Day 4

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Paper title Analysis of vertical profiles of cloud properties from passive sensor based on the EarthCARE Simulator
Authors
  1. Anja Hünerbein Leibniz-Institute for Tropospheric Research Speaker
  2. Sebastian Bley Leibniz Institute for Tropospheric Research (TROPOS)
  3. Hartwig Deneke Leibniz Institute for Tropospheric Research (TROPOS)
  4. David Patrick Donovan Royal Netherlands Meteorological Institute (KNMI)
  5. Moritz Haarig Leibniz Institute for Tropospheric Research (TROPOS)
  6. Shannon Mason European Centre for Medium-Range Weather Forecasts (ECMWF)
  7. Ulla Wandinger TROPOS
Form of presentation Poster
Topics
  • A1. Atmosphere
    • A1.09 EarthCARE: Preparing for the Scientific Mission Exploitation to Quantify the Impact of Clouds and Aerosols on Radiation
Abstract text The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. This will make it possible to extend the products obtained from the combined active/passive observations along the ground track into the swath by means of active/passive sensor synergy, to estimate the 3D fields of clouds and to assess radiative closure. The backscatter lidar (ATLID) and cloud profiling radar (CPR) will provide vertical profiles of cloud and aerosol parameters with high spatial resolution. Complementing these active measurements, the passive multi-spectral imager (MSI) delivers visible and infrared images for a swath width of 150 km and a pixel size of 500 m. MSI observations will be used to extend the spatially limited along-track coverage of products obtained from the active sensors into the across-track direction. In order to support algorithm development and to quantify the effect of different instrument configurations on the mission performance, an instrument simulator (ECSIM) has been developed for the EarthCARE mission. ECSIM is an end-to-end simulator capable to simulate all four instruments for complex realistic scenes. Specific ECSIM test scenes have been created from weather forecast model output data. The 6000 km long frames include clouds over the Greenland ice sheet, followed by high optical thick clouds, a high ice cloud regime as well as low-level cumulus cloud embedded in a marine aerosol layer below and an elevated intense dust layer above. These synthetic scenes make it possible to evaluate and intercompare the different cloud properties from active and passive sensors such as cloud liquid water path or cloud effective radius. Further the input of the synthetic scenes offer the opportunity to extract the extinction profiles for each MSI pixel, and to contrast them to the retrieved cloud properties and types. This approach can be used to better understand and quantify the differences between the retrieved cloud properties based on the different measurement principles (passive and active). For example, the cloud top height retrieved from MSI is an effective height of infrared emission located within the cloud, and it is important to quantify differences to the geometric cloud top height to constrain the longwave cloud radiative effect. Another quantity of interest is the cloud effective radius from CPR, which is most sensitive to large particles in the clouds, while MSI is only sensitive to very small particles on the top of the cloud. The goal is to understand the differences of the cloud products from CPR, ATLID and MSI by comparison to the reference fields to enable a consistent comparison.