MultiScale Simulation of Aerosols and Radiative Forcing within a Community Model

1
Multi-Scale Simulation of Aerosols and Radiative
Forcing within a Community Model

• Principal Investigator Jerome D. Fast
• Co-Investigators William I. Gustafson Jr.,
  Elaine G. Chapman, James C. Barnard, Rahul A.
  Zaveri
• Pacific Northwest National Laboratory, Richland,
  Washington
• ASP Science Meeting, 31 October - 1 November,
  Alexandria, Virginia

2
Research Tool WRF-chem

• The Weather Research and Forecasting (WRF) model
  is the next-generation meteorological model being
  developed collaboratively among several agencies
• NOAA / FSL developed the first version of
  WRF-chem
• Fully-coupled meteorology,chemistry and
  particulates that permit the simulation of
  aerosol direct and indirect forcing
• Nesting capability permits simulation of aerosol
  evolution over multiple spatial scales, from
  local (1 km) to continental ( 100 km)
• PNNL version of WRF-chem includes
• CBM-Z gas-phase chemistry mechanism
• MOSAIC aerosol mechanism
• FAST-J photolysis scheme
• aerosol optical property modules
• aqueous chemistry and aerosol-cloud interactions
• direct (complete) and indirect forcing (nearly
  complete)
• see http//www.pnl.gov/atmos_sciences/JDF/wrf-chem
  .html

3
Research Tool WRF-chem

• Why WRF-chem?
• community model for research and operational
  applications, share ASP developed code with
  atmospheric sciences community
• PNNL developed code will soon be made available
  via NCAR distribution
• Ability to merge ASP aerosol modules into
  regional climate model versions of WRF that are
  also linked to the CCSM global climate model

aerosol modeling community
DOE Atmospheric Science Program
modeling research
4
Radiative Forcing in WRF-chem

• Direct Effect James Barnard and Rahul Zaveri
• In-Direct Effect Steven Ghan and Richard Easter

size and number distribution, composition,
aerosol water
scattering and absorption of shortwave radiation
refractive indices
3-D ?? , ?o , and g
Mie theory
cloud albedo, precipitation, cloud lifetime
prognostic cloud droplet number, aqueous chemistry
aerosol activation
wet removal
aerosol number
Nk - grid cell mean droplet number mixing ratio
in layer k Dk - vertical diffusion Ck - droplet
loss due to collision/coalescence collection.
Ek - droplet loss due to evaporation Sk -
droplet source due to nucleation
5
Cloud-Aerosols Interactions
Explicit Convective Cloud Simulation
CCN at 0.5 supersaturation
PM2.5
venting
aqueous phase aerosols
cloud boundary
scavenging
rain boundary
surface PM2.5
PM2.5 aloft
surface PM2.5 difference with and without
scavenging
scavenging
160 km
6
TexAQS 2000
Instantaneous Aerosol Radiative Forcing Noon,
August 31, 2000
Average Aerosol Radiative Forcing August 28 - 1
September, 2000
NW wind
W m-2
W m-2
36 33 30 27 24 21 18 15
27 26 25 24 23 22 21 20
largest impact north of industrial corridor
Houston
Houston
Galveston Bay
Galveston Bay
lines major highways dots major industrial
sources
?x 1.3 km
?x 1.3 km
120 km
impact of organic and elemental carbon from urban
and industrial sources
impact of sulfate from power plant
(typical GCM ?x 100 km)

• Impact of anthropogenic particulates are a major
  uncertainty in GCMs large spatial variations in
  particulates and the resulting radiative forcing
  over urban areas are not resolved by Global
  Climate Models (GCMs)
• PNNLs WRF-chem model and results from TexAQS
  submitted to JGR

7
TexAQS 2000
Observed and Simulated Quantities at LaPorte
Supersite
8
ICARTT 2004
Simulated NOx and SO2 900 m AGL at 19 UTC 9
August 2004 and G-1 Measurements 17 - 19 UTC
ppb
ppb
NOx
SO2
55 50 45 40 35 30 25 20 15 10 5
55 50 45 40 35 30 25 20 15 10 5
Keystone
Homer
Pittsburgh
Pittsburgh
Reliant
Dx 2 km
200 km

• NOx too high because NEI99 emission estimates too
  high
• Currently performing another simulation that uses
  information from Continuous Emissions Monitoring
  System for stack emission sources

9
ICARTT 2004
Simulated NH4 and SO4 900 m AGL at 19 UTC 9
August 2004 and G-1 Measurements 17 - 19 UTC
mg m-3
mg m-3
SO4
NH4
14 13 12 11 10 9 8 7 6 5 4
5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5
Keystone
Homer
Pittsburgh
Pittsburgh
Reliant
10
ICARTT 2004
Simulated and Observed Aerosol
Simulated Aerosol Optical Depth
cm-3
22000 20000 18000 16000 14000 12000 10000 8000 600
0 4000 2000
1.2 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2
Indiana
Keystone
Homer
Pittsburgh
Pittsburgh
Reliant
1.0 0.5 0.0
AOD (500 ?m)

• 8 9
  10
• August 2004

11
ICARTT 2004
MODIS 17 UTC 9 August
MODIS 16 UTC 10 August
MODIS 17 UTC 11 August
Simulated Aerosol Optical Depth (colors) and
clouds (white)
1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
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Future Applications of WRF-chem

• Evaluate predictions from WRF-chem using ASP data
  
• ICARTT Evolution of particulates from power
  plant emissions, effect of clouds, impact of
  power plant aerosols downwind
• MAX-Mex Particulate evolution from source up to
  several days downwind, radiative forcing,
  feedback effects
• Carl Berkowitz and Larry Berg will be using
  WRF-chem for cloud venting and aerosol-cloud
  interactions
• Collaboration with Steve Ghan using WRF-chem to
  develop parameterized pollutants for global
  climate models