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Audine Laurian, Alban Lazar, and Gilles Reverdin

Abstract

Oceanic teleconnections between the low and midlatitudes are a key mechanism to understanding the climate variability. Spiciness anomalies (density-compensated anomalies) have been shown to transport temperature and salinity signals when propagating along current streamlines in the subtropical gyres of the Atlantic and Pacific Oceans. The generation mechanism of spiciness anomalies in the North Atlantic subtropical gyre is investigated using an analytical model based on the late-winter subduction of salinity and temperature anomalies along isopycnal surfaces. The keystone of this approach is the change of the coordinates frame from isobaric to isopycnic surfaces, suited for subduction problems. The isopycnal nature of spiciness anomalies and the use of a linear density equation allows for the analytical model to depend only upon surface temperature and salinity anomalies, the mean thermocline currents, and the surface density ratio. This model clarifies and above all quantifies the mechanism by which surface temperature and salinity anomalies are modulated by density ratios to produce fully different isopycnal temperature and salinity anomalies.

A global run from the ocean GCM (OGCM) Océan Parallélisé (OPA) over the period 1948–2002 provides the reference data in which the North Atlantic subtropical thermocline spiciness variability is analyzed. Two EOF modes are sufficient to explain half of the low-frequency variability in the OGCM: one is maximum over the northeastern subtropics, and the other is in the central basin. The analytical model reproduces well the spatial pattern, amplitude, and sign of these two main modes. It confirms that the two centers of action of the anomalies are conditioned by the surface density ratio, the first corresponding to null salinity gradients and the second to near-density-compensated temperature gradients. Considering that the analytical model has good skills at reproducing the decadal variability of the OGCM spiciness anomalies in the permanent thermocline, it is believed that this is an interesting tool to understand and forecast the ventilation of the North Atlantic subtropical gyre at this time scale.

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George C. Craig, Andreas H. Fink, Corinna Hoose, Tijana Janjić, Peter Knippertz, Audine Laurian, Sebastian Lerch, Bernhard Mayer, Annette Miltenberger, Robert Redl, Michael Riemer, Kirsten I. Tempest, and Volkmar Wirth

Abstract

Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-year phase of our planned duration of 12 years and employ 36 doctoral and post-doctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely upscale error growth, errors associated with cloud processes, and probabilistic prediction of high impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early career scientists, and to support education, equal opportunities, and outreach, which are also described here.

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