Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018JD028317 |
POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator | |
Matsui, Toshi1,2; Dolan, Brenda3; Rutledge, Steven A.3; Tao, Wei-Kuo1; Iguchi, Takamichi1,2; Barnum, Julie3,4; Lang, Stephen E.1,5 | |
2019-04-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2019 |
卷号 | 124期号:8页码:4634-4657 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | 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, rho(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. 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. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000469071400022 |
WOS关键词 | HYDROMETEOR IDENTIFICATION ALGORITHM ; ENSEMBLE KALMAN FILTER ; PART I DESCRIPTION ; X-BAND ; MICROPHYSICS SCHEMES ; CONVECTIVE SYSTEMS ; CLOUD MICROPHYSICS ; HABIT PREDICTION ; WRF SIMULATIONS ; HIGH-RESOLUTION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/182478 |
专题 | 气候变化 |
作者单位 | 1.NASA, Goddard Space Flight Ctr, Code 916, Greenbelt, MD 20771 USA; 2.Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA; 3.Colorado State Univ, Dept Atmospher Sci, Ft Collins, CO 80523 USA; 4.Lab Atmospher & Space Phys, Boulder, CO USA; 5.Sci Syst & Applicat Inc, Lanham, MD USA |
推荐引用方式 GB/T 7714 | Matsui, Toshi,Dolan, Brenda,Rutledge, Steven A.,et al. POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(8):4634-4657. |
APA | Matsui, Toshi.,Dolan, Brenda.,Rutledge, Steven A..,Tao, Wei-Kuo.,Iguchi, Takamichi.,...&Lang, Stephen E..(2019).POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(8),4634-4657. |
MLA | Matsui, Toshi,et al."POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.8(2019):4634-4657. |
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