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Decadal predictability of winter SST in the Nordic Seas and Barents Sea in three CMIP5 models NACLIM ANNUAL MEETING, OCTOBER 14, 2014 BERLIN H. R. Langehaug,

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Presentation on theme: "Decadal predictability of winter SST in the Nordic Seas and Barents Sea in three CMIP5 models NACLIM ANNUAL MEETING, OCTOBER 14, 2014 BERLIN H. R. Langehaug,"— Presentation transcript:

1 Decadal predictability of winter SST in the Nordic Seas and Barents Sea in three CMIP5 models NACLIM ANNUAL MEETING, OCTOBER 14, 2014 BERLIN H. R. Langehaug, K. Lohmann, T. Eldevik, D. Matei, Y. Gao

2 The research leading to these results has received funding from: RCN-EPOCASA Enhancing seasonal-to-decadal Prediction Of Climate for the North Atlantic Sector and Arctic EU-NACLIM North Atlantic climate

3 Main goal Assessment of decadal predictability wrt SST (winter)  What do we expect from the models in this particular region? 3 Nordic Seas Barents Sea Region of interest Map based on NASA Worldwind-globe The region of interest has not been investigated in detail before wrt hindcast prediction experiments in CMIP5 Atlantic domain

4 Outline ›Introduction of the three models ›How is the model initialized? ›What is the surface condition compared to HadISST? ›How well do the hindcasts reproduce the observed SST changes in the Atlantic domain? ›Hindcasts are compared with non-initialized runs and the persistence forecast ›Are there specific regions with high predictive skill compared to the rest of the region? 4 Nordic Seas Barents Sea Map based on NASA Worldwind-globe Atlantic domain

5 Variance in winter SST in the period 1961-2010 HadISST MPI-ESM-LR mean SST MPI-ESM-LR Anomaly initialization 3D assimilation of T & S from ocean reanalysis initialized every fifth year

6 Variance in winter SST in the period 1961-2010 HadISST CNRM-CM5 mean SST CNRM-CM5 Full-field initialization  Correct for the drift 3D assimilation of T & S from ocean reanalysis

7 Variance in winter SST in the period 1961-2010 HadISST IPSL-CM5 Anomaly initialization SST assimilation, where sea ice concentration is less than 50% mean SST

8 8 Assessment of decadal predictability wrt winter SST Time (years) after initialization Lead time = 1-3 yrs Persistence: HadISST is correlated with itself with a time lag of 1-3 yrs Hindcast CMIP5 model Non-initialized CMIP5 model hindcast non-initialized

9 99 MPI-ESM-LR CNRM-CM5 IPSL-CM5 hindcast non-initialized How well do the models reproduce the observed SST changes in the Atlantic domain?

10 . Significant correlation MPI-ESM-LR

11 . Significant correlation

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15 CNRM-CM5

16 . Significant correlation

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20 IPSL-CM5

21 . Significant correlation

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25 Summary ›Introduction of the three models: similarities/differences? ›How well do the hindcasts reproduce the observed SST changes? ›Local and remote influence on the prediction skill? 25 Barents Sea MPI-ESM-LR and CNRM-CM5 most similar to observations in terms of SST variance MPI-ESM-LR


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