Circulation Patterns Associated with Current and Future Rainfall over Ethiopia and South Sudan from a Convection-Permitting Model

Ethiopia and South Sudan contain several population centers and important ecosystems that depend on July–August rainfall. Here we use two models to understand current and future rainfall: the first ever pan-African numerical model of climate change with explicit convection and a parameterized model that resembles a typical regional climate model at 4.5 and 25 km horizontal grid-spacing, respectively. The explicit convection and higher resolution of the first model offer a greatly improved representation of both the frequency and intensity of rainfall, when compared to the parametrized convection model. Furthermore, only this model has success in capturing the east–west propagation of rainfall over the full diurnal cycle. Enhanced low-level westerlies were found for extremely wet days, though this response was weaker in the explicit convection model. The increased orographic detail in the explicit model resulted in the splitting of the low-level Turkana Jet core into smaller cores, and inhibited its penetration far into South Sudan. Some projected changes were found to be independent of model, such as changes in the strength of Somali and Turkana jets, as well as the shifting of Turkana jet core to lower levels. However, the explicit model end-of-century projections showed a larger and clearer decrease in wet days, accompanied by an increase in wet day intensity and extreme rainfall. This study highlights serious limitations of relying solely on simulations which parameterize convection to inform decisions in the region of South Sudan and Ethiopia

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–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 characterized 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

Scientific understanding of East African climate change from the HyCRISTAL project

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic

Scientific understanding of East African climate change from the HyCRISTAL project

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic

Advances, gaps and way forward in provision of climate services over the Greater Horn of Africa

The Greater Horn of Africa is prone to extreme climatic conditions, thus, making climate services increasingly important in supporting decision-making processes across a range of climate sensitive sectors. This study aims to provide a comprehensive review of the recent advances, gaps and challenges in the provision of climate services over the region, for each of the components of the Global Framework for Climate Services. The study explores various milestones that have been achieved toward climate service delivery. The achievements include improvement of station network coverage, and enhancing the capacity of member states to utilize various tools in data analysis and generate routine climate products. The advancement in science, and availability of High-Performance Computing has made it possible for forecast information to be provided from nowcasting to seasonal timescales. Moreover, operationalizing of the objective forecasting method for monthly and seasonal forecasts has made it possible to translate tercile forecasts for applications models. Additionally, innovative approaches to user engagement through co-production, communication channels, user-friendly interfaces, and dissemination of climate information have also been developed. Despite the significant progress that has been made in the provision of climate services, there are still many challenges and gaps that need to be overcome in order to ensure that these services are effectively meeting the needs of users. The research of the science underpinning climate variability, capacity building and stakeholder engagement, as well as improved data management and quality control processes are some of the gaps that exist over the region. Additionally, communication and dissemination of climate information, including timely warnings and risk communication, require improvement to reach diverse user groups effectively. Addressing these challenges will require strengthened partnerships, increased investment in capacity building, enhanced collaboration between the climate information producers and stakeholders, and the development of user-friendly climate products. Bridging these gaps will foster greater resilience to climate-related hazards and disasters in the Greater Horn of Africa and support sustainable development in the region

A westward extension of the warm pool leads to a westward extension of the Walker circulation, drying eastern Africa

Observations and simulations link anthropogenic greenhouse and aerosol emissions with rapidly increasing Indian Ocean sea surface temperatures (SSTs). Over the past 60 years, the Indian Ocean warmed two to three times faster than the central tropical Pacific, extending the tropical warm pool to the west by ~40° longitude (><4,000 km). This propensity toward rapid warming in the Indian Ocean has been the dominant mode of interannual variability among SSTs throughout the tropical Indian and Pacific Oceans (55°E–140°W) since at least 1948, explaining more variance than anomalies associated with the El Niño-Southern Oscillation (ENSO). In the atmosphere, the primary mode of variability has been a corresponding trend toward greatly increased convection and precipitation over the tropical Indian Ocean. The temperature and rainfall increases in this region have produced a westward extension of the western, ascending branch of the atmospheric Walker circulation. Diabatic heating due to increased mid-tropospheric water vapor condensation elicits a westward atmospheric response that sends an easterly flow of dry air aloft toward eastern Africa. In recent decades (1980–2009), this response has suppressed convection over tropical eastern Africa, decreasing precipitation during the ‘long-rains’ season of March–June. This trend toward drought contrasts with projections of increased rainfall in eastern Africa and more ‘El Niño-like’ conditions globally by the Intergovernmental Panel on Climate Change. Increased Indian Ocean SSTs appear likely to continue to strongly modulate the Warm Pool circulation, reducing precipitation in eastern Africa, regardless of whether the projected trend in ENSO is realized. These results have important food security implications, informing agricultural development, environmental conservation, and water resource planning

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

Background Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann–Kendall test and Sen’s slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique. Results According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool sub-humid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r2 = 0.62) and negatively correlated to the minimum (r2 = 0.58) and maximum (r2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin. Conclusion The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale

Seasonal-to-Interannual Variability of Ethiopia/Horn of Africa Monsoon. Part I: Associations of Wavelet-Filtered Large-Scale Atmospheric Circulation and Global Sea Surface Temperature

Horn of Africa rainfall varies on multiple time scales, but the underlying climate system controls on this variability have not been examined comprehensively. This study therefore investigates the linkages between June–September Horn of Africa (especially Ethiopian) rainfall and regional atmospheric circulation and global sea surface temperature (SST) variations on several key time scales. Wavelet analysis of 5-day average or monthly total rainfall for 1970–99 identifies the dominant coherent modes of rainfall variability. Several regional atmospheric variables and global SST are then identically wavelet filtered, based on the rainfall frequency bands. Regression, correlation, and composite analyses are subsequently used to identify the most important rainfall–climate system time-scale relationships. The results show that Ethiopian monsoon rainfall variation is largely linked with annual time-scale atmospheric circulation patterns involving variability in the major components of the monsoon system. Although variability on the seasonal (75–210 days), quasi-biennial (QB; 1.42–3.04 yr), and El Niño–Southern Oscillation (ENSO; 3.04–4.60 yr) time scales accounts for much less variance than the annual mode (210 days–1.42 yr), they significantly affect Ethiopian rainfall by preferentially modulating the major regional monsoon components and remote teleconnection linkages.The seasonal time scale largely acts in phase with the annual mode, by enhancing or reducing the lower-tropospheric southwesterlies from the equatorial Atlantic during wet or dry periods. The wet QB phase strengthens the Azores and Saharan high and the tropical easterly jet (TEJ) over the Arabian Sea, while the wet ENSO phase enhances the Mascarene high, the TEJ, and the monsoon trough more locally. The effects of tropical SST on Ethiopian rainfall also are prominent on the QB and ENSO time scales. While rainfall–SST correlations for both the QB and ENSO modes are strongly positive (negative) over the equatorial western (eastern) Pacific, only ENSO exhibits widespread strong negative correlations over the Indian Ocean. Opposite QB and ENSO associations tend to characterize dry Ethiopian conditions. The relationships identified on individual time scales now are being used to develop and validate statistical prediction models for Ethiopia

Regional climate modeling : advances, constraints and use for adaptation planning

This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km(2)) in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH) of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced) is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960-1971 is selected for calibration while the period 1972-1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT) from the European program ENSEMBLES, forced by two global climate models (GCM): ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature) are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to reproduce the occurrence of dry days but still underestimates them. From the statistical distribution point of view, corrected SMH precipitation data introduced into the MBBH model were not able to reproduce extreme runoff values generated by observed precipitation data during validation (larger than 80 mm/month). This may be due to the SMH weakness in reproducing moderate and high rainfall levels even after bias correction. This approach may be considered as a way to use regional climate models (RCM) model outputs for studying hydrological impact

Representation of land–atmosphere coupling processes over Africa in coupled model intercomparison project Phase 6

Climate models are useful tools for monthly to decadal prediction of the evolution of climate. This study assesses how CMIP6 models represent soil moisture-latent heat regimes and coupling processes between the land and atmosphere. Metrics considered are terrestrial and atmospheric coupling indices to show the nature and strength of the coupling over Africa, focusing on the March to May (MAM) and June to August (JJA) seasons over East, Central, and West Africa. Characterization of the annual cycle indicates that model biases are highest during the peak of the rainfall season and least during the dry season, while soil moisture biases correspond with rainfall. Models show appreciable sensitivity to regional characteristics; there was model consensus in representing East Africa and the Sahel as regions of limited soil moisture, while major differences were noted in the wet regime over Central Africa. Most CMIP6 models tend to overestimate the strength of the terrestrial and atmospheric coupling pathways over East and Southern Africa. Inter-model differences in coupling indices could be traced to their inter-annual variability rather than the mean biases of the variables considered. These results encourage further advancement of land surface schemes in the next generation of climate models for a better representation of climate over Africa