# Presentation: 344027

## 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

## Goal 1:

**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

## to 1:

**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

## Goal 1:

**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

**Notes:**
In future distinguish between
Issues in ocean circulation physics (PO)
b) Expertise of PO to address wider issues

## 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 

- Kleine Bildunterschrift

- Text

- J. Dengg

## 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

## THC evolution in greenhouse scenario:

-  large model dependence

- Latif et al. (2000)

- Latif (2002, pers. comm.)

- Ocean model
- responsible for
- difference?

## Labrador Sea convection may stop even in stable THC scenario

- U.Schweckendiek (2002, pers. comm.)

**Notes:**
In future distinguish between
Issues in ocean circulation physics (PO)
b) Expertise of PO to address wider issues

## 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

- Temperature from sediments and ice cores  (Rahmstorf, 2002)

- 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“

## - transport of radiatively active gases (CO2, methane) 

- 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..

**Notes:**
In future distinguish between
Issues in ocean circulation physics (PO)
b) Expertise of PO to address wider issues

## OCMIP-2: Anthropogenic CO2 Flux, Storage and Transport

- Large model dependence

## Resolution Dependence of Anthropogenic CO2 Flux

- (poster Biastoch et al.)

- 4/3° resolution

- 1/3° resolution

- December 1989, in mol/m∆/yr

## Simulated Surface Chlorophyll in an Eddy-resolving model

- A.Oschlies

## 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