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Meteorological Simulations of Utah Basin Cold-Air Pools
Erik Crosman, Chris Foster, John Horel, Erik Neemann University of Utah Department of Atmospheric Sciences Photo: Sebastian Hoch
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Outline Challenges of meteorological modeling of cold-air pools with emphasis on Uintah Basin Broad overview of the modifications implemented to WRF model to improve simulations Discussion of validation of recent cold-air pool cases for Utah PM2.5 SIP Next steps…
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Critical Weather Details Associated with Poor Winter Air Quality: Difficult to Simulate
Turbulent Mixing Clouds Transport Depth of polluted layer Transport Pollution concentrations Surface fluxes
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Collaborations with the Utah Division of Air Quality
First study was for heavily studied Uintah Basin Wintertime Ozone Study (UBWOS) cold-air pool in February 2013 (Neemann et al. 2015) More recently, working with UDAQ on modeling SIP with focus on Salt Lake Valley, but all major Utah Basins were modeled (Foster et al. 2017) Will focus on Uintah Basin meteorological modeling
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The Perfect Basin Uintah Basin Cache Valley
Uintah: Large, deep bowl-like basin with mountains rising over 1000 m on all sides 1300 m 3200 m Salt Lake Valley 4000 m Uintah Basin Utah Valley 25 km
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Uintah Basin Cold-Air Pools: High Longevity (e.g., ongoing episode)
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Uintah Basin Cold-Air Pools are Dynamic 3 Feb 22 UTC to 5 Feb 14 UTC
Fruitland Ouray
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4 Univ Utah Cold-air Pool Simulations for UDAQ
Cold-air pool start date (approximate) Cold-air pool end date (approximate) Duration of clouds(% of cold-air pool) Duration of snow cover (% of cold-air pool) Snow depth in valleys (m) January 1st 2011 (UDAQ SIP) January 11th 2011 20% 100% 5-15 cm 31 January 2013 (UBWOS) 6 February 2013 75% 10-15 cm December 7th 2013 (UDAQ SIP) December 21st 2013 40% 10-20 cm February 1st 2016 (UDAQ SIP) February 17th 2016 50% 0-8 cm
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Meteorology Modeling Set-Up
Domain 1 Doman 2 Domain 3 Vertical levels 42 Vertical grid spacing 20-40 m in boundary-layer Horizontal resolution (km) 12 4 1.33 Land use data set NLCD2011 modified 9s Veg parm table variables modified in BASE simulation SNUP, MAXALB Snow cover initialization in BASE (improved) simulation Linear UofU obs analysis Snow cover initialization in DFLT simulation NAM
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Summary of Modifications to Improve CAP Simulations
Surface state specification --Snow cover, depth, albedo --Land use type and vegetation Ice fog parameterization Forcing considerations --Nudging not recommended --Initializing in the middle of an episode can be problematic --Because all models struggle with turbulent erosion, only cold-air pools with mountaintop winds < ~20 m s-1 until the last day of the cold-air pool are considered.
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Feb 2013 Mean 2-m Temperatures Sensitivity to Snow Cover
-2 -12 -10 -8 -4 -6 °C SNOW No Snow -9.7 °C -2.1 °C -6 -4 -2 2 4 6 8
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Simulating Snow Effects Better
Albedo Before correction After correction Depth Vegetation
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Improve Land Use Specification
Default USGS Land Use outdated Additional changes required based on satellite imagery (frozen lake, dry lake) and surface albedo measurements Allows albedo to increase significantly over barren surfaces in the Uintah Basin Foster et al. 2017
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Ice Cloud Parameterization
Over the entire model run, liquid clouds produced an average of 7-20 W/m2 more longwave energy than ice clouds in the Uintah Basin. (Neemann et al. 2015)
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Trang Tran1, Huy Tran1, Erik Crosman2
FDDA (nudging) impacts on WRF-CMAQ model performance in simulating winter O3 formation in Uintah Basin Trang Tran1, Huy Tran1, Erik Crosman2
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Overview of 2016 UDAQ Met Simulations for Uintah Basin
Winds: All simulations have low biases and RMS errors in wind speed, simulating very low wind speeds during all episodes Station (Vernal) Bias (m s-1) RMS Error (m s-1) 1-13 January 2011 -0.339 1.153 7-21 December 2013 0.027 1.136 1-17 Feb 2016 -0.261 1.445
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Cold-Air Pool Temperature Simulations
Stable layer timing and depth consistent with observations Problems in 2-m temperature simulations identified resulting from A) Spurious clouds B) insufficient snow melt Jan 2011 Dec 2013 Red = model Black = obs Feb 2016 Feb 2016
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2016 UDAQ SIP Met Modeling in Uintah
Red = model Black = obs January 2011 Snow cover/ albedo correct Timing and winds very good Spurious clouds in model middle of episode large impact on temperatures
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Future Directions Scale-aware parameterizations Large-eddy simulation Evaluate HRRR model (improved data assimilation) References Neemann, E. M., Crosman, E. T., Horel, J. D., and Avey, L, 2015: Simulations of a cold-air pool associated with elevated wintertime ozone in the Uintah Basin, Utah, Atmos. Chem. Phys., 15, , doi: /acp , Foster, C., E.T. Crosman, and J.D. Horel, 2017: Simulations of a Cold-Air Pool in Utah’s Salt Lake Valley: Sensitivity to Land Use and Snow Cover. In Press, Boundary-Layer Meteorology Crosman, E.T., and J.D. Horel, 2017: Large Eddy-Simulations of a Salt Lake Valley cold-air pool. Under review, Atmospheric Research.
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Extra slides
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Improve Turbulent Mixing: Large-Eddy Simulation of CAP
Depth Duration Clouds Physics Ɵ PBL: YSU ΔX 1335 m CAP too shallow Ɵ PBL: none LES ΔX 250 m Important To verify vertical profiles PCAPS Ɵ observations Crosman and Horel (2017)
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WRF Sensitivity to Modifications
Roosevelt Potential Temperature profiles 2-m Temperature Bias Original Modified Original Modified Observed 4 Feb 2013 5 Feb 2013 Model Run Bias (deg C) Mean Abs Error (deg C) RMSE (deg C) Original Thompson 3.3858 3.8293 4.6104 Modified - Full Snow 0.1134 2.4394 2.9837
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Mean Afternoon Ozone Concentration
1 - 6 Feb 2013 UTC Snow CMAQ output provided by Lance Avey at UTDAQ No Snow 4km WRF output run through Utah DAQ’s air quality model (CMAQ) Modified WRF produced ozone concentrations up to 129 pbbv Average decrease of ~ 25 ppbv when snow removed from basin floor Highest concentrations confined to lowest m in stable PBL/inversion, as observed during UBOS 2013 No Snow run contains much lower ozone and deeper PBL
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Uintah Basin Flow Patterns
Average Potential Temperature profile at Ouray Average Zonal Wind - All Hours Ouray Greatest Stability Inversion/greatest stability typically between m MSL Weak easterly flow exists within and below inversion layer Core greater than 0.5 m/s Likely important role in pollutant transport within the basin
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Uintah Basin Flow Patterns
Daytime Hours 0800L L Nighttime Hours 1700L L Inversion Stable down to Surface upslope downslope Weak “mixed” layer Easterly flow stronger during the day, weaker during the night Indicates thermal gradients likely the main driver Core winds greater than 1 m/s during the day Diurnal upslope/downslope flows also apparent in day/night plots
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Summary of WRF Modifications Sensitivity to Microphysics
Idealized snow cover in Uintah Basin and mountains Snow albedo changes Edited VEGPARM.TBL Microphysics modifications (Thompson) in lowest ~500m: Turned off cloud ice sedimentation Turned off cloud ice autoconversion to snow Results in ice-phase dominated low clouds/fog vs. liquid-phase dominated Allows model to achieve high albedos measured in basin Sensitivity to Microphysics Before After Cloud Ice Cloud Water Cloud Ice Cloud Water
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Meteorology Modeling Set-Up
Domain 1 Doman 2 Domain 3 Grid Size (x,y) 200 x 190 250 x 250 475 x 499 Vertical levels 42 Vertical grid spacing 20-40 m in boundary-layer Horizontal resolution (km) 12 4 1.33 Model time step (s) 45 15 5 Topographic dataset USGS GTOPO30 Land use data set NLCD2011 modified 9s Veg parm table variables modified in BASE simulation SNUP, MAXALB Snow cover initialization in BASE (improved) simulation Linear UofU obs analysis Snow cover initialization in DFLT simulation NAM Initial and boundary-layer meteorology
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