Challenges in Post-WOCE Research and Meeting Goals

After WOCE what are the remaining challenges and how should we set about meeting them? Jürgen Willebrand, IfM Kiel Input appreciated from: G. Holloway, P. Killworth, W. Large J. Marotzke, T. McDougall, J. Sarmiento R. Schmitt, P. Rhines, C. Wunsch Thanks to A.Biastoch

WOCE Goals Goal 1: to develop models for predicting climate change, collect data necessary to test models Goal 2: to determine representativeness of WOCE data sets for long-term behavior of the ocean, and to find methods to determine long-term changes

WOCE Achievements (short version) to 1: - models greatly improved (but far from perfect) - WOCE data give unprecedented view of global ocean but important gaps in understanding remain - test of models against data usually qualitative to 2: - large variability on interannual/decadal time scales found - much progress with technologies to determine long-term changes

What else has changed since 1980 ? • Better understanding of • role of ocean circulation for climate • record of past changes • role of circulation for biogeochemistry / ecology • role of other parts of earth system for global change • global change has arrived

View of SurfaceTemperature Changes 1000 – 2100 • Past and projected surface temperature anomalies • Mann et al reconstruction • Instrumental record • IPCC scenarios • J. Gould

Goals for post - WOCE research Goal 1: to develop ocean models for simulating past and future changes in ocean circulation, climate and environment, collect data as necessary to test models Goal 2: to continuously and adequately observe the ocean on a global basis

Goal 1 specific objectives • 1. to understand ocean processes/mechanisms relevant • for ocean circulation variability at all time scales • (PO-community) • 2. describe and understand large-scale ocean variability • at all time scales, and its role for climate • (PO with climate and paleo communities) • 3. understand interaction of ocean circulation • with environmental changes • (PO with biogeochemical / ecological communities)

1. Understanding processes / mechanisms a) Mixing b) Effects of mesoscale eddies c) Interaction with topography d) improve air-sea fluxes e) is ocean in equilibrium with 20th century forcing? f) relation convection - sinking g) interaction w. sea-ice . . . z) Energy balance of circulation To be addressed by process experiments, theory, modeling ... Where applicable, ‚understanding‘ should eventually translate into physically-based parameterizations for models!

processes / mechanisms cont’d • a) Mixing • How is the mixing distributed in the ocean? • How can we find out? Consequences of spatial variations? • Dynamics and energetics (local/global) of mixing? • Under which conditions diffusivities for T/S are different? • - On what time scales mixing becomes important for • circulation changes? • Which mixing processes support the THC? • Where do they occur?

processes / mechanisms cont’d b) Effects of mesoscale eddies - eddy tracer transports (bolus transport, pv vs. layer thickness diffusion ...) local vs. non-local effects - momentum exchange with mean circulation - connection of lateral stirring with diapycnal mixing? - percentage of eddy energy used for diapycnal mixing - parameterizations of sub-mesoscale processes

processes / mechanisms cont’d • c) Interaction of circulation with topography • parameterizations of unresolved topography • barotropic recirculations • flow through straits • slope convection • ... Denmark Strait pot.density (R. Käse)

Overflow representation effects large-scale overturning J. Dengg Text Kleine Bildunterschrift

2. Describe/understand large-scale variability and ocean’s role in climate CLIVAR organization along time scales: Seasonal - Interannual: El Nino, Monsoon systems ... emphasis on predictability / prediction Decadal - centennial: - Subpolar/subtropical circ: response to atm. forcing patterns (e.g. NAO) - Cross-equatorial transports/cells, coupling w/ extratropics - thermohaline circulation ... Data from combination of observations, analysis of historical data sets, reconstructions from proxy- data (e.g. corals, tree rings, ..) Anthropogenic climate change: prediction + detection

THC evolution in greenhouse scenario: large model dependence Good argument for - modelers to improve their models - observers to start measuring THC change North Atlantic overturning in climate change simulations (IPCC 2001)

THC evolution in greenhouse scenario: large model dependence Latif et al. (2000) Ocean model responsible for difference? Latif (2002, pers. comm.)

Labrador Sea convection may stop even in stable THC scenario U.Schweckendiek (2002, pers. comm.)

Role of ocean for climate variability Tropical oceans: - dominant influence on seasonal/interannual var. (e.g. El Nino) - strong influence also on decadal extratropical var. (e.g. NAO)? Mid-latitude oceans: - very little influence on interannual-decadal var. (except through heat storage) - some influence on interdecadal var. ? Recently: - role of ocean heat transport challenged by atmospheric modelers but: - thermohaline circ. dominant for centennial/millenial var. ?

Centennial-millenial climate variability during last glacial Millenial time scales (not part of CLIVAR) allow view of different dynamical regimes opens possibility to obtain long-term perspective so far most explanations involve thermohaline circulation changes „Physics of most paleo-models is unimpressing“ Temperature from sediments and ice cores (Rahmstorf, 2002)

3. Interaction ocean circulation – environment Understand role of ocean circulation for - transport of radiatively active gases (CO2, methane) - natural carbon cycle and anthrop. perturbation - ocean ecosystem/biological pump - natural variability and response to greenhouse warming joint observations where possible forward/inverse modeling of joint system Help interpreting paleo-record by modeling paleo-proxies (e.g. 13C, 18O), sedimentation rates..

OCMIP-2: Anthropogenic CO2 Flux, Storage and Transport Large model dependence

Resolution Dependence of Anthropogenic CO2 Flux 4/3° resolution 1/3° resolution December 1989, in mol/m∆/yr (poster Biastoch et al.)

Simulated Surface Chlorophyll in an Eddy-resolving model A.Oschlies

SeaWiFS surface chlorphyll 10S-12S during 1998 Rossby wave propagation(Kawamiya and Oschlies, 2002) Can we learn from biol. distributions about ocean physics? A.Oschlies

Ocean model development - parameterization of subgrid-scale processes - models should be sufficiently adiabatic - what resolution is sufficient for a) convergence of coupled climate integrations? b) convergence of eddy energy / WBC structure? c) convergence of biological production? d) convergence of eddy stirring effects? e) numerical convergence? - model errors should be quantified - model hierarchies helpful - same circulation models for physical oceanography, biogeochemical and paleo applications - software engineering

Observing System(s) - design: follows from objectives and techn./econ. possibilities climate prediction climate change detection ocean prediction (e.g. ecosystem) understanding ocean variability applications .. - should evolve with technological advances - should stay close to assimilation activities

Combining observations and models (assimilation) - obtain global state estimation on ongoing basis - develop robust methods that work a) with non-Gaussian statistics b) with chaotic models - include biogeochemical state variables Proof of the (assimilation) pudding is in the eating!

The End

Challenges in Post-WOCE Research and Meeting Goals