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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
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
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)
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”)
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”)
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
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
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
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
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)
Mesoscale Model Results
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
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)
WRF Results: Line-averaged Reflectivity (t = 6 h)
ObservationsdBZ
MOR-G
MOR-H
THO
WSM6
WDM6P3
MY2
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
Precipitation rate at 1 km height
Time-averaged from 6-7 h
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)
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
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
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
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)
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…