Title: An evaluation of experimental decadal predictions using CCSM4

Abstract

This study assesses retrospective decadal prediction skill of sea surface temperature (SST) variability in initialized climate prediction experiments with the Community Climate System Model version 4 (CCSM4). Ensemble forecasts initialized with two different historical ocean and sea-ice states are evaluated and compared to an ensemble of uninitialized coupled simulations. Both experiments are subject to identical twentieth century historical radiative forcings. Each forecast consists of a 10-member ensemble integrated over a 10-year period. One set of historical ocean and sea-ice conditions used for initialization comes from a forced ocean-ice simulation driven by the Coordinated Ocean-ice Reference Experiments interannually varying atmospheric dataset. Following the Coordinated Model Intercomparison Project version 5 (CMIP5) protocol, these forecasts are initialized every 5 years from 1961 to 1996, and every year from 2000 to 2006. A second set of initial conditions comes from historical ocean state estimates obtained through the assimilation of in-situ temperature and salinity data into the CCSM4 ocean model. These forecasts are only available over a limited subset of the CMIP5 recommended start dates. Both methods result in retrospective SST prediction skill over broad regions of the Indian Ocean, western Pacific Ocean and North Atlantic Ocean that are significantly better than reference skill levelsmore » from a spatio-temporal auto-regressive statistical model of SST. However the subpolar gyre region of the North Atlantic stands out as the only region where the CCSM4 initialized predictions outperform uninitialized simulations. Some features of the ocean state estimates used for initialization and their impact on the forecasts are discussed.« less

Authors:

Karspeck, A.; Yeager, S.; Danabasoglu, G.; Teng, H.

Publication Date:

2014-07-04

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); UT-Battelle LLC/ORNL, Oak Ridge, TN (Unted States)

Sponsoring Org.:

USDOE Office of Science (SC)

OSTI Identifier:

1565278

DOE Contract Number:  

AC05-00OR22725

Resource Type:

Journal Article

Journal Name:

Climate Dynamics

Additional Journal Information:

Journal Volume: 44; Journal Issue: 3-4; Journal ID: ISSN 0930-7575

Publisher:

Springer-Verlag

Country of Publication:

United States

Language:

English

Subject:

Meteorology & Atmospheric Sciences