Search

This study analyses the spatiotemporal variability of meteorological drought over Africa and its nine climate subregions from an ensemble of 19 multisource datasets (gauge-based, satellite-based and reanalysis) over the period 1983–2014. The standardized precipitation index (SPI) is used to represent drought on a 3-month scale. We analyse various drought characteristics (duration, events, frequency, intensity, and severity) for all drought months, and moderate, severe, and extreme drought conditions. The results show that drought occurs across the continent, with the equatorial regions displaying more negative SPI values, especially for moderate and severe droughts. On the other hand, Eastern Sahara and Western Southern Africa portray less negative SPI values. The study also reveals that extreme drought months have the largest interannual variability, followed by all drought months and severe drought months. The trend analysis of SPI shows a significantly increasing trend in drought episodes over most regions of Africa, especially tropical areas. Drought characteristics vary greatly across different regions of Africa, with some areas experiencing longer and more severe droughts than others. The equatorial region has the highest number of drought events, with longer durations for severe and extreme drought months. The Eastern Sahara region has a low number of drought events but with longer durations for moderate, severe, and extreme drought months, leading to an overall higher drought severity over the area. In contrast, Western Southern Africa and Madagascar display a consistently low drought severity for all categories. The study demonstrates the importance of conducting drought analysis for different drought levels instead of using all drought months. Drought management and adaptation strategies need to enhance community resilience to changing drought situations and consider drought variability in order to mitigate different impacts of drought across the continent. [ABSTRACT FROM AUTHOR]

Climate models are vital to the assessment of the impacts of climate change in the Central African regions. Establishing how well models reproduce key processes is important to the confidence we attach to these tools. This study examines model representation of the September to November characteristics, such as location and intensity, of the African Easterly Jet (AEJ) north and south in a sample of 16 commonly evaluated CMIP5 and CMIP6 models and in two reanalyses (ERA5 and MERRA2). The analysis evolves to assess key drivers of the AEJ from energetic interactions, the characteristics of mid-level highs and thermal lows and the nature of surface thermal heating. Over West Africa, several models miss the southeast-northwest orientation of the AEJ-N core, leading to a gap of around 60 in the location of the jet while most CMIP5 models also fail to locate AEJ-S over southern Central Africa. In general, the spread of simulated AEJ locations around reanalyses is larger for the CMIP5 sample compared to CMIP6 equivalent models, indicating improvement from CMIP5 to CMIP6 in this 16 model subset. However, this improvement in some CMIP6 models (e.g. GISS-E2-1-G and MIROC6) is not related to a maximum surface meridional gradient in temperature. Most CMIP5 and CMIP6 models underestimate the surface temperature gradient over AEJ-N region. As a first order diagnostic of the jet's acceleration, most coupled models better simulate the atmospheric energetic interactions over AEJ-N region that leads to its strong contribution to AEJ-N maintenance compared to AEJ-S. This study strengthens our understanding of the mid-level circulation over Central Africa by detecting gaps in the mechanisms maintaining the AEJ in coupled models and highlights processes that should be improved in future ensembles. [ABSTRACT FROM AUTHOR]

The redistribution of biological (transpiration) and non‐biological (interception loss, soil evaporation) fluxes of terrestrial evaporation via atmospheric circulation and precipitation is an important Earth system process. In vegetated ecosystems, transpiration dominates terrestrial evaporation and is thought to be crucial for regional moisture recycling and ecosystem functioning. However, the spatial and temporal variability in the dependency of precipitation on transpiration remains understudied, particularly in sparsely sampled regions like Africa. Here, we investigate how biological and non‐biological sources of evaporation in Africa contribute to rainfall over the major watersheds in the continent. Our study is based on simulated atmospheric moisture trajectories derived from the Lagrangian model FLEXPART, driven by 1° resolution reanalysis data over 1981–2016. Using daily satellite‐based fractions of transpiration over terrestrial evaporation, we isolate the contribution of vegetation to monthly rainfall. Furthermore, we highlight two watersheds (Congo and Senegal) for which we explore intra‐ and interannual variability of different precipitation sources, and where we find contrasting patterns of vegetation‐sourced precipitation within and between years. Overall, our results show that almost 50% of the annual rainfall in Africa originates from transpiration, although the variability between watersheds is large (5%–68%). We conclude that, considering the current and projected patterns of land use change in Africa, a better understanding of the implications for continental‐scale water availability is needed. Key Points: We show the contribution of transpiration to precipitation over 25 African watersheds based on satellite data and Lagrangian modelingTranspiration contributes to more than 50% of the precipitation over the African continent, although the variability among watersheds is largeThe Congo and Senegal show contrasting trends in precipitation, seemingly associated with different contributions of transpiration and oceanic evaporation [ABSTRACT FROM AUTHOR]

Although climate models are important for making projections of future climate, little attention has been devoted to model simulation of the complex climate of Central Africa (CA). This study investigates rainfall biases through processes in three versions of the Met Office Unified Model over CA with both coupled and atmosphere‐only formulations for each version. The study shows that the models depict a wet (dry) bias over the eastern (coastal western) CA in the September–November season with the wet (dry) bias stronger in coupled (atmosphere‐only) models. Here, we explore potential regional to large‐scale causes of these biases. Results reveal that the overestimation of the simulated sinking branch of the Atlantic‐Congo zonal overturning cell is associated with a strong near‐surface temperature and pressure gradient between CA and the eastern Atlantic Ocean. This leads to strong low‐level westerlies (LLWs) which dry the coastal western CA and strengthen the intensity of the Congo basin cell. Over eastern CA, the wet bias is partially due to the misrepresentation in the strength of both African easterly jet components that shift the mid‐tropospheric moisture flux convergence southward favouring more convection south of the equator. Furthermore, the overestimation in the simulated width and intensity of the Congo basin cell is associated with a strong low‐level moisture convergence over eastern CA which contributes to more precipitation. Remote contributions to the wet bias come from both the Atlantic and the Indian Oceans. The simulated Atlantic‐Congo zonal overturning circulation dries the coast through its overestimated lower branch (LLWs) which moves further into the continent and advects more moisture to the eastern CA. In the meantime, during positive Indian Ocean Dipole years, the advected moisture from the Indian Ocean to the CA region is overestimated in models, much more in coupled models and contributes to the eastern CA wet bias. [ABSTRACT FROM AUTHOR]

The synoptic precipitation variability over Central Africa (CA) in the March-to-May (MAM) and September-to-November (SON) seasons is investigated in this study. The composite analysis is used to highlight the evolution of synoptic precipitation, related convection, and dynamic fields. Composite analysis findings show that synoptic precipitation anomalies increase/fade with an increase/decrease in convection, with the largest amplitude over 5° S–10° N and 2.5–20° E in MAM and 5° N–7.5° N and 5–15° E in SON. Precipitation anomalies and convection associated with the synoptic variability progress eastward preceded (followed) by eastward (westward) low-level wind. This synoptic sequence is associated with a downward motion and an inflow, indicating the storm's presence, which contributes significantly to precipitation initiation over CA. The empirical orthogonal function for precipitation during the SON season is lower than that observed during the MAM season in the context of the size and spatial pattern. During these precipitation occurrences, the zonal moisture component contributes the most to the moisture initiation over the region. The findings of this study show that the observed convergence/divergence position remains unchanged in intensity irrespective of the positive/negative precipitation events. Overall, the synoptic-scale conditions in MAM contribute around 58% of the total variability in precipitation. [ABSTRACT FROM AUTHOR]

In this study we evaluate the reliability of the Regional Climate Model (RegCM4.6) by performing several sensitivity tests at 50 km horizontal resolution using 10 convection schemes or combination of convection schemes. Emphasis on model output is made for the September-October--November 2017-2019 seasonal period. Part of the Central African region, five sub-regions, was identified. The simulated temperatures are compared to the daily climatology of near-surface temperature of the European Centre for Medium-Range Weather Forecasts Reanalysis fifthgeneration and the National Center for Environmental Prediction datasets, while the simulated precipitations are compared to the precipitation of the Global Precipitation Climatology Project and Climate Hazards Group Infrared Precipitation with Stations datasets. In most analyses, the Grell scheme with Arakawa--Schubert closure assumption tends to have the best index of agreement but its spatial distribution shows underestimation of rainfall. Generally, the Emanuel convection scheme is more suitable to represent rainfall and temperature over Central Africa. Compared to our previous study (Komkoua Mbienda et al., International Journal of Climatology, 2017, 37, 328-342), the present study shows that we have to pay attention to the choice of convective scheme when using any version of RegCM4 released for climate study over Central Africa. This choice is strictly related to the RegCM version released, the study years and the season. It is important to note, however, that the results presented are a preliminary study of the response to the selected convection schemes. The analysis uses a limited sample of climate model simulation (three model years for each convection scheme). Follow-up work, featuring longer duration climate simulations and a full assessment of statistical significance, is therefore required to confirm the robustness of the analysis presented. [ABSTRACT FROM AUTHOR]

Tropical Africa is home to an astonishing biodiversity occurring in a variety of ecosystems. Past climatic change and geological events have impacted the evolution and diversification of this biodiversity. During the last two decades, around 90 dated molecular phylogenies of different clades across animals and plants have been published leading to an increased understanding of the diversification and speciation processes generating tropical African biodiversity. In parallel, extended geological and palaeoclimatic records together with detailed numerical simulations have refined our understanding of past geological and climatic changes in Africa. To date, these important advances have not been reviewed within a common framework. Here, we critically review and synthesize African climate, tectonics and terrestrial biodiversity evolution throughout the Cenozoic to the mid‐Pleistocene, drawing on recent advances in Earth and life sciences. We first review six major geo‐climatic periods defining tropical African biodiversity diversification by synthesizing 89 dated molecular phylogeny studies. Two major geo‐climatic factors impacting the diversification of the sub‐Saharan biota are highlighted. First, Africa underwent numerous climatic fluctuations at ancient and more recent timescales, with tectonic, greenhouse gas, and orbital forcing stimulating diversification. Second, increased aridification since the Late Eocene led to important extinction events, but also provided unique diversification opportunities shaping the current tropical African biodiversity landscape. We then review diversification studies of tropical terrestrial animal and plant clades and discuss three major models of speciation: (i) geographic speciation via vicariance (allopatry); (ii) ecological speciation impacted by climate and geological changes, and (iii) genomic speciation via genome duplication. Geographic speciation has been the most widely documented to date and is a common speciation model across tropical Africa. We conclude with four important challenges faced by tropical African biodiversity research: (i) to increase knowledge by gathering basic and fundamental biodiversity information; (ii) to improve modelling of African geophysical evolution throughout the Cenozoic via better constraints and downscaling approaches; (iii) to increase the precision of phylogenetic reconstruction and molecular dating of tropical African clades by using next generation sequencing approaches together with better fossil calibrations; (iv) finally, as done here, to integrate data better from Earth and life sciences by focusing on the interdisciplinary study of the evolution of tropical African biodiversity in a wider geodiversity context. [ABSTRACT FROM AUTHOR]

The Congo basin in central equatorial Africa is home to some of the most intense convection in the global tropics. Mesoscale convective systems (MCSs) provide much of the annual rainfall over this region during the March–April–May (MAM) and September–October–November (SON) rainy seasons. Features of these systems are essential to rainfall variability in this region and greatly impact human health, agriculture, livestock, and drought monitoring. Knowledge of variability is hindered by the lack of in‐situ observations and meteorological stations. The present study identifies and tracks MCSs for the 33‐year period 1983–2015 for MAM and SON. MCS and environmental parameters are calculated for the rainy seasons using satellite and reanalysis data. Spatial distributions of MCS parameters and diurnal cycles for select MCS parameters are compared to prior research. Statistical significance testing is performed to determine if there are meaningful differences between the seasons. Seasonal differences are briefly discussed. 650 hPa relative vorticity patterns suggest localized terrain effects may play a role near a local maximum in MCS initiation frequency in the lee of the Great Rift Valley. Spatial distributions of 33‐year MCS counts, trajectories, speeds, sizes, maximum intensities, and durations, based on initiation locations, agree well with prior research. Differences between seasons are statistically significant and variable and latitude dependent. There is high interannual variability among all MCS and environmental parameters. [ABSTRACT FROM AUTHOR]

We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs (SMHI-RCA4 and HCLIM38-ALADIN) are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100, and 200 km. In addition to the two RCMs, two different parameter settings (configurations) of the same RCA4 are used. By contrasting different downscaling experiments, it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation, while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle in precipitation is completely controlled by model formulation (convection scheme), while its amplitude is a function of resolution. However, the impact of higher resolution on the time-mean climate is mixed. An improvement in one region/season (e.g. reduction in dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). At the same time, higher resolution leads to a more realistic distribution of daily precipitation. Consequently, even if the time-mean climate is not always greatly sensitive to resolution, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and can, in general, not be considered as an added value of downscaling. [ABSTRACT FROM AUTHOR]

In this study, an analysis of present day climate simulation (1998–2008) is presented for the Central African (CA) region with the COnsortium for Small‐scale MOdelling in CLimate Mode (CCLM) regional climate model, forced by the ERA‐Interim (ERAINT) reanalysis data. The ability of the CCLM to simulate the observed precipitation with particular focus on the mean spatial pattern, low‐level circulation, seasonal cycles, and daily characteristics is evaluated. Likewise, the added value of the regional model CCLM compared to the driving ERAINT reanalysis is also investigated. It is shown that ERAINT and CCLM exhibit quite different sign of bias, which is an indication of the importance of internal variability and fine scale processes representation for the simulation of surface climate. Despite the CCLM is constantly dry over southern CA, the model succeeds to reproduce reasonably the mean spatial patterns of precipitation and low‐level circulation features, along with the associated seasonal cycles over the whole CA and majority of the five selected analysis sub‐regions. Results also show that daily precipitation indices are well represented, although the better performance greatly depends on the considered seasons. Nevertheless, CCLM substantially outperforms the ERAINT daily precipitation characteristics, thus highlighting the added value of the downscaling exercise over the region. The analysis of daily precipitation indices also reveals that the dry character of the model could probably be connected to the underestimation of the simulated less intense events, which in turn result to an overestimation of the simulated dry spell duration. [ABSTRACT FROM AUTHOR]

Climate change is expected to significantly impact on the availability of water resources in West and Central Africa through changes in rainfall, temperature and evapotranspiration. Understanding these changes in this region, where surface water is fundamental for economic activity and ecosystem services, is of paramount importance. In this study, we examine the potential impacts of climate variability and change on hydrological systems by the mid-21st century in West and Central Africa, as well as the uncertainties in the different climate-impact modelling pathways. Simulations from nine global climate models downscaled using the Rossby Centre Regional Climate model (RCA4) are evaluated and subsequently bias-corrected using a nonparametric trend-preserving quantile mapping approach. We then use two conceptual hydrological models (GR2M and IHACRES), and a regression-based model built upon multi-timescale sea surface temperatures and streamflow teleconnections, to understand hydrological processes at the subcontinental scale and provide hydrological predictions for the near-term future (2020–2050) under the RCP4.5 emission scenario. The results highlight a zonal contrast in future precipitation between western (dry) and eastern (wet) Sahel, and a robust signal in rising temperature, suggesting an increase in potential evapotranspiration, across the multi-model ensemble. Overall, across the region, a significant increase in discharge (~ + 5%) is expected by the mid-21st century, albeit with high uncertainties reported over most of Central Equatorial Africa inherent to climate models and gridded observation data quality. Interestingly, in this region, teleconnections-based regression models tend to be an alternative to hydrological models. [ABSTRACT FROM AUTHOR]

The African Easterly Jet South (AEJ-S) is an important feature of the central African mid tropospheric circulation and has been identified as a key contributor to convection over the region. This study uses 21-year (1983–2003) Reanalysis data sets of ERA-Interim, NCEP2 and MERRA2 to establish mechanisms related to AEJ-S dynamics. Results demonstrate that AEJ-S is dominated by rotational circulation and is maintained by a mid-level high that forms over the Kalahari region during September to November. Because of the role played by this high pressure system in the AEJ-S dynamics, an effort is made to understand how this anticyclone develops. We show that this mid-tropospheric high over the Kalahari region is established in response to lower tropospheric dry convection over the region from September to November. At the core of this high, anticyclonic circulation is induced and maintains AEJ-S located at the northern flank of the high. A link between AEJ-S dynamics and southern subtropical westerly waves is also revealed. It is shown that, when waves amplify over the southern subtropics, they modify lower tropospheric heating. Depending on the phase of the wave, this modifies the cross latitude temperature gradient throughout equatorial regions, therefore modulating the intensity of the jet. By clarifying the mechanisms that govern the AEJ-S, this research work contributes to insight into central Africa climate mechanisms and also suggests a link between central Africa and Southern Africa climate systems. This research work also improves the foundation of new mechanisms that help to identify suitable metrics for the evaluation of Global models over the Central Africa region. [ABSTRACT FROM AUTHOR]

In this paper, daily characteristics of the Central Africa rainfall are assessed using the regional model REMO in the framework of contributions to the CORDEX-Africa project. The model is used to dynamically downscale two global climate models (MPI-ESM-LR and EC-EARTH) for the present (1981–2005) and future (2041–2065, 2071–2095) climate under the Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5 emission scenarios. A substantial spatio-temporal variability of the daily precipitation characteristics is obtained, as well as varying inferences for individual indices. For the present days, both REMO's runs capture reasonably well the mean seasonal rainfall, the frequency of wet days, the threshold of extreme rainfall, and the cumulative frequency of daily rainfall. The model better simulates the frequency of rainy days than their intensity. It is found that origins of model biases differ as a function of regions. Over the continent, boundary conditions tend to influence the spatial distribution of rainfall whereas over oceanic and coastal regions, REMO's physics seems to dominate over the boundary forcing. The projected frequency of wet days shows a decrease along the twenty-first century over most part of the continent. Throughout the century, all scenarios of REMO decrease the rate of rainfall with increasing intensity, and which will be noticeable in the Sahelian region at late twenty-first century. Furthermore, the extreme event thresholds decrease over Sahelian regions and increase along the coastal regions. [ABSTRACT FROM AUTHOR]

Reliable drought projections are crucial for the effective managements of future drought risk. Most of the existing drought projections over Southern Africa are based on precipitation alone, neglecting the influence of potential evapotranspiration (PET). The present study shows that inclusion of PET may alter the magnitude and robustness of the drought projections. The study used two drought indices to project potential impacts of global warming on Southern African droughts, focusing on four major river basins. One of the drought indices (SPEI: Standardized Precipitation Evapotranspiration Index) is obtained from climate water balance (i.e. precipitation minus potential evapotranspiration) while the other (SPI: Standardized Precipitation Index) is calculated from precipitation alone. For the projections, we analyzed multi-model regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level and used the self-organizing maps to classify the drought projections into groups based on their similarities. Our results show that the CORDEX simulations give a realistic representation of all the necessary climate variables for quantifying droughts over Southern Africa. The simulations project a robust increase in SPEI drought intensity and frequency over Southern Africa and indicate that the magnitude of the projection increases with increasing GWLs, especially over the various river basins. In contrast, they project a non-significant change in SPI droughts at all the GWLs. The majority of the simulations clearly distinguish between the projected SPEI and SPI drought patterns, and the distinction becomes clearer with increasing GWLs. Hence, using precipitation alone for drought projection over Southern Africa may underestimate the magnitude and robustness of the projections. This study has application in mitigating climate change impacts on drought risk over Southern African river basins in the future. [ABSTRACT FROM AUTHOR]

An intercomparison of seven gridded rainfall products incorporating satellite data (ARC, CHIRPS, CMORPH, PERSIANN, TAPEER, TARCAT, TMPA) is carried out over Central Africa, by evaluating them against three observed datasets: (a) the WaTFor database, consisting of 293 (monthly records) and 154 (daily records) rain‐gauge stations collected from global datasets, national meteorological services and monitoring projects, (b) the WorldClim v2 gridded database, and (c) a set of stations expanded from the FAOCLIM network, these two latter sets describing climate normals. All products fairly well reproduce the mean rainfall regimes and the spatial patterns of mean annual rainfall, although with some discrepancies in the east–west gradient. A systematic positive bias is found in the CMORPH product. Despite its lower spatial resolution, TAPEER shows reasonable skills. When considering daily rainfall amounts, TMPA shows best skills, followed by CMORPH, but over the central part of the Democratic Republic of the Congo, TARCAT is amongst the best products. Skills ranking is however different at the interannual time‐scale, with CHIRPS and TMPA performing best, though PERSIANN has comparable skills when only fully independent stations are used as reference. A preliminary study of Southern Hemisphere dry season variability, from the example of Kinshasa, shows that it is a difficult variable to capture with satellite‐based rainfall products. Users should still be careful when using any product in the most data‐sparse regions, especially for trend assessment. [ABSTRACT FROM AUTHOR]

Long‐term trends in equatorial African rainfall have proven difficult to determine because of a dearth in ground‐measured rainfall data. Multiple, satellite‐based products now provide daily rainfall estimates from 1983 to the present at relatively fine spatial resolutions, but in order to assess trends in rainfall, they must be validated alongside ground‐based measurements. The purpose of this paper is twofold: (a) to assess the accuracy of four rainfall products covering the past several decades in western Uganda; and (b) to ascertain recent, multi‐decadal trends in annual rainfall for the region. The four products are African Rainfall Climatology Version 2 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR), and TAMSAT African Rainfall Climatology And Timeseries (TARCAT). The bias and accuracy of 10‐day, monthly, and seasonal rainfall totals of the four products were assessed using approximately 10 years of data from 10 rain gauges. The homogeneity of the products over multiple time periods was assessed using change‐point analysis. The accuracy of the four products increased with an increase in temporal scale, and CHIRPS was the only product that could be considered sufficiently accurate at estimating seasonal rainfall totals throughout most of the region. TARCAT tended to underestimate totals, and ARC2 and PERSIANN were in general the least accurate products. Only annual rainfall estimates from CHIRPS and TARCAT were significantly correlated with ground‐measured rainfall totals. TARCAT was the most homogeneous product, while ARC2, CHIRPS, and PERSIANN had significant negative change points that caused a drying bias over the 1983–2016 period. After adjusting the satellite‐based rainfall estimates based on the timing and magnitude of the change points, annual rainfall totals derived from all four products indicated that western Uganda experienced significantly increasing rainfall from 1983 to 2016. [ABSTRACT FROM AUTHOR]

Smallholder farmers and livestock keepers in sub-Saharan Africa are on the frontlines of climate variability and change. Yet, in many regions, a paucity of weather and climate data has prevented rigorous assessment of recent climate trends and their causes, thereby limiting the effectiveness of forecasts and other services for climate adaptation. In rainfed systems, farmer perceptions of changing rainfall and weather patterns are important precursors for annual cropping decisions. Here, we propose that combining such farmer perceptions of trends in seasonal rainfall with satellite-based rainfall estimates and climate station data can reduce uncertainties regarding regional climatic trends. In western Uganda, a rural and climatically complex transition zone between eastern and central equatorial Africa, data from 980 smallholder households suggest distinct changes in seasonal bimodal rainfall over recent decades, specifically wetter rainy seasons and drier dry seasons. Data from three satellite-based rainfall products beginning in 1983 largely corroborate respondent perceptions over the last 10–20 years, particularly in the southernmost sites near Queen Elizabeth National Park. In addition, combining all three information sources suggests an increasing trend in annual rainfall, most prominently in the north near Murchison Falls National Park over the past two decades; this runs counter to recent research asserting the presence of a drying trend in the region. Our study is unique in evaluating and cross-validating these multiple data sources to identify climatic change affecting people in a poorly understood region, while providing insights into regional-scale climate controls. [ABSTRACT FROM AUTHOR]

Photoassimilate distribution inside leaves is less studied than photosynthesis, and yet the topic is important as it gives insights into the vital roles played by leaves in plant survival. We combined greenhouse measurements of light response curves with 11C-labelling using leaves of 3-year-old potted Maesopsis eminii Engl. trees to improve our understanding of its leaf carbon physiology. This fast-growing pioneer tree species showed low photosynthetic rates for a common tropical pioneer during well-watered reference conditions (5.0 ± 0.7 µmol m-2 s-1), which further decreased in response to drought. 11C-autoradiography indicated active phloem loading and/or rapid phloem transport rates. Active loading is uncommon in tree species, but might be related to deciduousness traits and continuous investment in growth, like in herbaceous active loaders. Active loading involves higher carbon allocation to growth, which might explain why low photosynthetic rates were observed in this fast-growing species. These findings suggest that examining photoassimilate distribution and transport may be critical for understanding the role tree physiology plays in terrestrial carbon cycling. [ABSTRACT FROM AUTHOR]

Previous studies show that Indo-Pacific sea surface temperature (SST) variations may help to explain the observed long-term drought during April–May–June (AMJ) since the 1990s over Central equatorial Africa (CEA). However, the underlying physical mechanisms for this drought are still not clear due to observation limitations. Here we use the AMIP-type simulations with 24 ensemble members forced by observed SSTs from the ECHAM4.5 model to explore the likely physical processes that determine the rainfall variations over CEA. We not only examine the ensemble mean (EM), but also compare the “good” and “poor” ensemble members to understand the intra-ensemble variability. In general, EM and the “good” ensemble member can simulate the drought and associated reduced vertical velocity and anomalous anti-cyclonic circulation in the lower troposphere. However, the “poor” ensemble members cannot simulate the drought and associated circulation patterns. These contrasts indicate that the drought is tightly associated with the tropical Walker circulation and atmospheric teleconnection patterns. If the observational circulation patterns cannot be reproduced, the CEA drought will not be captured. Despite the large intra-ensemble spread, the model simulations indicate an essential role of SST forcing in causing the drought. These results suggest that the long-term drought may result from tropical Indo-Pacific SST variations associated with the enhanced and westward extended tropical Walker circulation. [ABSTRACT FROM AUTHOR]

Smallholder farmers in Sub-Saharan Africa (SSA) are not only dealing with decreased production from land degradation, but are also impacted heavily by climate variability. Farmers perceive decreased rainfall or shortened rainy seasons throughout SSA; however, the link between perceptions and climate variability is complex, especially in areas with increasing land degradation. Moreover, little is known about climate variability and farmers' perceptions in central equatorial Africa. The purpose of this study is to quantify interannual rainfall variability from 1983 to 2014 in western Uganda and to relate the rainfall variability and associated changes in soil moisture to perceptions and coping strategies of local farmers. Surveys of 308 farming households and 14 group interviews were conducted near Kibale National Park, and daily satellite-based rainfall data for the region were extracted from the African Rainfall Climatology version 2 database. Results indicate a decrease in the long rains by approximately 3 weeks throughout much of the region; thus, soil-water deficits have intensified. Farmers perceived later onsets of both the short rains and long rains, while also reporting decreasing soil fertility and crop yields. Therefore, farmers' perceptions of rainfall variability in the Kibale region may reflect more the decrease in soil fertility than the shortened rainy seasons and decreased soil moisture. Expanding croplands has been the farmers' most prevalent coping strategy to decreased yields; however, nearly all the unfarmed land in western Uganda is now in protected areas. Consequently, western Uganda is facing a crisis at the nexus of population growth, land use change, and climate change. [ABSTRACT FROM AUTHOR]

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. [ABSTRACT FROM AUTHOR]

The rainforests are the great green heart of Africa, and present a unique combination of ecological, climatic and human interactions. In this synthesis paper, we review the past and present state processes of change in African rainforests, and explore the challenges and opportunities for maintaining a viable future for these biomes. We draw in particular on the insights and new analyses emerging from the Theme Issue on 'African rainforests: past, present and future' of Philosophical Transactions of the Royal Society B.A combination of features characterize the African rainforest biome, including a history of climate variation; forest expansion and retreat; a long history of human interaction with the biome; a relatively low plant species diversity but large tree biomass; a historically exceptionally high animal biomass that is now being severely hunted down; the dominance of selective logging; small-scale farming and bush meat hunting as the major forms of direct human pressure; and, in Central Africa, the particular context of mineral- and oil-driven economies that have resulted in unusually low rates of deforestation and agricultural activity. We conclude by discussing how this combination of factors influences the prospects for African forests in the twenty-first century. [ABSTRACT FROM AUTHOR]

The article discusses various papers published within the issue, including one on the impact of hunting on African rainforests, another on the history of climate variation in Africa since the Ice Age and a paper on the use of climate models to determine likely patterns of rainfall change and their links to changes in ocean surface temperatures.

Background: Although the molecular basis of resistance to a number of common antimalarial drugs is well known, a geographic description of the emergence and dispersal of resistance mutations across Africa has not been attempted. To that end we have characterised the evolutionary origins of antifolate resistance mutations in the dihydropteroate synthase (dhps) gene and mapped their contemporary distribution. Methods and Findings: We used microsatellite polymorphism flanking the dhps gene to determine which resistance alleles shared common ancestry and found five major lineages each of which had a unique geographical distribution. The extent to which allelic lineages were shared among 20 African Plasmodium falciparum populations revealed five major geographical groupings. Resistance lineages were common to all sites within these regions. The most marked differentiation was between east and west African P. falciparum, in which resistance alleles were not only of different ancestry but also carried different resistance mutations. Conclusions: Resistant dhps has emerged independently in multiple sites in Africa during the past 10-20 years. Our data show the molecular basis of resistance differs between east and west Africa, which is likely to translate into differing antifolate sensitivity. We have also demonstrated that the dispersal patterns of resistance lineages give unique insights into recent parasite migration patterns. [ABSTRACT FROM AUTHOR]

In large freshwater river basins across the globe, the composite influences of large-scale climatic processes and human activities (e.g., deforestation) on hydrological processes have been studied. However, the knowledge of these processes in this era of the Anthropocene in the understudied hydrologically pristine South Central African (SCA) region is limited. This study employs satellite observations of evapotranspiration (ET), precipitation and freshwater between 2002 and 2017 to explore the hydrological patterns of this region, which play a crucial role in global climatology. Multivariate methods, including the rotated principal component analysis (rPCA) were used to assess the relationship of terrestrial water storage (TWS) in response to climatic units (precipitation and ET). The use of the rPCA technique in assessing changes in TWS is warranted to provide more information on hydrological changes that are usually obscured by other dominant naturally-driven fluxes. Results show a low trend in vegetation transpiration due to deforestation around the Congo basin. Overall, the Congo (r2 = 76%) and Orange (r2 = 72%) River basins maintained an above-average consistency between precipitation and TWS throughout the study region and period. Consistent loss in freshwater is observed in the Zambezi (−9.9 ± 2.6 mm/year) and Okavango (−9.1 ± 2.5 mm/year) basins from 2002 to 2008. The Limpopo River basin is observed to have a 6% below average reduction in rainfall rates which contributed to its consistent loss in freshwater (−4.6 ± 3.2 mm/year) from 2006 to 2012.Using multi-linear regression and correlation analysis we show that ET contributes to the variability and distribution of TWS in the region. The relationship of ET with TWS (r = 0.5) and rainfall (r = 0.8) over SCA provides insight into the role of ET in regulating fluxes and the mechanisms that drive precipitation in the region. The moderate ET–TWS relationship also shows the effect of climate and anthropogenic influence in their interactions. [ABSTRACT FROM AUTHOR]

Focuses on the cross-species amplification success of avian microsatellites in the redbilled quelea Quelea quelea. How microsatellites are used to study natural populations; Number of redbilled quelea in sub-Saharan Africa; Details of study testing available avian microsatellite primers in the redbilled quelea; Results of study.

The fidelity of 28 CMIP5 models and their multimodel mean (MMM) in simulating the historical climate of Africa is assessed in this study. For the historical period of 1975–2005, the spatial distribution of the seasonal precipitation is simulated with pattern correlation coefficients (PCCs) of 0.91, 0.95, 0.94, and 0.95 for March–May (MAM), June–August (JJA), September–November (SON), and December–February (DJF) seasons, respectively, when compared with the CRU data. For the surface temperature, the PCCs are 0.96, 0.98, 0.83, and 0.97, respectively, for the four seasons mentioned in the preceding. The root mean square error (RMSE) for the precipitation are 0.86, 0.77, 0.97, and 1.05 mm day−1 for the MAM, JJA, SON, and DJF seasons, respectively, whereas for the temperature, the respective values are 1.64, 1.28, 1.68, and 1.87°C. The study also assesses the performance of the models over four sub‐regions of Africa, viz. North, South, East, and West Africa. The observational trends show large spatial heterogeneity in warming for each season. The MMM does not show the strong warming over Africa and simulate generally a weak warming over most of the region. The MMM fails to capture the sign and magnitude of the observed precipitation trends. [ABSTRACT FROM AUTHOR]