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VISTAS Meteorological Modeling November 6, 2003 National RPO Meeting St. Louis, MO Mike Abraczinskas North Carolina Division of Air Quality. Contract with Baron Advanced Meteorological Systems (BAMS) Formerly known as MCNC Don Olerud, BAMS Technical Lead Contract initiated January 2003.
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VISTAS Meteorological Modeling November 6, 2003 National RPO Meeting St. Louis, MO Mike Abraczinskas North Carolina Division of Air Quality
Contract with Baron Advanced Meteorological Systems (BAMS) Formerly known as MCNC Don Olerud, BAMS Technical Lead Contract initiated January 2003
Phase I: Test model to define the appropriate set up for our region Investigate -> Model -> Evaluate -> Make decisions Meteorological Modeling Goals
Summary of recent and relevant MM5 sensitivity studies Draft delivered: January 2003 Learn from what others have done Inter-RPO collaboration Will serve a starting point for VISTAS Recommend a set of sensitivity tests Draft delivered: January 2003 Different physics options and inputs proposed for testing Meteorological Modeling GoalsPhase I
Evaluation methodologies Draft delivered: January 2003, Updated April 2003 Assessing Model Performance Conceptual understanding correct? placement, timing of features Are diurnal features adequately captured Are clouds reasonably well modeled Are precipitation fields reasonable Do wind fields generally match observations Do temperature and moisture fields match observations Million dollar question… Do the meteorological fields produce acceptable air quality model results? Meteorological Modeling GoalsPhase I
Evaluation: Spatial Products Spatial Aloft Products Timeseries Products Sounding Products Spatial Statistics Products Timeseries Statistics Products Combination Products Timeseries Statistics Aloft Products Statistical Tables Form Profiler Products Cross Sensitivity products Meteorological Modeling GoalsPhase I
Phase I: Test model to define the appropriate set up for our region Investigate -> Model -> Evaluate -> Make decisions Periods that we’re modeling ? Geographical extent of testing ? Meteorological Modeling Goals
January 1 – 20, 2002 Episode 1 July 13 – 27, 2001 Episode 2 July 13 – 21, 1999 Episode 3 Choice of episode periods was based on: Availability of robust AQ databases Full AQ cycle (clean-dirty-clean) Availability of meteorological data Air quality and meteorological regime Sensitivity episodes
12 km 36 km
PX_ACM Pleim-Xiu land-surface model, ACM pbl scheme NOAH_MRF NOAH land-surface model, MRF pbl scheme Multi_Blkdr Multi-layer soil model, Blackadar pbl scheme NOAH ETA M-Y NOAH land-surface model, ETA Mellor-Yamada pbl Sensitivity Tests BASE CASE
PX_ACM case significantly cold-biased PX_ACM runs are continuous (i.e. soil/moisture values from one modeling segment serves as initial conditions for following segment) Significantly better results obtained by making each P-X run independent (PX_ACM2) January 2002 – Episode 1
T T
T T
T T
T T
Run Bias abserr IA PX -2.68 3.15 0.854 PX2 -1.38 2.25 0.877 1.5m Temperature stats12 km domain - All hours - Episode 1
NOAH_MRF by far the highest and smoothest Probably too high PX_ACM2 ~= Multi_blkdr PX_ACM2 subject to some suppressed PBL heights (in areas) during the day Some of this may be real ? (over melting snow, or in presence of clouds/precipitation) Lack of observations make this nearly impossible to evaluate PX_ACM2 very low at night NOAH_ETA-MY lowest during day PBL HeightsSubjective observations
3-Panel Plots Bias, Error, Index of Agreement for t, q, cld, spd, dir, RH Bias, Accuracy, Equitable Threat Score for pcp (0.01, 0.05, 0.10, 0.25, 0.5, 1.0 in) Labels sometimes difficult to see, so colors remain consistent px_acm(2): Blue noah_mrf: Red multi_blkdr: Black noah_eta-my: Purple Pcp plots only available for “Full” regions Time Series Statistics
