1. Toward Improved Numerical Forecasting of Wintertime Stable Boundary Layers Erik Crosman 1, John Horel 1, Chris Foster 1, Erik Neemann 1, Brian Blaylock 1, Lance Avey 2 1 University of Utah Department of Atmospheric Sciences 2 Utah Division of Air Quality

2. Motivation Persistent cold air pools forced by small-scale processes (e.g., turbulence) and by large-scale processes (e.g., subsidence and fronts Cold air pools and attendant air quality are particularly difficult to forecast—large ‘bust’ potential for high temperatures and clouds Need to improve NWP in stable wintertime conditions

3. Why are Cold Air Pools so Difficult to Model? Craig Clements photo Jim Steenburgh photo Erik Crosman photo Source: Bourne (2008) MODELOBS Poor model representation of Snow cover, snow albedo, skin temperature, and vegetation density Initialization Low clouds (Gultepe et al. 2014) Stable stratification, turbulence and mix-out by PBL schemes (Baklanov et al. 2011; Holtslag et al. 2013)

4. Example CAP Forecast Challenge AREA FORECAST DISCUSSION AREA FORECAST DISCUSSION NATIONAL WEATHER SERVICE GRAND JUNCTION CO 944 PM MST SAT NOV 30 2013.UPDATE... ISSUED AT 940 PM MST SAT NOV 30 2013SAT HAVE ADJUSTED AREAS OF FOG FOR TONIGHT THROUGH SUNDAY WITH FOG MAINLY IN THE VALLEY BOTTOMS AND ALONG THE SLOPES OF THE WESTERN MOUNTAINS. SOUNDINGS OVER THE LAST 36HRS AT GJT SHOW THE STRATUS LAYER NEAR 7500FT SO HAVE ADDED FOG TO THE SLOPES DEFINED BY 7-8KFT. THE NEW NAM IS NOT RECOGNIZING THE BOUNDARY LAYER FOG SO ITS FORECAST TEMPS ARE TOO HIGH FOR THE WESTERN VALLEY SITES.FOG STRATUSFOGNAMBOUNDARY LAYERFOG NAM OBS

5. Types of Persistent Cold Air Pools Craig Clements photo CloudyDry Jim Steenburgh photo Erik Crosman photo Heterogeneous No two CAPs are alike! Numerical model may struggle with one type more than others! Different physical processes important for different CAPs pre-mix out cloudy Multi-level Elevated inversion nocturnal cloudy Lareau et al. 2013 BAMS PCAPS observational data available at www.pcaps.utah.edu

6. Recent Utah Wintertime Cold Pool Field Campaigns The Persistent Cold Air Pool Study (PCAPS) 1 December 2010- 7 February 2011 The Bingham Canyon Mine Experiment Overview and Air Quality: Silcox et al. 2012; Young 2013; Lareau et al. 2013 Whiteman et al. 2014; Whiteman and Hoch 2015 Large-Scale Dynamics: Lareau et al. 2013; Lareau and Horel, 2014, Lareau and Horel, 2015 Numerical Modeling and Local Forcing: Wei et al. 2013; Lu and Zhong 2014; Neemann et al. 2014. Lareau and Horel, 2015; Crosman and Horel 2015 Uintah Basin (High O 3 ): Uintah Basin Wintertime Ozone Study (UBWOS) December 2011- February 2012 December 2012- February 2013 December 2013- February 2014 Salt Lake Valley (High PM 2.5 ):

7. Ongoing Work to Improve Wintertime Cold Air Pool Simulations Surface state characterization (e.g., snow, albedo, land use, vegetation) Initialization Cloud microphysics Boundary-layer turbulence

8. USGS  higher albedo USGS  colder temps WRF CAP Sensitivity to Land Use 9 Day Average 2-m Temperature Difference USGS minus MODIS

9. Improving WRF Snow Cover Parameterization -Idealized snow cover in Uintah Basin and mountains -Snow albedo changes -Edited VEGPARM.TBL Allows model to achieve high albedos measured in basin 9 Snow Depth

10. Albedo Changes 10 OriginalModified 0.62- 0.65 0.81 - 0.82 -0.82 is average albedo measured at Horsepool during 2013 Uintah Basin Winter Ozone Study

11. Initialization 2 Initialization 1 31 December 20101 January 2011 2 January 2011 WRF CAP Sensitivity to Initialization Time Identical simulations started 1 day apart Obs 31 Dec 1 Jan WRF CAP Sensitivity to Initialization Time Identical simulations started 1 day apart 1 Jan

12. Uinta Mountains Wasatch Range Tavaputs Desolation Canyon Plateau WY CO UT 1250 1500 1750 2250 2750 3250 3750 4000 3500 3000 2500 2000 Roosevelt Myton Ouray Horsepool Red Wash Vernal WRF CAP Sensitivity to Initialization Time Identical simulations started 1 day apart

13. WRF Cloud and Fog Modifications -Microphysics modifications (Thompson) in lowest 15 model layers (~500m): -Turned off cloud ice sedimentation -Turned off cloud ice autoconversion to snow  Results in ice-phase dominated low clouds/fog vs. liquid-phase Simulated Clouds Reality http://wwc.instacam.com/instacamimg/UBATC/UBATC _l.jpg Photo: Erik Crosman Cloud Ice Cloud Water Before After 13 Ice Fog

14. LES ΔX 250 m PCAPS OBSERVATIONS ΔX 1335 m Large-Eddy Simulations of CAPs Depth Duration Clouds Physics CAP too shallow Ɵ PBL: YSU Ɵ PBL: none PCAPS Ɵ observations Important To verify vertical profiles

15. PBL: YSU ΔX = 1.33 kmLES: ΔX = 0.250 km 0 12 6 Wind Speed (m s -1 ) 2-m Temp (C) Great Salt Lake Salt Lake Valley Salt Lake Valley Great Salt Lake 3 9 10 0 5 -5 sltrib.com Toxic soup continues… Time to exercise!

16. CAP simulations sensitive to --Land use and snow cover treatment --Initialization time --Cloud microphysics parameterizations --Turbulence parameterization (LES vs PBL) Future Work --Implementing ice fog and aerosol-aware Thompson schemes (Kim et al. 2014; Thompson & Eidhammer 2014) --Testing several new PBL schemes and additional LES simulations --Additional research regarding albedo/snow treatment, land use, initialization Summary and Future Work