Anya Schlich-Davies

Anya Schlich-Davies


I am using atmospheric and glacier modelling to produce catchment scale predictions, to improve on the current coarser predictions, of Himalayan glacier response to climate change. I am focussing on modelling the mass balance of the Khumbu glacier, which flows down the flanks of Mount Everest and has the worlds highest accumulation area. I am using improved, finer resolution climate data from weather stations, climate reanalysis data, CMIP models and WRF runs to test how sensitive melt rates are to differing climate inputs. This will then be used to feed into an ice flow model to simulate the future evolution of the glacier, with Dr Ann Rowan at the University of Sheffield.

I completed an MSc in Polar and Alpine Change at the University of Sheffield. My dissertation was titled 'How will the decline of sea-ice in the Russian Arctic seas influence phytoplankton productivity?' and involved analysis of satellite imagery, as well as modelling of sea ice, nutrient availability and sea surface temperature as key controls over phytoplankton growth. During my Masters I spent 6 weeks at UNIS (Svalbard), where I took a course in 'Melt Season Dynamics'.

I graduated from a BSc in Physical Geography from Sheffield in 2014. My undergraduate dissertation used data collected over 6 weeks on several glaciers in Switzerland to analyse the effect of supraglacial debris layer thickness and grain size on glacier melt.


Research interests

Project title: Himalayan glacier response to future atmospheric forcing.

Supervised by:

  • Dr Andrew Ross (SEE)
  • Dr Duncan Quincey (SoG)

Funded by:

  • Priestley International Centre for Climate Change and the University of Leeds

Project description:

I am using regional climate models and in situ data to downscale and validate current coarse climate simulations for the Everest region of the Nepal Himalaya, with a current focus on the Khumbu glacier. The aim is to improve predictions of future glacier change in the region. Catchment scale precipitation and temperature datasets will be used in order to refine climate inputs, which will act as inputs for an glacier energy mass balance model. Sensitivity runs to test the importance of the climate variables, and the resolution of these variables, will be carried out. A3D glacier ice flow model will be used to simulate ice flow, with an evolving surface debris layer, and quantify glacier change until 2100. to be created. The uncertainty associated with these models will be tested and quanitified, and field observations will be used for validation.

Research groups and institutes

  • Atmospheric and Cloud Dynamics
  • Climate Science and Impacts
  • Institute for Climate and Atmospheric Science