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Ocean Initialization and Decadal Prediction Skill in the Community Earth System Model
Decadal Prediction Experiments
Gokhan Danabasoglu,
Steve Yeager, and Alicia KarspeckNational Center for Atmospheric Research, Boulder, CO
Outline
• Decadal Prediction (DP) simulations with the Community Climate System Model version 4 (CCSM4) for CMIP5 Initialization methodsForecast skill considering SSTs Impacts of a spurious, large-scale warm SST bias on the forecast skill
• New DP experiments with CESM1, using “improved” ocean initial conditions
• Summary
Initialization Methods for the CCSM4 DP Experiments Submitted to CMIP5
Hindcast Initialization (HDInit): • Ocean and sea-ice initial conditions are obtained from a hindcast simulation
forced with the Coordinated Ocean-ice Reference Experiments inter-annually varying atmospheric data sets for the 1948-2007 period (CORE-II)
• Ensembles for the DP experiments are generated by initializing the atmosphere and land from time staggered states from a 20th century (NoInit) integration
• DP experiments from 1961 to 2006, following the CMIP5 protocol• Initial start date gaps, i.e., 5-year vs. every year, were filled in later.
Initialization Methods for the CCSM4 DP Experiments Submitted to CMIP5
Data Assimilation Initialization (DAInit):• The Data Assimilation Research Testbed (DART) framework is utilized to
produce a 48-member ensemble of ocean states through assimilation of in-situ temperature and salinity observations
• Each ensemble member of the ocean is forced by a member of an independently generated atmospheric reanalysis, making this a loosely coupled framework
• A single atmospheric and land state taken from an AMIP-style, CAM4 simulation is used as the initial condition in DP experiments
• The sea-ice state is obtained from a CORE-II experiment where strong restoring to climatological salinity is used
• DP experiments from 1975 to 2006, following the CMIP5 protocol
Bias correction: Cross-validated method recommended for CMIP5 as outlined in CLIVAR (2011 ); with respect to HADISST
Karspeck et al. (2015)
HDInit forecasts
> the ‘no-skill’ statistical reference forecast at the 90 % confidence level
Average Anomaly Correlation Coefficients for SST
AND > the uninitialized run at a 90 % confidence
SST Hindcasts and Skill
HDInit and DAInitSolid black: HADISSTGray: NoInit (20C)
Gray dashed: no-skillGreen dashed: LIMGray-green: Noinit
Karspeck et al. (2015)
SST Forecasts from HDInit Relative to Observations
Karspeck et al. (2015)
Nino3 region
Equatorial Pacific SSTs and Zonal Wind in the Hindcast Simulations
Yeager et al. (2016, in preparation)
OBSCORE-II20CR
NCEPCORE-II20CRJRA55
Hindcast Initialization: • Ocean and sea-ice initial conditions are obtained from a hindcast simulation
forced with a MODIFIED Coordinated Ocean-ice Reference Experiments inter-annually varying atmospheric data sets for the 1948-2015 period. The modifications include:
20CRv2 winds in the tropics (20°S-20°N) for the 1948-2009 period, blended back to the NCEP winds between 20°-30°
JRA-55 winds in the tropics (20°S-20°N) for the 2010-2015 period, blended back to the NCEP winds between 20°-30°
Extended NCEP state with new precipitation data for the 2010-2015 period
New Suite of DP experiments with CESM1
• Inclusion of full biogeochemistry• New atmospheric model (CAM5)• New ocean initial conditions• Ensembles for the DP experiments are generated by round-off level
perturbations of the atmospheric temperature field from a 20th century integration
• DP experiments from 1961 to 2015, following the CMIP6 protocolALL DP EXPERIMENTS ARE COMPLETED RECENTLY
Data Assimilation Initialization: • 30-member, cross-component coupled data assimilation with DART• Assimilation is ongoing
Yeager et al. (2016, in preparation)
Forecast year 2
OBSOcean-ice hindcastDP
Significant improvement in short lead time skill by eliminating ΔSST trend in ocean initial conditions
Nino3 SST Predictions (CCSM4 DP vs CESM1 DP)
Summary• (Not surprisingly) DP skill can be increased using improved ocean
initial conditions in the CESM1 DP experiments
• Ocean states obtained via hindcast and reanalysis products are quite diverse. They are used for initializing the ocean components in DP experiments. Despite substantial differences in the ocean states, groups report increased skill in initialized DP experiments beyond those of uninitialized experiments, etc.
• What aspects / areas of initialization is important?