MESOSCALE OCEAN PROCESSES IN RELATION TO OCEAN BIOGEOCHEMISTRY

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MESOSCALE OCEAN PROCESSES IN RELATION TO
OCEAN BIOGEOCHEMISTRY

• Jean-François MINSTER

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Impact of mesoscale activity on
primary production in the North Atlantic (V.
Garçon et al.)
Three 3-D numerical experiments a) without
mesoscale activity, b) with mesoscale activity
c) with mesoscale activity and assimilation of
combined T/P and ERS1 altimetric data.
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SeaWiFS Monthly data January 01 1998 January
31 1998 (G. Charrin et al.)
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Mean sea level anomaly (SLA) data January 1998
(21/01-31/01)
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Surface chlorophyll enrichment by Rossby waves
Modification of the isopycnals due to the passage
of waves ------gt more phytoplankton cells closer
to the surface (increase of the cells amount seen
by the captor and/or increase growth in the
enlightened (euphotic) zone)
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Eddy pumping mechanism Upwelling of nutrients
due to rising of the nitracline associated with
wave ----gt effect on the phytoplankton growth
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Advection of meridional gradients of
phytoplankton due to the geostrophic currents
associated with the baroclinic anomaly
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1-Chlorophylllight and shift of isopycnals
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2- Nutrient eddy pumping
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CONCLUSION
Center of the South Atlantic ocean increase of
0.25 mg/m3 to 0.38 mg/m3 (0.13 mg/m3 ?
54) West part of the South Atlantic ocean
0.38 to 0.51 mg/m3 (0.13 ? 34 ) East part
of the South Atlantic ocean 0.39 to 0.59 mg/m3
(0.20 ? 49 )
Modification of the isopycnals due to the passage
of Rossby waves induced a shift of the DCM
(increase of the cells amount seen by the captor)
could explain the ocean color anomalies
But The other processes could also act 2-
Nutrient eddy pumping 3- Advection of meridional
gradients of phytoplankton
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Phytoplankton and radiant heating in the
Equatorial Pacific

• variations of chlorophyll content
• modulation of the attenuation of solar radiation
• modification of stratification, heat budget, and
  surface heat fluxes

• availability of ocean color data
• estimation of the contribution of phytoplankton
  to radiant heating at intra-seasonal to
  inter-annual time-scales

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COASTAL OCEAN PHENOMENA

• Related to
• MESOSCALE OCEAN CURRENTS
• RIVER PLUMES
• NITRATE POLLUTION
• (F. Gohin, C. Labris, A Herbland)

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Thanks to SeaWiFS the seasonal cycle of the
chlorophyll production in the Bay of Biscay is
better known

• High production can occur as soon as
  mid-February outside of the river plumes in
  stratified areas (haline stratification)
• Peak in production occurs from mid-may to
  mid-June in the river plumes

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Late winter production in the Bay of
BiscayChlorophyll concentration (left) versus
Suspended Matters (right)
The bloom occurs in a clear and stratified area
River plumes are too turbid to sustain
significant production
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In mid-spring the production is enhanced in the
river plumes
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ZOOM in the Loire-Vilaine area
May 22
May 21
2001 May 23
May 24
in situ May 23
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Maximum chlorophyll concentration at sea surface
has been observed at the end of May 2001
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PEL 2000, AVRIL-MAI Surface
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PEL 2000, AVRIL-MAI Surface
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CONSTRAINING BIO-GEOCHEMICAL PARAMETERS

• Through assimilation
• of in situ
• and satellite data
• 1 Dimensional models
• Lagrangian models

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June 1998 mean surface Chlorophyll, Top  Model,
Bottom  SeaWiFS (Gunson et al.)
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Time series of chlorophyll following float 8
over the 270 days of the assimilation. Green
stars are the SeaWiFS observations (within 50 km
and 1 day of float) along with an error bar
(dotted line) of /- 0.1 mg Chl/m-3. Blue line
is the chlorophyll following the float and the
1-D model using the a priori parameters. Red
line is using parameters estimated from
observations taken only from float 8. Orange line
is using parameters estimated from observations
taken from float 8 and float 9.
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An ensemble Kalman filter for the assimilation
of ocean colour data into a biochemical model of
the North Atlantic
Lars-Jørgen Natvik
Nansen Environmental and Remote Sensing Center
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Motivation

• Data assimilation for linear models is well
  understood, but the data assimilation problem for
  nonlinear models is non-trivial.
• Basin scale coupled physical-biochemical models
  exist.
• Data assimilation for ocean circulation models
  well understood.
• Data assimilation for ocean biochemical models
• Parameter estimation is well understood
• Less focus on state estimation

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The photic zone biochemical model
Nitrate
Phytoplankton
Ammonium
Zooplankton
Bacteria
DON/DOC
PON/POC
Alkalinity
DIC
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Model grid (140 x 130 resolution)
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EnKF analysis at day 147
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Conclusion - hindcast experiment

• The analyzed distribution of phytoplankton is in
  better agreement with the observations than the
  forecast distribution.
• Analysis estimate is consistent with specified
  error statistics.
• The multivariate analysis also affects the
  unobserved compartments.
• The variance of all variables decrease
  significantly during the analysis.
• There is a considerable improvement from the
  analysis even using 60 observation errors.
• 60-80 ensemble members are required to have
  reasonably well resolved covariances within the
  defined radius of influence.

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The scheme of operational oceanography
SATELLITE OBSERVATION
JASON
MERCATOR
IN SITU OBSERVATION
CORIOLIS
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AVAILABILITY of weekly, real-time
Multiparameter products derived from
preoperationnal multisatellite sensors
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Operational Algae Monitoring (G. Evensen et al.)
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S P R I N G 2 0 0 2
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Algae Bloom Type Discrimination
High pigments and low reflection flagellate
blooms Low pigments and high reflection
Coccolito- phophorid bloom (Emiliania huxley and
Skeletonema )
mg.l-1
Data courtesy Remote Sensing Group, PML, UK /
NASA SeaWiFS Project
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CONCLUSION

• Well-established mesoscale phenomena with a net
  average effects
• Observing very high resolution features
  deciphered in numerical models
• Progress in assimilating biogeochemical
  parameters in coupled models but still a lot to
  be done
• Using preoperational high-resolution systems for
  ocean currents in support to biogeochemical
  modelling and forecast