％。在室内和野外生产试验中，发现脉冲电镀钻头较直流电镀钻头有如下优点：钻进地层适用范围广、钻进时效高。     

瞬变电磁测深法的研究深度

研究发现,瞬变测深法研究深度除了与采样时间(采样间隔,起始和终止采样时间等)有关外,还与信号源强度、大地电导率、系统噪音水平以及仪器观测精度等因素有关,文中对研究深度与这些量之间的关系作了数学描述。     

用CAPPI和PPI资料测定区域降水量精度比较

应用上海中心气象台７１４数字化天气雷达的体积扫描资料所得的不同高度上的ＣＡＰＰＩ资料和低仰角时ＰＰＩ资料。估算区域降水量并得到降水量分布形势。然后采用平均校准法进行了校准，最后又与用雨量计网测量的区域降水量及其分布形势作了比较，得到一些有意义的结果。     

集成奇异谱分析和自回归滑动平均预测日本近海海平面变化

本文从日本沿岸选取了28个验潮站及联测的GPS站,利用奇异谱分析（Singular Spectrum Analysis,SSA）和SSA+自回归滑动平均（Auto Regression Moving Average,ARMA）方法预测了2014—2018年的近海海平面变化和地壳垂直变化.并用同时段的验潮及GPS的实际测量值进行验证,结果显示,SSA+ARMA预测的相对海平面精度为0.0357~0.0607 m,地壳垂直运动的精度为0.0049~0.0077 m,绝对海平面的精度为0.0433~0.0683 m,且三者SSA+ARMA的预测结果均优于只用SSA预测的结果.在此基础上本文利用SSA+ARMA预测了日本沿岸2019—2023年的近海绝对海平面变化,结果显示,2019—2023年的平均海面高较往年（2014—2018）升高0.0353 m,2003—2023年绝对海平面的变化率为0.0039 m·a^-1,预测结果较为理想.     

珠江三角洲东部常平地区景观异质性研究

本文以１９８８年－１９９６年６个时段景观遥感类型图为主要信息源,利用信息熵法和空隙度指数法对珠江三角洲东部常平地区的景观异质性进行了研究。重点探讨了景观组分的空间分布差异和异质性动态变化情况。结果显示,开发区主要呈宏观异质性分布,果园,农田和林地呈微观异质性分布,城镇和水体的异质性分布特征均出现显著变化。     

Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique

ABSTRACT

The reliable and robust monitoring of air temperature distribution is essential for urban thermal environmental analysis. In this study, a stacking ensemble model consisting of multi-linear regression (MLR), support vector regression (SVR), and random forest (RF) optimized by the SVR is proposed to interpolate the daily maximum air temperature (T_max) during summertime in a mega urban area. A total of 10 geographic variables, including the clear-sky averaged land surface temperature and the normalized difference vegetation index, were used as input variables. The stacking model was compared to Cokriging, three individual data-driven methods, and a simple average ensemble model, all through leave-one-station-out cross validation. The stacking model showed the best performance by improving the generalizability of the individual models and mitigating the sensitivity to the extreme daily T_max. This study demonstrates that the stacking ensemble method can improve the accuracy of spatial interpolation of environmental variables in various research fields.     

On smoothing techniques for the removal of periodic noise of known period

This paper is concerned with the analysis of the linear modely(n)=X(n)+S(n)+(n) for the data sequencey(n) (n=1, 2, ..., N) whereX={x _IJ} is a knownJ × M matrix of full rankM. Here, the(n) are unknown vectors, which we wish to estimate for eachn; S(n) (n=1, 2, ..., N) is a periodic component (which we wish to estimate or remove) superimposed on the linear structureX(n); and(n) is an error vector which is specified as having zero expectation (with possible further properties). Such models commonly occur in geophysical data analysis.Modified from Technical Report No. 33, Computer Centre, The Australian National University.