How is climate variability controlled in the North Atlantic?

External Supervisors: Dr Doug Smith (Hadley Centre) and Prof. Susan Lozier (Duke University, USA)


Introduction:

This studentship examines how climate change is operating in the North Atlantic Ocean (Fig. 1a). The general expectation for climate change is that the ocean is warming and there is a stronger freshwater cycle. However, analysis of historical data reveals a more complex response in the North Atlantic. There are extensive regions of warm and salty anomalies, changing in time to cool and fresh anomalies, and then returning to warm and salty anomalies; see Fig. 1b for 1969 & 1989 [Lozier et al., 2008, 2010;Williams et al., 2014]. This studentship aims to investigate how this ocean variability is controlled, addressing both the issue of natural variability and the imprint of climate forcing.

The studentship will be part of the NERC funded UK-OSNAP programmme: Overturning in the Subpolar North Atlantic,http://www.ukosnap.org/, designed to understand how the temperature and salinity properties of the high latitude North Atlantic are controlled. The student will have an extended visit to work with Professor Susan Lozier (Duke University, USA), who leads the international OSNAP programme, as well as attending national meetings and having the opportunity to participate in fieldwork.

Project Summary:

The studentship aims to investigate the mechanisms by which climate variability is occurring in the North Atlantic, including why there is a more complex regional response than the expected basin-scale signals of surface warming and a strengthening in the freshwater cycle.

The studentship will examine the following research questions:

• Ocean redistribution of heat and salt often obscures the expected climate-change signals of surface warming and a strengthening in the freshwater cycle, as well as potentially affecting the signature in surface warming;

• Surface forcing generally induces density anomalies in the surface ocean, which are communicated over the basin through changes in the ocean circulation and overturning;

• Part of the surface forcing of temperature and salinity is density compensated and will form warm and salty or cold and fresh anomalies. These opposing temperature and salinity anomalies are relatively persistent and long lived, as these density-compensated signals do not alter the circulation. Temperature and salinity contrasts over the ocean basin are then possibly formed via a passive advection of density-compensated signals by the background circulation.

The plan of work for the student involves:

1. Analyse the climate variability using historical data in the North Atlantic [Smith et al., 2015]. In particular, identify how temperature and salinity anomalies vary in density space, involving the vertical migration of density surfaces and the change in temperature/salinity properties along density surfaces [Bindoff & McDougall, 1994];

2. Compare the temperature and salinity anomalies in the historical data with the implied anomalies induced by air-sea heat and freshwater fluxes;

3. Assess how the climate anomalies are communicated over the basin and how persistent climate anomalies are formed by integrating ocean circulation experiments (cf. Lozier et al., 2008). The ocean anomalies can either contain density anomalies or be density-compensated with opposing temperature-salinity anomalies. The experiments will investigate the extent that the anomalies spread via the circulation and how opposing basin-scale contrasts in the temperature-salinity distribution are formed over the North Atlantic;

4. The student will analyse recent subpolar North Atlantic data being gathered from the ongoing UK-OSNAP programme, comparing observations of temperature, salinity and density changes in the subpolar gyre with implied diagnostics of the heat and freshwater transport into the subpolar gyre.

This work plan can be revised and modified according to the input and aptitude of the student.

Applicants should have a strong academic track record with a science degree, such as including Ocean Sciences, Meteorology, Mathematics, Physics or Engineering. The project involves analysing data and integrating ocean models, so that the student needs to have an aptitude for quantitative work. Prior experience in computational and numerical work is though not required, as training in developing simple models and analysing data is provided in the first year of the PhD.