16 th Annual CMAS conference Surface Turbulent Fluxes

16 th Annual CMAS conference Surface Turbulent Fluxes during Cold Air Pool Events Xia Sun, Heather A. Holmes, Cesunica E. Ivey Atmospheric Sciences Program, University of Nevada, Reno 10/25/2017 1

Motivation § Build up of air pollutant concentrations § Identified in many cities across the intermountain west U. S. § WRF failed to replicate the meteorological conditions § CMAQ underestimates the air pollutant concentrations Stratified layer of pollution during a “cold pool” event near Salt Lake City, Utah. Erik Crosman (photographed December 19, 2009) (Baker et al. 2011) 2

Particulate Matter: Observations vs. Model CAP (Holmes et al. , ES&T 2015) 3

Surface turbulent flux § Surface layer coupled to the PBL § Latent heat flux impacts the surface water exchange § Illustration of surface and PBL processes (Jimy Dudhia, NCAR) 4

Objectives Objective q To characterize turbulent fluxes and surface energy balance over different land use types during CAP events. q Evaluation of WRF simulation results on each component of the surface energy budget. q Evaluation of WRF performance on simulation of PBL structure based on observational datasets during CAPs. Hypothesis q Daily surface fluxes will be smaller during CAP periods compared to non-CAP episodes. q Energy balance depends on land use type. q NWP models will not adequately capture the turbulence magnitude and variation during daytime of persistent CAPs periods. q Vertical gradients are difficult for models to simulate during CAPs 5

Observation Sites Persistent Cold Air Pool Study (PCAPS) *PI – David Whiteman (U. Utah), NSF Integrated Surface Flux System (ISFS) Code Site Land Use (Lareau et al. 2013) BL Playa Barren land DH ABC Urban Developed, high intensity DM Highland Developed, medium intensity DL 1 West Valley Developed, low intensity DL 2 East Slope Developed, low intensity PH West Slope Pasture/Hay CR Riverton Cultivated crops 6

PCAPS Study Time Period: Winter 2010 -2011 • • 10 Intensive Observation Periods (IOPs) Brief and weak CAPs throughout 4 IOPs with Strong Multiday Persistent CAPs Modeling – IOP 3 & IOP 5 7

Measurements Gas analyzer Sonic anemometer (https: //www. campbellsci. com/irgason) Friction velocity § covariance of vertical and horizontal wind components Sensible heat flux Latent heat flux § ρ: air density § Cp: the specific heat capacity at constant pressure (J kg-1 K-1) § θs: the sonic temperature § q: water mixing ratio § L: the latent heat of vaporization for water(J kg -1). 8

Surface Meteorology Fields T (℃) WS (m s-1) RH (%) P (h. Pa) 9

Surface Turbulent and Energy Fluxes H (W m-2) Rn (W m-2) 10

Surface Energy Balance Closure Energy Balance Ratio Bowen Ratio Site Name Land Use n EBR B BL Barren land 1236 0. 981 0. 594 DH Developed, high intensity 1347 1. 276 1. 261 DM 999 0. 953 0. 995 DL 1 Developed, medium intensity Developed, low intensity 1539 0. 887 0. 577 DL 2 Developed, low intensity 1402 0. 635 0. 009 PH Pasture/Hay 1546 0. 559 -0. 070 CR Cultivated crops 1554 0. 671 0. 331 11

Non-CAPs vs CAPs H (W m-2) u* (m s-1) 12

Non-CAPs vs CAPs Mean midday (± 3 h around the solar noon) averages Item Non-PCAPs Weak PCAPs Strong PCAPs Rn 97. 79(± 88. 88) 166. 25(± 84. 91) 72. 20(± 85. 76) H 38. 11(± 54. 26) 51. 30(± 44. 08) 25. 46(± 29. 99) LE 26. 26(± 23. 96) 31. 54(± 16. 03) 12. 92(± 14. 76) H/Rn 0. 40 0. 32 0. 39 (H+LE)/Rn 0. 72 0. 52 0. 60 u* 0. 34(± 0. 23) 0. 24(± 0. 14) 0. 19(± 0. 12) 13

Case Study-IOP 9 (Cloudy PCAPs) Ceiling height (km) Energy Fluxes (W m-2) 14

WRF Simulation Configurations § NAM analysis dataset § 3 Two-Way Nested Domains (12 km, 2. 4 km, 480 m) § 30 Vertical Levels (10 in first 1, 000 m AGL) § Surface and Upper Air Nudging (OBSGRID) Common Physics § Cloud Microphysics: Lin § Longwave Radiation: Rapid Radiative Transfer Model § Shortwave Radiation: Dudhia § Cumulus Parameterizations: Kain-Fritsch § Cloud Fraction Option: Xu-Randall 15

WRF Sensitivity Experiments Planetary Boundary Layer, Surface Physics, Land Surface 1. ACM 2, Pleim-Xiu (with soil nudging) [ACM 2] 2. YSU, Monin-Obukhov Similarity, Noah [YSU] 3. MYJ, Monin-Obukhov Janjic Eta Similarity, Noah [MYJ] Combination based on what the PBL model developers intended the configuration to be! 16

Simulated Meteorology (IOP 3) Buildup Maintenance Breakup Temperature (K) Wind Speed (m/s) 17

Simulated Surface Fluxes (IOP 3) Buildup Maintenance Breakup Sensible HF (W/m 2) Friction Velocity (m/s) 18

Simulated Vertical Profiles 14 Dec 2010 0500 MST 14 Dec 2010 1100 MST 19

Summary • • • Friction velocity decreases during CAPs Sensible heat flux decreases during strong PCAPs Low level clouds induce weak surface turbulence WRF reasonably simulated SHF & friction velocity (IOP 3) WRF vertical profiles do not show observed gradients 20