Challenges and ways forward for sustainable weather and climate services in Africa

Sustainability of African weather and climate information can only be ensured by investing in improved scientific understanding, observational data, and model capability. These requirements must be underpinned by capacity development, knowledge management and partnerships of co-production, communication and coordination

Institutionalising co-production of weather and climate services: learning from the African SWIFT and ForPAc projects

There is growing recognition of the multiple benefits of co-production for forecast producers, researchers and users in terms of increasing understanding of the skill, decision-relevance, uptake and use of forecasts. This policy brief identifies lessons learnt from two operational research projects, African SWIFT and ForPAc, on pathways for embedding co-production into operational weather and climate services as the new standard operational procedure. Experiences across these projects identifies the following potential pathways for institutionalising co-production practises within operational weather and climate services: • Changing mindsets and systems to enable co-production of enhanced forecasts and systematic approaches for their use. • Strengthening in-country institutional links between operational forecasting centres and academic institutions to develop sustainable and improved forecasting capacities to meet users’ evolving weather and climate information needs. • Ensuring continued access to raw forecast data from global forecasting centres to continue and further develop new and improved decision-relevant forecasts. • Formalising user engagement in co-production, through agreeing standard and continuity of representation and commitment to providing regular feedback. • Mainstreaming stakeholder engagement and co-production in meteorological training, forecasting operations and environmental research. • Working through existing channels, such as agricultural and livestock extension services, and harnessing social media and remote ways of working to develop sustainable forms of continuous user engagement. • Establishing monitoring systems to demonstrate the benefits of investing in forecasting capacities. • Incentivising collaboration between complementary initiatives. • Addressing the risks of operationalising new and improved weather and climate services in resource- constrained environments

Using co-production to improve the appropriate use of sub-seasonal forecasts in Africa

Forecasts on sub-seasonal to seasonal (S2S) timescales have huge potential to aid preparedness and disaster risk reduction planning decisions in a variety of sectors. However, realising this potential depends on the provision of reliable information that can be appropriately applied in the decision-making context of users. This study describes the African SWIFT (Science for Weather Information and Forecasting Techniques) forecasting testbed which brings together researchers, forecast producers and users from a range of African and UK institutions. The forecasting testbed is piloting the provision of real-time, bespoke S2S forecast products to decision-makers in Africa. Drawing on data from the kick-off workshop and initial case study examples, this study critically reflects on the co-production process. Specifically, having direct access to real-time data has allowed user-guided iterations to the spatial scale, timing, visualisation and communication of forecast products to make them more actionable for users. Some key lessons for effective co-production are emerging. First, it is critical to ensure there is sufficient resource to support co-production, especially in the early co-exploration of needs. Second, all the groups in the co-production process require capacity building to effectively work in new knowledge systems. Third, evaluation should be ongoing and combine meteorological verification with decision-makers feedback. Ensuring the sustainability of project-initiated services within the testbed hinges on integrating the knowledge-exchanges between individuals in the co-production process into shaping sustainable pathways for improved operational S2S forecasting within African institutions

Customization and Validation of a Regional Climate Model Using Satellite Data Over East Africa

This study focused on the customization of the fourth generation International Center for Theoretical Physics Regional Climate Model version 4.4 and its ability to reproduce the mean climate and most dominant modes of variability over East Africa. The simulations were performed at a spatial resolution of 25 km for the period 1998–2013. The model was driven by ERA-Interim reanalysis. The customization focus was on cumulus and microphysics schemes during the Short Rains for the year 2000. The best physics combinations were then utilized for the validation studies. The East Africa region and Lake Victoria Basin region are adapted to carry out empirical orthogonal function analysis, during the Short and Long Rains. Tropical Rainfall Measuring Mission data was utilized in the validation of the model. The first mode of variability from the model and observational data during the Short Rains was associated with the warming of the Pacific Ocean and the sea surface temperature gradients over the Indian Ocean. During the Long rains, the inter-annual rainfall variability over the Lake Victoria region was associated with the sea surface temperature anomaly over the Indian Ocean and for the East Africa region the associations were weak. The drivers during the Long Rains over East Africa region were then further investigated by splitting the season to the March–April and May periods. The March–April period was positively correlated to the West Pacific and Indian Ocean dipole index, while May was associated with the Quasi-Biennial Oscillation. In conclusion, although the model can reproduce the dominant modes of variability as in the observational data sets during the Short Rains, skill was lower during the Long Rains

Evaluation of the skill of monthly precipitation forecasts from global prediction systems over the Greater Horn of Africa

The skill of precipitation forecasts from global prediction systems has a strong regional and seasonal dependence. Quantifying the skill of models for different regions and timescales is important, not only to improve forecast skill, but to enhance the effective uptake of forecast information. The sub-seasonal to seasonal prediction (S2S) database contains near real-time forecasts and re-forecasts from 11 operational centres and provides a great opportunity to evaluate and compare the skill of operational S2S systems. This study evaluates the skill of these state-of-the-art global prediction systems in predicting monthly precipitation over the Greater Horn of Africa. This comprehensive evaluation was performed using deterministic and probabilistic forecast verification metrics. Results from the analysis showed that the prediction skill varies with months and region. Generally, the models show high prediction skill during the start of the rainfall season in March and lower prediction skill during the peak of the rainfall in April. ECCC, ECMWF, KMA, NCEP and UKMO show better prediction skill over the region for most of the months compared with the rest of the models. Conversely, BoM, CMA, HMCR and ISAC show poor prediction skill over the region. Overall, the ECMWF model performs best over the region among the 11 models analyzed. Importantly, this study serves as a baseline skill assessment with the findings helping to inform how a subset of models could be selected to construct an objectively consolidated multi-model ensemble of S2S forecast products for the Greater Horn of Africa region, as recommended by the World Meteorological Organization

Atmospheric and oceanic conditions associated with early and late onset for eastern Africa short rains

Timing of the rainy season is essential for a number of climate sensitive sectors over Eastern Africa. This is particularly true for the agricultural sector, where most activities depend on both the spatial and temporal distribution of rainfall throughout the season. Using a combination of observational and reanalysis datasets, the present study investigates the atmospheric and oceanic conditions associated with early and late onset for Eastern Africa short rains season (October to December). Our results indicate enhanced rainfall in October and November during years with early onset and rainfall deficit in years with late onset for the same months. Early onset years are found to be associated with warmer sea surface temperatures (SSTs) in the western Indian Ocean, and an enhanced moisture flux and anomalous low-level flow into Eastern Africa from as early as the first dekad of September. The late onset years are characterised by cooler SSTs in the western Indian Ocean, anomalous westerly moisture flux and zonal flow limiting moisture supply to the region. The variability in onset date is separated into the interannual and decadal components, and the links with SSTs and low-level circulation over the Indian Ocean basin are examined separately for both timescales. Significant correlations are found between the interannual variability of the onset and the Indian Ocean dipole mode index. On decadal timescales the onset is shown to be partly driven by the variability of the SSTs over the Indian Ocean. Understanding the influence of these potentially predictable SST and moisture patterns on onset variability has huge potential to improve forecasts of the East African short rains. Improved prediction of the variability of the rainy season onset has huge implications for improving key strategic decisions and preparedness action in many sectors, including agriculture

Application of real time S2S forecasts over Eastern Africa in the co-production of climate services

A significant proportion of the population in Sub-Saharan Africa are vulnerable to extreme climatic conditions, hence there is a high demand for climate information. In response to this need, the Global Challenges Research Fund African Science for Weather Information and Forecasting Techniques has been undertaking a two-year testbed to co-produce tailored forecasts for different sectors using the sub-seasonal to seasonal forecast data- sets from the sub-seasonal to seasonal Real Time Pilot Initiative project. Sub-seasonal forecasts are essential for early warning and informed decision-making in the agriculture and food security sector. This study summarises the co-production process of climate services between the Intergovernmental Authority on Development (IGAD) Climate Prediction and Applications Centre and the Food Security and Nutrition Working Group for Eastern and Central Africa, highlighting the importance of efficient communication as well as the lessons learnt and chal- lenges faced in the co-production process. A case study approach is utilised to evaluate the model performance. Two contrasting case studies, one for an extreme rainfall event in week three in April and another for the evolution of tropical cyclone Gati were conducted for the year 2020. Skillful and timely climate information and services co-produced has the potential to increase the uptake, ownership, and appropriate use of sub-seasonal forecasts for resilience building in Eastern Africa

Exploiting sub-seasonal forecast predictability in Africa: a key to sustainable development

New real-time sub-seasonal forecast information is aiding preparedness and disaster risk reduction decisions in key flood- and drought-vulnerable sectors across Africa and enabling significant progress in sub-Saharan Africa towards the UN Sustainable Development Goals. These services are demonstrating the potential for wider development of sub-seasonal user-focussed services at scale across Africa. We make key recommendations to achieve this vision

Projected effects of 1.5 °C and 2 °C global warming levels on the intra-seasonal rainfall characteristics over the Greater Horn of Africa

This study examines the effects of 1.5 °C and 2 °C global warming levels (GWLs) on intra-seasonal rainfall characteristics over the Greater Horn of Africa. The impacts are analysed based on the outputs of a 25-member regional multi-model ensemble from the Coordinated Regional Climate Downscaling Experiment project. The regional climate models were driven by Coupled Model Intercomparison Project Phase 5 Global Climate Models for historical and future (RCP8.5) periods. We analyse the three major seasons over the region, namely March–May, June–September, and October–December. Results indicate widespread robust changes in the mean intra-seasonal rainfall characteristics at 1.5 °C and 2 °C GWLs especially for the June–September and October–December seasons. The March–May season is projected to shift for both GWL scenarios with the season starting and ending early. During the June–September season, there is a robust indication of delayed onset, reduction in consecutive wet days and shortening of the length of rainy season over parts of the northern sector under 2 °C GWL. During the October–December season, the region is projected to have late-onset, delayed cessation, reduced consecutive wet days and a longer season over most of the equatorial region under the 2 °C GWL. These results indicate that it is crucial to limit the GWL to below 1.5 °C as the differences between the 1.5 °C and 2 °C GWLs in some cases exacerbates changes in the intra-seasonal rainfall characteristics over the Greater Horn of Africa