Key messages from the UMFULA project

UMFULA has addressed questions of climate science, climate impacts and decision-making processes for adaptation, including:

  • How does the climate of central and southern Africa work? And how well do climate models represent the key processes responsible for climate?
  • How might the climate of central and southern Africa change in future decades out to ~2050 and how sure are we about the projected changes?
  • To what extent can decision-making approaches incorporate climate change uncertainties within investment decisions that cut across the water, energy and food sectors?
  • How does the political and institutional environment influence the usefulness and usability of climate information for adaptive decision-making?

Our results show:

  • Understanding the likely future characteristics of climate risk is a key component of adaptation and climate resilient planning, but given future uncertainty it is important to design approaches that are strongly informed by local considerations and are robust to uncertainty, i.e. options that work reasonably well across a range of uncertain future climate (and other) conditions.
  • Choosing the right tools and approach for climate risk assessment and adaptation to suit the scale of the decision allows a suitable trade-off between robustness and resources required (time and expertise) for analysis.
  • In the medium term, policy decisions require careful cross-sectoral planning, particularly in cases involving large investments, long life-times and irreversibility, where there is a strong argument for assessing resilience to future climate change (for example around water, energy and food in Malawi and Tanzania).
  • The process of co-production of knowledge by researchers and wider stakeholders contributes to building societal and institutional capacity to factor climate risks into long-term planning. It also builds the capacity of researchers to better understand real world decision contexts in which climate change is one of many important factors.