Variability in the ocean - from modewater biogeochemistry to SST

transcript

Variability in the Variability in the ocean - from ocean - from modewater modewater

biogeochemistry to biogeochemistry to SSTSST

Holger BrixHolger Brix

UCLA, JIFRESSE and Dept. of UCLA, JIFRESSE and Dept. of Atmospheric and Oceanic Atmospheric and Oceanic

SciencesSciences

JPL, 16 September 2008JPL, 16 September 2008

AcknowledgementsAcknowledgements

Curtis Deutsch, UCLACurtis Deutsch, UCLA

Nicolas Gruber, ETH, ZNicolas Gruber, ETH, Zürichürich

Scott Doney, Ivan Lima, WHOIScott Doney, Ivan Lima, WHOI

Crews and scientists of NOAA, UH, Crews and scientists of NOAA, UH,

BBSR, and other research vesselsBBSR, and other research vessels

Dimitris Menemenlis, JPLDimitris Menemenlis, JPL

OutlineOutline Mode water biogeochemistryMode water biogeochemistry

Global Carbon Cycle PerturbationsGlobal Carbon Cycle Perturbations Carbon and the OceanCarbon and the Ocean Why mode waters (and what are they Why mode waters (and what are they anyway)?anyway)?

Mode water variability - time-Mode water variability - time-scales and placesscales and places

Modeling the gapsModeling the gaps Sea surface temperatures and Sea surface temperatures and heat flux variability in ECCO2 heat flux variability in ECCO2 and beyondand beyond

The Global Carbon The Global Carbon CycleCycle

Sarmiento & Gruber, 2002

deforestation

tropicsextra-tropics

2000-2006

Time (y)Le Quéré, unpublished; Canadell et al. 2007, PNAS

Perturbation of Global Carbon Budget (1850-2006)

deforestation

fossil fuel emissions 7.6

2000-2006

fossil fuel emissions

deforestation

2000-2006

deforestation

2000-2006

Time (y)

atmospheric CO2

Le Quéré, unpublished; Canadell et al. 2007, PNAS

atmospheric CO2

deforestation

Time (y)

2000-2006

Le Quéré, unpublished; Canadell et al. 2007, PNAS

atmospheric CO2

deforestation

2.22.8

2000-2006

Sea-air COSea-air CO22 Flux Flux

N. Gruber, 2002

The Biogeochemical loopThe Biogeochemical loop

Marine PhytoplanktonMarine Phytoplankton

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

From top left: Diatoms, Radiolaria, Dinoflagellateshttp://www.amonline.net.au/exhibitions/beyond/phytoplnkton/

N. Gruber, 2002

Production

Export

CO2Corg

Phytopl.

Zoopl.Bacteria

Respiration (Heterotrophic)

Photosynthesis “Net Primary Production (NPP)”

Export Production

Production, Respiration, Production, Respiration, ExportExport

Net Community Production:

NCP = NPP - Rh

N. Gruber, 2002

Production

Export(=NCP)

NPP-NCP-POC at HOTNPP-NCP-POC at HOT(Hawaii Ocean Time-Series)(Hawaii Ocean Time-Series)

Brix et al., 2006POC: Particulate Organic Carbon

Spatial patterns in ∆pCO2 due to biology and temperature are also mostly opposing each other!

Anthropogenic COAnthropogenic CO22

Gruber (2002)

The Ocean ConveyorThe Ocean Conveyor

Waters will move mostly along surfaces of constant density.

Surface density, isopycnal Surface density, isopycnal outcropsoutcrops

What Are Mode Waters?Definitions after Hanawa and Talley (2001)

Homogeneity of water properties (such as temperature, salinity, oxygen)

Thickening of isopycnal layer - substantial volume

At a single vertical profile, mode water appears as low vertical density gradient (pycnostad) between high gradients (seasonal and main pycnocline)

Mode water is found well beyond its outcropping areas as a result of advection

Formation or maintenance usually associated with wintertime convective mixing

Mode WatersExample: 18o Mode Water

Subtropical Mode Water (STMW) in the North Atlantic

Potential Temperature

Why are we interestedin Mode Waters?

Mode waters can take up anthropogenic CO2 and hide it from the atmosphere (buffer capacity)

After a time delay (years to decades) mode waters re-emerge at (possibly distant) regions

And where do we find them? In all ocean basins “Descending” on isopycnals from outcrop regions

Mode Waters

Talley, 1999

Intermediate Waters

Talley, 1999

LSWNPIW

U.S. JGOFS Time-series U.S. JGOFS Time-series SitesSites

DIC at BATS (Bermuda)DIC at BATS (Bermuda)

Bates et al., 2001

Chlorophyll in the Chlorophyll in the NAtl.NAtl.

Lévy, 2005; Palter et al., 2005

Apparent Oxygen Apparent Oxygen UtilizationUtilization

Figure prepared by Niki Gruber

AOU = OAOU = O2,SAT2,SAT - O - O22 (measure of respiration) (measure of respiration)

Johnson &Gruber, Prog. Oceanography, 2007

AOU = [O2sat] - [O2]

APPARENT

OXYGEN

UTILIZATION

AOU CHANGES 2003-1993

AOU AND DIC

CHANGES

2003-1993

Expected change from anthropogenic CO2: max 0-8 mol/kg

OO22 anomaly at HOT anomaly at HOT (Hawaii)(Hawaii)

Deutsch, 2006

Observed AOU Observed AOU differences North differences North

PacificPacific

Deutsch et al. (2006)

Case study ICase study IThe North The North PacificPacific

Modeled AOU differences Modeled AOU differences North PacificNorth Pacific

Surface COSurface CO22 Flux Flux VarianceVariance

Components of Components of VariabilityVariability

Changes in AOU can be decomposedinto components:

AOU = AOUbiol + AOUvent + AOUcirc

Using: Multiple simulations with climatological OUR (OUR = dAOU/dt) and/or preformed climatological AOU fields

Total Circulation

Ventilation

Biology

OO22 change, 1990’s-1980’s, change, 1990’s-1980’s, = 26.6= 26.6

Deutsch et al. (2006)Deutsch et al. (2006)

Origin of OOrigin of O22 anomalies anomalies1990s - 1980s1990s - 1980s

a a,b: ventilationc,d: circulation

a,d: decadal trendsb,c: interannual perturbations

Case study IICase study IIThe North The North AtlanticAtlantic

A16N Repeat A16N Repeat HydrographyHydrography

Johnson & Gruber, Prog. Oceanography, 2007

∆AOU: 2003 - 1993 Mean 40o-60oN

Apparent Oxygen Utilization (AOU):Apparent Oxygen Utilization (AOU):AOU = OAOU = O2,SAT2,SAT - O - O22 (measure of respiration) (measure of respiration)

Modeled AOU Modeled AOU (standard deviation)(standard deviation)

UCLA CCSM model runs

Changes in AOU can be decomposedinto components:

AOU = AOUbiol + AOUvent + AOUcirc

Using: A single simulation analyzing nutrient concentrations and the (de-)coupling of C and O2

Changes in AOU can be decomposed into components:

AOU = AOUbiol + AOUvent+AOUcirc

AOUbiol can be approximated using a constant stochiometic O2:PO4 ratio:

AOU = rO2:PO4 · PO4 + AOU*

AOU* can be analyzed using the (de-)coupling of C and O2

rO2:PO4·PO4

– Total

Biology

– Physics

Biology / Physics Correlation DIC-AOU

Modewater Modewater Observations and Observations and

ModelingModeling Mode and Intermediate Waters are Mode and Intermediate Waters are “hotspots” of oxygen, carbon and “hotspots” of oxygen, carbon and nutrient variability in mid-latitudesnutrient variability in mid-latitudes

Formation regions of these Mode Waters Formation regions of these Mode Waters also show substantial surface also show substantial surface variability variability

Analyses of components of Analyses of components of biogeochemical variability require biogeochemical variability require either:either: Multiple model simulations Multiple model simulations Multi-tracer correlationsMulti-tracer correlations

SST variability in SST variability in ECCO2 and beyond….ECCO2 and beyond….

QuickTime™ and aYUV420 codec decompressor

ECCO2 AVHRR-AMSRE ROMS model satellite data model

SST variability in SST variability in ECCO2 and beyond….ECCO2 and beyond….

Mixed layer heat budget Mixed layer heat budget governs SSTgoverns SST

This project will investigate the components of mixed layer heat budget and its associated errors as a function of region, spatial scale, and frequency.

Thank you!!!Thank you!!!

Variability in the ocean - from modewater biogeochemistry to SST

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