Dr Stephen Dye (Cefas/UEA)
Dr Clare Goodess (UEA)
Dr John Pinnegar (Cefas/UEA)
The Caribbean Small Island Developing States face a variety of impacts from climate variability and climate change. The Caribbean Sea surface temperatures change from year to year due to both natural variability (for example associated with El Niño or the Atlantic Multidecadal Oscillation) and anthropogenically forced climate change. Anomalously warm years can lead to an early start to the rainfall season, coral bleaching and more hurricanes or more intense hurricanes. In cooler years the start of the rainfall season is delayed. Both flooding and drought are a risk. Damage to corals can impact biodiversity, fisheries, tourism, and weaken the defence they provide against stormy seas.
You will analyse observations of sea surface temperature, winds, rainfall and other key variables to determine the main patterns of climate variability that impact the Caribbean. You will assess how well these observed patterns are represented in a range of state-of-the-art climate models. You will use the model output to determine the key drivers of variability and determine any processes leading to model deficiencies. You will use model projections of future climate to understand how these patterns of climate variability might change.
Training and research environment
You will join an active research group at UEA (which includes the Cefas Collaborative Centre for Sustainable use of the Seas) in meteorology, oceanography and climate. You will be trained in modelling the climate system and you will learn to use state-of-the-art computer systems to rigorously analyse large climate model datasets. You will have the opportunity to present your work at an international conference. There will also be an opportunity to undertake fieldwork to gain an appreciation of data collection and quality issues.
We seek an enthusiastic, pro-active student with strong scientific interests and self-motivation. You will have at least a 2.1 honours degree in physics, mathematics, meteorology, oceanography or environmental science with good numerical ability. Experience of a programming language will be advantageous. This project will suit an applicant intending to start a scientific career in meteorology, oceanography or climate science.