水体后向散射系数校正方法研究

后向散射系数是水色反演半分析模型的重要参数,后向散射系数的测量与分析是固有光学测量与分析的重要组成部分。为了更准确的获得后向散射系数数据,根据不同的实际测量情况提出了两种后向散射系数数据的校正方法,即利用散射与后向散射系数模型计算的散射系数替代法和实测数据替代法。结果表明这两种方法在比传统的数据校正方法有明显的优势,是一种符合水体剖面固有光学特性规律的数据校正方法。     

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.     

太阳光度计反演大气水汽总量的方法与结果对比分析

详述了使用太阳光度计反演大气水汽柱总量的反演方法—单通道法和双通道法,其中双通道法又可采用不同 的非水汽通道来实现。考虑到气溶胶光学厚度及瑞利散射的影响,分析了不同方法反演所得水汽总量相对探空数据的 误差。结果表明,这些方法的反演结果非常接近。在实际应用中,可使用任一种方法来反演水汽。