Coupled Data Assimilation and Ensemble Initialization with Application to Multiyear ENSO Prediction

• Published in: Journal of climate 2019-02, Vol.32 (4), p.997-1024
• Main Authors: O’Kane, Terence J., Sandery, Paul A., Monselesan, Didier P., Sakov, Pavel, Chamberlain, Matthew A., Matear, Richard J., Collier, Mark A., Squire, Dougal T., Stevens, Lauren
• Format: Article
• Language: English
• Subjects: Atmosphere; Atmospheric circulation; Atmospheric convection; Climate change; Climate models; Climate system; Communication; Convection; Data assimilation; Data collection; Data processing; El Nino; El Nino phenomena; El Nino-Southern Oscillation event; El Nino-Southern Oscillation event forecasting; Ensemble forecasting; Error analysis; Fisheries; General circulation models; Hadley circulation; Interpolation; Kalman filters; Mooring; Oceans; Perturbations; Predictions; Sea surface; Sea surface temperature; Southern Oscillation; Surface salinity; Surface temperature; Thermocline; Tropical atmosphere; Tropical circulation; Tropical climate; Tropical climates; Tropical convection; Variability; Vectors; XBTs
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-18-0189.1

We develop and compare variants of coupled data assimilation (DA) systems based on ensemble optimal interpolation (EnOI) and ensemble transform Kalman filter (ETKF) methods. The assimilation system is first tested on a small paradigm model of the coupled tropical–extratropical climate system, then implemented for a coupled general circulation model (GCM). Strongly coupledDAwas employed specifically to assess the impact of assimilating ocean observations [sea surface temperature (SST), sea surface height (SSH), and sea surface salinity (SSS), Argo, XBT, CTD, moorings] on the atmospheric state analysis update via the cross-domain error covariances from the coupled-model background ensemble. We examine the relationship between ensemble spread, analysis increments, and forecast skill in multiyear ENSO prediction experiments with a particular focus on the atmospheric response to tropical ocean perturbations. Initial forecast perturbations generated from bred vectors (BVs) project onto disturbances at and below the thermocline with similar structures to ETKF perturbations. BV error growth leads ENSO SST phasing by 6 months whereupon the dominant mechanism communicating tropical ocean variability to the extratropical atmosphere is via tropical convection modulating the Hadley circulation. We find that bred vectors specific to tropical Pacific thermocline variability were the most effective choices for ensemble initialization and ENSO forecasting.