Location: University of Soithampton (Geography & Environment)
Supervisory team: Prof. David Sear, Prof. Justin Sheffield, Prof Ian Croudace (National Oceanographic Centre, Southampton).
Rationale: Because of their small size and isolation, islands in the Pacific have limited and fragile natural resources, making them more vulnerable to climate hazards and stresses than are continents1. Pacific Island Nations (PINS) also occupy the region of the earth’s surface most immediately impacted by ENSO events. The impacts of El Nino events are felt across 3,975 islands, 13 island nations, affecting a population of 12.9 million who rely on rainfall for freshwater and food security. To date our understanding of the mechanisms of drought, their frequency and duration, and their biophysical effects in PINs remain poorly quantified. In addition island types experience droughts differently, varying according to their location, topography, geological history and ecology. Droughts are also thought to have been important drivers of the human colonization of the Pacific2. Drought frequency is likely to increase in the tropical pacific but again its specific impacts are largely unknown. This PhD seeks to develop a step change in our understanding of droughts based on novel coupling of long term data on drought frequency with process based drought modelling.
Methodology: This PhD aims to develop new knowledge about the hydroclimatology of droughts in the tropical Pacific through an integrated approach that will (1) couple process based hydrological modelling and observational data to better define droughts, their drivers (e.g. ENSO, IPO) and impacts (water and plant stress) across a range of Island types; (2) extend the record of drought frequency and magnitude over the past 2ka (covering MCA-LIA-GHG Warming World climate transitions) through development of new drought specific geochemical proxies based on existing lake sediment core archives (e.g. Gypsum deposition); (3) Apply climate model products (e.g PMIP) and existing palaeoclimate datasets to better understand drought development over centennial-millennial timescales; (4) Use existing climate model outputs to determine future drought risk in PINs based on (1-3).
Training: The SPITFIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the University of Southampton and hosted at Geography & Environment. Specific training will include:
- Drought modeling using existing approaches developed by Prof Sheffield.
- Development and interpretation of Palaeodrought proxies using existing lake sediment geochemical datasets held by the supervisory team (Croudace, Langdon, Sear).
- Interpretation of palaeoclimate datasets (e.g. time series analysis) and statistical analysis using R. (Sear, Sheffield, Langdon).
Eligibility & Funding Details: This SPITFIRE project is open to applicants who meet the SPITFIRE eligibility, alongside other exceptional applicants and will come with a fully funded studentship for UK students and EU students who meet the RCUK eligibility criteria. To check your eligibility and find information on how to apply click here.
UK applicants and EU students who meet the RCUK eligibility criteria please contact firstname.lastname@example.org
This project is also open to applicants who DO NOT meet the SPITFIRE funding eligibility criteria via applying to PGRapply.FSHMS@southampton.ac.uk
Please make sure you apply to the correct programme any applications from non SPITFIRE eligible applicants will be rejected automatically.
Allen, M.S. (2006) New Ideas about Late Holocene Climate Variability in the Central Pacific: Current Anthropology, 47; 3: 521-535.
Sheffield, J., and E. F. Wood, 2008: Global Trends and Variability in Soil Moisture and Drought Characteristics, 1950–2000, from Observation-Driven Simulations of the Terrestrial Hydrologic Cycle. J. Climate, 21, 432–458.