African Rainfall Research Articles

Drivers and impacts of Eastern African rainfall variability

Eastern Africa exhibits bimodal rainfall consisting of long rains (March–May) and short rains (October–December), changes in which have profound socioeconomic and environmental impacts. In this Review, we examine the drivers and corresponding impacts of Eastern African rainfall variability. Remote teleconnections, namely the El Niño–Southern Oscillation and the Indian Ocean Dipole, exert a dominant influence on interannual variability. From the mid-1980s to 2010, the long rains have tended toward a drier state (trends of −0.65 to −2.95 mm season−1 year−1), with some recovery thereafter, while the short rains have become wetter since the mid 1980s (1.44 to 2.36 mm season−1 year−1). These trends, overlain by substantial year-to-year variations, affect the severity and frequency of extreme flooding and droughts, the stability of food and energy systems, the susceptibility to water-borne and vector-borne diseases, and ecosystem stability. Climate model projections of rainfall changes differ, but there is some consensus that the short rains will deliver more rainfall than the long rains by 2030–2040, with implications for sustaining agricultural yields and triggering climate-related public health emergencies. Mitigating the impacts of future Eastern African climate requires continued investments in agriculture, clean water, medical and emergency infrastructures, and development and adoption of adaptation strategies, as well as targeted early-warning systems driven by improved meteorological observations. Rainfall variability in Eastern Africa is associated with considerable social and environmental impacts, including threats to water, energy and food security. This Review outlines the drivers of this rainfall variability, their corresponding impacts, and potential future changes with anthropogenic warming.

Intraseasonal descriptors and extremes in South African rainfall. Part II: Summer teleconnections across multiple timescales

AbstractExtreme events contribute significantly to rainfall variability in semi‐arid regions like South Africa. Here, following the definition of a novel typology of rainfall extremes, disentangling large‐ and small‐scale events in Part I, we use quality‐controlled observational databases in South Africa, the ERA5 reanalysis and satellite estimates TRMM‐3B42 to examine the relationship between these two types of rainfall extremes and different modes of climate variability at various timescales. At low frequencies, rainfall extremes are assessed at interannual (IV: 2–8 years) and quasi‐decadal (QDV: 8–13 years) timescales, which are primarily associated with the El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO), respectively. At subseasonal timescales, the typology of rainfall extremes is analysed depending on the synoptic configurations, as inferred by seven convective regimes including tropical temperate troughs (TTTs: 3–7 days), and the intraseasonal variability associated with the Madden–Julien Oscillation (MJO: 30–60 days). At the IV timescale, the occurrence of large‐scale extremes is substantially higher during its wet phases thereby suggesting a 400% rise in the occurrence of large‐scale extremes as compared to its dry phases. At the QDV timescale, variability mostly relates to the modulation of small‐scale extremes during its wet phases. Teleconnections with global sea surface temperature (SST) confirm that La Niña conditions favour overall wet conditions and extremes in South Africa. The numbers of large‐scale extremes are consistently related to warmer SSTs in the North Atlantic, while their link with warmer Indian and tropical South Atlantic oceans is found to be statistically independent of the state of ENSO. At the subseasonal timescales, large‐scale extremes largely occur during three out of the seven convective regimes identified in the southern African region whereas small‐scale extremes are nearly equiprobable during all convective regimes. The occurrence of large‐scale extremes during continent‐rooted TTT is further enhanced during the locally wet phases of the MJO and is symmetrically weakened during its dry phases.

Climatic shocks and multidimensional energy poverty in Ugandan households: does women empowerment play a moderating role?

ABSTRACT This study examines the effect of climatic shock and women empowerment on multidimensional energy poverty using panel data from Uganda National Panel Surveys from 2013/14–2019/20, complemented by the World Bank African Rainfall Climatology version 2 (ARC2) database. We find that climatic shocks increase energy poverty. However, there is great potential in energy poverty alleviation when women are more empowered in relation to men, but it is even greater when both genders are empowered in the same household amidst climatic shocks. Combating the impacts of drought, floods, landslides, and irregular rainfall while enhancing women's economic empowerment avenues should be a priority on the policy agenda for multidimensional energy poverty alleviation in Uganda.Highlights Energy poverty is assessed using a multidimensional approach. Four waves of the Uganda National panel survey and weather data were used Climatic shocks increase energy poverty. Women empowerment reduces energy poverty amidst climatic shocks, more so when both genders are empowered in the same household.

Identification of sources and sinks of atmospheric aerosols and their impact on east African rainfall

Identification of sources and sinks of atmospheric aerosols and their impact on east African rainfall

Patterns of atmospheric circulation linking the positive tropical Indian Ocean dipole and southern African rainfall during summer

Patterns of atmospheric circulation linking the positive tropical Indian Ocean dipole and southern African rainfall during summer

Verification of operational numerical weather prediction model forecasts of precipitation using satellite rainfall estimates over Africa

AbstractRainfall is an important variable to be able to monitor and forecast across Africa, due to its impact on agriculture, food security, climate‐related diseases and public health. Numerical weather models (NWMs) are an important component of this work, due to their complete spatial coverage, high resolution and ability to forecast into the future. In this study, the spatio‐temporal skill of short‐term forecasts of rainfall across Africa from 2016 through 2018 is evaluated. Specifically, the European Centre for Medium‐Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction‐Global Forecast System (NCEP‐GFS) forecast models are verified by Rainfall Estimates 2.0 (RFE2) and African Rainfall Climatology Version 2 (ARC2), which are fused products of satellite and in situ observations and are commonly used in analysis of African rainfall. Model rainfall forecasts show good consistency with the satellite rainfall observations in spatial distribution over Africa on the seasonal timescale. Evaluation metrics of daily and weekly forecasts show high spatial and seasonal variations over the African continent, including a strong link to the location of the inter‐tropical convergence zone (ITCZ) and topographically enhanced precipitation. The rainfall forecasts at 1 week aggregation time are improved against daily forecasts.

Enhancement of East African Monsoon Long Rainfall (March to May) Variability from Weekly to Annual Scale by Climatic Extremes

Enhancement of East African Monsoon Long Rainfall (March to May) Variability from Weekly to Annual Scale by Climatic Extremes

Investigation into Recent Temperature and Rainfall Trends in Mali Using Mann-Kendall Trend Test: Case Study of Bamako

Rainfall and temperature variability analysis is important for researchers and policy formulators in making critical decisions on water availability and use in communities. The Western Sahel, which comprises Mali is considered as one of the vulnerable regions to climate change, and also encountered the challenges of climatic shocks such as flood and drought. This research therefore sought to investigate climate change effects on hydrological events and trends in Sahelian rainfall intensity using Bamako (Mali) as a case study from 1991 to 2020, as limited data availability did not allow an extended period of study. Monthly observed data provided by MALI-METEO was used to validate daily rainfalls data from African Rainfall Climatology Version 2 (ARC2) satellite-based rainfall product on monthly basis. The validated model performance used Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBAIS) and gave results of 0.904 and 1.0506 respectively. Trends in annual maximum temperatures and rainfalls were analyzed using Mann-Kendall trend test. The result indicated that the trend in annual maximum rainfalls was decreasing, while annual total rainfall was increasing but not significant at 5% significance level. The rate of increase in annual total rainfalls was 0.475 mm/year according to the observed annual rainfall series and decreased to 0.68 mm/year in annual maximum. The analysis further found that annual maximum temperatures were increasing at the rate of 0.03°C/year at 5% significance level. To provide more accurate climate predictions, it is recommended that further studies on rainfall and temperature with data sets spanning 60 - 90 years be carried out.

Importance of Madden–Julian oscillation phase to the interannual variability of East African rainfall

AbstractPrecipitation across East Africa shows marked interannual variability. Seasonal forecast skill for the OND short rains is significantly higher than for the MAM long rains, which also exhibit poorly understood decadal variability. On sub‐seasonal time‐scales rainfall is influenced strongly by the phase of the Madden–Julian Oscillation (MJO); here we investigate whether this influence extends to interannual and decadal scales. We show that the number of days that the MJO is active and in phases 1–3 has a greater influence than the mean amplitude of the MJO on interannual long rains variability (ρ = 0.59 for the count of phases 1–3, compared to ρ = 0.40 for amplitude). The frequency of these days is linked to a newly identified gradient in Pacific sea‐surface temperatures (SSTs), whose influence on long rains variability we show is itself mediated by the MJO. We develop a statistical model estimating East African rainfall from MJO state, and show that the influence of the MJO on seasonal rainfall extends to the short rains, and to a lesser extent also into January and February. Our results show the importance of capturing the SST‐MJO phase relationship in models used for predictions of East African rainfall across time‐scales, and motivate investigating this further.

Representation of the Mozambique channel trough and its link to southern African rainfall in CMIP6 models

The topography of Madagascar and the strength of the Mozambique Channel Trough (MCT) modulate summer rainfall over southern Africa. A strong MCT hinders the penetration of moisture bearing easterlies from the South Indian Ocean into the mainland, thus reducing rainfall there and vice versa for weak MCT summers. Given the link between the MCT and rainfall, it is important to analyse how climate models represent the trough. Here, output from 20 models within the CMIP6 ensemble of Coupled General Circulation Models (CGCMs) are analyzed to investigate how state-of-the-art CGCMs represent the MCT and its link to southern African rainfall. Overall, the ensemble mean insignificantly underestimates the observed MCT. There is a large spread among the models, with the strength of the MCT significantly correlated with the Froude number based on the mountain height over Madagascar. In models, the vorticity tendency in the MCT area is dominated by the stretching and friction terms, whereas the vertical advection, tilting and residual terms dominate in the ERA5 reanalysis. The link between MCT and rainfall in the southern African subcontinent is missing in the models. Large rainfall biases are depicted over mainland even in models with a very strong MCT. It is found that the impacts of the MCT in the models could be masked by a complex mix of processes such as the strength of the Angola low, moisture fluxes from the Indian and South Atlantic Oceans as well as overestimated convection in the Mozambique Channel area.

Spatio-Temporal Assessment of Satellite Estimates and Gauge-Based Rainfall Products in Northern Part of Egypt

Egypt’s climate is generally dry all over the country except for the Northern Mediterranean Coast. The Egyptian Meteorological Authority (EMA) uses few meteorological stations to monitor weather events in the entire country within the area of one million square kilometers, which makes it scarce with respect to spatial distribution. The EMA data are relatively expensive to obtain. Open access rainfall products (RP) are commonly used to monitor rainfall as good alternatives, especially for data-scarce countries such as Egypt. This paper aims to evaluate the performance of 12 open access rainfall products for 8 locations in the northern part of Egypt, in order to map the rainfall spatial distribution over the northern part of Egypt based on the best RP. The evaluation process is conducted for the period 2000–2018 for seven locations (Marsa-Matrouh, Abu-Qeir, Rasheed, Port-Said, Tanta, Mansoura, and Cairo-Airport), while it is conducted for the period 1996–2008 for the Damanhour location. The selected open access rainfall products are compared with the ground stations data using annual and monthly timescales. The point-to-pixel approach is applied using four statistical indices (Pearson correlation coefficient (r), Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE) and bias ratio (Pbias)). Overall, the results indicate that both the African Rainfall Estimation Algorithm (RFE) product and the Climate Prediction Center (CPC) product could be the best rainfall data sources for the Marsa-Matrouh location, with relatively higher r (0.99–0.93 for RFE and 0.99–0.89 for CPC) and NSE (0.98–0.79 for RFE and 0.98–0.75 for CPC), in addition to lower RMSE (0.94–7.78 for RFE and 0.92–12.01 for CPC) and Pbias (0.01–11.95% for RFE and −2.22–−12.15% for CPC) for annual and monthly timescales. In addition, the Global Precipitation Climatology Centre (GPCC) and CPC give the best rainfall products for the Abu-Qier and Port-Said locations. GPCC is more suitable for the Rasheed location. The most appropriate rainfall product for the Tanta location is CHIRPS. The current research confirms the benefits of using rainfall products after conducting the recommended performance assessment for each location.

Reliability of Gridded Precipitation Products for Water Management Studies: The Case of the Ankavia River Basin in Madagascar

Hydrological modeling for water management in large watersheds requires accurate spatially-distributed rainfall time series. In case of low coverage density of ground-based measurements, gridded precipitation products (GPPs) from merged satellite-/gauge-/model-based rainfall products constitute an attractive alternative. The quality of which must, nevertheless, be verified. The objective of this study was to evaluate, at different time scales, the reliability of 6 GPPs against a 2-year record from a network of 14 rainfall gauges located in the Ankavia catchment (Madagascar). The GPPs considered in this study are the African Rainfall Estimate Climatology (ARC2), the Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), the European Centre Medium-Range Weather Forecasts ECMWF Reanalysis on global land surface (ERA5-Land), the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement V06 Final (IMERG), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), and the African Rainfall Estimation (RFEv2) products. The results suggest that IMERG (R2 = 0.63, slope of linear regression a = 0.96, root mean square error RMSE = 12 mm/day, mean absolute error MAE = 5.5 mm/day) outperforms other GPPs at the daily scale, followed by RFEv2 (R2 = 0.41, a = 0.94, RMSE = 15 mm/day, MAE = 6 mm/day) and ARC2 (R2 = 0.30, a = 0.88, RMSE = 16 mm/day, MAE = 6.7 mm/day). All GPPs, with the exception of the ERA5, overestimate the ‘no rain’ class (0–0.2 mm/day). ARC2, IMERG, PERSIANN, and RFEv2 all underestimate rainfall occurrence in the 0.2–150 mm/day rainfall range, whilst CHIRPS and ERA5 overestimate it. Only CHIRPS and PERSIANN could estimate extreme rainfall (>150 mm/day) satisfactorily. According to the Critical Success Index (CSI) categorical statistical measure, IMERG performs quite well in detecting rain events in the range of 2–100 mm/day, whereas PERSIANN outperforms IMERG for rain events larger than 150 mm/day. Because it performs best at daily scale, only IMERG was evaluated for time scales other than daily. At the yearly and monthly time scales, the performance is good with R2 = 0.97 and 0.87, respectively. At the event time scale, the probability distribution function PDF of rain gauge values and IMERG data show good agreement. However, at an hourly time scale, the correlation between ground-based measurements and IMERG data becomes poor (R2 = 0.20). Overall, the IMERG product can be regarded as the most reliable gridded precipitation source at monthly, daily, and event time scales for hydrological applications in the study area, but the poor agreement at hourly time scale and the inability to detect extreme rainfall >100 mm/day may, nevertheless, restrict its use.

Reconstruction of the holocene climate and environmental changes of Niayes peat bog in northern coast of Senegal (NW Africa) based on stable isotopes and charcoals analysis

A core from a peat bog in the “Niayes” region, northwest of Senegal, provides a valuable insight into the evolution of the landscape and fire regime related to the West African Monsoon rainfall and to human impact over the Holocene. The high-resolution multiproxy approach based on stable carbon isotopic composition (δ13C), Rock-Eval® thermal analysis, and charcoal analysis, provides an understanding of vegetation composition (C3/C4) and fire regime in the continental watershed. The analysis of our data indicates a more woody landscape and a higher water table level, related to increased monsoonal rainfall during the African Humid period (AHP) between 9.5 and 5.5 cal kyr BP. High insolation and orbital changes account for a northward migration of the African Rain Belt and a reinforced West Africa monsoon. The amount of forest fires was low and most likely of natural occurrence, as human density was very low. A short dry event interrupts the AHP and gives rise to a weakly grassy landscape at around 8.2 cal kyr BP. This drought of centennial scale (400 years) occurring between 8.4 and 8 cal kyr BP is concomitant with the general cooling observed in the Northern Hemisphere. After a period of transition, the millennial-scale Late Holocene dry period begins at 4.8 cal kyr BP. The low water table level, resulting from a decrease in precipitation, coincides with the appearance of a grassy savanna landscape. Insolation decrease and reduced vegetation were likely driven by a southward migration of the African Rain Belt and a weakening of the monsoon. During the late Holocene the “Niayes” zone evolved into a phase of environmental stress often interrupted by Little Humid Periods (LHP) of centennial scale (500 and 600 years) respectively between 4.4 and 3.9 and between 1.1 and 0.5 cal kyr BP. After 0.5 cal kyr BP the decrease in precipitation and the increase in savanna fires, probaly of anthropogenic origin, favor the landscape opening.

Predictive skill of North American Multi‐Model Ensemble seasonal forecasts for the climate rainfall over Central Africa

AbstractThis study evaluates the predictive performance of the North American Multi‐model Ensemble (NMME) over Central Africa (CA) using the historical rainfall data. The African Rainfall Climatology Version 2 (ARC2) is used as a substitute for reference observational data to examine the capability of 11 NMME and their NMME ensemble mean (MME) in simulating rainfall. Using the Kling‐Gupta efficiency (KGE), Taylor skill score (TSS), and Heidke skill score, the predictive evaluation of the models is performed from lead 0 to lead 5 of each season. The results show that the NMME models satisfactorily reproduce the bimodal and unimodal structure of rainfall in CA at the lead 0 level of different seasons: December–February (DJF), March–May (MAM), June–August (JJA), and September–November (SON). The pattern correlation coefficient (PCC) shows values of NMME and MME greater than ~0.69 and TSS > 0.60 for all four seasons. The MME presents a maximum in DJF between 0 and 1 month lead time. With the same time scale, just over of the NMME have a KGE between 0 and 0.42. It follows that as the forecast lead time increases, the PCC and TSS of each model become small, with PCC in JJA and DJF, TSS < 0.21 in JJA at lead 5. The NMME models exhibit an important rainfall bias and the calculated scores show the quality of the forecast decreases with increasing lead time; this may justify a constraint on the models to keep the good quality of the long‐term seasonal forecast in CA.

Differential signal of change among multiple components of West African rainfall

Rainfall components likely differ in the magnitude and direction of their long-term changes for any given location, and some rainfall components may carry a greater regional signal of change than rainfall totals. This study evaluates the magnitude of change of multiple rainfall components relative to other components, and the greatest regions of change across all rainfall components in West Africa. Hourly rainfall data from the ERA5 reanalysis dataset was used to derive twelve rainfall components, which were evaluated for long-term means, interannual variability, and long-term changes. For rainfall totals and rainfall intensity, the central Sahel is witnessing increasing trends while the western Sahel is experiencing significant decreasing trends. In general, decreasing trends predominate in the study domain, especially in the northwestern Congo Basin, where annual rainfall is decreasing by 120 mm per decade. Importantly, rainfall frequency accounts for 49% of all significant grid-point trends for the whole domain. In contrast, rainfall totals account for 26% of all combined significant trends across the domain, while rainfall intensity (12.6%), rainy season length (9.5%), and seasonality (3.3%) account for the remaining signals of change. Most of the changes among the rainfall components are in the tropical wet and dry regions (59% of all significant trends); the Saharan and equatorial regions account for the least changes. This study finds evidence that rainfall frequency is changing more across the regions compared to rainfall totals and should be explored as rainfall inputs in climate models to potentially improve regional predictions of future rainfall.

Carnivore stable isotopes as environmental integrators in southern African winter rainfall ecosystems

The study explores the effects of environmental and climatic variables on the δ13C, δ15N and δ18O values of carnivores from modern C3 dominated environments in South Africa. Stable isotope ratios of carnivores may reflect large-scale environmental patterns better than those of herbivores because carnivores integrate variation seen at lower trophic levels. To explore this further, we have analysed δ13C and δ15N in bone collagen and δ13C and δ18O in tooth enamel of 12 species of carnivores obtained mostly from game parks and nature reserves in the winter and year-round rainfall zones of southern Africa. Sampling localities span several vegetation types, with varying rainfall, temperature, etc. We developed regression models for carnivore δ13C, δ15N and δ18O against nine meteorological variables: mean annual precipitation, mean annual temperature, mean annual soil moisture stress, mean annual potential evapotranspiration, relative humidity, summer aridity index, winter concentration of rainfall, moisture index and water deficit. There were significant correlations between δ13Cenamel and δ13Ccollagen and eight out of nine of the meteorological factors tested; the strongest correlations were with mean annual soil moisture stress (MASMS) (δ13Cenamelr2(adj) = 0.69 and δ13Ccollagenr2(adj) = 0.66). δ18Oenamel showed significant correlations with mean annual precipitation, mean annual potential evapotranspiration, summer aridity index, water deficit, relative humidity and the moisture index, but the r2 values were low. δ15Ncollagen showed significant correlations with eight out of nine of the meteorological factors (r2 values up to 0.63); only summer aridity index was not significantly correlated). Correlations between consumer δ13C values and meteorological variables were stronger for carnivores than in a previously published study of herbivores from the same region; the opposite pattern was seen in δ18O. Carnivore δ13C and δ15N are therefore effective integrators of environments. Where sample sizes permit, carnivores may be better proxies than herbivores for palaeoenvironmental reconstruction.

Modulation of East African Boreal Fall Rainfall: Combined Effects of the Madden–Julian Oscillation (MJO) and El Niño–Southern Oscillation (ENSO)

Abstract Climate variabilities can have significant impacts on rainfall in East Africa, leading to disruption in natural and human systems and affecting the lives of tens of millions of people. Subseasonal and interannual variabilities are critical components of total rainfall variability in the region. The goal of this study is to examine the combined effects of the Madden–Julian oscillation (MJO), operating at a subseasonal time scale, and El Niño–Southern Oscillation (ENSO), operating at an interannual scale, on the modulation of East African boreal fall [October–December (OND)] rainfall, commonly called the short rains. Composite analysis shows that daily rainfall responses depend on MJO phase and its interaction with ENSO state. In particular, MJO modulation of rainfall is generally stronger under El Niño conditions relative to ENSO neutral and La Niña conditions, leading to increased potential for daily precipitation excesses during wet MJO phases under El Niño. There is evidence for both dynamic and thermodynamic mechanisms associated with these impacts, including an increase in westerly moisture transport and easterly advection of temperature and moist static energy. Seasonal analysis shows that the frequency and intensity of wet MJO phases during an El Niño contribute notably to the seasonal total precipitation anomaly. This suggests that the MJO can mediate El Niño’s impact on OND rainfall in East Africa.

Assessment of Climate-Driven Variations in Malaria Transmission in Senegal Using the VECTRI Model

Several vector-borne diseases, such as malaria, are sensitive to climate and weather conditions. When unusual conditions prevail, for example, during periods of heavy rainfall, mosquito populations can multiply and trigger epidemics. This study, which consists of better understanding the link between malaria transmission and climate factors at a national level, aims to validate the VECTRI model (VECtor borne disease community model of ICTP, TRIeste) in Senegal. The VECTRI model is a grid-distributed dynamical model that couples a biological model for the vector and parasite life cycles to a simple compartmental Susceptible-Exposed-Infectious-Recovered (SEIR) representation of the disease progression in the human host. In this study, a VECTRI model driven by reanalysis data (ERA-5) was used to simulate malaria parameters, such as the entomological inoculation rate (EIR) in Senegal. In addition to the ERA5-Land daily reanalysis rainfall, other daily rainfall data come from different meteorological products, including the CPC Global Unified Gauge-Based Analysis of Daily Precipitation (CPC for Climate Prediction Center), satellite data from the African Rainfall Climatology 2.0 (ARC2), and the Climate Hazards InfraRed Precipitation with Station data (CHIRPS). Observed malaria data from the National Malaria Control Program in Senegal (PNLP/Programme National de Lutte contre le Paludisme au Senegal) and outputs from the climate data used in this study were compared. The findings highlight the unimodal shape of temporal malaria occurrence, and the seasonal malaria transmission contrast is closely linked to the latitudinal variation of the rainfall, showing a south–north gradient over Senegal. This study showed that the peak of malaria takes place from September to October, with a lag of about one month from the peak of rainfall in Senegal. There is an agreement between observations and simulations about decreasing malaria cases on time. These results indicate that the southern area of Senegal is at the highest risk of malaria spread outbreaks. The findings in the paper are expected to guide community-based early-warning systems and adaptation strategies in Senegal, which will feed into the national malaria prevention, response, and care strategies adapted to the needs of local communities.

The Effect of Explicit Convection on Climate Change in the West African Monsoon and Central West African Sahel Rainfall

AbstractThe West African monsoon (WAM) is the dominant feature of West African climate providing the majority of annual rainfall. Projections of future rainfall over the West African Sahel are deeply uncertain, with a key reason likely to be moist convection, which is typically parameterized in global climate models. Here, we use a pan-African convection-permitting simulation (CP4), alongside a parameterized convection simulation (P25), to determine the key processes that underpin the effect of explicit convection on the climate change of the central West African Sahel (12°–17°N, 8°W–2°E). In current climate, CP4 affects WAM processes on multiple scales compared to P25. There are differences in the diurnal cycles of rainfall, moisture convergence, and atmospheric humidity. There are upscale impacts: the WAM penetrates farther north, there is greater humidity over the northern Sahel and the Saharan heat low regions, the subtropical subsidence rate over the Sahara is weaker, and ascent within the tropical rain belt is deeper. Under climate change, the WAM shifts northward and Hadley circulation weakens in P25 and CP4. The differences between P25 and CP4 persist, however, underpinned by process differences at the diurnal scale and large scale. Mean rainfall increases 17.1% in CP4 compared to 6.7% in P25 and there is greater weakening in tropical ascent and subtropical subsidence in CP4. These findings show the limitations of parameterized convection and demonstrate the value that explicit convection simulations can provide to climate modelers and climate policy decision makers.

Orbital controls on eastern African hydroclimate in the Pleistocene

Understanding eastern African paleoclimate is critical for contextualizing early human evolution, adaptation, and dispersal, yet Pleistocene climate of this region and its governing mechanisms remain poorly understood due to the lack of long, orbitally-resolved, terrestrial paleoclimate records. Here we present leaf wax hydrogen isotope records of rainfall from paleolake sediment cores from key time windows that resolve long-term trends, variations, and high-latitude effects on tropical African precipitation. Eastern African rainfall was dominantly controlled by variations in low-latitude summer insolation during most of the early and middle Pleistocene, with little evidence that glacial–interglacial cycles impacted rainfall until the late Pleistocene. We observe the influence of high-latitude-driven climate processes emerging from the last interglacial (Marine Isotope Stage 5) to the present, an interval when glacial–interglacial cycles were strong and insolation forcing was weak. Our results demonstrate a variable response of eastern African rainfall to low-latitude insolation forcing and high-latitude-driven climate change, likely related to the relative strengths of these forcings through time and a threshold in monsoon sensitivity. We observe little difference in mean rainfall between the early, middle, and late Pleistocene, which suggests that orbitally-driven climate variations likely played a more significant role than gradual change in the relationship between early humans and their environment.