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Comparing GEM Regional, GEM-LAM 2.5 and RUC Model
Simulations of Mesoscale Features over Southern Ontario
2009 CMOS Congress31 May – 4 June, Halifax, NS
David Sills, Norbert Driedger and Emma HungCloud Physics and Severe Weather Research Section,
Environment Canada, Toronto, Canada
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Introduction and Motivation• Variety of NWP models used at the OSPC RSD for mesoscale analysis and nowcasting guidance:
• REG - regional version of EC’s Global Environmental Multiscale (GEM) model with 15 km horizontal grid spacing, • LAM - limited-area version of the GEM model with 2.5 km horizontal grid spacing, and• RUC - the US Rapid Update Cycle (RUC) model with 13 km horizontal grid spacing
• LAM’s higher resolution should provide more accurate solutions in regions of complex topography
• RUC’s 1-hr data assimilation cycle should effectively ‘nudge’ the model solution closer to reality
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Methodology• Focused on features with mesoscale detail over southern Ontario and surrounding areas:
• Early-season, late-season and summer lake breezes• Winter land breezes with snow squalls• Warm / cold fronts• Low positions• Others: prefrontal convergence, trofs, lake funnelling, etc.
• used 18 UTC data from June 2008 to May 2009
• Model performance ranked (1st, 2nd, 3rd) based on subjective comparison of mesoscale features against observations (sfc winds, radar reflectivity, vis sat)
• Ties were always ranked as 2 (1-2-2, 2-2-3, 2-2-2)
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• 232 mesoscale features were compared from 217 days
• Overall averaged rankings:
LAM – 1.78 RUC – 1.94 REG – 2.19
• LAM ranked higher than REG: 115 events or 49.5%• RUC ranked higher than REG: 103 events or 44.4%
1s 2s 3s 1s + 2s
LAM 74 136 22 210
RUC 74 97 61 171
REG 11 167 54 178
Results - Overall
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• Model rankings have clear monthly differences
• LAM model superior Aug-Oct and Feb-Mar, worse than REG Nov and Jan
• RUC model superior Nov-Jan and Apr-May, worse than REG Oct and Mar
• No month has REG the highest ranked model
Results – By Month
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• Model ranking also has clear differences based on feature type
• LAM superior with early and late season lake breezes, worse than REG for winter land breezes
• RUC superior with low positions, worse than REG for early- and late- season lake breezes
• REG does well with winter land breezes
Results – By Feature Type
(N=25)
(N=19)
(N=32)
(N=105)
(N=21) (N=23)
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Results – By Convection• Is there a difference for summer convective environments?
• Very little change for convection vs. no convection
• Model rankings consistent as well
Summer – All Events
Summer -Convection
Summer – No Convection
LAM 1.71 1.70 1.79
RUC 1.84 1.86 1.82
REG 2.23 2.20 2.32
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Case Study – Low on 6 Apr 09
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Case Study – Low on 6 Apr 09
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Case Study – Low on 6 Apr 09
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Late Season Lake Breezes - 15 Oct 09
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Late Season Lake Breezes - 15 Oct 09
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Late Season Lake Breezes - 15 Oct 09
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Winter Land Breezes - 16 Jan 09
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Winter Land Breezes - 16 Jan 09
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Winter Land Breezes - 16 Jan 09
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Conclusions
• Overall, the mesoscale features generated by the LAM and the RUC were closer to observations than the REG, with LAM having the highest averaged ranking
• There were clear monthly differences in model rankings, as well in differences due to feature type
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Conclusions Cont’d
• The LAM and RUC ranked about the same for summer lake breezes and warm/cold fronts
•The LAM ranked first for early- and late-season lake breezes, while RUC ranked first for low positions
• LAM ranked last for winter land breezes, while RUC ranked last for early- and late-season lake breezes
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• There appeared to be little difference between events with convection and events without convection
• This is a preliminary investigation – a more objective approach and larger sample sizes are needed
• Would a high-resolution LAM with an hourly data assimilation cycle produce even better results?
Conclusions Cont’d
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Thank you!