Parameter estimation for treatment of PBL errors with an EnKF · 1.PBL schemes remain one of the...
Transcript of Parameter estimation for treatment of PBL errors with an EnKF · 1.PBL schemes remain one of the...
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Parameter estimation for treatment of PBL errors with an EnKF
Xiaoming Hu and Fuqing Zhang
Penn State University
John Nielsen-Gammon
Texas A&M University
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Test WRF sensitivity to PBL schemes Episode & Resolution Period: July – Sept., 2005 Resolution: 108km, 36km, 12km, 4km Grids: 53×43, 97×76, 145×100, 166×184
Model Configurations
YSU, ACM2, MYJ PBL schemes
WSM 6-class graupel scheme
NOAH land-surface model (LSM)
Dudhia short wave radiation RRTM long wave radiation Grell-Devenyi ensemble cumulus
scheme Domains and TCEQ, NWS/FAA sites
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Mean T2 and dew point
Different PBL schemes performs significantly different.
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Mean profiles of T and moisture
Vertical mixing strength plays an important role in performance of PBL schemes
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WSP sensitivity to 10 parameters in ACM2
WSP is mostly sensitive to p, Rc.
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Correlation between parameters & WSP
WSP shows the largest correlation with p, Rc.
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Sensitivity to p
Lower p => stronger vertical mixing => higher PBL height.
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Use EnKF to update p, Rc
• Deterministic simulation
• Regular EnKF (No PE EnKF)
• Parameter estimation EnKF (PE EnKF)
– Update p, Rc simultaneously as updating regular states
– Assimilate wind profiler data only every 6-hour between Aug. 30-Sept. 2, 2006 over Texas
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Wind vectors at Sept 1, 11 CST
(a) Independent observations
(b) Deter
(c) No PE EnKF
(d) PE EnKF
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Mean wind speed profile
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Evolution of p
During most of time, PE EnKF predicts p value lower than 2 (default).
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Mean T2 over NWS/FAA sites
PE EnKF predicts the least cold bias.
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Conclusions
1.PBL schemes remain one of the primary sources
of inaccuracies in model simulation. Vertical
mixing strength plays an important role in
performance of PBL schemes
2.Preliminary results with real-data show that
simultaneous state and parameter estimation with
EnKF performs better than deterministic
simulation and regular EnKF by providing
optimized flow dependent parameters in the PBL
scheme