• University of Leeds Featured PhD Programmes
  • Carlos III Health Institute Featured PhD Programmes
  • University of Glasgow Featured PhD Programmes
  • University of Mannheim Featured PhD Programmes
  • London School of Economics and Political Science Featured PhD Programmes
  • University of Leeds Featured PhD Programmes
  • University of Leeds Featured PhD Programmes
University College London Featured PhD Programmes
University of Kent Featured PhD Programmes
Manchester Metropolitan University Featured PhD Programmes
University of Glasgow Featured PhD Programmes
Birkbeck, University of London Featured PhD Programmes

Large-scale drivers of the seasonal to decadal variability in terrestrial water storage

This project is no longer listed in the FindAPhD
database and may not be available.

Click here to search the FindAPhD database
for PhD studentship opportunities
  • Full or part time
    Dr Demory
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

The hydrological cycle is a fundamental link between components of the Earth System: atmosphere, hydro-sphere and biosphere. It is mainly driven by solar energy, is strongly influenced by the ocean, and involves complex interactive processes that drive the movement of water at various time and spatial scales. This complexity, together with a lack of homogeneous and accurate global observational datasets, compounds the difficulty climate modellers encounter in simulating the hydrological cycle with global climate models
(GCM). This leads to large uncertainties in predictions of climate change.

In 2002, NASA JPL launched the Gravity Recovery and Climate Experiment (GRACE) satellite mission, which has been measuring for the first time Earth’s gravity field variations and revealing key insights into Earth’s water storage and transport processes over land, ice and oceans. GRACE is a truly independent observational product, providing new resources to understand the hydrological cycle. The decade-long record has revealed how inter-annual variations in terrestrial water storage are tied with the El Nino Southern Oscillation. Combining GRACE data with GCM simulations would offer unprecedented opportunities to improve mid- to long-term predictions of floods and droughts, which threaten lives because of climate variability.

This PhD aims to exploit the GRACE data to 1) evaluate state-of-the-art GCM simulations of seasonal to decadal variability in terrestrial water storage at regional to global scales; 2) better understand large-scale drivers of terrestrial water storage variability; 3) make use of such information for improving seasonal to decadal predictions of terrestrial water storage variability, which govern the long-term frequency of floods and droughts over the globe. This is an innovative approach to assess GCMs and will advance the state of our knowledge in understanding the processes underlying changes in the hydrological cycle.

The student will be embedded in a large research team with international leaders in global climate modelling. He/she will be trained in the use of advanced global climate models and in manipulating the GRACE satellite data. There may be opportunities to visit JPL and to attend the NCAS Climate Modelling Summer School.

The project is supervised by Marie-Estelle Demory (University of Reading), and co-supervised by Carmen Boening (Jet Propulsion Laboratory), and Pier Luigi Vidale (University of Reading).

The full project description is available at: http://www.met.reading.ac.uk/nercdtp/home/available/desc/SC201624.pdf

A video is also available at https://youtu.be/61Zkv4jmTDY

Funding Notes

This project is for students with their own funding.

To apply for this PhD project please visit http://www.met.reading.ac.uk/nercdtp/home/apply.html

This project would be suitable for students with a degree in physics, mathematics or related environmental science. Numeracy and data management are preferred, but not essential, as long as the student is willing to undertake training and to become an expert in manipulating complex models and treating Big Data.

References

Boening et al. (2012). The 2011 La Nina: So Strong, the Oceans Fell, Geophys. Res. Lett., 39, L19602.

How good is research at University of Reading in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 75.68

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities
Share this page:

Cookie Policy    X