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Seasonal forecasts using coupled ocean-atmosphere climate models are increasingly employed to provide regional climate predictions. For the quality of forecasts to improve, regional biases in climate models must be diagnosed and reduced. The evolution of biases as initialized forecasts drift away from the observations is poorly understood, making it difficult to diagnose the causes of climate model biases. This study uses two seasonal forecast systems to examine drifts in sea surface temperature (SST) and precipitation, and compares them to the long-term bias in the free-running version of each model. Drifts are considered from daily to multi-annual time scales. We define three types of drift according to their relation with the long-term bias in the free-running model: asymptoting, overshooting and inverse drift. We find that precipitation almost always has an asymptoting drift. SST drifts on the other hand, vary between forecasting systems, where one often overshoots and the other often has an inverse drift. We find that some drifts evolve too slowly to have an impact on seasonal forecasts, even though they are important for climate projections. The bias found over the first few days can be very different from that in the free-running model, so although daily weather predictions can sometimes provide useful information on the causes of climate biases, this is not always the case. We also find that the magnitude of equatorial SST drifts, both in the Pacific and other ocean basins, depends on the El Niño Southern Oscillation (ENSO) phase. Averaging over all hindcast years can therefore hide the details of ENSO state dependent drifts and obscure the underlying physical causes. Our results highlight the need to consider biases across a range of timescales in order to understand their causes and develop improved climate models. [ABSTRACT FROM AUTHOR]

The reversibility of the Atlantic meridional overturning circulation (AMOC) is investigated in multi-model experiments using global climate models (GCMs) where CO concentrations are increased by 1 or 2 % per annum to 2× or 4× preindustrial conditions. After a period of stabilisation the CO is decreased back to preindustrial conditions. In most experiments when the CO decreases, the AMOC recovers before becoming anomalously strong. This "overshoot" is up to an extra 18.2Sv or 104 % of its preindustrial strength, and the period with an anomalously strong AMOC can last for several hundred years. The magnitude of this overshoot is shown to be related to the build up of salinity in the subtropical Atlantic during the previous period of high CO levels. The magnitude of this build up is partly related to anthropogenic changes in the hydrological cycle. The mechanisms linking the subtropical salinity increase to the subsequent overshoot are analysed, supporting the relationship found. This understanding is used to explain differences seen in some models and scenarios. In one experiment there is no overshoot because there is little salinity build up, partly as a result of model differences in the hydrological cycle response to increased CO levels and partly because of a less aggressive scenario. Another experiment has a delayed overshoot, possibly as a result of a very weak AMOC in that GCM when CO is high. This study identifies aspects of overshoot behaviour that are robust across a multi-model and multi-scenario ensemble, and those that differ between experiments. These results could inform an assessment of the real-world AMOC response to decreasing CO. [ABSTRACT FROM AUTHOR]