Impacts of Climate on EcoSystems and Chemistry of the

Arctic Pacific Environment (ICESCAPE)

Kevin R. ArrigoStanford University

Background

Given ongoing changes in the Arctic Ocean…

How has primary production changed in recent years?

Changes in Arctic Productivity

• Between 1998 and 2009, annual primary production increased by 134 Tg C (statistically significant trend)

• A 38% increase over the last twelve years

• Unexpected given presumed nutrient limitation

• Largest increases on continental shelf

Changes in Arctic Productivity

Annual production highly correlated to open water area

Changes in Arctic Productivity

Increase in production also related to increase in open water season

Open water season has lengthened by an average of 3.8 days yr-1 over last 12 years

45 days longer in 2009 than in 1998

Da

ys o

pen

wat

er

>5

x 1

06 k

m2

Length of Open Water Season

Annual Primary Productivity (1998-2009)

Tg C yr-1

2726

109

50

23

29

123

40

Regional variability

Atlantic sectors most productive

• >50% of Arctic primary production

• Low sea ice cover

Percent yr-1 Change in Primary Productivity 1998-2009

Largest annual increase:East Siberian Sea

Smallest:Greenland Sea

Significant values in white

4.410

2.3

4.7

3.8

0.2

-0.3

4.8

Changes in Arctic Productivity

What is responsible for this increase?

• Lower ice cover and longer growing seasons play a role

• Increased nutrient supply also must be important- Greater shelf-break upwelling as sea ice retreats?- Increased eddy activity?- Intensified advection of nutrients from Bering Strait?

ICESCAPE

Central science question:

What is the impact of climate change (natural and anthropogenic) on the biogeochemistry and ecology of the Chukchi and Beaufort seas?

ICESCAPE

ICESCAPE

ICESCAPE

ICESCAPE

ICESCAPE

When?June 15 - July 21, 2010 & September 2011

Where?Start in Dutch Harbor, AK Cruise to Bering StraitBeaufort/Chukchi Sea

- Continental shelf- Canada Basin

Sea ice samplingBack through Bering StraitEnd In Seward, AK

ICESCAPE

Physical Oceanography:

Bob Pickart – XBTs, ADCP, eddies

Jim Swift – CTD, O2, salinity

Mike Steele – ARGO floats

Jinlun Zhang – 3D coupled physical-chemical-biological ice-ocean modeling

ICESCAPE

Eddy formation from dense water outflow

Mid-depth, cold-core eddy

We hope to conduct a We hope to conduct a three-dimensionalthree-dimensional survey of a cold- survey of a cold-core eddy, with the full suite of biological measurements. core eddy, with the full suite of biological measurements.

Pickart/Arrigo Pickart/Arrigo 2-D transect2-D transectthrough athrough acold-core eddycold-core eddyin 2002in 2002

Biological Oceanography:

Kevin Arrigo and Greg Mitchell – Primary production, microalgal abundance (ice and water column) and physiology

Sam Laney – Phytoplankton community composition

Eva Ortega-Retuerta - Bacterial production

Jinlun Zhang – 3D coupled physical-chemical-biological ice-ocean modeling

ICESCAPE

Combines flow cytometry, individual cell imaging, & automated image classification to assess the composition of microalgal assemblages.

Use Imaging FlowCytobot technology to assess spatial & vertical variability in Arctic algal assemblages.

Uses a computer & classifier algorithm to sort images by “taxon”

Instrument images ~500 cells per mL in ~ 4 mins.

& ~25 other categories currently…

Chaetoceros CylindrothecaCeratium

Monitoring Climate-Driven Changes in Arctic Algal Assemblages

PIs: Sam Laney & Heidi Sosik

Biology Dept., Woods Hole Oceanographic Institution

Quantifies cells ml-1 of different algal taxa

Olson et al. 2003; Olson & Sosik 2007; Sosik & Olson 2007

Chemical Oceanography:

Nick Bates – Carbon cycle measurements (e.g. DIC, alkalinity)

Jim Swift – Nutrients (e.g. NO3, NO2, NH4, PO4 , SiO3), O2, salinity

Jinlun Zhang – 3D coupled physical-chemical-biological ice-ocean modeling

ICESCAPE

STS/ODF will collect water samples from a 12-place rosette with 30-liter bottles. Rosette will be outfitted with: - SeaBird 911+ CTD w/ dual C/T sensor - Oxygen sensor, - Flourometer - Tranmissometer - CDOM fluorometer

On-board seawater analysis equipment will include: - Salinometers - Oxygen autotitration rig - 5-channel nutrient autoanalyzer (NO3, NO2, NH4, PO4, and SiO3).

Optical Oceanography:

Stan Hooker and Greg Mitchell – Spectral Lu, Ed, AOPs, IOPs

Rick Reynolds and Dariusz Stramski – Particle size distribution, bb, volume scattering, SPM

Atsushi Matsuoka – aCDOM

Robert Frouin – Atmospheric correction algorithm

ICESCAPE

(Lwn 443 > Lwn490 > Lwn510) / Lwn555

1 100.01

0.1

1

10

100SO non-SPGOC4v4SPGANTv4SO SPGSO SPG HPLC

Mitchell Group

In polar regions, standard NASA algorithms based on low latitude data underestimate Chl a (Mitchell 1992, Arrigo et al. 1998).

Will collect data to determine relationships between reflectance, Chl a and IOPs.

10-1 100 101

10-2

10-1

100

CalCOFISouthern Ocean Bricaud et al. [1998]

Chl-a [mg m-3]

A BSouthern Ocean 0.041 0.927CalCOFI 0.076 0.690Bricaud et al. [1998] 0.052 0.635

ap(440)=A*chlaB

10-1 100 101

10-2

10-1

100

CalCOFISouthern Ocean Bricaud et al. [1998]

Chl-a [mg m-3]

A BSouthern Ocean 0.041 0.927CalCOFI 0.076 0.690Bricaud et al. [1998] 0.052 0.635

ap(440)=A*chlaB

Make detailed measurements of ap, ad, CDOM and backscatter to better understand Arctic Ocean bio-optical properties to

Improve Chl a and productivity algorithms required for ecological modeling.

Southern Ocean

Chl

a (

mg

m-3)

High latitudes are unique

Inversion of the bio-optical properties in Mackenzie Bay, Beaufort Sea using MODIS-Aqua data of 7/6/2008 and QAAv5 algorithm of Lee et al. A. aph = phytoplankton absorptionB. adg = CDOM + detritusC. bbp = particle backscatter.

Will determine details of absorption and backscattering to improve algorithms and retrievals for key biogeochemical properties

Will provide near-real time delivery of satellite imagery to the ship for cruise planning.

aph440 adg440 bbp4400000

A B C

Mitchell Group

Improving Existing Satellite Color Observations of the Chukchi and Beaufort Seas for Biogeochemical Modeling

PI: Robert Frouin, SIO/UCSD; Co-I: P.-Y. Deschamps, LOA/U. Lille; Co-I: B. Pelletier, I3M/U. Montpellier

Theme

Improved atmospheric correction of satellite ocean-color imagery in the presence of snow/ice and clouds.

Objective

Generate, for the Chukchi and Beaufort seas, a daily time series of satellite-derived marine reflectance and chlorophyll concentration at 4.63 km resolution.

Approach

- Use of multiple ocean-color sensors (MERIS, SeaWiFS, MODIS).

- Use of appropriate atmospheric correction algorithm (POLYMER).

- Reconstruction of missing data.

MERIS image of the Chukchi Sea showing that water reflectance is correctly retrieved by the POLYMER algorithm, but not by the MEGS algorithm in the presence of a large semi-transparent cloud.

Sea Ice:

Don Perovich – Concentration, thickness, salinity, snow cover, optical properties

Kevin Arrigo – Primary production, microalgal abundance, and physiology

Karen Frey – CDOM, DOC, O2 isotopes

Jinlun Zhang – 3D coupled physical-chemical-biological ice-ocean modeling

ICESCAPE

Planktonic Ecosystem Response to Changing Sea Ice and Upper Ocean Physics in the Chukchi and Beaufort Seas: Modeling, Satellite and In Situ Observations

Jinlun Zhang, Carin Ashjian,

Robert Campbell, Victoria Hill,

Yvette Spitz, and Mike Steele

Biology/Ice/Ocean Modeling and Assimilation System (BIOMAS)

Synthesis and modeling of the integrated system of sea ice, the upper ocean, and the plankton ecosystem in the Chukchi and Beaufort seas

BIOMAS grid configurationand ecosystem model

Data Policy:

• Preliminary data will be staged at an ftp site at Stanfordhttp://ocean.stanford.edu/ICECAPS

• All data collected will be subject to the standard NASA Earth Science data policy (http://nasascience.nasa.gov/earth-science/earth-science-data-centers/data-and-information-policy/).

• Data collected are required to be submitted to the NASA SeaBASS archive (http://seabass.gsfc.nasa.gov/) within one year of collection.

ICESCAPE

ICESCAPE

Thank You