NASA CMAI WorkshopApril 20-21, 2006 Modeling Studies of Aerosol-Cold Cloud Interactions Sonia M....

NASA CMAI Workshop April 20-21, 2006

Modeling Studies of Modeling Studies of Aerosol-Cold Cloud InteractionsAerosol-Cold Cloud Interactions

Sonia M. Kreidenweis and Paul J. DeMottSonia M. Kreidenweis and Paul J. DeMottDepartment of Atmospheric ScienceDepartment of Atmospheric Science

Colorado State UniversityColorado State University


MotivationMotivation• Aerosol indirect effects on climate

– Includes effects on mixed and ice phase clouds… but these are poorly understood [IPCC TAR]

• For warm clouds, and homogeneous freezing processes, aerosol effects depend on size distribution, number concentration, composition– Probably true for ice formation at warmer

temperatures

• Models will need to move toward representation of aerosol sources, sinks, and key characteristics


Assessing ice nuclei (IN) concentrations, their variability, their Assessing ice nuclei (IN) concentrations, their variability, their sources, and their role in cloud ice formationsources, and their role in cloud ice formation

Measurement of IN in the Measurement of IN in the field and in the labfield and in the lab

Evidence for relation of IN Evidence for relation of IN to ice in cloudsto ice in clouds

IN variability in atmosphere? IN variability in atmosphere? Why? Does it matter?Why? Does it matter?

Improve Improve representation of representation of

cold cloud cold cloud formation in formation in

climate modelsclimate models


What ice nucleation mechanisms do we measure?What ice nucleation mechanisms do we measure?

Yes

YesYes/maybe

No, but…

Aerosols nucleate ice by varied mechanisms, most depending on T, some on RH as well

No instrument yet capable of measuring all mechanisms

What can a CFDC measure?


What can be improved in models?What can be improved in models?• Newer and more observations of IN now available to revisit prior

parameterizations

• Also clear that IN must be prognostic

– evidence that ice doesn’t form in depleted air masses

• Certain aerosol types (dust, metallic particles) and certain sizes appear to be more active IN


What can be improved in models?What can be improved in models?• For solution droplets, the theory of Koop et al. (2000) predicts that

homogeneous freezing occurs at a defined aw(T)

• We have developed methods for converting hygroscopic growth data into solution water activity data (example below is for levoglucosan, a compound in wood smoke)

– Already applied to prediction of CCN activity

• If models carry soluble particle type, and information on hygroscopicity, homogeneous freezing can be predicted

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

30 40 50 60 70 80 90 100RH (%)

GF

HTDMA

fit to GF data

Mochida and Kawamura (2004)

0.8

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00x (%)

water activity


Proposed WorkProposed Work

1. Build parcel models for aerosol-cloud interactions a. Begin with Feingold et al. (1998) aerosol-warm cloud model

and Young (1974) model

b. Modifications to include the ice phase, incorporating our lab and field data

c. Run as adiabatic parcel or from saved histories

2. Develop parameterizations for CRMs and GCMs to replace saturation-adjustment schemes

a. Implement and test through CMAI structure

3. Make models available through web interface


Seeking correlation of IN with larger aerosol Seeking correlation of IN with larger aerosol using a variety of data setsusing a variety of data sets

r2 = 0.7526


Examining cumulative distribution of [IN] and Examining cumulative distribution of [IN] and sampling conditions in many projectssampling conditions in many projects

Increasing dust Increasing dust particle impactsparticle impacts

MPACE: Arctic Fall FIRE-ACE: Arctic Spring

INSPECT-2: Western U.S. SpringCRYSTAL-FACE: Florida July


Parcel ModelParcel Model

• Each parcel initialized with thermodynamic fields and aerosol size distributions, composition, hygroscopicity, ice forming characteristics (onset conditions [T, RH] for homogeneous freezing and for heterogeneous freezing, if applicable)

LES simulationof marine stratus

Run ensemble of parcels using trajectories & analyze for cloud particle characteristics


Sample interfaceSample interface


Specific “framework” activitiesSpecific “framework” activities

• Implement and test parameterization ideas across the whole range of models• We contribute one model type to the investigation

encompassing multiple model types• As suggested in the White Paper, analyze results to

make link to larger-scale models more explicit

• Help define observational tests for comparing process representation at all scales• Threshold conditions for glaciation; precip onset?• Mean particle size, IWC• CloudSat / CALIPSO


Specific “support” elements to be usedSpecific “support” elements to be used

• Any trajectory data generated by other investigators

• Datasets produced for observational tests of model physics and performance

• Liaison team support for optimization of parameterizations


ExtraExtra


How do we measure IN and interpret the data?How do we measure IN and interpret the data?


In deeper and mostly ice phase clouds: In deeper and mostly ice phase clouds:

400

500

600

700

800

900

1000

-30 -20 -10 0 10

TAMB

TCFDC400

500

600

700

800

900

1000

-30 -20 -10 0 10

TAMB

TCFDC

Secondary ice formation or sampling issue?

Closest correspondence between ice and IN from CVI residuals Closest correspondence between ice and IN from CVI residuals occurs only in upper regionoccurs only in upper region

Nov. 19, 2003


Some cases for IN = primary initial ice formation: Some cases for IN = primary initial ice formation: studies in/around orographic wave cloudsstudies in/around orographic wave clouds

(WAVEICE, CO-WY, Wyoming King Air, March 2000)

(Rogers and DeMott, 2002 AMS Conf. Cloud Phys.)

IN


Some evidence that presence or absence of ice in Some evidence that presence or absence of ice in clouds is linked to the availability of ice nuclei clouds is linked to the availability of ice nuclei

(AIRS-2, Ontario/Quebec, NCAR C-130, Nov. 2003)(AIRS-2, Ontario/Quebec, NCAR C-130, Nov. 2003)

IN by CFDC from CVI cloud particle residuals

CFDC processing temperature approximately equal to cloud temperature


Great difficulty assigning true ice crystal Great difficulty assigning true ice crystal concentrations based on particle probe dataconcentrations based on particle probe data


Measuring ice nuclei: Continuous flow Measuring ice nuclei: Continuous flow diffusion chamber (CFDC)diffusion chamber (CFDC)

OPC

0.3 1.5 m

aerosolaerosol Activated INActivated IN


heated inlet heated inlet (ambient sample)(ambient sample)

Interior tubing and transfer to Interior tubing and transfer to other aerosol instrumentsother aerosol instruments

CVI inlet CVI inlet (residual (residual particles particles from from evaporated evaporated cloud cloud particles)particles)

Sampling involves inlets and their potential effects Sampling involves inlets and their potential effects on the nuclei we are trying to measureon the nuclei we are trying to measure

CFDCCFDC

CCNCCN


Future plans – PACDEX with HIAPER Future plans – PACDEX with HIAPER aircraft (April-May 2007)aircraft (April-May 2007)

Goal: Dust-pollution effects on clouds and radiation following from near-source across ocean. Includes IN measurements.


Future opportunity – ICE-L (Ice in Clouds Experiment – Future opportunity – ICE-L (Ice in Clouds Experiment – Layer clouds) with NCAR C-130 aircraft (March-April 2007)Layer clouds) with NCAR C-130 aircraft (March-April 2007)

Altostratus/altocumuli

Wave clouds

Goal: Identify ice formation mechanisms in clouds, Includes aerosol, IN, CCN measurements.

International Ice Nucleation Workshop: AIDA cloud chamber

facility (Karlsruhe, Germany), Summer or Fall 2007, Several

new instruments


IN variability in atmosphere? Why? Does it matter?IN variability in atmosphere? Why? Does it matter?


IN relations to aerosols have been explored during IN relations to aerosols have been explored during sampling periods at mountaintop laboratorysampling periods at mountaintop laboratory

SPL: Storm Peak Laboratory, 3.2km MSL, SPL: Storm Peak Laboratory, 3.2km MSL, Steamboat Springs, COSteamboat Springs, CO

INSPECT (Ice Nuclei INSPECT (Ice Nuclei Spectroscopy) I,II – Fall 2001, Spectroscopy) I,II – Fall 2001, Spring 2004Spring 2004


IN relation to dust particles is clear, which may IN relation to dust particles is clear, which may explain IN-aerosol size relation (most times!)explain IN-aerosol size relation (most times!)

Timeline of global aerosol model dust Timeline of global aerosol model dust mass concentration, measured aerosol mass concentration, measured aerosol volume, and IMPROVE dust mass volume, and IMPROVE dust mass concentration (April to May 2004)concentration (April to May 2004)

Timeline of IN concentration and Timeline of IN concentration and aerosol particle concentration in aerosol particle concentration in the 300 to 700 nm size range.the 300 to 700 nm size range.

Heavy pollution event

NAAPS model results courtesy of Doug Westphal, NRL, Monterrey).

µg

m-3

µm3 cm-3

µg

m-3

Per std liter

cm-3


Relation apparent between larger aerosol and IN from Relation apparent between larger aerosol and IN from mixed-phase cloud residual particlesmixed-phase cloud residual particles

Nov. 19, 2003

Appear related

Appear not related


A case for IN impacting Arctic cloudiness during a A case for IN impacting Arctic cloudiness during a dust-poor scenario: M-PACE (October 2004)dust-poor scenario: M-PACE (October 2004)

Prenni et al. (2006)Prenni et al. (2006)

Observed cloudiness

Cloud model (RAMS) with “global” IN allowed to “deplete”

North Slope AlaskaIN

measured

“Global” IN function often assumed (Meyers et al.)

Cloud modeled with observed IN allowed to “deplete”

Knowing IN concentrations was critical to predicting cloud presence, phase, liquid water path, and surface net infrared radiation. Allowing the nuclei to be redistributed and used up was also very important.

NASA CMAI WorkshopApril 20-21, 2006 Modeling Studies of Aerosol-Cold Cloud Interactions Sonia M....

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