Toward Improved Numerical Forecasting of Wintertime Stable Boundary Layers

1. Toward Improved Numerical Forecasting of Wintertime Stable Boundary Layers Erik Crosman1, John Horel1, Chris Foster1, Erik Neemann1, Brian Blaylock1, Lance Avey2 1University of Utah Department of Atmospheric Sciences 2Utah 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? • 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) Jim Steenburgh photo Craig Clements photo OBS MODEL Source: Bourne (2008) Erik Crosman photo

4. Example CAP Forecast Challenge NAM 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 2013 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 LAYERFOGSO ITS FORECAST TEMPS ARE TOO HIGH FOR THE WESTERN VALLEY SITES. OBS

5. Types of Persistent Cold Air Pools Heterogeneous Cloudy Dry 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 cloudy Jim Steenburgh photo Craig Clements photo Elevated inversion Multi-level nocturnal • PCAPS observational data available at • www.pcaps.utah.edu Erik Crosman photo Lareau et al. 2013 BAMS

6. Recent Utah Wintertime Cold Pool Field Campaigns • Uintah Basin (High O3): • Uintah Basin Wintertime Ozone Study (UBWOS) • December 2011- February 2012 • December 2012- February 2013 • December 2013- February 2014 Salt Lake Valley (High PM2.5): • 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

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. WRF CAP Sensitivity to Land Use9 Day Average 2-m Temperature DifferenceUSGS minus MODIS USGS  higher albedo USGS  colder temps

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

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

11. WRF CAP Sensitivity to Initialization TimeIdentical simulations started 1 day apart WRF CAP Sensitivity to Initialization TimeIdentical simulations started 1 day apart Initialization 1 Initialization 2 Obs 1 Jan 1 Jan 31 Dec 31 December 2010 1 January 2011 2 January 2011

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

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 Ice Fog • Simulated Clouds • Reality Before After Cloud Ice Cloud Water Cloud Ice Cloud Water http://wwc.instacam.com/instacamimg/UBATC/UBATC_l.jpg Photo: Erik Crosman

14. Large-Eddy Simulations of CAPs • 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 OBSERVATIONS PCAPS Ɵ observations

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

16. Summary and Future Work • 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