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Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. 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 promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. 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 are used to evaluate the scattering improvements.

Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator 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
20230002598
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Isaac Moradi
(University of Maryland, College Park College Park, Maryland, United States)
Benjamin Johnsson
(National Center for Atmospheric Research Boulder, Colorado, United States)
Patrick Stegmann
(National Center for Atmospheric Research Boulder, Colorado, United States)
Alan Geer ORCID
(European Centre for Medium-Range Weather Forecasts Reading, United Kingdom)
Patrick Eriksson ORCID
(Chalmers University of Technology Gothenburg, Sweden)
Ronald Gelaro
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Satya Kalluri
(National Oceanic and Atmospheric Administration Washington D.C., District of Columbia, United States)
Will McCarty
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Date Acquired
February 24, 2023
Subject Category
Communications and Radar
Meeting Information
Meeting: ESSIC Seminar Series
Location: College Park, MD
Country: US
Start Date: February 27, 2023
Sponsors: University of Maryland, College Park
Funding Number(s)
CONTRACT_GRANT: 80NSSC21K1361
CONTRACT_GRANT: NA19NES4320002
CONTRACT_GRANT: 80NSSC23M0011
CONTRACT_GRANT: GSFC - 606.2 GRANT
CONTRACT_GRANT: NOAA-JPSS
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
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