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A new approach to parameterize ice-phase cloud microphysics

A new approach to parameterize ice-phase cloud microphysics The Predicted Particle Properties (P3) Scheme. Hugh Morrison 1 and Jason Milbrandt 2 1 National Center for Atmospheric Research, Boulder, CO, USA 2 Environment Canada, Montreal, Canada. WWOSC 2014 Montreal, Canada

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A new approach to parameterize ice-phase cloud microphysics

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  1. A new approach to parameterize ice-phase cloud microphysics The Predicted Particle Properties (P3) Scheme Hugh Morrison1 and Jason Milbrandt2 1National Center for Atmospheric Research, Boulder, CO, USA 2Environment Canada, Montreal, Canada WWOSC 2014 Montreal, Canada August 17, 2014

  2. Environment Canada’s High Resolution (2.5-km) Deterministic Prediction System Column-maximum REFLECTIVITY* * Computed from microphysics (Milbrandt-Yau 2-moment) Experimental implementation: summer 2014 Operational implementation: 2015

  3. 101 101 101 N(D) N(D) N(D) 100 100 100 [m-3 m-1] [m-3 m-1] [m-3m-1] 10-1 10-1 10-1 10-2 10-2 10-2 Bin-resolving: Bulk: 0 0 0 40 40 40 20 20 80 80 20 80 60 60 60 100 100 100 (spectral) D [ m] D [ m] D [ m] Microphysics Parameterization Schemes ULTIMATE GOAL: Predict evolution of hydrometeor size distributions 1 m3 (unit volume)

  4. RAIN CLOUD Mass Density [g m-3 (lnr)-1] Time [min] Radius [cm] Bin-resolving coalescence modelBerry and Reinhardt (1974) BACKGROUND – Representation of Hydrometeors • Historical development of bulk scheme approach: • start with liquid-only (“cloud” and “rain”)

  5. Example of Observed Ice Particles Photos c/oAlexei Korolev BACKGROUND – Representation of Hydrometeors • Historical development of bulk scheme approach: • start with liquid-only (“cloud” and “rain”) • add ice-phase (“ice”)

  6. BACKGROUND – Representation of Hydrometeors Traditional approach of bulk microphysics schemes: HAIL h = 900 kg m-3 V = ahDbh “SNOW” s = 100 kg m-3 V = asDbs GRAUPEL g = 400 kg m-3 V = agDbg CLOUD ICE s = 500 kg m-3 V = aiDbi  abrupt / unphysical conversions Problems with pre-defined categories: 1. Conversions between categories are ad-hoc 2. Conversions lead to large, discrete changes in particle properties etc. …

  7. The simulation of ice-containing cloud systems is often very sensitive to how ice is partitioned among categories MOR-hail (only) MOR-graupel (only) MY2-baseline (g + h) MY2 - hail (only) • idealized 1-km WRF simulations (em_quarter_ss) • base reflectivity Microphysics Schemes: MOR: Morrison et al. (2005, 2009) MY2: Milbrandt and Yau (2005) Morrison and Milbrandt (2011), MWR

  8. BACKGROUND – Representation of Hydrometeors • Recent developments: • 2-moment – Ziegler (1985), Ferrier (1994), Reisner et al. (1998), etc. • 3-moment – Milbrandt and Yau (2005) • predicted rime fraction – Morrison and Grabowski (2008) • predicted crystal habit – Harrington et al. (2013) • predicted graupel density – Connolly et al. (2005), Mansell et al. (2010), Milbrandt and Morrison (2013) There is a paradigm shift in the parameterization of ice-phase microphysics  Increased emphasis on the prediction of hydrometeor properties Partial mitigation to the problems with pre-defined categories

  9. Which of the following is more duck-like? QUACK! DUCK SQUEAK! • has a label that says “DUCK” • big, round eyes • yellow, wing-like appendages • plastic exterior, hollow interior • no feet • makes a “squeak” noise • has no label • small, round eyes • white, wing-like appendages • feathery exterior, meaty interior • webbed feet • makes a “quack” noise IF IT QUACKS LIKE A DUCK …

  10. New Bulk Microphysics Parameterization: Predicted Particle Properties (P3) Scheme* Based on a conceptually different approach to parameterize ice-phase. LIQUID PHASE:2 categories, 2-moment: qc, qr, Nc, Nr ICE PHASE: 1 category, 4 prognostic variables: qi, qrim, Ni, Brim  predicts wide range of properties (and thus types of ice) • Compared to traditional (ice-phase) schemes, P3: • avoids some necessary evils (category conversion, pre-defined properties) • has self-consistent physics • is better linked to observations • is more computationally efficient * Morrison and Milbrandt (2014) J. Atmos. Sci (in press)

  11. Mesoscale Model Results

  12. 3D Squall Line case: • (June 20, 2007 central Oklahoma) • WRF_v3.4.1, Dx = 1 km, Dz ~ 250-300 m, 112 x 612 x 24 km domain • initial sounding from observations • convection initiated by u-convergence • no radiation, surface fluxes

  13. 2007 OK Squall Line: Base Reflectivity (1 km AGL, t = 6 h) MOR-H WDM6 P3 MOR-G THO Observations dBZ MY2 WSM6 Morrison et al. (2014) J. Atmos. Sci (in press)

  14. WRF Results: Line-averaged Reflectivity(t = 6 h) WDM6 MOR-H P3 THO MOR-G Observations dBZ WSM6 MY2

  15. P3 SIMULATION Fr ~ 0-0.1  ~ 900 kg m-3 V ~ 0.3 m s-1 Dm ~ 100 μm  small crystals  Fr ~ 0  ~ 50 kg m-3 V ~ 1 m s-1 Dm ~ 3 mm  aggregates  Fr ~ 1  ~ 900 kg m-3 V > 10 m s-1 Dm ~ 5 mm  hail Vertical cross section of model fields (t = 6 h) DERIVED Ice Physical Properties     ρp Fr     Dm Vm etc.

  16. Precipitation rate at 1 km height Time-averaged from 6-7 h

  17. P3 SIMULATION Z qi Z qc qr  ρp Fr Small, dense ice  Low-density, unrimed snow Rimed snow/ low-density graupel Vm Dm Vertical cross section of model fields (t = 24 h)

  18. 2014 OU CAPS Ensemble (HWT) MY2-v2 THO MY2-v1 MOR-G OBS P3 1 km Reflectivity, 22 UTC 8 May, 2014 22 h forecast http://hwt.nssl.noaa.gov/Spring_2014

  19. Timing Tests for 3D WRF Simulations • Average wall clock time per model time step (units of seconds.) • Times relative to those of WSM6 are indicated parenthetically. • P3* is one of the fastest schemes in WRF *1 ice-phase category version

  20. New Bulk Microphysics Parameterization: Predicted Particle Properties (P3) Scheme* Based on a conceptually different approach to parameterize ice-phase. LIQUID PHASE:2 categories, 2-moment: qc, qr, Nc, Nr ICE PHASE: 1 category, 4 prognostic variables: qi, qrim, Ni, Brim  predicts wide range of properties (and thus types of ice) The single “free (ice-phase) category” version shows very promising early results * Morrison and Milbrandt (2014) J. Atmos. Sci (in press)

  21. New Bulk Microphysics Parameterization: Predicted Particle Properties (P3) Scheme Multi-category version* LIQUID PHASE: 2 categories, 2-moment: qc, qr, Nc, Nr ICE PHASE: category 1:qi_1, qrim_1, Ni_1, Brim_1 category 2:qi_2, qrim_2, Ni_2, Brim_2 category 3:qi_3, qrim_3, Ni_3, Brim_3 … …  predicts wide range of properties (and thus types of ice) – as before – BUT now allows for different types of ice in the same grid point * Milbrandtand Morrison (2015) (in preparation)

  22. Conclusions • The P3 approach introduces a conceptual departure from current bulk microphysics schemes. • Preliminary results – idealized, real-case simulations, and real-time forecasts – are very promising… • Further developments to the P3 scheme will include: • more predicted properties + spectral dispersion (3-moment) + liquid fraction + etc…

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