Www.cmar.csiro.au/bluelink/ Building Bluelink Richard Matear, David Griffin, Peter Oke, Andreas Schiller et al. June 2007 CSIRO Marine and Atmospheric

www.cmar.csiro.au/bluelink/

Building Bluelink

Richard Matear, David Griffin, Peter Oke, Andreas Schiller et al.June 2007

CSIRO Marine and Atmospheric Research

Bluelink: a partnership between the

Bureau of Meteorology, CSIRO and

the Royal Australian Navy

Introduction

Bluelink: a partnership between the

Bureau of Meteorology, CSIRO and

the Royal Australian Navy

Talk Outline

•Ocean Forecasting Australia Model, OFAM

•Bluelink Ocean Data Assimilation System, BODAS

•Bluelink ReANalysis, BRAN

•Bluelink High-Resolution Regional Analysis HRRA

•Bluelink biological modelling

Introduction

Ocean Forecasting Australia Model, OFAM

… every 10th grid point shown

Global configuration of MOM4

Eddy-resolving around Australia

10 m vertical resolution to 200 m, then coarser

Surface fluxes from ECMWF (for reanalyses)

Minimum resolution: ~100km

~10km resolution

Bluelink Ocean Data Assimilation System, BODAS

The spatial structure of the covariances are determined by the statistics of the free-running model.

Influence of sealevel obs at x

Ensemble OI: vertical projection of surface observations- similar to multiple linear regression

Cross-section of temperature

increments

Plan view of sea-level

increments

Cross-section of temperaturebkgnd (grey) &

analysis (black-colour)

Plan view of sea-level

increments

-> need both SST and SLA.

BLUElink Reanalyses

Ocean Reanalysis over last 15 years

(1992-2006) with focus on Asian-Australian

Region

Boundary conditions for nested models

Physical fields for biogeochemical applications

Evaluate strength/weaknesses of ocean monitoring and forecasting systems in Asian-Australian Region (part of GODAE Intercomparison Project)

Timor Sea Volume Transports

BRAN1.0 BRAN1.5 BRAN2.0


10/1992-12/2004 1/2003-6/2006 10/1992-12/2006

Assimilates along-track SLA, T(Z), S(z)

Assimilates along-track SLA, T(z), S(z), AMSRE - SST

Assimilates along-track SLA, T(z), S(z), AMSRE – SST or Rey 1/4o OISST

no rivers no rivers Seasonal climatological river fluxes

SSS restoring (30 days); SST restoring (30 days)

no SSS or SST restoring SSS restoring (30 days in deep water only); no SST restoring

ECMWF surface heat, freshwater and momentum fluxes

ECMWF surface heat, freshwater and momentum fluxes

ECMWF surface heat and freshwater fluxes; and momentum fluxes from 10 m winds

3 day assimilation cycle 7 day assimilation cycle with 1 day nudging using 1 day relaxation

7 day assimilation cycle with 1 day nudging using 0.25 day relaxation

A few bugs No known bugs (yet) Fingers crossed



Warm bias No temperature bias

Noticeably discontinuous in time (jumpy, shocks etc)

Acceptably continuous (can track features easily)

SST errors ~ 2-3 degrees SST errors ~ 0.6-0.8 degrees

SLA errors ~ 15 cm SLA errors ~ 8 cm

Relocatable Ocean-Atmosphere Model, ROAM

•Automatic implementation via visual interface of hydrodynamic model (MECO) and atmospheric model (RAMS [CSU]) with minimum user input

•Forecasts of ocean and atmosphere state out to 3 days

•Ocean domains of scales down to 100 km x 100 km with resolution down to 2km

•Boundary Conditions:oLateral ocean boundary information from OFAMoLateral boundary information for atmosphere from LAPSoSurface atmospheric data for ocean from RAMS

1. Present-day climate: BRAN and/or Mk3 simulation (FY 2007/2008)2. Future scenarios: Mk3 or other IPCCC simulations (FY 2008/2009)

OFAM (~10km): Australian Region Responsibility: WAMSI Node 2 (CSIRO)

Mk3 or other (~100km): GlobalResponsibility: CSIRO

SHOC (~1km): SW-WA Resp.: WAMSI Node 1 (CSIRO)

Multiple Nesting down to sub-km scale



SHOC (~1km): GBR Resp.: MTSRF (AIMS, CSIRO)

ROMS (~1km): Ningaloo Resp.: WAMSI Node 2 (AIMS/UWA)

New Application: Downscaling of Climate Change in the Marine Environment (WAMSI + MTSRF)

•Focus on nutrient and carbon cycling in the upper ocean for multi-year simulations•Linked to carbon cycling in the ocean

ARBGC Model: Nitrogen Cycling in the Photic Zone

Figure adapted from Pearce & Griffiths 1991

Possible mechanisms of eddy formation and entrainment of shelf waters.

SeaWiFS with SSHA overlay

May 6th 2000

Testing the hypothesis in-situ - TIP2000 cruise

TIP2000 Cruise

QuickTime™ and a decompressor

are needed to see this picture.

ARBCG model: phytoplankton and SST

Observed annual mean Chlorophyll

1D assimilation

3-D assimilation

Biological data assimilation: model calibration

Delivering information on the past, present and future state of the ocean

• “Ocean Weather” maps providing daily forecasts and information on the open and coastal ocean up to 7 days in advance

Outputs: Operational meso-scale nowcasts and short-range forecasts of upper ocean temperature, salinity and current fields

• Integrated reanalyses of the ocean state over the last 15+ years. Public access for registered users: http://www.marine.csiro.au/dods/nph-dods/dods-data/bluelink (Marine Environment, Ecosystem, Coastal Management, Climate Research)

• BLUElink 2: Improving the current forecast system and moving inshore (wave forecasting)

• New and challenging application outside Bluelink: Downscaling of Climate Change in the Marine Environment

• New Funding for Integrated Marine Observing System (IMOS) - provides an avenue to expand ocean observations (eg. ARGO, Radar systems, Gliders, Moorings )

Summary (I)

Summary (II)

• Present focus on the physical model but desire to expand to biological models

• A BGC model has been coupled to BLUElink physical model

• Plan to calibrate biological model by assimilating ocean colour into 1D and 3D biological models

Future Needs

• Sustained biogeochemical observations to support BGC modelling and data assimilation

environmental management fisheries management carbon management

Thank you!

Bluelink ReANalysis, BRAN

Thank you


Ensemble OI … sequential assimilation technique



Assimilates observations of SLA, SST, in situ T and S



Assimilates observations of SLA, SST, in situ T and S

To constrain the model to match reality, then make a forecast


Multivariate assimilation system:

sea level obs correct h,T,S,U,V

Single point assimilation …

Free-running model:

HRRA - Gridded altimetry and SST,statistically projected to depth:

BRAN1.0:

BRAN1.5smoother, more realistic, no warm bias

BRAN1.5 cf HRRA – 2005

Surface Zooplankton

Mixed Layer Depth and Phytoplankton

Phytoplankton refects a balance between growth and grazing

Delivering information on the past, present and future state of the ocean

• “Ocean Weather” maps providing daily forecasts and information on the open and coastal ocean up to 7 days in advance

Outputs: Operational meso-scale nowcasts and short-range forecasts of upper ocean temperature, salinity and current fields

• Integrated reanalyses of the ocean state over the last 15+ years. Public access for registered users: http://www.marine.csiro.au/dods/nph-dods/dods-data/bluelink (Marine Environment, Ecosystem, Coastal Management, Climate Research)

• BLUElink 2: Improving the current forecast system and moving inshore (wave forecasting)

• New and challenging application outside Bluelink: Downscaling of Climate Change in the Marine Environment (MTSRF and WAMSI)

Summary (I)

Summary (II)

• BGC model simulations coupled to BLUElink physical model

• Data Assimilation into 1D and 3D biological model

• Sustained biogeochemical observations to support BGC modelling and assimilation

environmental management fisheries management carbon management

Thank you!

Documents

Www.cmar.csiro.au/bluelink/ Building Bluelink Richard Matear, David Griffin, Peter Oke, Andreas Schiller et al. June 2007 CSIRO Marine and Atmospheric