A020-02
A satellite-derived ice cloud parameterization for numerical weather prediction models
Monday, 7 December 2020: 16:04
Virtual
Erica Dolinar, American Society for Engineering Education, Monterey, CA, United States, James R Campbell, Naval Research Laboratory, Monterey, CA, United States, Anne Garnier, Science Systems and Applications, Inc. Hampton, Hampton, VA, United States, Jared Wayne Marquis, University of North Dakota, Department of Atmospheric Sciences, Grand Forks, ND, United States, Theodore McHardy, University of Arizona, Department of Hydrology and Atmoshperic Sciences, Tucson, AZ, United States, Bryan Mills Karpowicz, Goddard Earth Sciences Technology and Research, Greenbelt, MD, United States and Kevin Viner, U.S. Naval Research Laboratory, Marine Meteorology Division, Monterey, CA, United States
Abstract:
A new ice cloud parameterization for numerical weather prediction (NWP) applications is described based on satellite remote sensing data products. We demonstrate the new model and its impact on the performance of the Navy’s global NAVGEM NWP system. Size-agnostic NWP models solve for ice particle size (D
e) as a function of ice water content and temperature in order to predict the cloud radiative properties (i.e., spectral scattering and absorption). Many such parameterizations still in use today rely on relationships developed from decades-old in situ aircraft measurements, which are now recognized as having likely been biased by crystal shattering induced by older sensor designs. Satellite-based D
e retrievals are thus applied as a means for creating sufficiently robust datasets to render statistically-significant parameterization relationships, as well as to constrain potential regional variability in such relationships.
A combination of measurements from instruments on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat satellites are used to develop relationships between ice cloud De, temperature, & 532 nm lidar-derived extinction coefficient (σ532). De is passively derived from the Imaging Infrared Radiometer (IIR) instrument for relatively cold, single-layer semi-transparent ice clouds, whereas the corresponding effective σ532 comes from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. For thicker and warmer cloud elements, cloud layers are characterized based on the CloudSat-CALIPSO Ice Cloud Property (2C-ICE) product. Since IIR estimates are tied to a single downstream optical model (i.e., Yang et al. 2013), portions of the parameterization are physically consistent with the optical model, which we have further integrated for testing in NAVGEM. One month’s worth of global data (January 2008) are combined to derive a new set of equations that relate De, temperature, and σ532 for a spectrum of ice clouds ranging 190 – 280 K. We demonstrate impact on NAVGEM over two months of runs from 2018.
