FOCUS-Africa Editorial, Roberta Boscolo

News

The FOCUS-Africa project is already well in its third year of implementation and I continue to be surprised by the level of achievement and commitment so far but especially in the last year. Thanks to the relaxation of the COVID restrictions, the different teams involved in the case studies had the opportunity to meet in person with the various stakeholders in Southern African and hence making significant progress with the co-design, co-development and co-production of the climate services.

The team led by WEMC, in charge of developing end-user tailored climate services prototypes, was able to collect the requirements for the climate services in each of the case studies. The team also conducted a considerable amount of work in meteorological and sector-specific (agriculture, energy, etc.) data collection as well as their initial assessment. These data analyses, which effectively started the co-development phase of co-production, have been a very useful way to strengthen the engagement with users, also as a way of demonstrating to them different methods of producing and delivering useful climate information. Each case study now has a well-developed workflow, which is being used to guide the development of the trial climate services. The workflows also highlight key stakeholders, beyond the immediate users, and possible paths for exploitation.

The strong collaboration with the Impact Assessment Team (IAT of Work Package 6) was very effective for the development of the co-production workflow.

The IAT, lead by LGI, is working on the socio-economic baseline assessment by applying the methodology that builds on the Sustainable Development Goals but adapted to fit the context of FOCUS-Africa. The four macro-categories considered are:

  • Inclusive Economy growth
  • Food-Water-Energy nexus
  • Governance Innovation, Partnership and Capacity Building
  • Climate Change and Disaster Resilience

This approach facilitated the development of eight impact assessment grids, one for each case study. Every grid is composed of transversal indicators, common to all case studies, and of case study specific indicators, allowing to produce a context-adapted baseline assessment. Every country was also assessed with regards to the existing climate services, producing a climate services benchmark for the country, as well as a regional benchmark for each sector.

The assessment of the socio-economic situation was largely based on meetings, interviews and focus group discussions made during the missions to the five countries, as well as academic literature and public reports. Each case study team travelled to their respective country at least once to complete this task. During the travels, the teams were able to include stakeholders in the discussion and establish a strong collaboration with the fellow users, which allowed to produce this report.

On the climate science underpinning the development of the climate services, we made excellent progress on understanding of the regional climate processes and on the verification of the climate predictions and projections.

The team in charge of assessing the regional climate processes has completed all their tasks under the leadership of MetOffice. One of their major contributions was on the analysis of the predictability of seasonal and decadal forecasts over the SADC region. For inter-annual variability, predictive skill is high in summer in association with ENSO forcing. In winter, however, the seasonal prediction of rainfall needs to focus on improved systems of initialization and data assimilation because the sources of predictability are weak.  The final contribution of this Work Package was in the identification and variability analysis of extreme events and their distribution in high-resolution climate projections. Despite the biases and uncertainties in the simulations of extreme daily events by the regional climate models, new methodologies can be applied to determine risks related to future climate extremes using Machine Learning. The team defined a specific multi-hazard Extreme Climate Index (ECI) which is particularly efficient in detecting extreme events in the SADC region.

Building on the understanding of the climate extremes in the region, the team looking at the climate services requirements and user’s challenges, led by CSIR, looked more closely at the climate extremes relevant to food security under a changing climate. Their analysis shows that Southern Africa is likely to become generally drier in the incoming decade under low mitigation pathways. The area suitable for maize production, the staple food in southern Africa, is projected to decrease substantially in western and central southern Africa and over parts of the eastern region. Over Lesotho, however, the projected reduction of cold extremes, may result in increasing climatic suitability for maize. Finally, the study highlights that the projected warmer and drier climate with associated reduced soil moisture availability, in combination with increases in the number of heatwaves and high fire danger days, may trigger the occurrence of regional tipping points in southern Africa. Examples include the collapse of the maize crop in marginal regions, or of the cattle industry across southern Africa.

The team led by BSC in charge of developing methods and tools for the climate services reported on the verification of seasonal forecasts and the characterization of climate projections and decadal predictions. The study revealed that there is no calibration method that simultaneously improves all the aspects of forecast quality for seasonal and decadal climate predictions, therefore a systematic forecast quality assessment is needed to identify the best approach for calibrating the raw simulations for each use-case. Information on the systematic assessment is available in a R shiny app here https://earth.bsc.es/shiny/FOCUS-Africa/

A new bias correction method was proposed for seasonal extremes based on extending the classic quantile mapping (QM) and improving the distribution tail with a generalized extreme value distribution (GEV).  The multi-model combination (which consists of merging the predictions provided by several forecast systems) is expected to enhance the quality and reliability of the predictions due to the error compensation and the signal addition that each system sums to the multi-model ensemble. Also, downscaling techniques will improve the information provided to users, as many applications need predictions at regional to local scales.

The various research and findings under the work packages and case studies is being tailored into capacity building materials where possible, with ACMAD, who lead Work Package 7, coordinating the systematic documentation and collation of the materials.

As mentioned in the beginning of this editorial, the past year was characterized by an increase of in-person events. The most important was the 3rd Stakeholders workshop held in Pretoria, South Africa, in May/June 2022. This was also the occasion for the first in-person consortium assembly a very emotional gathering after so many forced virtual meetings. During the assembly and the workshop, we were also joined by a few Advisory Board members. You can read more about the FOCUS-Africa week in Pretoria in this issue of the Newsletter in addition to the videos and reporting of the missions in Tanzania, Malawi and Mozambique during 2022. Our next FOCUS-Africa week will take place in May 2023 in in Maputo and Macaneta in Mozambique.