www.ncof.gov.uk use of ocean colour (globcolour) data for operational oceanography rosa barciela,...
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www.ncof.gov.uk
Use of ocean colour (GlobColour) data for operational oceanography
Rosa Barciela, NCOF, Met OfficeThanks to Matt Martin (Met Office) and John Hemmings (NOCS)
www.ncof.gov.uk
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 ?
www.ncof.gov.uk
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?
www.ncof.gov.uk
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 Navy’s ability to minimise risks to the maritime environment when deploying active sonar systems.
supplying boundary conditions for the Shelf Seas system.
www.ncof.gov.uk
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?
www.ncof.gov.uk
What tools are we using?
– FOAM
Forecasting Ocean Assimilation Model
– HadOCC Hadley Centre Ocean Carbon Cycle Model
• Coupling together two models …
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Forecasting the open ocean: the FOAM system
• 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
FOAM = Forecasting Ocean Assimilation Model
Real-time data
Obs QC
Analysis
Forecast to T+144
NWP 6 hourly fluxes
Automatic verification Product
delivery
Input boundary
data
Output boundary
data
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Operational configurations
12km (1/9º) Mediterranean
6km (1/20º) North East Atlantic
36km (1/3º) North Atlantic and Arctic
12km (1/9º) North Atlantic1º Global
36km (1/3º) Indian Ocean
12km (1/9º) Arabian Sea
27km (1/4º) Antarctic
• All configurations run daily in the operational suite
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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
www.ncof.gov.uk
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?
www.ncof.gov.uk
FOAM-HadOCC at 1º & 1/3 º resolutions, Mar 27th 2003
pCO2 (ppm) Chlorophyll (mg m-3)
1º Global
1/3º NA & Arctic
www.ncof.gov.uk
Validation of FOAM-HadOCC results
Validation of surface chlorophyll against SeaWiFS dataDaily mean North Atlantic fields for 20th April 2003
1º Global 1/3º North
Atlantic & Arctic
1/9º North Atlantic
SeaWiFS 5-day
composite
www.ncof.gov.uk
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?
www.ncof.gov.uk
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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3D analysis
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 model’s N:Chl 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.
2D analysis of log(Chl)
2D analysis of P
ΔN
ΔP
ΔZ
ΔD
Δalk
ΔDIC
Model forecast
N:Chl
Observations
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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 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.
Increments to other pools (N, Z, D, DIC, Alk) depend on the likely contributions to phytoplankton error from errors in growth and loss
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Phytoplankton (mmol N/m3) Zooplankton (mmol N/m3)
Detritus (mmol N/m3) Nutrients (mmol N/m3)
Control - truth Assimilation - truth
3-D Twin experiments: daily mean RMS errors in the North Atlantic
Total DIC (mmol C/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
Free run
BDA run
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Real world experiments – annual mean
No biological assimilation
With biological assimilation
Phytoplankton Nutrients
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Real world experiments
Global average RMS (solid lines) and mean (dashed lines) errors compared to the satellite chlorophyll data.
Green – no data assimilationBlack – with physical data assimilationRed – physical and biological assimilation
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FOAM-HadOCC run from Jan 2003 to Jan 2005
Inter-annual variability
2003
2004 2004
200337.5 N 27.5 W⁰ ⁰
37.5 N 27.5 W⁰ ⁰
47.5 N 27.5 W⁰ ⁰
47.5 N 27.5 W⁰ ⁰ 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?
Red: ChlorophyllBlue: Nutrient
Solid line: physical da onlyDashed line: chl + physical da
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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?
Summary of ocean colour assimilation work
www.ncof.gov.uk
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?
www.ncof.gov.uk
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
www.ncof.gov.uk
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?
www.ncof.gov.uk
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 R&D product into operations However:
development work will be required funding
www.ncof.gov.uk
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) from model with no biological assimilation
Log(chl) observations
Log(chl) from model withbiological 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%
- Extensive product quality control: include quantified errors and quality flags
- Validation against in situ data and across biogeochemical regions.
- Product format: WMO GRIB or netCDF
- Delivery method: FTP
- Large biases in the merged product corrected by in situ data
- Spatial resolution: 4 Km spacing (highest resolution models have)
- Bias information from individual sensors
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Phytoplankton background error before the first analysis.
Phytoplanktonanalysis error after the first analysis, with data everywhere.
Phytoplankton errors (mmolN/m3)
Assimilation of Derived ChlorophyllR
esu
lts fr
om 3
-D tw
in
exp
erim
ent
s
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GlobCOLOUR/Ocean ColourOperational User Requirements
• 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
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
• NW European Shelf (NOOS) user requirements may need to be gathered ([email protected])
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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)