VOCALS: Improving understanding,
model simulations, and prediction of the
Southeast Pacific Climate System
Robert Wood
University of Washington
Field Program
Regional pollution
Mesoscale ocean eddies
Stratocumulus clouds
The VAMOS Ocean-Cloud-Atmosphere-Land
Study
Aim: to promote activities leading to improved understanding and model predictions
of the SEP coupled system on diurnal to interannual timescales
http://www.eol.ucar.edu/projects/vocals/
Universities
Collaborating Institutions
C. R. Mechoso, Chair, VOCALS SWG
R. Wood, VOCALS-REx PI
Operational
Centers
Logistic Support:
NCAR JOSS
BMRC Australia
CPTEC Brazil
ECMWF Int.
JMA Japan
NCEP US
UKMO UK
Arizona State U.
U. Concepción, Ch
CSU
Drexel U.
U. Hawaii
U. Manchester UK
U. Miami
North Carolina State
Oregon State U.
U. Reading UK
U. Arizona
U. Chile
UCLA
U. Colorado
UCSD
U. Leeds UK
U. Washington
U. Wyoming
Research
Labs
Brookhaven Nat.
COLA
CNRS/LMD France
IMARPE
IPRC
LEGOS
NASA GSFC
NASA JPL
NCAR
NOAA/CIRES
NOAA/GFDL
NRL
Pacific Northwest
Woods Hole
SST anomaly
from zonal
mean
highly reflective
low clouds
[%]
0
20
40
60
80
ISCCP inferred
St/Sc amount
20oS
Longitudinal cross-section at 20oS
85oW
65oW
Why are the SSTs so low in the SEP?
AGCM with
mixed layer
ocean model
(50 m depth)
contours
qv at 925 hPa
SSTANDES – SSTAQUA
Takahashi
and Battisti (2007)
A coupled problem
• Correct prediction of
stratus properties is
important for the correct
prediction of the climate
over the tropical warm
pool
– connections with ITCZ
through both ocean and
atmosphere
Yu and Mechoso 2001
Precip [mm day-1]
0 2 4 6
8 10 12 14
SST Biases in Coupled Models
• SST Biases in NCAR CCSM (Collins et al. 2006)
Ocean surface heat budget
Net heat input into ocean at center of stratus sheet > 50 W m-2
Must be corresponding cold water transport from somewhere
Annual Heat Fluxes 20oS, 85oW
W/m2
250
Net SW
200
Net LW
150
Sensible
100
Latent
Net Heat
50
0
-50
-100
-150
Bob Weller, WHOI
Mesoscale ocean eddies
• Mesoscale ocean
eddies form in coastal
upwelling regions and
propagate westward
• Their impact on the
heat, nutrient, and
freshwater budgets is
poorly known
• They are not resolved
in coupled GCMS
Simulation from Penven et al. (2005)
14-year animation of eddies identified
using satellite altimetry (courtesy Dudley
Chelton, OSU)
Clouds and cloud processes
ERBE
-SWCF
(W m-2)
NCAR
GFDL
Clouds in
Global
Models
GMAO
Annual mean
Control run
Atmospheric models
Matt Wyant, CPT Project
Why this Uncertainty?
resolution of ~5m
required to resolve
inversion!
~12K!
Free-tropospheric
T set by ITCZ
θe
2,000km
~1km
BL T set by local SST
Drizzle is important over the SEP
200 km
Pockets of
Open Cells
(POCs)
Mesoscale stratocumulus structure
• Cloud albedo
dependent upon
open/closed cells
Open Cells
Satellite
Closed Cells
Low albedo
100 km
• Precipitation
associated with
open cell structure
• Open cells form in
clean marine
environment –
potential
anthropogenic
impacts
• Important
feedbacks between
precipitation and
aersosols
High albedo
Strong drizzle
Ship Radar
Weak drizzle
Drizzle and cloud droplet concentration
EPIC data, Bretherton et al. (2004)
Global cloud droplet concentration
(MODIS, annual mean 2001-2004)
Yim et al. (2007) – GFDL Model
MODIS
Cloud
Microphysical
Variability
MODIS
Cloud Droplet
Concentration
(SON 2001-2004)
Smelter locations
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.
Oct 1st
to Nov 28th
2008
VOCALS-REx Platforms
NSF C-130
IMARPE José Olaya
NOAA Ronald H Brown
UK FAAM BAe-146
NERC Dornier 228
DoE ASP G-1
CIRPAS Twin Otter
VOCALS-REx Platforms and Sampling
Aircraft:
NSF C-130
CIRPAS Twin
Otter
DoE G-1
UK BAe-146
NERC Do 228
Ships:
NOAA Ronald H
Brown
José Olaya
Land sites:
Iquique
Paposo
Models in VOCALS
RAMS
AGCM
OGCM
ROMS
Trajectory
Models
Large Eddy Simulation
Cloud Resolving Models
PreVOCA (VOCALS Model Assessment)
• GOAL: To critically assess the ability of
global/regional models (atmospheric, chemical
transport…) to predict/ simulate the VOCALS region
• WHY? Learn about model forecast support for REx;
compare model ability to represent VOCALS region;
compare with observations
• WHAT? Hindcasts for October 2006
• WHEN? In progress
• NOT: An intercomparison; participants use their
forecast/analysis
PreVOCA Model Simulations submitted
Model
Vertical
Levels
Horizontal
Resolution [km]
(inner domain)
COAMPS
42
81 (27)
COLA RSM
28
50
IPRC Reg_CM (IRAM)
28
~25
PNNL (WRF-Chem)
44
45 (15)
UCLA (WRF)
34
45 (15)
U. Chile (WRF)
43
45
ECMWF oper. 3-12h forecast
91
~25
ECMWF 5-day forecast
91
~40
ECMWF coupled fcst ensemble
62
~125
GMAO GEOS-5 DAS
72
~56
NCEP oper. 12-36h forecast
64
~38
UKMO oper. 12-36h forecast
50
~40
LMDZ
38
50
Low Cloud Fraction
Liquid Water Path (g m-2)
SW Downward Heat Flux (W m-2)
10m Winds (m s-1)
THE
VOCALS
STRATEGY
VOCALS Timeline
IUGG Perugia
Planning
Phase
REx and
Modeling
Workshops
2003
- 2006
Field site
surveys
2007
PI
Proposal
submission
VOCALS
REx
2008
VOCALS
Conference
2009
2010
Field and modeling
synthesis/analysis
Mean SST departure from zonal mean
GFDL
Clouds in
climate
models
- change in low
cloud amount for
2CO2
CCM
model number
from Stephens (2005)
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)
Prec
• These errors adversely affect the
skill of CFS climate forecasts (ENSO).
SST
What model developments are
required to alleviate these
errors?
CLD
source: IPCC 2007
ISCCP inferred St/Sc amount
Aerosol, cloud, drizzle and POCs
SST anomaly
from zonal mean
ERBE net cloud
forcing
Mesoscale ocean eddies
Height
SST
Eddies impact SST and can be observed using altimetry
courtesy Shang-Ping Xie, University of Hawaii