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2002 MM5 Model Evaluation 12 vs. 36 km Results

2002 MM5 Model Evaluation 12 vs. 36 km Results. Chris Emery, Yiqin Jia, Sue Kemball-Cook, and Ralph Morris ENVIRON International Corporation Zion Wang UCR CE-CERT Western Regional Air Partnership (WRAP) Regional Modeling Center (RMC) National RPO Meeting May 25, 2004.

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2002 MM5 Model Evaluation 12 vs. 36 km Results

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  1. 2002 MM5 Model Evaluation12 vs. 36 km Results Chris Emery, Yiqin Jia, Sue Kemball-Cook, and Ralph Morris ENVIRON International Corporation Zion Wang UCR CE-CERT Western Regional Air Partnership (WRAP) Regional Modeling Center (RMC) National RPO Meeting May 25, 2004

  2. 2002 MM5 Evaluation Review • IA/WI 2002 MM5 Configuration on National RPO 36 km Grid, except: • Used MM5 v3.6.2 • Invoked Reisner II, disregarded INTERPX • Evaluation Methodology • Synoptic Evaluation • Statistical Evaluation using METSTAT and surface data • WS, WD, T, RH • Evaluation against upper-air obs • Compared statistical performance against EDAS, VISTAS

  3. METSTAT Evaluation Package • Statistics: • Absolute Bias and Error, RMSE, IOA • Daily and, where appropriate, hourly evaluation • Statistical Performance Benchmarks • Based on an analysis of > 30 MM5 and RAMS runs • Not meant as a pass/fail test, but to put modeling results into perspective

  4. Datasets for Met Evaluation • NCAR dataset ds472 airport surface met observations • Twice-Daily Upper-Air Profile Obs (~120 in US) • Temperature • Moisture • Scatter plots of performance metrics • Include box for benchmark • Include historical MM5/RAMS simulation results • WS RMSE vs. WD Gross Error • Temperature Bias vs. Temperature Error • Humidity Bias vs. Humidity Error

  5. Subdomains for Model Evaluation 1 = Pacific NW 2 = SW 3 = North 4 = Desert SW 5 = CenrapN 6 = CenrapS 7 = Great Lakes 8 = Ohio Valley 9 = SE 10 = NE 11 = MidAtlantic

  6. Evaluation of 36-km WRAP MM5 Results • Model performed reasonably well for eastern subdomains, but not the west (WRAP region) • General cool moist bias in Western US • Difficulty with resolving Western US orography? • May get better performance with higher resolution • Pleim-Xiu scheme optimized more for eastern US? • More optimization needed for desert and rocky ground? • MM5 performs better in winter than in summer • Weaker forcing in summer • July 2002 Desert SW subdomain exhibits low temperature and high humidity bias

  7. Comparison: EDAS vs. WRAP MM5 • Is it possible that 36-km MM5 biases may be caused by the analyses used to nudge (FDDA) the model? • We evaluated EDAS analysis fields to see whether biases exist • Used Metstat to look at the EDAS surface fields • Input EDAS fields do not have the cold moist bias seen in the 36 km MM5 simulation, but wind speed underestimation bias is present • Performance issues not due to EDAS analysis fields, must be internally generated by MM5

  8. Comparison: VISTAS vs. WRAP MM5 • Evaluate VISTAS 2002 MM5 simulation to see whether similar bias exists • Different configuration: KF II, Reisner I • Both MM5 simulations had trouble in western U.S. – same subdomains lie outside the statistical benchmarks • Both MM5 simulations performed better in winter than in summer

  9. Comparison: VISTAS vs. WRAP MM5 • VISTAS: • Better simulation of PBL temperature and humidity profiles • Less surface humidity bias in the western U.S. • Markedly better summer precipitation field • WRAP: • Less surface temperature bias than VISTAS during winter • Overall, VISTAS did better in the west • Further tests indicate use of KF II has larger effect on performance than Reisner I

  10. Addition of 12-km WRAP Grid • IC/BC’s extracted from 36-km MM5 fields • 3-D FDDA fields extracted from 36-km MM5 fields • Preliminary 5-day run starting 12Z July 1

  11. Comparison: 12 vs. 36-km WRAP MM5 • Performance scatter plots prepared • Directly compare 36-km statistics with 12-km statistics for each western sub-region • Provides mean stats over July 1-6 preliminary test period

  12. Comparison: 12 vs. 36-km WRAP MM5 • Results: • No significant or consistent impact on wind speed/direction performance • Temperature bias dramatically improved for all areas, but gross error is made worse • Impacts on humidity performance are minor, and worse in the Desert SW • There appear to be larger issues that 12-km grid resolution does not improve upon • Remember that all IC/BC and 3-D FDDA are derived from 36-km results • This issue addressed in 12-km sensitivity tests

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