assimilation of dual- polarimetric radar and gpm observations with gsi in regional wrf
DESCRIPTION
Assimilation of Dual- Polarimetric Radar and GPM Observations with GSI in regional WRF. Xuanli Li 1 , John Mecikalski 1 , Bradley Zavodsky 2 , and Jayanthi Srikishen 3 1 Department of Atmospheric Sciences, University of Alabama in Huntsville 2 NASA Marshall Space Flight Center - PowerPoint PPT PresentationTRANSCRIPT
Assimilation of Dual-Polarimetric Radar and GPM Observations with GSI in
regional WRFXuanli Li1, John Mecikalski1,
Bradley Zavodsky2, and Jayanthi Srikishen3
1Department of Atmospheric Sciences, University of Alabama in Huntsville2NASA Marshall Space Flight Center
3Universities Space Research Association
21-23 May 2014
12th JCSDA Science Workshop on Satellite Data Assimilation, College Park, MD 1
Outline
Background and objectives
Previous work: Assimilation of ground-based dual-pol radar data with GSI Comparison of dual-pol radar data assimilation using GSI vs. WRFVAR
Work plan and current progress: assimilation of GPM ground validation data with GSI
Background and Goals
• ROSES-13 A.33 project to assimilate GPM DPR reflectivity and GMI products, collaborated with NASA SPoRT Center.
• NWS WSR-88D network has been updated to include dual-polarimetric capability. The dual-pol radar can provide more information on cloud and precipitation particles. Assimilation of the dual-pol radar data is a relatively new area.
• GPM has been launched and DPR and GMI data will be available soon. Broader coverage than the ground-based radar system, better measurement for snow storm events.
• Project goal is to develop methodology to implement GPM
DPR and GMI data with GSI into regional WRF model, and investigate the potential of using GPM observation in convective scale NWP for operational environment.
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Dual-Polarimetric Radar
Horizontal and vertical signals: more info about the type, shape, and size of the hydrometeors – more accurate estimates of precipitation and cloud particles.
Variables:
ZH: Horizontal reflectivity
VR: Radial velocity
ZDR: Differential reflectivity ZDR = 10
log10(ZH/ZV)
ρHV: Correlation coefficient, the coefficient between the horizontal and vertical power returns. ΦDP: Differential phase, the measured phase shift between horizontal and vertical pulses SW: Spectrum width, measures the consistence of the phase shifts
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Dual-Pol Radar Data Assimilation with GSI
WRF model ARW v3.5
GSI v3.2
Assimilation procedure:
• Reflectivity is used by the Global Systems Division
(GSD) cloud analysis to improve precipitation analysis
• ZDR information is added in calculation of rain amount.
GSD Cloud Analysis for rain:
• Kessler (1969):
With ZDR, using Ulbrich and Atlas (1984):
br aq arg)(
94.141028.1 DRHr ZZq
WSR-88D Dual-Pol Radar Observation
VR
ZDR ZH
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2 km height
0631 UTC 2 September 2013
Case Study: 2 September 2013
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Reflectivity at 0600 UTC 2 September 2013
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Model starts at 0000 UTC, no convection in model simulation at 0600 UTC
Data Assimilation Experiments
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Experiment Radar Data Assimilation Variables
VR 0600 and 0900 UTC2 September 2014 Vr
ZH 0600 and 0900 UTC 2 September 2014 Vr and ZH
ZHZDR 0600 and 0900 UTC 2 September 2014
Vr, ZH and ZDR
Reflectivity 0900 UTC 2 September 2013
ZH
ZHZDR
10
VR
NEXRAD
Zdr data shows impact on the initial reflectivity and hydrometeor fields
Impact found in low level temperature field
Temperature 0900 UTC 2 September 2013
VR ZH
ZHZDR
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Stronger dry region found in low level moisture field
Moisture 0900 UTC 2 September 2013
VR ZH
ZHZDR
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Forecast Validation 1200 UTC 2 September 2013
NEXRADZHZDR
VR
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ZH
Zdr data assimilation shows impact on the convective scale model forecast
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GSI: GSD cloud analysis system
Indirect incorporation of dual-pol radar data
Convert to cloud type, precipitation amount
WRFVAR: direct assimilation of dual-pol radar data
moist control variables: water vapor, rain water, and
cloud water mixing ratio
Assimilation: using Ulbrich and Atlas (1984):
cycled assimilation at 0600 and 0900 UTC
94.141028.1 DRHr ZZq
Dual-Pol Radar Data Assimilation: GSI vs. WRFVAR
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CTRL GSI
WRFVAR
Analysis field at 0600 UTC for reflectivity: more significant increment in WRFVAR than GSI
Dual-Pol Radar Data Assimilation: GSI vs. WRFVAR
GSI WRFVAR
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Analysis field at 0600 UTC for low level temperature: more significant temperature change in WRFVAR than GSI
Dual-Pol Radar Data Assimilation: GSI vs. WRFVAR
GSI WRFVAR
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Analysis field at 0600 UTC for low level moisture: higher value of moisture in GSI field than WRFVAR
Dual-Pol Radar Data Assimilation: GSI vs. WRFVAR
NEXRAD
GSI
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WRFVAR
1200 UTC 2 September 20136 h forecast: similar location and storm pattern
Dual-Pol Radar Data Assimilation: GSI vs. WRFVAR
NEXRAD
GSI
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WRFVAR
1500 UTC 2 September 20136 h forecast:different pattern Storm dissipate quicker than WRFVAR
Dual-Pol Radar Data Assimilation: GSI vs. WRFVAR
Work Plan
Generate a dual-frequency radar and microwave radiometer observation dataset, analyze GPM data
-- Ground validation data now available
Develop a methodology for assimilation of GPM DPR and GMI observations with GSI
-- Test first with ground validation data
Assimilation of real GPM data
Current Work Case study: 2012-02-24 snowstorm observed by GPM
ground validation GCPEx field campaign.
WRF model control run NEXRAD
1700 UTC 24 February 2012