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Title: The VAMOS Ocean-Cloud-Atmosphere-Land Study


1
The VAMOS Ocean-Cloud-Atmosphere-Land
Study Robert Wood, University of Washington
2
  • Improving understanding, model simulations, and
    prediction of the Southeast Pacific Climate
    System

Field Program and Modeling
Regional pollution
Mesoscale ocean eddies
Stratocumulus clouds
3
The Southeast Pacific Climate
  • Cold SSTs, coastal upwelling, subsidence
  • Cloud-topped MBLs
  • Influenced by and influential on remote climates
    (ENSO)
  • Unresolved issues in heat and nutrient budgets
  • Important links between clouds and aerosol
  • Poorly simulated by atmosphere-ocean GCMs

4
Clouds in climate models- change in low cloud
amount for 2?CO2
GFDL
CCM
model number
from Stephens (2005)
5
source IPCC 2007
6
EPIC 2001 Stratocumulus Cruise and PACS cruise
explorations of SEP stratus
7
Drizzle is important over the SEP
8
Mesoscale variability in stratocumulus
9
Aerosol issues in SEP
VOLCANOES
  • Locations and strengths of sources of natural and
    anthropogenic aerosols and precursors
  • Regional distribution of aerosol. Relative
    contribution of anthropogenic and natural sources
  • Effects of aerosol on micro and macrophysical
    cloud properties

SMELTERS
DUST
DMS
10
Global cloud droplet concentration (MODIS, annual
mean 2001-2004)
11
Cloud Microphysical Variability
Smelter locations
MODIS Cloud Droplet Concentration (SON
2001-2004)
12
Comparison of in-situ and satellite microphysical
properties
13
Aerosol speciation over the SEP
D0.05 mm
Tomlinson et al. (2007)
Ammonium Bisulfate
Sulfuric Acid
D0.2 mm
50 100 150 200 250
Temperature C
Results indicate that submicron aerosol is
predominantly composed of a mixture of sulfuric
acid and ammonium bisulfate
14
Pockets of Open Cells (POCs)
200 km
15
POCs and drizzle
16
Importance of POCs
  • Open cell coverage can be significant
  • Strong synoptic and intraseasonal variability
  • Association with drizzle

17
The POC breeding grounds
18
Sub-monthly variability
19
Aerosol, cloud, drizzle and POCs
20
POCs and Aerosols
  • Strong reductions in accumulation mode aerosol
    concentration
  • New nucleation
  • Links between aerosol microphysics and cloud
    macrophysics?

21
POC formation
22
VOCALS Regional Experiment (REx)
Field Program to address VOCALS science
questions Chiefly sponsored by NSF and NOAA,
with contributions from ONR, DoE, and
international agencies When Oct-Nov 2008
Scientific Program Overview NSF Proposal Robert
Wood, VOCALS-REx PI, University of
Washington Christopher Bretherton, GEWEX/GCSS
Representative, University of Washington Barry
Huebert, SOLAS Representative, University of
Hawaii C. Roberto Mechoso, VOCALS Science Working
Group Chair, UCLA Robert Weller, Woods Hole
Oceanographic Institution
23
VOCALS Regional Experiment (REx)
  • VOCALS-Rex will collect datasets required to
    address a set of issues that are organized into
    two broad themes
  • Aerosol-cloud-drizzle interactions in the marine
    boundary layer (MBL) and the physicochemical and
    spatiotemporal properties of aerosols
  • Chemical and physical couplings between the
    upper ocean, the land, and the atmosphere.

24
  • AEROSOL-CLOUD-DRIZZLE HYPOTHESES
  • Variability in the physicochemical properties of
    aerosols has a measurable impact upon the
    formation of drizzle in stratocumulus clouds over
    the SEP
  • Precipitation is a necessary condition for the
    formation and maintenance of pockets of open
    cells (POCs) within stratocumulus clouds
  • The small effective radii measured from space
    over the SEP are primarily controlled by
    anthropogenic, rather than natural, aerosol
    production, and entrainment of polluted air from
    the lower free-troposphere is an important source
    of cloud condensation nuclei (CCN)
  • Depletion of aerosols by coalescence scavenging
    is necessary for the maintenance of POCs.

25
  • COUPLED-OCEAN-ATMOSPHERE-LAND HYPOTHESES
  • Oceanic mesoscale eddies play a major role in
    the transport of heat and fresh water from
    coastally upwelled water to regions further
    offshore
  • By changing the physical and chemical properties
    of the upper ocean, upwelling has a systematic
    and noticeable effect on aerosol precursor gases
    and the aerosol size distribution over the SEP
  • The diurnal subsidence wave (upsidence wave)
    originating in northern Chile/southern Peru has
    an impact upon the diurnal cycle of clouds that
    is well-represented in numerical models
  • The entrainment of cool fresh intermediate water
    from below the surface layer during mixing
    associated with energetic near-inertial
    oscillations generated by transients in the
    magnitude of the trade winds is an important
    process to maintain heat and salt balance of the
    surface layer of the ocean in the SEP.

26
VOCALS-REx Platforms
NSF C-130
NOAA Ronald H Brown
DoE ASP G-1
27
NSF C-130 Payload
  • Standard instruments Microphysics, Turbulence,
    Thermodynamics suite
  • Remote sensing Wyoming Cloud Radar
    (zenithnadirslant), Cloud Lidar (zenith),
    Microwave radiometer (183 GHz, zenith), AIMR
    (nadir), MODIS Airborne Simulator (MASTER,
    nadir), BBRs
  • Chemistry/aerosols/clouds LDMA, RDMA, ToF Mass
    Spec, nephelometer, PSAP, CN counters
    (ultrafine), CCN, CVI, Cloud water collector,
    Impactors
  • Dropsondes

28
NOAA Ronald H Brown Payload
  • Remote sensing Cloud profiling radar (94 GHz,
    motion stabilized), C-band scanning radar,
    Microwave radiometer (21/32/90 GHz), Laser
    ceilometer, Wind profiler, BBRs
  • Meteorology Flux tower, Turbulence, Meteorology
    suite
  • Oceanography XBTs, ADCP, SeaSoar, Ocean
    microstructure profiles, SST sensors, thermistor
    chains
  • Chemistry/Aerosols DMS fluxes, Aerosol
    composition (impactors, PILS), Ozone, Radon,
    Nephelometers, PSAP, DMA/APS, CCN (5 channels)

29
CIRPAS Twin Otter Payload
  • Standard instruments Microphysics (PDPA, FSSP,
    CIP), Turbulence, Thermodynamics suite
  • Remote sensing 94 GHz FMCW radar, chaff
    dispenser
  • Chemistry/aerosols/clouds PCASP, 2 CPCs,
    DMA/TDMA, CCN, SP2 (black carbon)
  • Towed platform (optional)

30
DoE ASP G-1 Payload
  • Standard instruments Microphysics, Turbulence,
    Thermodynamics suite
  • Chemistry/aerosols/clouds Aerosol size
    distribution/conc (PCASP, FIMS, CPC), composition
    (PILS, ToF aerosol mass spectrometer), CCN,
    nephelometer, aethelometer, O3, CO, SO2,
    DMS/organics

31
FAAM BAe-146 payload
  • Standard instruments Microphysics, Turbulence,
    Thermodynamics suite
  • Remote sensing Microwave Radiometer (MARSS),
    Shortwave Spectrometer (SWS), Spectral
    Hemispheric Irradiance Measurement (SHIM), BBRs,
    Heiman, Airborne Research Interferometer
    Evaluation System (ARIES)
  • Chemistry/aerosols/clouds CCN, CPC, Aerosol mass
    spectrometer, SP2 (black carbon), filters, CVI,
    nephelometer (dry/wet), PSAP

32
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33
VOCALS-REx Flight-plan for C-130 Cross-section
missions
34
VOCALS-REx Flight-plan for C-130 POC-Drift
missions (Lagrangian)
35
VOCALS Modeling
  • Improved simulation of the large-scale
    circulation in the atmosphere and mesoscale ocean
    eddy transports of heat and biogenic species
    offshore over the SEP
  • Detailed process modeling (LES, chemistry, eddy
    resolving ocean models)
  • Multiscale simulation and prediction system
  • Improved representation of the aerosol indirect
    effects over the SEP by regional and/or global
    models

36
PreVOCA
GOAL To critically assess the ability of the
models (atmospheric, chemical transport.) to
simulate the salient characteristics of the
VOCALS region WHY? Learn more about model
biases, current ability of CTMs to forecast for
REx etc. A means for leveraging REx data -
successful endeavor during previous VAMOS
projects (e.g. NAME)
37
What to compare
  • 3-hourly data for October 2006 gridded to 1x1o
    resolution over the VOCALS Region (0-40oS,
    60-110oW)
  • Fields
  • meteorology
  • clouds (LWC, fractional coverage, microphysics)
  • major aerosol and precursor species
  • Not all fields can be grounded with observations,
    but many can
  • GOES (diurnal clouds)
  • MODIS (clouds, microphysics)
  • Quikscat (surface winds)
  • AMSR (WVP, cloud LWC)
  • CloudSat/CALIPSO (drizzle, MBL depth,)

38
Who?
  • NCAR CAM (Rasch/Breth)
  • WRF-Chem (Fast)
  • NASA GMAO (Bacmeister)
  • GFDL (Ramaswamy)
  • ECMWF (Koehler)
  • NCEP GFS (Pan)
  • iROAM (Y. Wang)
  • U. Chile WRF (Garreaud)
  • COAMPS (S. Wang)
  • MMF (Khairoutdinov)
  • Other modeling groups are welcome.

39
VOCALS Legacy
  • Improved large scale coupled ocean-atmosphere
    model simulations and predictions of the SEP
    climate system through a coordinated modeling and
    observational program
  • Integrated datasets (IDs), and complete data
    archive
  • Development of a multi-scale simulation and
    prediction system
  • Education and training for both US and regional
    climate scientists.

40
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41
Satellite issues
42
MODIS VIS/NIR Retrievals Problematic
Liquid water path
Effective radius
Cloud drop conc.
open cells
closed cells
MODIS 10/19/2001 1000 Local (1600 UTC)
43
CloudSat observes drizzle
44
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45
VOCALS Timeline
IUGG Perugia
Planning Phase
VOCALS REx
VOCALS Conference
Field site surveys
REx and Modeling Workshops
2003 - 2006
2007
2008
2009
2010
Field and modeling synthesis/analysis
PI Proposal submission
46
THE VOCALS STRATEGY
47
IGBPs Surface Ocean Lower Atmosphere Study
(SOLAS) has formally agreed to collaborate with
CLIVAR on VOCALS. http//www.uea.ac.uk/env/sola
s/
In the remote marine atmosphere the supply of DMS
and its oxidation mechanisms limit the rates of
new particle nucleation and growth. These
processes probably control the re-filling of POCs
with clouds. Iodine, ammonia, and organics may
also play a role. SOLAS proposes to study this
chemistry from both ships and aircraft.
48
CGCM Problems NOAA CFS Model
CFS Errors
  • The CFS model has significant errors in the SEP
  • There is a meridional shift in ITCZ (top), a
    warm SST bias (middle) and insufficient
    stratocumulus cloud cover, (bottom)
  • These errors adversely affect the skill of CFS
    climate forecasts (ENSO).
  • What model developments are required to alleviate
    these errors?

Prec
SST
CLD
49
VOCALS Science Working Group
  • Roberto Mechoso, UCLA, USA (chair)
  • Chris Bretherton, Univ of Washington, Seattle,
    USA
  • Chris Fairall,  NOAA/ESRL, Boulder, USA
  • Barry Huebert, Univ of Hawaii at Manoa, USA
  • Jim McWilliams, UCLA, USA
  • Oscar Pizarro, U Concepción, Chile
  • José Rutllant, U Chile, Santiago, Chile
  • Bob Weller, WHOI. Woods Hole USA
  • Hemantha Wijesekera , Oregon State Univ., USA
  • Robert Wood, Univ of Washington, Seattle, USA
  • Shang-Ping Xie, IPRC, Univ of Hawaii, USA
  • Carlos Ereño, Int'l CLIVAR
  • José Meitín (ex officio), NCAR EOL/VAMOS Office

50
SST Biases in Coupled Models
  • SST Biases in NCAR CCSM (Collins et al. 2006)

51
The effect of low clouds on climate
SST
Stratus Cloud Amount (Warren)
Net CRF
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