Use of ocean colour (GlobColour) data for operational oceanography Rosa Barciela, NCOF, Met Office Thanks to Matt Martin (Met Office) and John Hemmings (NOCS)

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Use of ocean colour (GlobColour) data for
operational oceanographyRosa Barciela, NCOF,
Met OfficeThanks to Matt Martin (Met Office) and
John Hemmings (NOCS)
rosa.barciela_at_metoffice.gov.uk
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The Talk

• Coupled physical-biogeochemical operational
  models
• Use of ocean colour data validation and data
  assimilation

- What are the aims? - What tools are we
using? - What have we developed so far? -
Assimilation of satellite-derived chlorophyll -
What will we be doing next? - What can we do as
champion user of GlobColour ?
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The Talk

• What are the aims?
• What tools are we using?
• What have we developed so far?
• Assimilation of satellite-derived chlorophyll
• What will we be doing next?
• What can we do as champion user of GlobColour?

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What are the aims?

• This work is part of the Centre for observation
  of Air-Sea Interactions and fluXes (CASIX), a UK
  project.
• The primary goal of CASIX is to quantify
  accurately the global air-sea fluxes of carbon
  dioxide.
• More accurate knowledge of the ocean biology is
  also required for
• water clarity predictions.
• improvement of light attenuation estimates SST,
  MLD, sea-ice.
• the Royal Navys ability to minimise risks to
  the maritime environment when deploying active
  sonar systems.
• supplying boundary conditions for the Shelf Seas
  system.

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The Talk

• What are the aims?
• What tools are we using?
• What have we developed so far?
• Assimilation of satellite-derived chlorophyll
• What will we be doing next?
• What can we do as champion user of GlobColour?

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What tools are we using?

• Coupling together two models

• FOAM
• Forecasting Ocean Assimilation Model

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Forecasting the open ocean the FOAM system
FOAM Forecasting Ocean Assimilation Model

• Operational real-time deep-ocean forecasting
  system
• Daily analyses and forecasts out to 6 days
• Low resolution global to high resolution nested
  configurations
• Relocatable system deployable in a few weeks
• Hindcast capability (back to 1997)
• Assimilates T and S profiles, SST, SSH, sea-ice
  concentration

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Operational configurations
36km (1/3º) North Atlantic and Arctic
12km (1/9º) North Atlantic
1º Global
6km (1/20º) North East Atlantic
36km (1/3º) Indian Ocean
12km (1/9º) Mediterranean
27km (1/4º) Antarctic

• All configurations run daily in the operational
  suite

12km (1/9º) Arabian Sea
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Hadley Centre Ocean Carbon Cycle model

• HadOCC is a NPZD (plus DIC and alkalinity)
  biogeochemical model used at the Hadley Centre
  for climate studies.
• HadOCC has been coupled (on-line) within the
  FOAM system.
• Initial tests have been run with 1 global, 1/3
  NA and Arctic and 1/9 NA FOAM configurations.

Palmer, J.R. Totterdell, I.J. (2001). Deep-Sea
Research I, 48, 1169-1198
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The Talk

• What are the aims?
• What tools are we using?
• What have we developed so far?
• Assimilation of satellite-derived chlorophyll
• What will we be doing next?
• What can we do as champion user of GlobColour?

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FOAM-HadOCC at 1º 1/3 º resolutions, Mar 27th
2003
pCO2 (ppm)
Chlorophyll (mg m-3)
1º Global
1/3º NA Arctic
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Validation of FOAM-HadOCC results
Validation of surface chlorophyll against SeaWiFS
data Daily mean North Atlantic fields for 20th
April 2003
1/3º North Atlantic Arctic
1º Global

1/9º North Atlantic
SeaWiFS 5-day composite
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The Talk

• What are the aims?
• What tools are we using?
• What have we developed so far?
• Assimilation of satellite-derived chlorophyll
• What will we be doing next?
• What can we do as champion user of GlobColour?

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Observations

• SeaWiFS data processed at the University of
  Plymouth derived chl (GSM)
• For each observation, an estimate of the error
  is also provided.
• Data assimilation schemes generally assume
  observations to have Gaussian error statistics.
  However, chlorophyll obs do not have this
  property.
• To get around this problem, the data is
  converted into observations of log10(Chl) which
  has been shown to then have approximately
  Gaussian behaviour.

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Chlorophyll data assimilation scheme

• A 2D analysis of log10(Chl) is performed using
  the same method as for SST (OI-type scheme). This
  uses the error statistics described in the
  previous slide. The output from this is a field
  of surface log10(Chl) increments.
• These can then be converted into surface
  phytoplankton increments using the models NChl
  ratio.
• In order to start the model from a balanced
  state, increments to the other ecosystem model
  variables are calculated using a scheme jointly
  developed by NOCS and Met Office (next slide).
• The analysed ecosystem model variables are then
  used directly as the starting conditions for the
  next model forecast.

3D analysis
Observations
?N
?alk
NChl
2D analysis of log(Chl)
2D analysis of P
Model forecast
?P
?Z
?DIC
?D
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Chlorophyll data assimilation scheme

• Two stage analysis scheme
• Model chl vs. satellite obs increments (ACS)
• Balancing increments to biogeochemical variables

• Increments to other pools (N, Z, D, DIC, Alk)
  depend on the likely contributions to
  phytoplankton error from errors in growth and loss

• Increments constrained to conserve total nitrogen
  carbon at each grid point (if sufficient
  nitrogen is available)
• Surface increments applied to mixed layer.
  Nutrient-profile correction increments below
  mixed layer.
• Hemmings, Barciela and Bell (2007). Accepted by
  JMS.

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3-D Twin experiments daily mean RMS errors in
the North Atlantic

Phytoplankton (mmol N/m3)
Zooplankton (mmol N/m3)
Total DIC (mmol C/m3)
Free run
BDA run
Control - truth
Detritus (mmol N/m3)
Nutrients (mmol N/m3)

• Air-sea exchange of CO2 significantly improved
  after assimilating ocean colour data

• Joint assimilation of Medspiration SST and ocean
  colour is desirable as carbon solubility is
  strongly dependent on temperature

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Real world experiments annual mean
Phytoplankton
Nutrients

No biological assimilation
With biological assimilation
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Real world experiments
Green no data assimilation Black with
physical data assimilation Red physical and
biological assimilation

Global average RMS (solid lines) and mean (dashed
lines) errors compared to the satellite
chlorophyll data.
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Inter-annual variability

• FOAM-HadOCC run from Jan 2003 to Jan 2005

2003
2003
37.5N 27.5 W
47.5N 27.5 W
Red Chlorophyll Blue Nutrient
Solid line physical da only Dashed line chl
physical da

• Chl da has large impact on chl and
• other biological compartments
• Chl da wipes out seasonal variability
• Smoothing in chl assimilation or variability not
  present in obs?

47.5N 27.5 W
2004
2004
37.5N 27.5 W
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Summary of ocean colour assimilation work

• An ocean colour data assimilation scheme has
  been designed and implemented within FOAM-HadOCC.
• Initial identical twin experiments seem to
  indicate that the scheme has potential.
• Real-world experiments show that the scheme is
  able to improve the chlorophyll is difficult to
  verify other biological fields but some work is
  underway in this area.
• Further work needed to explore the lack of
  seasonal variability in oligotrophic regions
• - smoothing of assimilation?
• - absence of variability in satellite data?

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The Talk

• What are the aims?
• What tools are we using?
• What have we developed so far?
• Assimilation of satellite-derived chlorophyll
• What will we be doing next?
• What can we do as champion user of GlobColour?

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What will be doing next?

• Operational
• pre-operational status from January 2008.
• Climate
• 10-year re-analysis of FOAM-HadOCC with/without
  chlorophyll and physical assimilation.
• biological assimilation scheme to be assessed
  for implementation in Hadley Centre Carbon Cycle
  Data Assimilation System (CCDAS) IPCC report

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The Talk

• What are the aims?
• What tools are we using?
• What have we developed so far?
• Assimilation of satellite-derived chlorophyll
• What will we be doing next?
• What can we do as champion user of GlobColour?

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What can we do as champion user of GlobColour?

• Met Office has developed the capability for the
  simulation of surface and deep ocean
  biogeochemistry in NRT
• unique operational system fully coupled
  (on-line!) to an ecosystem and carbon cycle model
• state of the art data assimilation scheme for
  ocean colour/derived chl
• hindcast capability back to 1997, which makes
  possible the quantification of impact of
  GlobColour products on variables of climate
  interest air-sea CO2 flux, carbon sequestration,
  acidity, PP, chl, etc.
• well positioned to add value to the merged data
  by ensuring suitability for use for both
  operational oceanography and climate research
• transitioning of RD product into operations
• However
• development work will be required
• funding

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Rosa Barcielarosa.barciela_at_metoffice.gov.uk
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Experiments identical twin set-up

• Start from a spun-up model state, then run the
  model forced by 6 hourly NWP fluxes for 1 year,
  with physical (T, S, SST) data assimilation. This
  is called the true run.
• Observations of Chl are taken from this true
  model state once a day.
• The ecosystem model variables are initialised
  using the biological fields from March 2003, with
  the physical fields taken from the true run.

• Starting from these new initial conditions, the
  model is run from April 2003 without (control)
  and with (assim) the Chl observations
  assimilated.

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Real world experiments on 1st July 2003

Log(chl) observations
Log(chl) from model with no biological
assimilation
Log(chl) from model with biological assimilation
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GlobCOLOUR/Ocean Colour Operational User
Requirements

• Specific requirements for GlobCOLOUR

• L2 Global Area Coverage of chl a plus quantified
  errors from
• merged and individual sensors

- Best possible accuracy essential to decrease
errors in derived chl below 35
- Spatial resolution 4 Km spacing (highest
resolution models have)
- Extensive product quality control include
quantified errors and quality flags
- Validation against in situ data and across
biogeochemical regions.
- Large biases in the merged product corrected by
in situ data
- Bias information from individual sensors
- Product format WMO GRIB or netCDF
- Delivery method FTP
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Assimilation of Derived Chlorophyll

Results from 3-D twin experiments
Phytoplankton background error before the first
analysis.
Phytoplankton analysis error after the first
analysis, with data everywhere.
Phytoplankton errors (mmolN/m3)
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GlobCOLOUR/Ocean ColourOperational User
Requirements
For operational purposes

• Long-term provision of quality-controlled
  products in a timely (within 1 day) manner.
• sustainability is key as lots of investment
  required to use the data
• stable formats and delivery (very) high
  availability and reliability

• Joint GlobCOLOUR/Medspiration products would be
  an advantage
• single file format
• single file delivery
• reduced data processing time
• diagnostic data set applied to GlobCOLOUR data

• NW European Shelf (NOOS) user requirements may
  need to be gathered
• (martin.holt_at_metoffice.gov.uk)

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Future Plans

To use GHRSST-PP data operationally from next
year (development work required)
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Future plans

• To transition the FOAM-HadOCC system into
  pre-operational state by 2008
• (assimilation of ocean colour
  products)