observations two-moment one-moment

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Investigation of Microphysical Investigation of Microphysical Parameterizations of Snow and Ice in Arctic Parameterizations of Snow and Ice in Arctic Clouds During M-PACE through Model-Observation Clouds During M-PACE through Model-Observation Comparisons Comparisons Amy Solomon Amy Solomon 12 12 In collaboration with: In collaboration with: Hugh Morrison Hugh Morrison 3 , Ola Persson , Ola Persson 12 12 , Matt Shupe , Matt Shupe 12 12 , Jian-Wen Bao , Jian-Wen Bao 1

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Investigation of Microphysical Parameterizations of Snow and Ice in Arctic Clouds During M-PACE through Model-Observation Comparisons Amy Solomon 12 In collaboration with: Hugh Morrison 3 , Ola Persson 12 , Matt Shupe 12 , Jian-Wen Bao 1 - PowerPoint PPT Presentation

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Page 1: Observations Two-Moment One-Moment

Investigation of Microphysical Parameterizations of Snow and Investigation of Microphysical Parameterizations of Snow and Ice in Arctic Clouds During M-PACE through Model-Ice in Arctic Clouds During M-PACE through Model-

Observation ComparisonsObservation Comparisons

Amy SolomonAmy Solomon1212

In collaboration with:In collaboration with:

Hugh MorrisonHugh Morrison33, Ola Persson, Ola Persson1212, Matt Shupe, Matt Shupe1212, Jian-Wen Bao, Jian-Wen Bao11

11NOAA/Earth System Research Laboratory, Boulder, ColoradoNOAA/Earth System Research Laboratory, Boulder, Colorado

22CIRES/University of Colorado, Boulder, ColoradoCIRES/University of Colorado, Boulder, Colorado33National Center for Atmospheric Research, Boulder, ColoradoNational Center for Atmospheric Research, Boulder, Colorado

Investigation of Microphysical Parameterizations of Snow and Investigation of Microphysical Parameterizations of Snow and Ice in Arctic Clouds During M-PACE through Model-Ice in Arctic Clouds During M-PACE through Model-

Observation ComparisonsObservation Comparisons

Amy SolomonAmy Solomon1212

In collaboration with:In collaboration with:

Hugh MorrisonHugh Morrison33, Ola Persson, Ola Persson1212, Matt Shupe, Matt Shupe1212, Jian-Wen Bao, Jian-Wen Bao11

11NOAA/Earth System Research Laboratory, Boulder, ColoradoNOAA/Earth System Research Laboratory, Boulder, Colorado

22CIRES/University of Colorado, Boulder, ColoradoCIRES/University of Colorado, Boulder, Colorado33National Center for Atmospheric Research, Boulder, ColoradoNational Center for Atmospheric Research, Boulder, Colorado

Page 2: Observations Two-Moment One-Moment

Models that include prognostic equations for cloud water, rain, ice, and snow mixing ratio and number concentration (two-moment) successfully model horizontally extensive, persistent mixed-phase Arctic stratocumulus

Observations

Two-Moment

One-Moment

(After Morrison and Pinto 2006)

Impact of Microphysical Parameterization on Impact of Microphysical Parameterization on Simulations of Arctic StratocumulusSimulations of Arctic StratocumulusImpact of Microphysical Parameterization on Impact of Microphysical Parameterization on Simulations of Arctic StratocumulusSimulations of Arctic Stratocumulus

Climate models fail to produce Arctic clouds that maintain liquid water at low temperatures (e.g., Prenni et al. 2006, Inoue et al.

2006, Sandvik et al. 2007, Klein et al. 2008)

Since cloud liquid water causes an increase in the downwelling longwave radiation and a decrease in the incoming shortwave radiation

Inadequate simulations of Arctic clouds causes significant errors in the modeled surface energy budget

Page 3: Observations Two-Moment One-Moment

ObjectiveObjectivessObjectiveObjectivess

Process-oriented validation of microphysical parameterizations

Specifically, in this study:

Verify the simulations of mixed-phase clouds and boundary layer structure during M-PACE with the WRF V2.2

Comparisons of LWP/IWPComparisons of SWD/LWDVertical structure and temporal variability of LWC and IWCVariability of vertical velocitiesVariability of LWP/IWP

Investigate the sensitivity of the model simulations to the parameterization of snow/ice

Sensitivity to mid-latitude N0s

Sensitivity to two-moment N0s

Sensitivity to approximate observed N0i

Page 4: Observations Two-Moment One-Moment

Prognostic variables include mixing ratios and number concentrations of cloud ice, cloud droplets, snow, graupel, and rain Hydrometeors have the form of a complete gamma size distribution:(D) = N0DPce-D

= cN(Pc+d+1)1/d

q(Pc + 1) = the Slope Parameter

N0 = NPc+1 is the Intercept Parameter

Pc is the Spectral Parameter (Pc=0 for ice, snow, rain, graupel)

Bulk density of ice = 0.5 g cm-3 Bulk density of snow = 0.1 g cm-3

(Now available as a standard option in WRF V3)

Microphysical Microphysical SchemeSchemeMicrophysical Microphysical SchemeScheme

Page 5: Observations Two-Moment One-Moment

Control Set-Control Set-upupControl Set-Control Set-upup

Weather Research Forecast Model V2.2Nested 18/6/1 km horizontal grids50 vertical levels (20 levels below 800 hPa)Morrison Two-Moment microphysicsCAM Radiation3D PBL mixing in the 1km grid (YSU in 18/6 km)NOAH LSM

Page 6: Observations Two-Moment One-Moment

Control Set-up and Horizontal Structure in 1 km Control Set-up and Horizontal Structure in 1 km DomainDomainControl Set-up and Horizontal Structure in 1 km Control Set-up and Horizontal Structure in 1 km DomainDomain

Weather Research Forecast Model V2.2Nested 18/6/1 km horizontal grids50 vertical levels (20 levels below 800 hPa)Morrison Two-Moment microphysicsCAM Radiation3D PBL mixing in the 1km grid (YSU in 18/6 km)NOAH LSM

Page 7: Observations Two-Moment One-Moment

Impact of Horizontal Resolution on the Maintenance of Impact of Horizontal Resolution on the Maintenance of Liquid WaterLiquid WaterImpact of Horizontal Resolution on the Maintenance of Impact of Horizontal Resolution on the Maintenance of Liquid WaterLiquid Water

1 KM 50 KM24

-hou

r av

erag

e1-

hour

ave

rage

Page 8: Observations Two-Moment One-Moment

Vertical Velocity and Growth of Cloud Vertical Velocity and Growth of Cloud DropletsDropletsVertical Velocity and Growth of Cloud Vertical Velocity and Growth of Cloud DropletsDroplets

Hourly-averaged 2M vertical velocity at Barrow from Oct 2004 9 12Z to 10 11Z, in units of cm s-1

Hourly-averaged 2M vapor deposition with LWC is shown with dashed blue contours, in units of g m-3

W (cm/s) Vapor Droplets (g/m3/hour)

Page 9: Observations Two-Moment One-Moment

STD(W) at different averaging periods

Retrievals T

wo-M

oment

Validation of Dominant Timescales for Vertical Validation of Dominant Timescales for Vertical Motions and Ice/Liquid InteractionsMotions and Ice/Liquid InteractionsValidation of Dominant Timescales for Vertical Validation of Dominant Timescales for Vertical Motions and Ice/Liquid InteractionsMotions and Ice/Liquid Interactions

Correlation between IWP and LWP at different averaging periodsModel underestimates variability on

timescales shorter than 2 minutes

And overestimates variability on timescales between 2-30 minutes

An aliasing of fast processes to longer timescales?

Page 10: Observations Two-Moment One-Moment

STD(W) at different averaging periods

Retrievals T

wo-M

oment

Validation of Dominant Timescales for Vertical Validation of Dominant Timescales for Vertical Motions and Ice/Liquid InteractionsMotions and Ice/Liquid InteractionsValidation of Dominant Timescales for Vertical Validation of Dominant Timescales for Vertical Motions and Ice/Liquid InteractionsMotions and Ice/Liquid Interactions

Correlation between IWP and LWP at different averaging periods

Observations show significant correlations between IWP and LWP for timescales shorter than 12 minutes

The model shows significant correlations between IWP and LWP on all timescales

Another indication that the model is aliasing fast processes to longer timescales?

Page 11: Observations Two-Moment One-Moment

Validation of Liquid and Ice Water Validation of Liquid and Ice Water ContentContentValidation of Liquid and Ice Water Validation of Liquid and Ice Water ContentContent

Retrievals Morrison 2M MicrophysicsIW

C

LW

C

Page 12: Observations Two-Moment One-Moment

Validation of Water Paths and Surface Validation of Water Paths and Surface RadiationRadiationValidation of Water Paths and Surface Validation of Water Paths and Surface RadiationRadiation

SW

LW

P

IWP

LW

Observations2M Morrison1M Morrison

Page 13: Observations Two-Moment One-Moment

Validation of Cloud Droplet, Snow, and Ice Size Validation of Cloud Droplet, Snow, and Ice Size DistributionsDistributionsValidation of Cloud Droplet, Snow, and Ice Size Validation of Cloud Droplet, Snow, and Ice Size DistributionsDistributions

Two-moment scheme does a good job of simulating the observed cloud droplet and snow size distributions

In general, N0 is not known apiori and varies in space and time!

N0 for ice is underestimated by an order of magnitude…

Aircraft measurements Two-Moment

(After McFarquhar et al. 2007)

N0i?

N0s?

Page 14: Observations Two-Moment One-Moment

Mixing Ratio of Snow

Mixing Ratio of Cloud Droplets

Two-moment N0s (solid) One-moment N0s=8.e5 m-4 (dash)

Averaged for LWC>0.01 g m-3 at Barrow, Alaska

Impact of Specifying Two-Moment Impact of Specifying Two-Moment

NN0s0s

Impact of Specifying Two-Moment Impact of Specifying Two-Moment

NN0s0s

Page 15: Observations Two-Moment One-Moment

Two-moment N0i (solid)One-moment N0i=5.e7 m-4 (dash) at Barrow, Alaska

Aircraft Measurements of ice number concentration (d >53 microns):Mean (white line) and +/- one standard deviation (grey shading)

Impact of Specifying Observed Impact of Specifying Observed

NN0i0i

Impact of Specifying Observed Impact of Specifying Observed

NN0i0i24-hour mean ice number concentration 24-hour mean snow number concentration

Page 16: Observations Two-Moment One-Moment

FindingFindingss

FindingFindingss

1) Morrison two-moment microphysics does a good job of simulating the LWC in Arctic stratocumulus observed during M-PACE, as well as, the dominant initiation and growth mechanisms for cloud water, snow, and ice.

2) Cloud water forms at the cloud base and grows in updrafts. Coarser resolution runs (>18 km) do not resolve this process because the vertical velocity needed to lift the cloud water is underestimated, resulting in clouds that form closer to the ground.

3) Specifying N0s to typical mid-latitude values depletes the cloud liquid water--The

two-moment scheme is able to reproduce the observed LWC because it does a good

job of predicting N0s, which is advantageous since N0 is poorly constrained by

observations and varies in space and time.

4) Ice number concentration is underestimate by an order of magnitude in the two-moment simulation and there is an indication that variability is being aliased to longer (> 2 minutes) timescales.

5) Specifying the ice size distribution observed during this period in a one-moment simulation acts to deplete the liquid water, indicating that the vapor deposition to ice may be occurring too rapidly in the model.

6) Specifying the two-moment snow size distribution in a one-moment simulation results in similar snow mixing ratio and number concentration but a depletion of cloud water due to the coupling between mixing ratio and number concentration in the one-

moment scheme.

Page 17: Observations Two-Moment One-Moment

Structure of Arctic clouds

Mixed-phase clouds dominate the low-cloud fraction within the Arctic during the colder three-quarters of the year (Curry et al. 2000; Intrieri et al. 2002; Uttal et al. 2002; Wang et al. 2005)

Arctic low-level mixed-phase clouds tend to be long-lived and are not observed to glaciate quickly due to the Bergeron process (Pinto 1998; Hobbs and Rangno 1998; Curry et al. 2000)

Liquid layer were observed in the M-PACE experiment at temperatures down to -34°C (Verlinde et al. 2007)

Mixed-phase clouds are observed to Mixed-phase clouds are observed to occur in regions of both strong and occur in regions of both strong and weak surface forcing, indicating that the weak surface forcing, indicating that the cause of these cold, ice-precipitating cause of these cold, ice-precipitating clouds is microphysical in natureclouds is microphysical in nature ((Harrington et al. 1999; Morrison et al. 2005)Harrington et al. 1999; Morrison et al. 2005)

(After Shupe et al. 2006)

Observations of Mixed-Phase Arctic Observations of Mixed-Phase Arctic StratocumulusStratocumulusObservations of Mixed-Phase Arctic Observations of Mixed-Phase Arctic StratocumulusStratocumulus

Page 18: Observations Two-Moment One-Moment

Case Studied: Mixed-Phase Arctic Cloud Case Studied: Mixed-Phase Arctic Cloud ExperimentExperiment Case Studied: Mixed-Phase Arctic Cloud Case Studied: Mixed-Phase Arctic Cloud ExperimentExperiment

A B

160ºW 150ºW 140ºW

Intensive Observations Oct 6-11 2004:Intensive Observations Oct 6-11 2004:Measurements at DOE ARM NSA SiteMeasurements at DOE ARM NSA Site+ High Spectral Resolution Lidar+ High Spectral Resolution Lidar+ Atmospheric Emitted Radiance + Atmospheric Emitted Radiance InterferometerInterferometer+ Radiosonde launches+ Radiosonde launches+ Two Instrumented Aircraft with a + Two Instrumented Aircraft with a Compliment of Cloud Physics ProbesCompliment of Cloud Physics Probes

A strengthening high-pressure system north of Alaska

Caused air to flow from pack ice over the open Beaufort Sea to the North Slope of Alaska

Forcing roll clouds that extended from the pack ice to the North Slope of Alaska

These clouds are aligned closely to the direction of the boundary layer winds

With wavelength of 10-15km and a PBL 1km over the ocean and <1km inland

These clouds were mixed phase with total water content dominated by liquid hydrometeors throughout the cloud layer

MODIS visible image Oct 9 0Z 2004