170 likes | 292 Views
The AMOC in the Kiel Climate Model WP 3.1 Suitability of the ocean observation system components for initialization. PI: Mojib Latif With contribution from: Wonsun Park, Thomas Martin , Fritz Krüger , Jin Ba. NACLIM Kickoff Meeting 5- 9 November, 2012. Motivation.
E N D
The AMOC in the Kiel Climate ModelWP 3.1 Suitability of the ocean observation system components for initialization PI: Mojib Latif With contribution from: Wonsun Park, Thomas Martin, Fritz Krüger, Jin Ba NACLIM Kickoff Meeting 5- 9 November, 2012
Motivation • Modes of variability / time scales and forcing • Dynamics of the multi-decadal mode • Predictability and initialization • Observation
AMOC: RAPID array (26.5°N) http://www.noc.soton.ac.uk Transport timeseries obtained from the first 3.5 years of observations at 26.5°N. The different curves show the MOC (red line) and its constituents, i.e. the transport through the Florida Straits (blue line), the Ekman transport (black line), and the density driven transport obtained from the mooring data (pink line). The transport units are Sverdrups (Sv, 1Sv = 106m3s-1). The mean and standard deviations for the different transports are 18.5 ±4.9Sv (MOC), 31.7 ±2.8Sv (Florida Straits), 3.5 ±3.4Sv (Ekman), and -16.6 ±3.2Sv (transport from mooring densities).
Natural variability in Kiel Climate Model(4200 year control simulation) Park and Latif 2012
Atlantic Meridional Overturning Circulation in Kiel Climate Model Park and Latif 2008
Three time scales: MCV (300-400a), QCV (~100a), MDV (~60a) Singular Spectrum Analysis (SSA) Park and Latif 2012
Atlantic Multidecadal Variability (~60a) SST: (POP1:42% PDV; POP2: 20% AMV) NH SST [°C] Principal Oscillation Pattern: … -> Preal -> -Pimag -> -Preal -> Pimag -> … Park and Latif 2010
Atlantic Multidecadal Variability (~60a) (regression patterns) SST SLP SSH Park and Latif 2010
Atlantic Multidecadal Variability (~60a) (regression patterns) SST SLP SSH Park and Latif 2010
AMV and AMOC Ba et al. submitted 60yr
Salinity leads the AMOC Ba et al. submitted
Restored Salinity: variability goes down Ba et al. submitted
State-of-the-art ocean observing system http://www.argo.ucsd.edu/About_Argo.html
Satellite data SMOS SSH -Trend SSH: Regional trends Derived from multi-missions Ssalto/Duacs Period:1992-2010 ICDC, ZMAW; Germany
Scientific work plan • Perfect model approach • Initialization: sampling according to existing ocean observing system components • Hindcasts with reduced set of initial conditions • Quantification contribution of different components of ocean observing system • Investigate potential observational needs to enhance decadal prediction • Comparison with other models (e.g. KCMwith MPI-ESM)