Assessing the representation of teleconnective drivers of rainfall over Eastern Africa in global and regional climate models and projected future changes

Climate variability is an important characteristic of regional climate, and a subject to significant control from teleconnections. An extended diagnosis of the capacity of climate models to represent remote controls of regional climate (teleconnections) is vital for assessing model-based predictions of climate variability, understanding uncertainty in climate projections and model development. An important driver of climate variability for Africa is the sea surface temperature (SST) - rainfall teleconnection, such as the El Ni˜no/Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). In this study, an assessment of the teleconnection between tropical SSTs and Eastern African rainfall in global and regional climate models is presented, with particular attention paid to the propagation of large-scale teleconnection signals (as represented by model reanalyses and Coupled Global Climate models (CGCMs)) into the domain of the Regional Climate Models (RCMs). The teleconnection-rainfall relationship with the Eastern Africa region is assessed in two rainfall seasons (June-July-August-September and October-November- December) under present and future periods. Evaluation runs (RCMs driven by reanalysis datasets) and historical simulations (RCMs driven by CGCMs) are assessed to quantify the ability of the models to capture the teleconnection relationship. The future analysis is performed for two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) to assess future change in this relationship as a result of global warming. Using ERA-interim reanalysis as perfect boundary conditions, the RCMs adequately simulate the spatial and temporal distribution of rainfall in comparison with observations, although the model performance varies locally and seasonally within the region. Furthermore, the RCMs correctly capture the magnitude and spatial extent regional-scale seasonal rainfall anomalies associated with large-scale oceanic modes (ENSO and IOD). When the lateral boundary conditions are provided by CGCMs, RCMs barely capture the regional teleconnection patterns associated with large-scale modes, and mostly depend on the selection of the driving CGCM. Comparison of the CGCM-driven RCM simulations with the reanalysis-driven RCM simulations revealed that most of the errors in teleconnection found in the RCM simulations are inherited from the host CGCMs. The ERA-Interim driven downscaled results show better agreement with observed spatial teleconnection patterns than the CGCM driven downscaled results. Analysis of the CGCMs and corresponding downscaled results showed that in most cases both the CGCM and the corresponding downscaled simulations had similar teleconnection patterns, but in some cases the RCM results diverge to those of the driving CGCM results. It has been demonstrated that similarities in SST-rainfall teleconnection patterns between the RCM simulations and respective driving CGCM simulations are noted over the equatorial and southern part of the region during OND season, where the rainfall is primarily controlled by large-scale (synoptic-scale) features, with the RCMs maintaining the overall regional patterns from the forcing models. Di↵erences in RCM simulations from corresponding driving simulations are noted mainly over northern part of the domain during JJAS, which is most likely related to mesoscale processes that are not resolved by CGCMs. Looking at the model projections of the future, although the spatial pattern of teleconnections between ENSO/IOD and rainfall still persist, important changes in the strength of the teleconnection have been found. During JJAS, ENSO is an important driver of rainfall variability in the northern parts of the region where dry anomalies are associated with El Ni˜no and wetter anomalies with La Ni˜na. Both regional and global ensemble projections show higher rainfall during La Ni˜na and lower rainfall during El Ni˜no over the northern part of the region compared to the present period. During OND, the teleconnection between ENSO/IOD and rainfall is projected to strengthen (weaken) over Eastern horn of Africa (southern parts of the region) compared to the present period. This implies heavy seasonal rains associated with positive phases of ENSO and IOD will increase in future across the Eastern horn of Africa. The change OND rainfall teleconnections are stronger and also more consistent between the models and scenarios as compared to the change in JJAS teleconnections. These findings have an important implication for the water and agricultural managers and policies in the region to tackle the anticipated droughts and floods associated anthropogenic climate change. Finally, the analysis demonstrated that the largest source of uncertainty in the regional climate model simulations in the context of teleconnective forcing of rainfall over Eastern Africa is the choice of CGCM used to force the RCMs, reinforcing the understanding that the use of a single GCM to downscale climate predictions/projections and using the downscaled product for assessment of climate change projections is insufficient. Simulations from multiple RCMs nested in more than one GCM, as is undertaken in the Coordinated Regional Downscaling Experiment (CORDEX), are needed to characterize the uncertainty and provide estimates of likely ranges of future regional climate changes

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

Assessment of the performance of CORDEX Regional Climate Models in Simulating Eastern Africa Rainfall

This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region

Teaching Effectiveness of Postgraduate Diploma in Teaching and Integrated Curriculum Graduate Teachers: Investigating Students’ and Teachers’ Perceptions

A new teacher education package has been introduced in Ethiopia by the Ministry of Education, which is called the Postgraduate Diploma in Teaching (PGDT), for secondary schools since 2011, replacing the integrated curriculum teacher education program with the purpose of equipping trainees with the knowledge and skills needed. However, little research has been carried out on the effectiveness of the PGDT in relation to the previous (integrated curriculum) programme in the actual practices in secondary schools yet. This study, therefore, aims to assess the students’ and teachers’ perceptions of the teaching effectiveness of the PGDT and integrated curriculum graduate teachers in secondary schools in North Wollo Zone, Ethiopia. Data were gathered from participant students (n = 214) and teachers (n = 16) using purposive sampling. To gather data, questionnaires were employed. The data were analyzed quantitatively using mean, standard deviations, and one-sample t-test. The findings of the study revealed that students and teachers show slightly more positive perceptions of the effectiveness of PGDT, especially in subject matter knowledge; the scores are also significant. However, the results indicated that both the PGDT and integrated curriculum graduate teachers use the lecture method of teaching. Recommendations were forwarded for teacher development, instruction, and research on PGDT. Limitations and future directions of the study are also summarized and discussed

Teleconnection responses in multi‑GCM driven CORDEX RCMs over Eastern Africa

The ability of climate models to simulate atmospheric teleconnections provides an important basis for the use and analysis of climate change projections. This study examines the ability of COordinated Regional climate Downscaling EXperiment models, with lateral and surface boundary conditions derived from Coupled Global Climate Models (CGCMs), to simulate the teleconnections between tropical sea surface temperatures and rainfall over Eastern Africa. The ability of the models to simulate the associated changes in atmospheric circulation patterns over the region is also assessed. The models used in the study are Rossby Centre regional atmospheric model (RCA) driven by eight CGCMs and COnsortium for Small scale MOdeling (COSMO) Climate Limited-area Modelling (COSMO-CLM or CCLM) driven by four of the same CGCMs. Teleconnection patterns are examined using correlation, regression and composite analysis. In order to identify the source of the errors, CGCM-driven regional climate model (RCM) results are compared with ERA-Interim driven RCM results. Results from the driving CGCMs are also analyzed. The RCMs driven by reanalysis (quasi-perfect boundary conditions) successfully capture rainfall teleconnections in most examined regions and seasons. Our analysis indicates that most of the errors in simulating the teleconnection patterns come from the driving CGCMs. RCMs driven by MPI-ESM-LR, HadGEM2-ES and GFDL-ESM2M tend to perform relatively better than RCMs driven by other CGCMs. CanESM2 and MIROC5, and their corresponding downscaled results capture the teleconnections in most of the sub-regions and seasons poorly. This highlights the relative importance of CGCM-derived boundary conditions in the downscaled product and the need to improve these as well as the RCMs themselves. Overall, the results produced here will be very useful in identifying and selecting CGCMs and RCMs for the use of climate change projecting over the Eastern Africa.JRC.H.7-Climate Risk Managemen

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

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

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