Gala Wind, Arlindo da Silva, Kerry Meyer, Steven Platnick, Peter Norris, Shana Mattoo, Robert Levy and Sanjeeb Bhoi
We firmly believe that we achieve the best results when we get different disciplines to work together. MCARS is an open collaboration between modeling, cloud remote sensing and aerosol remote sensing communities. MCARS wears many hats and can act as both a remote sensing algorithm proofing sandbox and be a high-resolution model intercomparison tool all at the same time, from a single data run.
In this talk we will primarily look at the “sandbox” aspect of MCARS. We first examine performance of MODIS Data Collection 6 operational Dark Target aerosol product (MYD04_DT). We show the source of low bias in MYD04_DT retrievals for smoke aerosols and make suggestions for future development. We then examine performance of the research-level Above-Cloud Aerosol MODIS retrieval algorithm (MOD_ACAERO). We make suggestions for the algorithm development as it prepares to transition to operations. As above-cloud aerosols are of great interest to modeling community as a new source of data to assimilate, we examine the MOD_ACAERO retrievals and make suggestions as to what would be the best way to assimilate the retrieval data into a GCM such as GEOS-5.