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POLARRIS: A POLArimetric Radar Retrieval and Instrument SimulatorThis 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 (Zh, Zdr, Kdp, ρhv) 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 (Zdr, Kdp) on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. 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.
Document ID
20210013178
Acquisition Source
Goddard Space Flight Center
Document Type
Accepted Manuscript (Version with final changes)
Authors
Toshi Matsui ORCID
(University of Maryland, College Park College Park, Maryland, United States)
Brenda Dolan ORCID
(Colorado State University Fort Collins, Colorado, United States)
Steven A Rutledge ORCID
(Colorado State University Fort Collins, Colorado, United States)
Wei-Kuo Tao ORCID
(Goddard Space Flight Center Greenbelt, Maryland, United States)
Takamichi Iguchi ORCID
(University of Maryland, College Park College Park, Maryland, United States)
Julie Barnum
(Colorado State University Fort Collins, Colorado, United States)
Stephen Lang
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Date Acquired
April 5, 2021
Publication Date
March 29, 2019
Publication Information
Publication: JGR Atmospheres
Publisher: Wiley (AGU)
Volume: 124
Issue: 8
Issue Publication Date: April 27, 2019
ISSN: 2169-897X
e-ISSN: 2169-8996
URL: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018JD028317
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
WBS: 509496
CONTRACT_GRANT: GSFC - 613.0
CONTRACT_GRANT: NNG17HP01C
OTHER: DE-SC0014371
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Technical Review
External Peer Committee
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