Inclusion of sea‐surface temperature variation in the U.S. Navy ensemble‐transform global ensemble prediction system

Abstract

[1] The local ensemble transform (ET) analysis perturbation scheme is adapted to generate perturbations to both atmospheric variables and sea-surface temperature (SST). The adapted local ET scheme is used in conjunction with a prognostic model of SST diurnal variation and the Navy Operational Global Atmospheric Prediction System (NOGAPS) global spectral model to generate a medium-range forecast ensemble. When compared to a control ensemble, the new forecast ensemble with SST variation exhibits notable differences in various physical properties including the spatial patterns of surface fluxes, outgoing longwave radiation (OLR), cloud radiative forcing, near-surface air temperature and wind speed, and 24-h accumulated precipitation. The structure of the daily cycle of precipitation also is substantially changed, generally exhibiting a more realistic midday peak of precipitation. Diagnostics of ensemble performance indicate that the inclusion of SST variation is very favorable to forecasts in the Tropics. The forecast ensemble with SST variation outscores the control ensemble in the Tropics across a broad set of metrics and variables. The SST variation has much less impact in the Midlatitudes. Further comparison shows that SST diurnal variation and the SST analysis perturbations are each individually beneficial to the forecast from an overall standpoint. The SST analysis perturbations have broader benefit in the Tropics than the SST diurnal variation, and inclusion of the SST analysis perturbations together with the SST diurnal variation is essential to realize the greatest gains in forecast performance.

Impact of atmospheric convectively coupled equatorial Kelvin waves on upper ocean variability

“…This diurnal SST warming influences the distribution of tropical precipitation contributing to the coupled feedbacks between ocean and atmosphere that maintain the basic state, the timing of the seasonal cycle of SST, and the trade winds in the tropical Pacific [ Bernie et al , ]. The impact of the diurnal variability represented by a skin layer prognostic scheme [ Zeng and Beljaars , ] on the modeled tropical convection can be observed [ McLay et al , ]. Including the diurnal variability of SST in the global model ensembles improves the model precipitation pattern, diurnal variability of precipitation, and ensemble spread.…”

Progress and challenges in short- to medium-range coupled prediction

“…Further comparison shows that SST diurnal variation and the SST analysis perturbations are each individually beneficial to the forecast from an overall standpoint. The SST analysis perturbations have a broader benefit in the tropics than the SST diurnal variation, and inclusion of the SST analysis perturbations together with the SST diurnal variation is essential to realize the greatest gains in forecast performance (McLay et al 2012).…”

Statistical generation of SST perturbations with spatio‐temporally coherent growing patterns

“…McLay et al . () introduced SST perturbations to the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) medium‐range EPS in which the uncertainty of the analysed bulk (sub‐skin) SST is represented by initial SST perturbations generated by including SST in the state vector of their Ensemble Transform (ET) method, and the uncertainty associated with the diurnal variation of skin SST is taken into account by incorporating a skin‐layer SST scheme of Takaya et al . () into their atmospheric model which is run independently by each ensemble member.…”