School of Earth and Environment

Alexander Roberts Dr Alexander Roberts

Research Fellow

Telephone number: +44(0) 113 34 33389
Email address:
Room: 1.08, Fairburn House, NCAS

Affiliation: Institute for Climate and Atmospheric Science


Alex is a post-doctoral researcher within the Institute for Climate and Atmospheric Sciences (ICAS) at the University of Leeds. He is currently working on the SWAMMA project (see below) investigating the dynamics of the West African Monsoon in the Met Office Unified Model (UM). Prior to this he worked towards his PhD investigating meso-scale convective systems over West Africa close to the monsoon front. This included simulations using the Weather Research and Forecast (WRF) model and evaluation of reanalysis products over summertime West Africa.


  • PhD -Convective Episodes near the Intertropical Discontinuity in Summertime West Africa: Representation in Models and Implications for Dust Uplift, University of Leeds.
  • BSc - Meteorology and Atmospheric Sciences, University of Leeds.

Research Interests

  • Atmospheric mineral dust
  • Convection
  • Meso-scale dynamics
  • Numerical Weather Prediction
  • Reanalyses and effects of data assimilation

Project details

Project title

Saharan - West African Monsoon Multi-scale Analysis (SWAMMA).


  • John Marsham - University of Leeds
  • Ellie Highwood - University of Reading


Natural Environment Research Council (NERC)

Project outline

The SWAMMA project brings together recently acquired observations from the African Monsoon Multidisciplinary Analysis (AMMA) and Fennec field campaigns, with simulations from the Met Office Unified model. Observations in the remote Sahara and Sahel and a range of model setups allow the dynamics and couplings within the West African Monsoon (WAM) system to be investigated.

The WAM is critical to the livelihoods of millions of people, and yet, it presents a major challenge for weather prediction. This indicates that there are features of the WAM that are not well understood or represented in well enough in numerical weather prediction models. This lack of understanding also highlights the uncertainties in predicting important features such as rainfall and dust uplift on climate scales.