The VAMOS Ocean-Cloud-Atmosphere- Land Study Robert Wood, University of Washington

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The VAMOS Ocean-Cloud-Atmosphere-

Land Study

Robert Wood, University of Washington

Mesoscale ocean eddies

Improving understanding, model simulations, and prediction of the

Southeast Pacific Climate

System

Field Program and Modeling

Regional pollution

Stratocumulus clouds

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

GFDL

Clouds in climate models

change in low cloud amount for

2

CO

2 model number from Stephens (2005)

CCM

source: IPCC 2007

Surface mooring with 1-year turn-around starting October 2000

SW and LW, precipitation. Two systems. Sampling: 1 minute and PACS cruise explorations of SEP stratus above 250 m. Sampling: 7.5 to 60 minutes

Telemetry: Hourly surface met, not on GTS.

POCs

WHOI stratus buoy

Drizzle is important over the SEP

Mesoscale variability in stratocumulus

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

DUST

SMELTERS

DMS

Global cloud droplet concentration

(MODIS, annual mean 2001-2004)

Cloud

Microphysical

Variability

MODIS

Cloud Droplet

Concentration

(SON 2001-2004)

Smelter locations

Comparison of in-situ and satellite microphysical properties

Aerosol speciation over the SEP

D=0.05 m m

Tomlinson et al. (2007)

Sulfuric Acid

D=0.2 m m

Ammonium

Bisulfate

50 100 150 200 250

Temperature [C]

Results indicate that submicron aerosol is predominantly composed of a mixture of sulfuric acid and ammonium bisulfate

Pockets of

Open Cells

(POCs)

200 km

POCs and drizzle

Importance of POCs

• Open cell coverage can be significant

• Strong synoptic and intraseasonal variability

• Association with drizzle

The POC “breeding grounds”

Sub-monthly variability

Aerosol, cloud, drizzle and POCs

POCs and Aerosols

• Strong reductions in accumulation mode aerosol concentration

• New nucleation

• Links between aerosol microphysics and cloud macrophysics?

POC formation

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

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.

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.

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 nearinertial 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.

VOCALS-REx Platforms

NSF C-130 NOAA Ronald H Brown

DoE ASP G-1 CIRPAS Twin Otter

NSF C-130 Payload

• Standard instruments : Microphysics, Turbulence,

Thermodynamics suite

• Remote sensing : Wyoming Cloud Radar

(zenith+nadir+slant), 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

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)

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)

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, O

3

, CO, SO

2

, DMS/organics

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

VOCALS-REx:

Flight-plan for C-130

Cross-section missions

VOCALS-REx:

Flight-plan for C-130

POC-Drift missions (+Lagrangian)

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

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)

What to compare

• 3-hourly data for October 2006 gridded to 1x1 o resolution over the VOCALS Region (0-40 o S, 60-

110 o W)

• 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,…)

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.

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.

Satellite issues

MODIS VIS/NIR Retrievals Problematic

0 50 100 150 200 250 300

0 g m 5 10 15 20 25 30 m m

1000 cm -3

Liquid water path Effective radius Cloud drop conc.

open cells closed cells

250 km

MODIS 10/19/2001; 10:00 Local (16:00 UTC)

CloudSat observes drizzle

VOCALS Timeline

Planning

Phase

REx and

Modeling

Workshops

IUGG Perugia

Field site surveys

VOCALS

REx

VOCALS

Conference

2003

- 2006

2007

PI

Proposal submission

2008 2009 2010

Field and modeling synthesis/analysis

THE

VOCALS

STRATEGY

IGBP’s Surface Ocean Lower

Atmosphere Study (SOLAS) has formally agreed to collaborate with

CLIVAR on VOCALS. http://www.uea.ac.uk/env/solas/

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.

CGCM Problems: NOAA CFS

Model

CFS

Errors

• The CFS model has significant errors in the SEP

Pre c

• 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).

SS

T

What model developments are required to alleviate these errors?

CLD

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 Hawai`i 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 Hawai`i, USA

Carlos Ereño , Int'l CLIVAR

José Meitín (ex officio), NCAR EOL/VAMOS

Office

SST Biases in Coupled Models

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

The effect of low clouds on climate

SST Stratus Cloud Amount (Warren)

Net CRF

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