二维粒子形状分类技术在云微物理特征分析中的应用

本文介绍了一种针对飞机粒子探测系统中云二维图像探头开发的二维粒子形状分类技术。该技术利用粒子形状几何参数特征把云粒子分为8种类型,分别为微小状、线形状、聚合状、霰状、球状、六角形状、不规则状和枝状。同时结合冰水质量关系,给出了探头液水含量和冰水含量的计算方法。最后应用该技术对2006年4月6日一次飞机探测获取的数据进行了云微物理结构分析,聚合状、霰状、六角形状、不规则状的总出现频率为78%,其中霰状粒子的出现频率随着温度的降低而增加。非降水云中的液水含量、液滴粒子浓度、冰晶浓度明显小于降水云,非降水云中液水含量的平均值为0.01 g m-3,冰水含量的平均值0.007 g m-3,冰晶粒子浓度的平均值为11.9 L-1。     

A differential optical absorption spectroscopy method for {X_{CO_2}} retrieval from ground-based Fourier transform spectrometers measurements of the direct solar beam

A differential optical absorption spectroscopy (DOAS)-like algorithm is developed to retrieve the column-averaged dry-air mole fraction of carbon dioxide from ground-based hyper-spectral measurements of the direct solar beam. Different to the spectral fitting method, which minimizes the difference between the observed and simulated spectra, the ratios of multiple channel-pairs——one weak and one strong absorption channel——are used to retrieve X CO2 from measurements of the shortwave infrared (SWIR) band. Based on sensitivity tests, a super channel-pair is carefully selected to reduce the effects of solar lines, water vapor, air temperature, pressure, instrument noise, and frequency shift on retrieval errors. The new algorithm reduces computational cost and the retrievals are less sensitive to temperature and H2O uncertainty than the spectral fitting method. Multi-day Total Carbon Column Observing Network (TCCON) measurements under clear-sky conditions at two sites (Tsukuba and Bremen) are used to derive X CO2 for the algorithm evaluation and validation. The DOAS-like results agree very well with those of the TCCON algorithm after correction of an airmass-dependent bias.