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Niklas Schneider, Tim Barnett, Mojib Latif, and Timothy Stockdale

Abstract

The physics of the Indo–Pacific warm pool are investigated using a coupled ocean atmosphere general circulation model. The model, developed at the Max-Planck-Institut fair Meteorologic, Hamburg, does not employ a flux correction and is used with atmospheres at T42 and T21 resolution. The simulations are compared with observations, and the model's mean and seasonal heat budgets and physics in the Indo–Pacific warm pool region are explored for the T42 resolution run.

Despite the simulation of a split intertropical convergence zone, and of a cold tongue that extends too far to the west, simulated warm pool temperatures are consistent with observations at T42 resolution, while the T21 resolution yields a cold bias of 1K. At T42 resolution the seasonal migration of the warm pool is reproduced reasonably well, as are the surface heat fluxes, winds, and clouds. However, simulated precipitation is too small compared to observations, implying that the surface density flux is dominated by fluxes of heat.

In the Pacific portion of the warm pool, the average net heat gain of the ocean amounts to 30–40 W m−2. In the northern branch, this heat gain is balanced by vertical advection, while in the southern branch, zonal, meridional, and vertical advection cool the ocean at approximately equal rates. At the equator, the surface heat flux is balanced by zonal and vertical advection and vertical mixing. The Indonesian and Indian Ocean portions of the warm pool receive from the atmosphere 30 and 50 W m−2, respectively, and this flux is balanced by vertical advection. The cooling due to vertical advection stems from numerical diffusion associated with the upstream scheme, the coarse vertical resolution of the ocean model, and near-inertial oscillations forced by high-frequency atmospheric variability.

The seasonal migration of the warm pool is largely a result of the seasonal variability of the net surface heat flux, horizontal and vertical advections are of secondary importance and increase the seasonal range of surface temperature slightly everywhere in the warm pool, with the exception of its southern branch. There, advection reduces the effect of the surface flux. The seasonal variability of the surface heat flux in turn is mainly determined by the shortwave radiation, but evaporation modifies the signal significantly. The annual cycles of reduction of solar radiation due to clouds and SST evolve independently from each other in the Pacific portion of the warm pool; that is, clouds have little impact on SST. In the Indian Ocean, however, clouds limit the maximum SST attained during the annual cycle.

In the western Pacific and Indonesian portion of the warm pool, penetrative shortwave radiation leads to convective mixing by heating deeper levels at a greater rate than the surface, which experiences heat losses due to turbulent and longwave heat fluxes. In the deeper levels, there is no mechanism to balance the heating due to penetrative radiation, except convection and its attendant mixing. In the Indian Ocean, however. the resulting vertical heating profile due to the surface fluxes decreases monotonically with depth and does not support convective mixing. Concurrently, the warm pool is shallower in the Indian Ocean compared with the western Pacific, indicating that convective mixing due to penetrative radiation is important in maintaining the vertical structure of the Pacific portion of the warm pool.

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Timothy N. Stockdale, Magdalena A. Balmaseda, and Arthur Vidard

Abstract

Variations in tropical Atlantic SST are an important factor in seasonal forecasts in the region and beyond. An analysis is given of the capabilities of the latest generation of coupled GCM seasonal forecast systems to predict tropical Atlantic SST anomalies. Skill above that of persistence is demonstrated in both the northern tropical and equatorial Atlantic, but not farther south. The inability of the coupled models to correctly represent the mean seasonal cycle is a major problem in attempts to forecast equatorial SST anomalies in the boreal summer. Even when forced with observed SST, atmosphere models have significant failings in this area. The quality of ocean initial conditions for coupled model forecasts is also a cause for concern, and the adequacy of the near-equatorial ocean observing system is in doubt. A multimodel approach improves forecast skill only modestly, and large errors remain in the southern tropical Atlantic. There is still much scope for improving forecasts of tropical Atlantic SST.

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Geert Jan van Oldenborgh, Magdalena A. Balmaseda, Laura Ferranti, Timothy N. Stockdale, and David L. T. Anderson

Abstract

Since 1997, the European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification.

The main cause of seasonal predictability is El Niño and La Niña perturbing the average weather in many regions and seasons throughout the world. As a baseline to compare the dynamical models with, a set of simple statistical models (STAT) is constructed. These are based on persistence and a lagged regression with the first few EOFs of SST from 1901 to 1986 wherever the correlations are significant. The first EOF corresponds to ENSO, and the second corresponds to decadal ENSO. The temperature model uses one EOF, the sea level pressure (SLP) model uses five EOFs, and the precipitation model uses two EOFs but excludes persistence.

As the number of verification data points is very low (15), the simplest measure of skill is used: the correlation coefficient of the ensemble mean. To further reduce the sampling uncertainties, we restrict ourselves to areas and seasons of known ENSO teleconnections.

The dynamical ECMWF models show better skill in 2-m temperature forecasts over sea and the tropical land areas than STAT, but the modeled ENSO teleconnection pattern to North America is shifted relative to observations, leading to little pointwise skill. Precipitation forecasts of the ECMWF models are very good, better than those of the statistical model, in southeast Asia, the equatorial Pacific, and the Americas in December–February. In March–May the skill is lower. Overall, S1 (S2) shows better skill than STAT at lead time of 2 months in 29 (32) out of 40 regions and seasons of known ENSO teleconnections.

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Geert Jan van Oldenborgh, Magdalena A. Balmaseda, Laura Ferranti, Timothy N. Stockdale, and David L. T. Anderson

Abstract

The European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts since 1997 with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification.

Seasonal predictability is to a large extent due to the El Niño–Southern Oscillation (ENSO) climate oscillations. ENSO predictions of the ECMWF models are compared with those of statistical models, some of which are used operationally. The relative skill depends strongly on the season. The dynamical models are better at forecasting the onset of El Niño or La Niña in boreal spring to summer. The statistical models are comparable at predicting the evolution of an event in boreal fall and winter.

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