POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator

Journal Article · Fri Mar 29 00:00:00 EDT 2019 · Journal of Geophysical Research. Atmospheres

DOI:https://doi.org/10.1029/2018jd028317· OSTI ID:1612152

Matsui, Toshi ^[1]; Dolan, Brenda ^[2]; Rutledge, Steven A. ^[2]; Tao, Wei‐Kuo ^[3]; Iguchi, Takamichi ^[4]; Barnum, Julie ^[5]; Lang, Stephen E. ^[6]

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1. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Univ. of Maryland, College Park, MD (United States). Dept. of Physics; DOE/OSTI
2. Colorado State Univ., Fort Collins, CO (United States)
3. NASA Goddard Space Flight Center Greenbelt MD USA
4. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Univ. of Maryland, College Park, MD (United States). Dept. of Physics
5. Colorado State Univ., Fort Collins, CO (United States); Lab. for Atmospheric and Space Physics, Boulder, CO (United States0
6. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Science Systems and Applications, Inc., Lanham, MD (United States)

This paper introduces a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), for evaluating cloud-resolving models (CRMs). POLARRIS is composed of forward (POLARRIS-f) and inverse (retrieval and diagnostic) components (iPOLARRIS) to generate not only polarimetric radar observables ($$Z_h, Z_{dr}, K_{dp}, ρ_{hv})$$ but also radar-consistent geophysical parameters such as hydrometeor identification, vertical velocity, and rainfall rates retrieved from CRM data. To demonstrate its application and uncertainties, POLARRIS is applied to simulations of a mesoscale convective system over the Southern Great Plains on 23 May 2011, using the Weather Research and Forecasting model with both spectral bin microphysics (SBM) and the Goddard single-moment bulk 4ICE microphysics. Statistical composites reveal a significant dependence of simulated polarimetric observables $$(Z_{dr}, K_{dp})$$ on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. We note the simulated polarimetric variables differ considerably between the SBM and 4ICE microphysics in part due to the differences in their ice particle size distributions as revealed by comparisons with aircraft measurements. Regardless of these uncertainties, simulated hydrometeor identification distributions overestimate graupel and hail fractions, especially from the simulation with SBM. To minimize uncertainties in forward model, the particle shape and orientation angle distributions of frozen particles should be predicted in a microphysics scheme in addition to the size distributions and particle densities.

• Research Organization: Colorado State Univ., Fort Collins, CO (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: SC0014371
• OSTI ID: 1612152
• Journal Information: Journal of Geophysical Research. Atmospheres, Journal Name: Journal of Geophysical Research. Atmospheres Journal Issue: 8 Vol. 124; ISSN 2169-897X
• Publisher: American Geophysical Union
• Country of Publication: United States
• Language: English

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
54 ENVIRONMENTAL SCIENCES
CRM
MC3E
convection
meteorology & atmospheric sciences
microphysics
polarimetric radar
simulator