一阶Buterworth递归式带通滤波器技术改进方案

把一阶Ｂｕｔｔｅｒｗｏｒｔｈ递归式（ＦＢＲ）带通滤波器应用于滑动样本,输出序列出现了振幅和位相的相对误差。为了克服这种现象给制作中长期预报带来的困难,作者通过数值试验,分析了该滤波器的误差传递特性,并设计了“拟定初值的三步滤波方案”。大量试验表明,该方案可较为有效地抑制输出序列的误差和位相飘移     

CMIP5气候模式对中国东部夏季降水年代际变化的模拟性能评估

使用分类集合的方法评估了第五次耦合模式比较计划(CMIP5)多个耦合模式对中国东部夏季降水年代际变化的模拟性能.结果表明,在评估的38个模式中,仅有6个模式(第1类模式)可以成功再现1970年代末中国东部夏季降水年代际变化的主要特征,即长江流域降水偏多、而华北和华南偏少.这些模式模拟的成功归因于它们能较好再现1970年代末东亚夏季风的年代际减弱及相关的环流场的变化,包括东亚沿海的偏北风异常以及西太平洋副热带高压的偏向西南、强度增强等.而对降水年代际变化模拟很差的第2类模式,则模拟出不出东亚夏季风的这种减弱特征.进一步的分析表明,两类CMIP5模式对太平洋年代际振荡(PDO)空间分布特征都有较好的再现能力,但对PDO年代际转变特征的模拟能力则差异较大.第1类模式能很好地模拟出1970年代末热带海洋的增暖和相关的PDO位相由负到正的转换,而第2类模式所模拟的PDO位相转变与观测完全相反,且也不能模拟出热带中东太平洋海洋的年代际增暖及江淮流域夏季的变冷,因此导致该类模式对1970年代末东亚夏季风的减弱和中国东部夏季雨型的年代际转变没有模拟能力.由此也表明,对耦合模式来说,中国夏季降水年代际变化的模拟能力在很大程度上取决于模式对海洋年代际变化信号的模拟.     

基于显著性分析的SAR溢油图像中暗斑区域检测方法研究

为了提高合成孔径雷达(synthetic aperture radar,SAR)图像中海上溢油的检测精度,设计了一种图像显著性和均值偏移分割相结合的暗斑检测方法,验证了该方法在SAR溢油图像暗斑识别中的有效性,为溢油区域的准确检测奠定了基础.针对SAR溢油图像中暗斑区域在人类视觉中属于感兴趣区域的特性,利用图像显著性检...     

Data augmentation for bias correction in mapping PM2.5 based on satellite retrievals and ground observations

As most air quality monitoring sites are in urban areas worldwide, machine learning models may produce substantial estimation bias in rural areas when deriving spatiotemporal distributions of air pollutants. The bias stems from the issue of dataset shift, as the density distributions of predictor variables differ greatly between urban and rural areas. We propose a data-augmentation approach based on the multiple imputation by chained equations (MICE-DA) to remedy the dataset shift problem. Compared with the benchmark models, MICE-DA exhibits superior predictive performance in deriving the spatiotemporal distributions of hourly PM_2.5 in the megacity (Chengdu) at the foot of the Tibetan Plateau, especially for correcting the estimation bias, with the mean bias decreasing from –3.4 µg/m³ to –1.6 µg/m³. As a complement to the holdout validation, the semi-variance results show that MICE-DA decently preserves the spatial autocorrelation pattern of PM_2.5 over the study area. The essence of MICE-DA is strengthening the correlation between PM_2.5 and aerosol optical depth (AOD) during the data augmentation. Consequently, the importance of AOD is largely enhanced for predicting PM_2.5, and the summed relative importance value of the two satellite-retrieved AOD variables increases from 5.5% to 18.4%. This study resolved the puzzle that AOD exhibited relatively lower importance in local or regional studies. The results of this study can advance the utilization of satellite remote sensing in modeling air quality while drawing more attention to the common dataset shift problem in data-driven environmental research.