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Community Radiative Transfer Model: Implementing A New Cloud Scattering Database and Developing the Forward Radar Module The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promises in calculating the scattering properties of particles with different shapes in the microwave frequencies. The goal of the research was to enhance the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. Given that such optical properties cannot be practically calculated on the fly, pre-computed look-up tables need to be implemented into the fast RT models to calculate the scattering properties of these particles using the DDA technique and the inputs provided by the users. Therefore, we implemented such pre-computed DDA databases into CRTM. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system will be used to evaluate the scattering improvements. Additionally, we used the backscattering information from the DDA database to implement a radar simulator into CRTM. The radar operators takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.
Document ID
20220017886
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Isaac Moradi
(University of Maryland, College Park College Park, Maryland, United States)
Patrick Stegmann
(Joint Center for Satellite Data Assimilation Boulder, Colorado, United States)
Benjamin Johnson
(University Corporation for Atmospheric Research Boulder, Colorado, United States)
Ronald Gelaro
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Date Acquired
November 28, 2022
Subject Category
Meteorology and Climatology
Meeting Information
Meeting: AGU Fall Meeting 2022
Location: Chicago, IL
Country: US
Start Date: December 12, 2022
Sponsors: American Geophysical Union
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: 80NSSC21K1361
CONTRACT_GRANT: NA19NES4320002
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
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