Project Highlights:

  • Understanding climate change impacts on agricultural ecosystems in sub Saharan Africa
  • Predicting climate impacts on food security in sub Saharan Africa
  • Data assimilation as a cutting edge technology for data exploitation


Climate change is expected to impact African water and food security, sustainable development and economic sustainability (ISS, 2010). Already, climate change is affecting people, their livelihoods and cultures on the African continent (IPCC, 2001). Subsistence agriculture, which is frequently rain fed in large parts of Africa, will be potentially very severely impacted by climate change. Alexandratos et al. (2012) predict that anticipated climate variability in sub-Sahara Africa would adversely affect agriculture, e.g. by reducing cereal crop yields between 20%-30% by the end of 2050. This would pose significant food security, employment and economic challenge to poorer nations in sub-Sahara Africa (UNDP, 2007). Furthermore, the Inter-governmental Panel on Climate Change (IPCC, 2007) explicitly stated in its fourth assessment report that sub-Sahara Africa’s vulnerability is a results of its high dependence on agriculture. According to the International Labour Organization (ILO, 2011), over 60% of all employment in sub- Saharan Africa depend on agriculture, which has become extremely vulnerable to climate change. Furthermore sub-Sahara Africa’s vulnerability has been exacerbated by extreme poverty and inequality (Brooks, 2003 and Boko et al., 2007). There is therefore an urgent need to explore climate change impacts in more detail to facilitate the development of effective adaptations. Past work in the research group has considered precipitation patterns as well as land cover change in West Africa based on remotely sensed data (Figure 1). We now want to extend the work to modelling approaches. Recent improvements in remote sensing data sets have resulted in a range of different data at 1km resolution (e.g. soil, vegetation, surface temperature). This offers the opportunity to simulate land surface processes at a scale that becomes relevant for agriculture.  

Research questions:

  • Does the assimilation of medium resolution (1km) remote sensing data into a land surface model provide useful information in West Africa?
  • What is the impact of climate variability and change in West Africa on subsistence agriculture?
  • What is the impact of future climate change in West Africa on subsistence agriculture?


Figure 1: Spatial distribution slopes of the residuals of regressions of NDVI against time (a) from the RESTREND analysis using soil moisture and (b) areas with significant negative trends (95% confidence) (From Ibrahim et al., 2015)


The methods will be centred around simulations with and data assimilation into JULES, the joint UK land environment simulator, version 4.6, which includes a crop growth model. The work will use a range of different data at 1km resolution (e.g. soil, vegetation, surface temperature). First, past impacts of climate variability will be explored. Using data from recent decades and data assimilation, the model will be calibrated for West Africa. This then allows the impact of future climate change to be explored using simulated climate for future decades.   Results will be written up for publication in scientific journals.

Training and Skills

Throughout the PhD, training will progress from core to specific research skills. Specific training will be provided in programming, computer skills and data analysis. For data processing, training will be given on a data processing chain, in particular training on the use of linux systems, compilers (through the University of Leicester High Performance training courses) and the ferret and ‘R’ software packages – through participation in an ‘R’ training course as applicable. Specific training on land surface and JULES modelling will be achieved through engagement in annual JULES workgroup meetings and training in the Met-Office ROSE simulation system.


Year 1 Training in site maintenance, software usage and development, attending workshops on the eddy covariance method. Initial data analysis and evaluation of GHG fluxes. Initial writing and upgrade.

Year 2: Continued station maintenance, workshops, data analysis and evaluation of management and climate impacts on GHG fluxes, conference attendance, preparation of manuscript for journal submission. Continued development of thesis chapters.

Year 3: Continued station maintenance, data analysis, manuscript submission and revision, conference attendance, thesis preparation.


Partners and collaboration (including CASE)

Dr Jörg Kaduk has 25 years experience in carbon cycle and ecosystem modelling with particular focus on ecophysiology and has supervised 7 PhD students to completion. Dr Darren Ghent has 10 years experience in interpretation and application of remote sensing data and data assimilation and has supervised several Masters students.

Further Details

The student will join a vibrant and diverse research students community of the Centre for Landscape and Climate Research (CLCR) and the School of Geography, Geology and the Environment working on different aspects of global change.


Please contact:

Jörg Kaduk

School of Geography, Geology and the Environment

University of Leicester

University Road

Leicester, LE1 7RH

Jk61@le.ac.uk, 0116 252 3848