a new approach to parameterize ice-phase cloud microphysics
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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A new approach to parameterizeice-phase cloud microphysics
The Predicted Particle Properties (P3) Scheme
WWOSC 2014Montreal, CanadaAugust 17, 2014
Hugh Morrison1 and Jason Milbrandt2
1National Center for Atmospheric Research, Boulder, CO, USA2Environment Canada, Montreal, Canada
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Environment Canada’sHigh Resolution (2.5-km) Deterministic Prediction System
Column-maximum REFLECTIVITY*
* Computed from microphysics (Milbrandt-Yau 2-moment) Experimental implementation: summer 2014
Operational implementation: 2015
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N (D)
D [ m]100
[m-3 m-1]
20 40 60 800
101
100
10-1
10-2
Microphysics Parameterization SchemesULTIMATE GOAL: Predict evolution of hydrometeor size distributions
N (D)
D [ m]100
[m-3 m-1]
20 40 60 800
101
100
10-1
10-2
Bin-resolving: Bulk:DeDNDN 0)(i
I
i
NDN
1
)(
N (D)
D [ m]100
[m-3 m-1]
20 40 60 800
101
100
10-1
10-2
(spectral)
1 m3
(unit volume)
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Radius [cm]Bin-resolving coalescence model
Berry and Reinhardt (1974)
RAINCLOUD
Mas
s D
ensi
ty [
g m
-3 (
lnr)
-1]
Tim
e [m
in]
BACKGROUND – Representation of Hydrometeors
Historical development of bulk scheme approach:
• start with liquid-only (“cloud” and “rain”)
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Example of Observed Ice Particles
Photos c/o Alexei Korolev
BACKGROUND – Representation of Hydrometeors
Historical development of bulk scheme approach:
• start with liquid-only (“cloud” and “rain”)
• add ice-phase (“ice”)
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GRAUPELg = 400 kg m-3
V = agDbg
HAILh = 900 kg m-3
V = ahDbh
“SNOW”s = 100 kg m-3
V = asDbs
abrupt / unphysical
conversions
CLOUD ICEs = 500 kg m-3
V = aiDbi
Problems with pre-defined categories:
1. Conversions between categories are ad-hoc
2. Conversions lead to large, discrete changes in particle properties
etc. …
Traditional approach of bulk microphysics schemes:
BACKGROUND – Representation of Hydrometeors
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The simulation of ice-containing cloud systems is oftenvery sensitive to how ice is partitioned among categories
MOR-hail (only)
MY2 - hail (only)
MOR-graupel (only)
MY2-baseline (g + h)
Morrison and Milbrandt (2011), MWR
Microphysics Schemes:MOR: Morrison et al. (2005, 2009)MY2: Milbrandt and Yau (2005)
• idealized 1-km WRF simulations (em_quarter_ss)
• base reflectivity
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There is a paradigm shiftin the parameterization of ice-phase microphysics
Increased emphasis on the prediction ofhydrometeor properties
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)
BACKGROUND – Representation of Hydrometeors
Partial mitigation to the problems with pre-defined categories
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SQUEAK!
QUACK!
• 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
Which of the following is more duck-like?
IF IT QUACKS LIKE A DUCK …
DUCK
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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
New Bulk Microphysics Parameterization:
Predicted Particle Properties (P3) Scheme*
* Morrison and Milbrandt (2014)J. Atmos. Sci (in press)
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Mesoscale Model Results
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3D Squall Line case:(June 20, 2007 central Oklahoma)
• WRF_v3.4.1, x = 1 km, z ~ 250-300 m, 112 x 612 x 24 km domain• initial sounding from observations• convection initiated by u-convergence• no radiation, surface fluxes
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2007 OK Squall Line: Base Reflectivity (1 km AGL, t = 6 h)
MOR-G
MOR-H
THO
Observations
WSM6
WDM6P3
dBZ
MY2
Morrison et al. (2014)J. Atmos. Sci (in press)
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WRF Results: Line-averaged Reflectivity (t = 6 h)
ObservationsdBZ
MOR-G
MOR-H
THO
WSM6
WDM6P3
MY2
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DERIVED Ice Physical Properties
Fr ~ 0-0.1 ~ 900 kg m-3V ~ 0.3 m s-1
Dm ~ 100 μm small crystals
Fr ~ 0 ~ 50 kg m-3V ~ 1 m s-1
Dm ~ 3 mm aggregates
Fr ~ 1 ~ 900 kg m-3
V > 10 m s-1
Dm ~ 5 mm hail
etc.
Fr
VmDm
ρp
Vertical cross section of model
fields (t = 6 h)
P3 SIMULATION
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Precipitation rate at 1 km height
Time-averaged from 6-7 h
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Low-density, unrimed snow
Rimed snow/ low-density graupel
Small, dense ice
Z qi
qrqc
Fr
Vm Dm
ρp
Z
P3 SIMULATION
Vertical cross section of model fields (t = 24 h)
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2014 OU CAPS Ensemble (HWT)
1 km Reflectivity, 22 UTC 8 May, 201422 h forecast
OBSMOR-GP3
THO MY2-v2 MY2-v1
http://hwt.nssl.noaa.gov/Spring_2014
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Scheme Squall line case
(x = 1 km)
Orographic case
(x = 3 km)
# prognostic
variables
P3* 0.436 (1.043) 0.686 (1.013) 7
MY2 0.621 (1.485) 1.012 (1.495) 12
MOR-H 0.503 (1.203) 0.813 (1.200) 9
THO 0.477 (1.141) 0.795 (1.174) 7
WSM6 0.418 (1.000) 0.677 (1.000) 5
WDM6 0.489 (1.170) 0.777 (1.148) 8
• Average wall clock time per model time step (units of seconds.)
• Times relative to those of WSM6 are indicated parenthetically.
Timing Tests for 3D WRF Simulations
P3* is one of the fastest schemes in WRF
*1 ice-phase category version
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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)
New Bulk Microphysics Parameterization:
Predicted Particle Properties (P3) Scheme*
* Morrison and Milbrandt (2014)J. Atmos. Sci (in press)
The single “free (ice-phase) category” version shows very promising early results
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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
New Bulk Microphysics Parameterization:
Predicted Particle Properties (P3) Scheme
* Milbrandt and Morrison (2015) (in preparation)
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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…