A statistical analysis method estimating dust aerosol-ice cloud interactions using global circulation model and satellite data

A statistical analysis method to quantify dust aerosol interactions with ice cloud properties using IASI satellite data has been developed and published by L. Klüser et al. 2017. Key components of analyzing cloud properties are their classification by aerosol load and their normalization in respect to the meteorological state using a Bayes-approach. Comparing histograms of cloud properties for different aerosol classes gives then insight in statistical changes of their distribution. Using the same method twice on IASI-IMARS satellite retrieval and EMAC-MADE3 global circulation model data yields valuable insights on changes in cloud forming and lifecycle behavior inflicted by dust aerosol pollution. Overcoming scale differences between observation and simulation data sets has been a major obstacle as they have evident impact on the analysis results. Therefore, a statistical downscaling method has been customized to EMAC-MADE3 model data that focuses on preservation of critical processes while still approximating fine-scale patterns below model resolution. Both statistical analysis results for model and satellite data show clear aerosol impact on cloud property distributions with varying magnitudes and demonstrate the necessity of downscaling. More detailed analysis conducted with an increased number of aerosol classes shows quantifiable trends in aerosol impact on cloud properties.