C A S I X Centre for observation of Air-Sea Interactions and fluXes (A NERC Centre of Excellence in Earth Observation) Nick Hardman-Mountford, Jim Aiken CASIX Project Office, Plymouth Marine Laboratory & the CASIX Team PML, SOC/SOES, POL, UEA, UWB, U.Ply, U.Leics, U.Edi, U.Read, Met Office

CASIX: Open-Ocean Modelling of Air-sea Carbon Dioxide Fluxes Example The model captures the spring bloom signature in the SeaWiFS chlorophyll data in early March 2000 The model can extrapolate under cloud and to other quantities not remotely observable HadOCC 4 compartment ecosystem model plus carbon cycling FOAM Operational ocean models using data assimilation to forecast 5 days ahead Driven by 6-hourly fluxes from Met Office Numerical Weather Prediction (NWP) system + FOAM

. Vertical structure, salinity CASIX purpose: to exploit EO data to derive air-sea interactions, focus on CO 2 fluxes NOAA-AVHRR Terra & Aqua MODIS AIRS Seastar SeaWiFS TOPEX-Poseidon, JASON, Altimeters ERS-1 & 2 SAR Quickscat-SeaWinds Envisat MERIS, AATSR ASAR, RA-2 SCIAMACHY ADEOS II NSCAT, SeaWinds OCTS, Polder To exploit these complex, diverse data & address the global problem of CO 2 fluxes, we need integration and modelling: 1-D & 3-D Ocean and Shelf circulation models with coupled biology, the C-cycle. Primary focus will be on N Atlantic & N W European Shelf Seas with the assimilation of EO data into models Atmospheric aerosols and gases, CO 2 Air-sea exchange Surface roughness/ Surface height Ocean colour Plankton Marine Biogeochemistry Physical Structure Temperature

. Vertical structure, salinity CASIX purpose: to exploit EO data to derive air-sea interactions, focus on CO 2 fluxes NOAA-AVHRR Terra & Aqua MODIS AIRS Seastar SeaWiFS TOPEX-Poseidon, JASON, Altimeters ERS-1 & 2 SAR Quickscat-SeaWinds Envisat MERIS, AATSR ASAR, RA-2 SCIAMACHY ADEOS II NSCAT, SeaWinds OCTS, Polder To exploit these complex, diverse data & address the global problem of CO 2 fluxes, we need integration and modelling: 1-D & 3-D Ocean and Shelf circulation models with coupled biology, the C-cycle. Primary focus will be on N Atlantic & N W European Shelf Seas with the assimilation of EO data into models Atmospheric aerosols and gases, CO 2 Air-sea exchange Surface roughness/ Surface height Ocean colour Plankton Marine Biogeochemistry Physical Structure Temperature

CASIX: Aims & Rationale CASIX Purpose  The purpose of CASIX is: to exploit new-generation Earth Observation (EO) data, to advance the science of air-sea interactions and reduce the errors in the prediction of environmental change. The primary goal is to quantify accurately the global air-sea fluxes of CO 2, other gases and particles, using state-of-the- art, error-budgeted models.  This is a crucial element in furthering understanding the role of the ocean carbon cycle in the global carbon cycle and their role in climate change.  To do this, novel EO data sources and algorithms will be developed and integrated with 3-D coupled physical-ecosystem ocean models to produce new error-quantified climatologies of air-sea gas fluxes. Geographical range  Primary focus will be the N Atlantic & NW European Shelf Seas (validation data available)  We will provide results for the global ocean with lower confidence  Integration of shelf & ocean is a unique feature of CASIX CASIX Time Frame  Quantification and understanding of air-sea CO 2 fluxes - 5 yrs  Quantification and understanding of air-sea fluxes for a wider range of climatically important gases - 10 yrs

4: Integration (climatology and analysis) Wider application CASIX science elements and their interaction 1 : Physical controls on surface exchange 2: Biogeochemistry and bio-optics 3a: 3-D N. Atlantic ocean model for CO 2 3b: 3-D N.W. European shelf model for CO 2 3c: Interface modelling Experiment with parameterisations and process models Define flux parameterisation using EO input Optimise input from EO colour CO 2 flux climatology In situ flux data Satellite data 10 year hind-cast of CO 2 fluxes

SST AATSR, NPOES MSG, AMSR, TMI Wave height JASON, ALT-2 Surface topography TOPEX, JASON, ALT-2 CASIX will exploit a wide array of data sources Surface roughness Sea-Winds, N-SCAT ASAR, Radarsat, AMSR, Windsat TOPEX, JASON, ALT-2 Wind stress Surface films Air-sea flux parameterisations Air-sea gas flux (CO 2 ) climatology Atmospheric CO 2 Atmos. Sensors Sciamachy, AIRS Ocean colour SeaWiFS, MERIS, MODIS, GLI Chlorophyll Primary production processes controlling upper ocean pCO 2 Ocean circulation models with bio-geo- chemistry and air-sea interface processes

Coupled modelling in CASIX Example The model captures the spring bloom signature in the SeaWiFS chlorophyll data in early March 2000 The model can extrapolate under cloud and to other quantities not remotely observable HadOCC Ecosystem Models Hadley Centre Ocean Carbon Cycle Model (HadOCC) PML European Regional Seas Model (ERSEM) Physical Met Office Operational Forecasting Ocean Assimilation Model (FOAM) POL Coastal Ocean Modelling System (POLCOMS) Regional Seas Model. + FOAM

FOAM/HadOCC model output & data assimilation FOAM/HadOCC output fields  Model fields that contribute to estimation of chlorophyll and primary production Ocean colour data assimilation  Weekly chlorophyll fields from FOAM/HadOCC with corresponding SeaWiFS images  The challenge is to assimilate ocean colour data to correct and nudge the model for operational forecasting Moving towards CO 2 fluxes  The revised output field improves estimates of derived fields (e.g. primary production, CO 2 flux)  This is the goal of CASIX!

Shelf Seas Modelling with POLCOMS & ERSEM POLCOMS 3-D shelf-sea physical circulation model (incl. waves, tides, turbulence, benthic resuspension, spm) 6km & 1.8km horizontal resolution ERSEM Complex ecosystem model (benthic & pelagic) Coupled to POLCOMS  3-D ecosystem fields Importance of Shelf Seas Continental shelf waters = 10% of the global ocean area 30% of global ocean production occurs in shelf seas making them a sink for atmospheric CO 2 Shelf seas can also be a source of CO 2 to the atmosphere – origin terrestrially exported carbon Net flux is unknown

New CASIX CO 2 flux climatologies CO 2 flux maps Global estimates of CO 2 flux for January (top) and July (bottom) 2002 Hindcast CO 2 fluxes 20 year hindcast estimates of CO 2 flux for global areas shown as coloured panels on map. Optimal interpolation techniques are used to combine parameters influencing air-sea gas exchange: wind speed and wind speed variability, sea surface temperature, sea surface salinity, sea surface roughness and the gradient of CO 2 partial pressure across the air-sea interface Work in Progress Jan Jul