MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation using the SWIFT dataset

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1 MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation using the SWIFT dataset Rao Kotamarthi, Yan Feng, and Jiali Wang Argonne National Laboratory & MMC Team

2 Motivation: Bridging the scales from Mesoscale to LES The global grids show (left) a uniform 1/8 th (~12km) degree global grid with refinement to 1/8 th degree New observations & modeling techniques needed (~10-3km) Parameterized Physics (>10 km resolution) 2 Gray Zone (no clear path for dealing with the transition zone) Resolved Physics (< 3km resolution)

3 Objectives Interest in MPAS: Nesting vs Refinable Mesh: The scale-down ratio of 1:3 recommended widely used for WRF achieves a large refinement in resolution by using a number of nested domains but introduces numerical stability and convergence problems at each of the nesting boundaries. A newer dynamical core with unstructured mesh (MPAS: Model for Prediction Across Scales) has been tested over the last few years, and a version of the MPAS model implemented with WRF physics is now available. The nest down options provided by MPAS could likely be superior to that currently available with WRF We initiated this work to evaluate the suitability of using MPAS for reaching higher spatial resolutions ( < 3 km) for mesoscale phenomena. TEST CASE: Investigate the capability of WRF and Model for Prediction Across Scales (MPAS) models under various configurations to simulate an observed neutral boundary layer case

4 SWIFT Site (Lubbock, TX) Met Mast Configuration Experimental Research Test Site at Lubbock, Texas 58.5 m 56.5 m 3D Sonic T, RH Rapid Development and Validation Project Rotor Systems, Global Research 45 m 3D Sonic DP Cup DnV IEC standard boom arm m 31.5 m 27 m 31.5 m 29.5 m 27.5 m 3D Sonic T, RH, BP DP DP Cup Vane m 30 deg 18 m 3D Sonic Cup Guy wires 10 m 3D Sonic 2 m T, RH, BP DP CompactRIO Controller Met mast sensors 3D Sonic: ATI SATI/3A Sonic Anemometer Cup: Thies Wind Sensor First Class Advanced (IEC accred) Vane: Thies Wind Direction Sensor First Class T: 592 Met One Temperature sensor BP: 092 Met One Barometric Pressure sensor RH: 593 Met One Relative Humidity sensor DP: ATI PAD-401 DataPacker Met mast heights* 58.5 m: 3D Sonic 56.5 m: T, RH 45 m: 3D Sonic, Cup 31.5 m: 3D Sonic, Cup 29.5 m: 3D Sonic, Vane 27.5 m: T, RH, BP 18 m: 3D Sonic, Cup 10 m: 3D Sonic 2 m: T, RH, BP Guy wires Radius 47.5m m m m m *Boom arms not drawn to scale 3

5 Atmospheric Stability (Case Studies) dθ/dz = 0 dθ/dz > 0 Stable Neutral dθ/dz < 0 unstable

6 WRF Simulated Potential Temperature Profiles Near-Neutral Case: Centered at :50 6

7 WRF Setup SWIFT site height AGL [m] height AGL [m] pressure [hpa] pressure [hpa] Figure from Carolyn Draxl, NREL Model Setup YSU PBL scheme NCEP Boundary and Initial condition 80 vertical layers RRTM radiations physics

8 WRF nudging, 3DVAR Texas Mesonet Data Postprocessing WRFDA / observational nudging Modified IC and BC files WRFV3 - Simulation

9 Model Prediction Across Scales (MPAS) PBL Scheme: YSU Initial conditions: NCEP Surface conditions: (updated every 6 hours) Number of vertical levels: 41 (top 30km) Soil levels: 4 Land use: USGS Land Model: NOAH Convection: Kain_Fritsch Radiation: RRTMg Surface Layer physics: Monin Obukhov 15 km global grid (atmospheric model) Simulations: Month of August, 2012 Output size: 500 Gb /day

10 Case selection based on the weather conditions (NOAA daily weather maps) August 17 th, 2012 (7 AM) August 18 th, 2012 (7 AM) 10

11 Wind Flow at 5 km MPAS WRF

12 Neutral Case: Wind Profiles from two WRF configurations: WRF vs WRF-3DVAR

13 Comparison of Wind Profiles from MPAS vs WRF-3DVAR

14 Neutral Case: Potential Temperature Profiles from two WRF configurations: WRF vs WRF-3DVAR Observed theta profile

15 Comparison of Potential Temperature Profiles from MPAS vs WRF-3DVAR Different scale

16 Wind and Potential Temperature Profiles from WRF-LES Time: 00:00 hour on 08/17

17 Neutral Case: Planetary Boundary Layer Height Comparison of WRF, WRF-3DVAR, and MPAS

18 Comparison of Sensible Heat Flux (W m -2 ) from WRF-3DVAR vs MPAS WRF 3D-VAR 12 pm 6 pm 1 AM MPAS

19 Comparison of Latent Heat Flux (W m -2 ) from WRF-3DVAR vs MPAS WRF 3DVAR 12 PM 6 PM 1 AM MPAS

20 Conclusions and future work Surface heat fluxes calculated by WRF and MPAS are similar for the selected neutral case Boundary layer vertical profiles of wind speed calculated for the neutral case with MPAS were similar to the WRF meso-scale models WRF observationally nudged wind profiles with initialization the hour before produced the best comparison to the observed winds Potential temperature profiles for all three cases show a neutral profile at the time when the observations were made. WRF 3D-VAR and LES produced the closest reproduction of the observations The PBL heights calculated by the three models differ by several hundred meters during the daytime but show similar diurnal transition Higher vertical resolution for MPAS most likely will help. Data volumes from the MPAS model at spatial resolution of 15 km and higher will be a problem. Very few plotting and analysis tools are useful for handling this amount of output as we will need parallel processing tools (e.g. paraview).

21 Acknowledgements DOE NERSC Computing facility for providing the computing resource DOE EERE WWTPO Program for funding The entire MMC team lead by Susan Haupt (NCAR)