NACLIM CT1/CT31st CT workshop
22-23 April 2013 Hamburg (DE)
Johann Jungclaus
NACLIM structure
WP1.1: Predictability of the North Atl./Arctic ocean surface state & key oceanic quantities
MPI-M (30 PM), NERSC (24 PM)
Objectives:• To assess, in a multi-model approach, the predictability of the North Atlantic/Arctic Ocean surface state and ofkey ocean parameters controlling it• To quantify the uncertainty in predictions of the near-future North Atlantic/Arctic Ocean surface state
Tools: CMIP5 climate change/dec. pred. simulations
WP1.1: Predictability of the North Atl./Arctic ocean surface state & key oceanic quantities:
DeliverablesD11.25) Multi-model assessment of the hindcast predictability of NA/Arctic ocean surface state: Assessment on the hindcast predictability of the North Atlantic/Arctic ocean surface state including SST, SSS and Arctic sea ice cover [month 24]
D11.36) Quantification of uncertainty in predictions of near-future NA/Arctic ocean surface state: Report on the quantification of the uncertainty in predictions of the near-future North Atlantic/Arctic ocean surface state including SST, SSS and Arctic sea ice cover [month 36]
D11.56) Multi-model assessment of hindcast predictability of key oceanic quantities controlling North Atlantic/Arctic ocean surface state. Assessment on the hindcast predictability of the key oceanic quantities controlling the North Atlantic/Arctic ocean surface state including SST, SSS and Arctic sea ice cover [month 44]
WP1.2: Predictability of the atmosphere related to the North Atlantic/Arctic ocean surface
state
UPMC (48 PM), UHAM (48), NERSC (18)
Objectives:• Identify the sea surface temperature (SST), surface salinity, and sea ice patterns that optimally influence the atmosphere in the North Atlantic/European sector on seasonal to decadal time scales and quantify their climatic impacts.
• Assess the ability of climate models to reproduce these impacts, identify their potential predictability, and use observations to downscale the model predictions from global to local scales.
• Quantify the impact of Arctic changes on polar meso-cyclone activity.
Tools: THOR Adjoint Assimilation system, observational data sets, NACLIM obs., reanalysis products, atmosphere & climate model simulations
WP1.2: Predictability of the atmosphere related to the North Atlantic/Arctic ocean surface
state: DeliverablesD12.18) Report on the identification of NA/Arctic ocean surface state changes that most affect atmosphere: i.e. report on the influence of the ocean on the atmosphere, which processes and mechanisms are involved and which observations need to be taken to represent those processes best. [month 18]
D12.37) Assessment of the ability of climate models to reproduce response to boundary forcing: i.e. assessment of the ability of climate models used in CMIP5 to reproduce the response in the North Atlantic/European sector to changes in boundary forcing identified in the observations. [month 36]
D12.48) Report on the establishment of the climate impacts of surface state forcing: i.e. report on the establishment of the climate impacts of surface state forcing, including sea surface temperature and Arctic sea ice cover [month 44]
D12.49) Assessment on the link between weather regimes and Polar low developments in present &future climate: Assessment on the associations between dominant modes of variability (surface and atmospheric) and polar low developments in present climate as well as in future projections. [month 44]
WP1.3: Mechanisms of ocean surface state variability
UPMC (48 PM), UHAM (36)
Objektives:•Characterize the time-space sea surface variability in the Arctic/North Atlantic region.
• Identify the mechanisms underpinning this variability and link them to indices of variability of the ocean circulation.
• Provide information on the respective roles of the atmosphere and the ocean in this variability and identify feedback mechanisms between ocean anomalies and the overlaying atmosphere.
Tools: THOR Adjoint Assimilation System, observational data sets, NACLIM obs., reanalysis products, ocean & climate model simulations
WP1.3: Mechanisms of ocean surface state variability: Deliverables
D13.19) Description of the Arctic/North Atlantic ocean surface variability over the last decades: The report will describe the most important patterns of ocean surface (sea ice, SST) variability and regional indices of this variability as retrieved from observations and state-of-the-art models. The description will include assessment ofmodel skills against independent observations. [month 18]
D13.38) Report on identification of most relevant ocean mechanisms controlling the S2D variability of the Arctic/North Atlantic ocean surface state. The report will provide and discuss the statistical relationships between the surface state variability and the ocean variability based on a variety of model simulations and reanalyses and on available observations [month 36]
D13.50) Report on characterization of back-interaction of atmosphere on Arctic/North Atlantic ocean surface state. The report will provide a description of the key modes of atmospheric variability which influence the surface state changes and an evaluation of the underlying mechanisms. [month 44]
CT1/CT3 workshop
Each WP: Describe state of work/progressStatus and suitability of the toolsAny changes needed?
Cross WP / Cross-CT activitiesWPs 1.1, 1.2., 1.3, 3.2 overlaps/synergyNeed for coordination of joint model experiments?
Liaison with observations (CT2): Availability, NACLIM data portal;WP1.2: „joint model-observation data comparison“: UHAM/NERCSee deliverables D23XX
Liaison with WP4: Information/data exchange
Focus on CT1/CT3: Initialization, Focus on Arctic
Connections to other projects (e.g. RACE)
Plans for joint publications
CT1/CT3 workshop
Additions: data policy, select CT1 data manager
CT1/CT3 workshop
Additions:
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