Transcript (LANL) model

Biogeochemistry in the Los Alamos National Laboratory
(LANL) model
Clara Deal (UAF) and Scott Elliott (LANL)
Biogeochemistry: of or relating to the partitioning and cycling of chemical
elements and compounds between living and nonliving parts of an ecosystem
Our activities focus on marine organic C (i.e., primary production), and S (DMS).
Also N and Si cycling, methane, and carbonate system.
Influence of Sea Ice on Arctic Marine Sulfur Biogeochemistry
in the Community Climate System Model
DOE EPSCoR-State/National Laboratory Partnership Grant
PI: Clara Deal, Co-I: Meibing Jin
International Arctic Research Center (IARC), University of Alaska Fairbanks (UAF)
Scott Elliott, Elizabeth Hunke, Mathew Maltrud, Nicole Jeffery, and Adrian Turner
Coupled Ocean Sea Ice Modeling Group (COSIM), Los Alamos National Laboratory
Talk outline
Objectives
Motivation and background
1. food web - DMS interactions
2. importance of ice algae
3. 1-D ice-ocean ecosystem modeling
- map with sites
- findings
3-D Model results
1. primary production
2. DMS
3. impact of decreasing sea ice on biogeochemistry
Summary list of modeling activities
DOE EPSCoR Project Research Objectives
Overall: Improve the treatment of arctic marine
biogeochemistry in CCSM. Add sea ice algae and arctic
DMS production and related biogeochemistry in POP
coupled to CICE.
Specifically:
1)
Develop a state-of-the-art DMS ice-ocean ecosystem
model
2)
Assess and predict sea ice influences on DMS dynamics
DMS cycle is intimately linked to marine food web and plays important role in climate.
Radiative backscatter
Air
Phytoplankton
DMSP
Grazing
DMSO and
Other products
DMS
SO42lysis
or leakage
DMSP
(Dissolved)
bacteria
bacteria
bacteria
Demethylation/
demethiolation
Elimination
bacteria
Methanethiol
bacteria
Assimilation
Fecal or detrital
DMSP
Sinking/Export
Photolysis

Direct release
Grazer DMSP
Assimilated S
DMS (g)
Ventilation
Feedbacks?
?
Sea
h
SO2 &
CH3SO3H
“Sulfate”
Aerosol
CCN
Figure courtesy Ron Keine.
Organic sulfur
Dissolved and
Particulate
Why are sea ice algae important?
• important food source for benthic and
pelagic herbivores
• timing of ice algal bloom is more
important than the magnitude
• >50% primary production in central
Arctic Ocean (Gosselin et al. 1997)
• between 4 to 25% primary production
in arctic shelf seas (Legendre et al.
1992)
Schematic representation of seasonal cycle of marine production
Ice algal biomass is highest in the bottom 2-3 cm of arctic
FYI and MYI (Gradinger et al. 2009; and references therein),
where S compounds accumulate.
April through May, >90% ice algal
biomass (chlorophyll a) observed in
bottom of sea ice (3 cm layer)
(Shin et al., 2003).
Very high levels of total DMSP up
to 15 μM, were observed at Barrow,
Alaska (Uzuka et al., 2003).
1-D Physical ice-ocean Ecosystem model (PhEcoM) applied at:
land-fast ice zone, multi-year pack ice, and pack ice of SIZ.
Findings from 1-D modeling studies:
• suggest “seeding” of phytoplankton bloom by ice algae
(Jin, Deal, Wang, Alexander, Gradinger, et al. GRL 2007)
• shift in lower trophic level production and dominant
phytoplankton type in response to climate regime shift
(Jin, Deal, Wang, McRoy, JGR 2009)
• vertical mixing plays important role in determining
microalgal composition and DMS sea-to-air flux
(Jin, Deal, Wang, Tanaka, Ikeda, JGR 2006)
(Deal [Jodwalis], Benner, Eslinger, JGR 2000)
• major controls sea ice algal production
(Lee, Jin, Whitledge Polar Biol, 2010)
(Jin, Deal, Wang, Tanaka, Shin, Lee, Whitledge, Gradinger,
Annals Glaciol, 2006)
1-D DMS ice-ocean ecosystem (i.e., ice ecosystem-ocean ecosystem with DMS modules)
3-D Model Results
Simulated annual primary production within arctic sea ice (for 1992)
reproduces observed large-scale patterns and seasonality.
CICE with ice ecosystem (from PhEcoM):
(g C m-2)
Deal, Jin, Elliott, Hunke, Maltrud, and Jeffery (2010) Large-scale modeling of primary
production and ice algal biomass within arctic sea ice. J Geophys Res, minor rev. 2010.
High ice algal production in the Bering
Sea was due to high daily production
rates, while the large sea ice area in
the Canadian Archipelago/Baffin Bay
and, in particular, the Arctic Ocean
basins resulted in their considerable
contribution to primary production.
Model results show strong seasonality of ice algal bloom.
CICE with ice ecosystem (from PhEcoM):
Deal, Jin, Elliott, Hunke, Maltrud, and Jeffery (2010) Large-scale modeling of primary
production and ice algal biomass within arctic sea ice. J Geophys Res, minor rev. 2010.
DMS(P) production in bottom ice may add substantially to a maximum
of reduced S that dominates the marginal ice environment.
CICE with DMS ice ecosystem:
Baseline simulation DMS (log10
nM) injected into the ocean
product layer May 1992. Ice edges
are defined by the 15% contour
(white), and CICE thicknesses are
superimposed in meters (black).
S. Elliott, C. Deal, G. Humphries, E. Hunke, N. Jeffery, M. Jin, M. Levasseur, and J. Stefels, PanArctic simulation of coupled nutrient-sulfur cycling due to sea ice biology, in prep.
Modeled pan-Arctic annual primary production averaged over 1992-2007
in a) sea ice, and b) ocean upper 100m.
55-145 g C m-2 yr-1 observed Chukchi
shelf 2002-2004 (Lee et al. 2007)
Coupled CICE-POP with ice-ocean ecosystem (ocean ecosystem; Moore et al. 2004):
(g C m-2)
(g C m-2)
Jin, M., C. Deal, S. Lee, S. Elliott, E. Hunke, M. Maltrud and N. Jeffery. Modeling study of the Arctic sea ice and
ocean primary production and model validation in the western Arctic, Deep Sea Res Part-II (submitted).
Time series of modeled annual upper ocean 100m integrated primary
production within Arctic Circle compared to mean estimated using remotely
sensed Chl a and algorithm developed for the Arctic by Pabi et al. (2008).
Coupled CICE-POP with ice-ocean ecosystem:
Jin, M., C. Deal, S. Lee, S. Elliott, E. Hunke, M. Maltrud and N. Jeffery. Modeling study of the Arctic sea ice and
ocean primary production and model validation in the western Arctic, Deep Sea Res Part-II (submitted).
Modeled pan-Arctic annual primary production difference
(2007 minus 1992) in a) sea ice, and b) ocean upper 100m.
Coupled CICE-POP with ice-ocean ecosystem:
(g C m-2)
(g C m-2)
Jin, M., C. Deal, S. Lee, S. Elliott, E. Hunke, M. Maltrud and N. Jeffery. Modeling study of the Arctic sea ice and
ocean primary production and model validation in the western Arctic, Deep Sea Res Part-II (submitted).
Normalized time series of modeled sea ice primary production within
the Arctic Circle shows lack of correlation with ice area.
Coupled CICE-POP with ice-ocean ecosystem:
Jin, M., C. Deal, S. Lee, S. Elliott, E. Hunke, M. Maltrud and N. Jeffery. Modeling study of the Arctic sea ice and
ocean primary production and model validation in the western Arctic, Deep Sea Res Part-II (submitted).
Simulated surface seawater DMS concentrations, in general,
agree with observations; few nM under-ice, higher in SIZ, and
highest near ice edge.
Coupled CICE-POP with DMS ice-ocean ecosystem:
Summary of activities
Focus on marine organic C (i.e., primary production) and DMS cycle.
1-D DMS ice-ocean ecosystem modeling (i.e., ice ecosystem-ocean
ecosystem with ice DMS module and ocean DMS module)
Stand-alone CICE with DMS ice ecosystem modeling
Coupled CICE-POP DMS ice-ocean ecosystem modeling
A major challenge is the sparseness and heterogeneity of the available
biological and biogeochemical data for 3-D model initialization and
validation.
Thank you for your time and attention!
What is the impact of DMS on climate?
 Recent climate models (Gunson et al. 2006):
- 50% reduction of ocean DMS emission:
radiative forcing: +3 W/m2
air temperature: +1.6 °C
- doubling of ocean DMS emission:
radiative forcing: -2 W/m2
air temperature: -0.9 °C
 Use of a climate model to force ocean DMS model
in Barents Sea (Gabric et al. 2005):
- By the time of equivalent CO2 tripling (2080)
zonal annual DMS flux increase: >80%
zonal radiative forcing: -7.4 W/m2