S 1

Core Theme 1

Predictability of core ocean and atmosphere quantities

UHAM, MPG, UPMC, GEOMAR, NERSC

S 2

WP1.1

Predictability of sea surface temperature and sea ice in Nordic/Barents Seas (talk by H. Langehaug)

Predictability of North Atlantic sea surface salinity using multi-model hindcast simulations and observational-based dataset (talk K. Lohmann)

Deliverable D25 (M24): Multi-model assessment of the hindcast predictability of the North Atlantic/Arctic ocean surface state (Y. Gao)

Work planned for third year: Complete Langehaug et al. manuscript

• Atmospheric response to future Arctic sea ice (dedicated model experiments)

Deliverable D36 (M36): Quantification of uncertainty in predictions of near-future North Atlantic / Arctic Ocean surface state)

Task 1.1.1: Quantify hindcast predictability and uncertainties in near-future predictions of the North Atlantic/Arctic ocean surface state (MPG, NERSC)

S 3

WP1.1

• Relation between Arctic sea ice decline and ice export through Fram Strait (Langehaug et al., 2013) as well as on poleward ocean heat transport and related Arctic sea ice changes (Sandø et al., 2014)

• Collaboration with WP4.1 combining marine biogeochemistry observations and physical model output to investigate subdecadal variability and

potential for predictability of the Icelandic shelf ecosystem Work planned for 3rd project year:• Complete analysis of mechanism underlying predictability of mid-1990s

weakening of subpolar gyre as well as the manuscript (Lohmann and Matei, to be submitted to Climate Dynamics)

• Assess heat and volume transports over GSR from CMIP5 historical and compare with CT2

Deliverable D56 (M44): Multi-model assessment of the hindcast predictability of the key oceanic quantities controlling the North

Atlantic/Arctic ocean surface state

Task 1.1.2 : Quantify hindcast predictability and uncertainties in near-future predictions of key oceanic quantities controlling the North Atlantic /Arctic ocean surface state (MPG, NERSC)

S 4

WP1.2 Task 1.2.1 Identification of the atmospheric response to ocean surface state changes (UPMC, NERSC)

Sea ice concentration•Impact of winter-spring Arctic SIC variability (Frankignoul et al. JCLI 2014)•Impact of fall SIC variability in the Barents-Kara Seas on the NAO•(Garcia-Serrano et al., submitted). •SIC impact in other seasons under investigationSnow cover: Impact under investigation

Completed manuscript on review of Arctic sea ice and Eurasian Climate (Gao et al., 2014)• Autumn-winter atmospheric response to the projected autumn Arctic sea- ice free conditions and its detectability (Suo et al., 2014, Submitted)Planned:• Assess the air-sea coupling effect on the atmospheric response to projected Arctic sea ice• Assess the atmospheric response to changed Arctic sea ice: multi-model comparison

S 5

WP1.2 Task 1.2.1 Identification of the atmospheric response to ocean surface state changes (UHAM)

The CESAM model is used to identify sensitivities of predictable elements over northern Europe, such as air temperature or precipitation, on parameters in the North Atlantic and the Arctic, such as SST, sea surface salinity or sea ice concentration (Talk A. Vlasenko)

• A cost functional for measuring the averaged atmospheric near-land temperature has been defined, which reduces the numerical error related to differentiation in discrete Fourier space.• Development of a set of filters for removing numerical noise appearing at the coupling stage in the adjoint model• The sensitivity of mean near-land temperature in Europe to SST was estimated.

S 6

WP1.2 Task 1.2.2: Attribution and assessment of the boundary forced changes (UPMC, NERSC)

Mechanisms and sensitivities of the SST and sea ice impacts

LMDZ response to AMO-like AMOC footprint in IPSL-CM5-LR (Gastineau et al., in preparation)

NCAR ¼° CAM5 cold season response to meridional shifts of the subarctic front (NSF funding) (Smirnov et al, submitted)

Response of Speedo to AMOC SST and sea ice footprint (Gastineau, in preparation)

Role of stratosphere-troposphere coupling under study

Transient atmospheric response to boundary forcingSee Smirnov et al.

Deliverable D48 (M44): Report on the establisment of theclimate impacts of surface state forcing

Deliverable D37 (M36): Assessment of the ability of climate models to reproduce response to boundary forcing

S 7

WP1.2 Task 1.2.2: Attribution and assessment of the boundary forced changes (UHAM)

• The EU FP7 THOR adjoint assimilation system will be used to identify optimal SST or freshwater perturbation patterns that can lead to maximum impact on the atmosphere

• The mechanism by which SST anomalies impact the atmosphere will be investigated by tracing the sensitivities of air temperature over Europe to SST in the adjoint model. I. e. relation of sensitivities to SST to sensitivities to sensible and latent heat flux, etc.

S 8

WP1.2 Task 1.2.3: Application to climate model predictions (UPMC, NERSC)

Representation of the observed surface state impact

AMO impact and link to AMOC in control simulationsCompleted for IPSL-CM5-LR (Gastineau et al. 2013) and CCSM3 (Frankignoul et al. 2013), in preparation for CCSM4 (Frankignoul et al.) and IPSL-CM5-MR (Wen et al.), planned for CESM1 and FLOR (GFDL ) in year 3AMO impact and link to AMOC in historical simulationsMight be investigated in year 3SIC and snow influence in CMIP5 climate modelsUnder investigation, should be completed in year 3

Deliverable D37 (M36): Assessment of the ability of climate models to reproduce response to boundary forcing

S 9

WP1.2 Task 1.2.4: Impact of Arctic changes on polar meso-cyclone activity (UPMC)

Polar Lows: Analyses of remote sensing data and atmosphere reanalyses covering the last decade: talk by M. Vicomte

Next steps:Analysis of coupled ocean-atmosphere simulations in order to check if similar signatures are found in modelsand better understand the mechanisms which explain these results.

Deliverable D49 (M44): Assessment on the link between weather regimes and Polar low developments in present &future climate

NACLIM 3rd annual meeting

Berlin, October 14-15, 2014

WP1.3 : Mechanisms of ocean state variability

UPMC-LOCEAN contribution

• Task 1.3.1 : Characterize the spatial patterns of the ocean surface state variability on seasonal to decadal time scales

• Task 1.3.2 : Link ocean surface state variability to key ocean quantities (D38, month 36)

• Task 1.3.3 : Impact of the atmosphere on the Arctic North Atlantic ocean surface changes (50, month 44)

• Task 1.3.1 : Characterize the spatial patterns of the ocean surface state variability on seasonal to decadal time scales (D19, month 18)

- Analyse of the sea ice concentration and thickness : modes of covariability, trends, seasonality… (Close et al., in prep.)

• Task 1.3.2 : Link ocean surface state variability to key ocean quantities (D38, month 36)- Winter sea ice variability in the Barents Sea : impact of the ocean and surface atmosphere (Herbaut

et al., in prep.)- Atlantic water transport to the Arctic : forcing, pathways and impact on the heat transport

(Herbaut et al., to be submitted)- AMO linked to AMOC and ocean dynamics in CCSM4 (Frankignoul et al. In preparation)- Origin of Atlantic water temperature anomalies in the Arctic Ocean and possible impact on the

sea ice (in progress)

Task 1.3.3 : Impact of the atmosphere on the Arctic North Atlantic ocean surface changes Impact of atmospheric variability on the sea ice interannual variability and trends (in progress)

Driving patterns of AMOC and AMO, and feedback processes established in IPSL-CM5-LR, IPSL- CM5-MR, CCSM3, CCSM4.

Driving pattern of Kuroshio variability and feedback investigated

UPMC-LOCEAN contribution

Deliverable D38 (M36): Identification of most relev. ocean mechanisms controlling variability of NA/Arctic ocean surface

FUTURE WORK

•Statistical relationships between the surface state changes that most influence the atmosphere on seasonal to decadal time scales (e.g adjoint sensitivities of air temperature to SST which exitst from WP 1.2.2) and ocean variability will be established both in the available observations and in hindcast ocean simulations•Contribution with patterns of adjoint sensitivities and forward perturbation experiments

•The influence of changes in the AMOC, the gyre circulation, the inflow of Atlantic and Pacific water to the Arctic, and the redistribution of heat and fresh water in the ocean surface layer will be established.

Needs to be established, CESAM will deliver “sensitivity maps”, but effect in the ocean needs to be investigated with higher-resolution ocean model (UHAM, UPMC)

Task 1.3.2 Link ocean surface state variability to key ocean quantities (UHAM, UPMC)

S 13

CT1

Plan a half-year meeting CT1/CT3 in springFocus on specific themes

Establish collaborative work and model experiments, e.g., on the response of the atmosphere to surface changes (e.g. sea-ice)

Inter-CT collaboration:CT1-CT4: support marine ecosystem studies

CT1-CT2: assessment of overflows in models and observations

The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement n.308299

NACLIM www.naclim.eu