Project Description
Supervisors
Professor Manoj Joshi, School of Environmental Science, University of East Anglia – contact me
Professor Tim Osborn, UEA
Professor Laura Wilcox, University of Reading
Professor Bjørn Samset, CICERO (Center for International Climate Research), Oslo
Scientific Background:
The Atlantic Ocean has warmed significantly over the last few years partly from increasing greenhouse gases, but other climate forcing agents also play a role. In particular, dust produced and lifted into the atmosphere over Africa and transported thousands of miles over the Atlantic has important and complex effects on climate.
Saharan dust reflects sunlight to space and so cools the ocean, just as its absence warms the ocean. Dust in the atmosphere can alter the atmospheric circulation on vast scales and changes to the Atlantic Ocean sea surface temperature also impact on global atmospheric and oceanic circulation. Understanding changes in dust transport is, therefore, important for making better predictions of changes to temperature, atmospheric and oceanic circulation, and rainfall over the Atlantic ocean region. Observing, modelling and understanding the complexity of the dust cycle and its underlying processes presents a substantial but fascinating scientific challenge.
Research Methodology:
The project will be in two parts. First, you will analyse global datasets of observations and state-of-the-art climate models to understand the movement of dust, and its effects on temperature, atmospheric circulation, and impacts such as rainfall. Such analysis will involve examining similarities and differences between models to gain a more detailed understanding of the models’ treatments of dust and climate, and evaluating them against observations. Second, you will design, run and analyse experiments using slightly simpler climate models on the UEA high-performance computing system to untangle the mechanisms involved.
Research Aims and Outcomes:
To understand and better predict how dust influences Atlantic Ocean temperatures, and how these changes affect climate, ocean-atmosphere circulation and precipitation patterns.
Training:
You will be trained in statistical analysis, including computer coding, and interpretation of observational datasets and output from state-of-the-art climate models. You will also learn to design, run and analyse your own climate model experiments. Training activities also occur within the ARIES DTP.
Person Specification:
A degree in a quantitative science. An interest in data analysis and numerical modelling of weather systems and the climate system is essential, while some experience in coding is desirable.
Acceptable first degree subject(s): A degree in Physics, Maths, Meteorology, Oceanography, Geophysics or a similar quantitative science.