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Calls for humanity to act on environmental changes are becoming increasingly critical. The growing polycrisis including the impact of ongoing conflicts in contested geopolitical spaces and the struggles for ways to sustain a livelihood in areas of precarity and poverty, are just some of the intersecting challenges which have given rise to a Code Red alarm by the United Nations surrounding issues related to climate change. Rich narratives and stories of climate actions from Africa offer examples of potential paths. This paper explores how such narratives inform local development and climate action. A key message is that stories and narratives, created by various peoples, disciplines, and systems of knowledge, can all be powerful genres and sources for agentic change that can inspire and embolden development practice and action. [ABSTRACT FROM AUTHOR]

The level of solar activity and its influence on ionospheric variability has received a focal interest among the ionospheric community. This paper examines the impact of long-term solar activity on the ionosphere over an African equatorial global navigation satellite system (GNSS) station based on a large database of solar and ionospheric datasets. The ionospheric total electron content (TEC) periodic variations, climatology and its relation to solar activity are investigated through wavelet analyses. It is observed that the magnitude and intensity of TEC fluctuations measured by GNSS receivers vary substantially with solar radiation intensity. To probe the processes accountable for the TEC periodicities in the region, the wavelet analysis is undertaken by considering solar indices (solar radio flux and sunspot number) and observed TEC values. The results show a clear strong periodicity of 27 days in the ionospheric TEC, sunspots and F10.7 solar flux power spectra, associated with the sun's 27 days rotation period. The ultraviolet ray intensity and solar ionization were lower during the solar maximum period (2013 to 2014) of solar cycle 24 compared to the solar maximum period (2001 to 2002) of solar cycle 23, which is the key factor for driving the decreasing trend in TEC between 1999 and 2017. The ionospheric and solar climatology analysis indicates that ionospheric TEC behaviour could be a good indicator of long-term solar activity trend. A large mass of Africa lies within the equatorial and low latitudes making the ionosphere over the region being highly susceptible to low latitude electrodynamics. Results from this study would support the concerted efforts towards developing a reliable regional ionospheric forecasting model for technological applications relying on spaced-based navigation and satellite services. [ABSTRACT FROM AUTHOR]

Climate Smart Agriculture (CSA) has gained prominence in global agriculture and climate agendas for its perceived "triple win" contributions to food productivity, adaptation, and mitigation to climate change. This paper highlights three important challenges for CSA activities in Africa which provide insights into contested debates surrounding CSA's ability to respond holistically to the complex realities facing resource-constrained farmers in the global South. These are (1) prevailing neoliberal market policies that emphasize private-sector driven agricultural development in the face of rising input costs and falling commodity prices; (2) an expansion in diversified livelihood strategies amongst smallholder households as a response to the highly unpredictable biophysical environment and economic climate under which they live; and (3) a growing competition for land and other productive resources. A deeper dive into political economy processes surrounding these three issues aims to bring critical attention to factors relevant to African agricultural development that highly impact farm-level practices and carry important implications for rural livelihood outcomes. [ABSTRACT FROM AUTHOR]

A simple—yet powerful—indicator for monitoring agricultural drought is the water requirement satisfaction index (WRSI). In data-sparse, food-insecure areas, the WRSI is used to guide billions of dollars of aid every year. The WRSI uses precipitation (PPT) and reference evapotranspiration (RefET) data to estimate water availability relative to water demand experienced over the course of a growing season. If the season is in progress, to-date conditions can be combined with climatological averages to provide insight into potential end-of-season (EOS) crop performance. However, if the average is misrepresented, these forecasts can hinder early warning and delay precious humanitarian aid. While many agencies use arithmetic average climatologies as proxies for "average conditions," little published research evaluates their effectiveness in crop-water balance models. Here, we use WRSI hindcasts of three African regions' growing seasons, from 1981 to 2019, to assess the adequacy of the arithmetic mean climatological forecast—the Extended WRSI. We find that the Extended WRSI is positively biased, overestimating the actual EOS WRSI by 2%–23% in East, West, and southern Africa. The presented alternative combines to-date conditions with data from previous seasons to produce a series of historically realistic conclusions to the current season. The mean of these scenarios is the WRSI Outlook. In comparison with the Extended WRSI, which creates a single forecast scenario using average inputs that are not covarying, the WRSI Outlook employs an ensemble of scenarios, which more adequately capture the historical distribution of distribution of rainfall events along with the covariability between climate variables. More specifically, the impact of dry spells in individual years is included in the WRSI Outlook in a way that is smoothed over in the Extended WRSI. We find that the WRSI Outlook has a near-zero bias score and generally has a lower RMSE. In total, this paper highlights the inadequacies of the arithmetic mean climatological forecast and presents a less biased and more accurate scenario-based approach. To this end, the WRSI Outlook can improve our ability to identify agricultural drought and the concomitant need for humanitarian aid. [ABSTRACT FROM AUTHOR]

Relying on complex interdependence as a theoretical approach, this paper investigates the hypothetical damage that the U.S. withdrawal from the Paris Agreement could represent for Africa in terms of climate finance. In June 2017, President Donald Trump publicly declared the U.S. intention to withdraw from further participating in the multilateral Paris Agreement. To keen followers and analysts of the U.S. climate policy beyond its borders, such unilateral action was never a surprise. Rather, it is nostalgic of the experience of the Kyoto Protocol, particularly how more or less similar move unduly prolonged the global climate negotiations up till late 2015 when the Paris Agreement came about. Although the Paris Agreement is remarkable as it represents the first states-wide climate deal, it however left a number of issues unresolved. Notable among which is climate finance which has remained the most contentious and of critical concern to developing countries, particularly in Africa. Pitted against the fact that Africa contributes less to climate change and, ironically, the hardest-hit by the phenomenon, the U.S. withdrawal from the Paris Agreement aggravates concerns around climate finance and, indeed, portends additional burdens for a continent that is still struggling to cope with the untoward fallout of climate change. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth analysis of a significant global challenge the international organizations are faced within the 21st century - climate change. Climate change has detrimental effects on international security and stability. In the past decades, humanity has faced emerging natural occurrences such as the increase in the World Ocean level, higher frequency of monsoon rainfalls, impaired conditions of the ecosystems in the rain forests. The massive population increase in Africa and South Asia also points to the fact that natural resources are not infinite, and their spare use becomes a priority of worldwide importance. Managing climate change is a global problem, the solution of which mandates the unified efforts of the entire international community. And this is where climate diplomacy comes at play. The efforts of climate diplomacy need to be focused on two primary directions. The first priority is limiting global warming under 2°C compared to the pre-industrial levels and taking actions to reduce the harmful emissions of greenhouse gases. The second priority is about taking adequate measures to handle climate change consequences, amongst which the so-called climate migration. [ABSTRACT FROM AUTHOR]

In this paper the progress made in producing predictions of the Normalized Difference Vegetation Index (NDVI) over Kenya in the Greater Horn of Africa (GHA) for the October–December (OND) season is discussed. Several studies have identified a statistically significant relationship between rainfall and NDVI in the region. Predictability of seasonal rainfall by global climate models (GCMs) during the OND season over the GHA has also been established as being among the best in the world. Information was extracted from GCM seasonal prediction output using statistical transformations. The extracted information was then used in the prediction of NDVI. NDVI is a key variable for management of various climate-sensitive problems. For example, it has been shown to have the potential to predict environmental conditions associated with Rift Valley Fever (RVF) viral activity and this is referred to throughout the paper as a motivation for the study. RVF affects humans and livestock and is particularly economically important in the GHA. The establishment of predictability for NDVI in this paper is therefore part of a methodology that could ultimately generate information useful for managing RVF in livestock in the GHA. It has been shown that NDVI can be predicted skillfully over the GHA with a 2–3-month lead time. Such information is crucial for tailoring forecast information to support RVF monitoring and prediction over the region, as well as many other potential applications (e.g., livestock forage estimation). More generally, the Famine Early Warning System (FEWS), a project of the U.S. Agency for International Development (USAID) and the National Aeronautics and Space Administration (NASA) and other specialized technical centers routinely use NDVI images to monitor environmental conditions worldwide. The high predictability for NDVI established in this paper could therefore supplement the routine monitoring of environmental conditions for a wide range of applications. [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]

Climate change continues to unleash wider negative ramifications on humans, including grain production with attendant economic consequences. This paper explored the relationship between climateinduced temperature and grain production in Southern African countries. It contributes to the literature by charting the financial implication framework. Maize production was used as a proxy for grain production and archival data on maize production were collected from a sample of five Southern African countries, where high temperature and drought has inflicted havoc on grain farming within the recent years. Hence, data on the five countries were collected over six years 2011 - 2016. Applying the panel data approach and the fixed effect OLS regression, results showed a high correlation between high temperature and low maize productivity in Southern African countries. Further analysis showed that high temperature and drought has led to high cost of production on farmers, increasing price of grain and overall increase in consumer expenditure on maize, which is a staple crop in Southern Africa. The paper prepared a framework of financial implication, which touches on how the poor consumers might be affected by climate change-induced temperature increases. The paper recommends further study, which should expand on the sample size to conduct future research on this relationship. It also provides an agenda for further research on the effect of climate change induced-temperature on food poverty gap in Southern Africa. This recommendation is significant since eradication of food poverty is a vital feature of the 2030 Sustainable Development agenda. [ABSTRACT FROM AUTHOR]

Adaptation is a key component of climate policy, yet we have limited and fragmented understanding of if and how adaptation is currently taking place. In this paper, we document and characterize the current status of adaptation in 47 vulnerable 'hotspot' nations in Asia and Africa, based on a systematic review of the peer-reviewed and grey literature, as well as policy documents, to extract evidence of adaptation initiatives. In total, 100 peer-reviewed articles, 161 grey literature documents, and 27 United Nations Framework Convention on Climate Change National Communications were reviewed, constituting 760 adaptation initiatives. Results indicate a significant increase in reported adaptations since 2006. Adaptations are primarily being reported from African and low-income countries, particularly those nations receiving adaptation funds, involve a combination of groundwork and more concrete adaptations to reduce vulnerability, and are primarily being driven by national governments, NGOs, and international institutions, with minimal involvement of lower levels of government or collaboration across nations. Gaps in our knowledge of adaptation policy and practice are particularly notable in North Africa and Central Asia, and there is limited evidence of adaptation initiatives being targeted at vulnerable populations including socioeconomically disadvantaged populations, children, indigenous peoples, and the elderly. [ABSTRACT FROM AUTHOR]

Africa lags the rest of the world in climate model development. This paper explores the potential for region-specific, process-based evaluation to promote progress in modeling and confidence assessments. [ABSTRACT FROM AUTHOR]

Copyright of African Journal of Reproductive Health is the property of Women's Health & Action Research Centre and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite its local and regional importance, hydrometeorological data on the Sudd (one of Africa's largest wetlands) is very scanty. This is due to the physical and political situation of this area of Sudan. The areal size of the wetland, the evaporation rate, and the influence on the micro and meso climate are still unresolved questions of the Sudd hydrology. The evaporation flux from the Sudd wetland has been estimated using thermal infrared remote sensing data and a parameterization of the surface energy balance (SEBAL model). It is concluded that the actual spatially averaged evaporation from the Sudd wetland over 3 years of different hydrometeorological characteristics varies between 1460 and 1935mm/yr. This is substantially less than open water evaporation. The wetland area appears to be 70% larger than previously assumed when the Sudd was considered as an open water body. The temporal analysis of the Sudd evaporation demonstrated that the variation of the atmospheric demand in combination with the inter-annual fluctuation of the groundwater table results into a quasi-constant evaporation rate in the Sudd, while open water evaporation depicts a clear seasonal variability. The groundwater table characterizes a distinct seasonality, confirming that substantial parts of the Sudd are seasonal swamps. The new set of spatially distributed evaporation parameters from remote sensing form an important dataset for calibrating a regional climate model enclosing the Nile Basin. The Regional Atmospheric Climate Model (RACMO) provides an insight not only into the temporal evolution of the hydro-climatological parameters, but also into the land surface climate interactions and embedded feedbacks. The impact of the flooding of the Sudd on the Nile hydroclimatology has been analysed by simulating two land surface scenarios (with and without the Sudd wetland). The paper presents some of the model results addressing the Sudd's influence on rainfall, evaporation and runoff of the river Nile, as well as the influence on the microclimate. The paper presents a case study that confirms the feasibility of using remote sensing data (with good spatial and poor temporal coverage) in conjunction with a regional climate model. The combined model provides good temporal and spatial representation in a region characterized by extremely scarce ground data. [ABSTRACT FROM AUTHOR]

This paper extends the work of Dinku and Anagnostou overland rain retrieval algorithm for use with Special Sensor Microwave Imager (SSM/I) observations. In Dinku and Anagnostou, Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) rainfall estimates were used to calibrate TRMM Microwave Imager (TMI) retrieval. Regional differences in PR-based TMI calibration were investigated by testing the algorithm over four geographic regions, consisting of Africa, northern South America (containing the Amazon basin), the continental United States, and south Asia. In this paper the performance of Dinku and Anagnostou's technique applied on SSM/I data over three of these regions (Africa, Amazon, and South Asia) is demonstrated. Two approaches are investigated for using PR rainfall products to calibrate the algorithm parameters. In the first approach, TMI channels are remapped to the spatial resolutions of the corresponding SSM/I channels; then, PR is used to calibrate the rain retrieval on the remapped TMI data. In the second approach, the PR-based TMI algorithm calibration is performed at a coarser (0.25°) resolution. To assess the quality of algorithm estimates with respect to PR, rainfall fields derived from Dinku and Anagnostou, applied to SSM/I observations (using parameters determined from both approaches), are compared with matched (within ±15 min of the satellites' overpass time difference) PR surface rain rates. Calibration data come from the wet seasons (January–March) of 2000 and 2001. To assess the quality of the estimates with respect to PR, data from a 5-month period (December–April) of 2002, 2003, and 2004 are used. In comparison with the latest version of the Goddard profiling (GPROF) algorithm rain estimates, the current algorithm shows significant improvements in terms of both bias and random error reduction. The paper also shows that rain estimation based on TMI observations is associated with lower error statistics in comparison with the corresponding SSM/I retrievals. [ABSTRACT FROM AUTHOR]

• English-only searches for African climate change science introduce language-bias. • Non-English literature is poorly represented on Web of Science and Scopus. • Google Scholar incorporates a non-English voice, important for global assessments. • Supporting non-English authors may improve the global uptake of their work. • English-language research translated into local languages may encourage local use. Disregarding research not published in English may pose a risk to finding solutions for urgent global concerns, such as biodiversity loss, or climate change. To assess the extent of this 'missing voice', we compared the representation of 22 languages in scientific publications on climate change in Africa, indexed by widely used databases. Between 87 % and 95 % of publications were in English, with a small, but noteworthy, number in languages of the former European colonisers of Africa. We then assessed undergraduate monographs, master's dissertations, doctoral theses, and peer-reviewed papers derived from the doctoral theses, that are about Lusophone Africa and written in Portuguese, and found this research largely not accessible in English on online databases. If the goal of researchers, practitioners and policy makers is to obtain climate change information on, or present solutions for, individual developing countries, cultures, or localised issues, then searching in English may exclude local, context specific knowledge. This may prevent global assessments from being truly global, or locally down-scalable, by biasing science towards a single world view that marginalises key local stakeholders. [ABSTRACT FROM AUTHOR]

This article sets discourse by demonstrating the utility of indigenous climate knowledge (ICK) in understanding the science of climate change in Muzarabani, a rural community north of Zimbabwe. It argues that the notion of sacredness, enshrined in customary arrangements and belief systems, offers opportunities for exploitation in climate science. Through customary law, communities understand the sanctity and inviolability of the environment because of the varied cultural, political and ecological benefits derived from it. This perspective, although facing perpetuity challenges in Africa, can be exploited both to enhance understanding of climate change and to promote sustainable intervention strategies. By drawing from the experiences of indigenous people through in-depth conservations with a selected elderly local group, the paper proves that ICK offers capabilities in informing climate science. The local people have a range of sacred sites and environmental assets that can be used to understand past, current, and future climate systems from their many years of interactions with the same. Sacred forests and trees are also vital in climate change mitigation. It is concluded that, albeit limitations in scale, opportunities exist for tapping from the sacredness notions, to enhance the praxis of mitigation strategies such as Reducing Emissions from Deforestation and Forest Degradation (REDD+). [ABSTRACT FROM AUTHOR]

Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the products for decision making is improved by the routine provision of validation reports, for which the 10-day (dekadal) TAMSAT rainfall estimates are compared with independent gauge observations. This paper describes the methodology by which the TAMSAT method has been applied to generate the pan-African rainfall monitoring products. It is demonstrated through comparison with gauge measurements that the method provides skillful estimates, although with a systematic dry bias. This study illustrates TAMSAT's value as a complementary method of estimating rainfall through examples of successful operational application. [ABSTRACT FROM AUTHOR]

Climate models are basic tools to obtain reliable estimates of future climate change and its effects on the water resources and agriculture in given basin. However, all climate models are not equally valuable for all areas. Therefore, determining the most appropriate climate model for a specific study area is essential. This study examines the performance of 10 CORDEX-AFRICA-220 Regional Climate Models (RCMs), three downscaling institutional based ensembles mean (Reg ensemble, CCLM ensemble and REMOO ensemble) and the multi-model ensemble mean. The models were evaluated based on their ability in replicating the seasonal and annual rainfall, minimum and maximum temperature and inter-annual variability for the period of 1986–2005 using statistical metrics such as BIAS, Root Mean Square Error (RMSE), Pearson correlation coefficient (r), coefficient of variation (CV), Kling Gupta Efficiency (KGE) and Taylor diagram. The findings indicated that HadREMOO, MPI-Reg4-7, HadReg4-7, Reg ensemble, and multi-model ensemble mean performed relatively better in representing the mean annual observed rainfall at the Adiramets, Debarik Ketema, Niguse Maystebri, and Zarima stations, respectively. Whereas, NorESM-CCLM, MPI-CCLM, NorESM-Reg4-7, and NorESM-REMOO exhibited a weak performance in reproducing the observed mean annual rainfall at the Adiramets, Debarik Ketema Niguse, Maystebri, and Zarima stations, respectively. Similarly, RCMs generally capture the mean annual maximum temperature of climatic stationsof Zarima subbasin well. Specifically, the MPI-Reg4-7 simulation performs well in representing the mean annual observed maximum temperature at Adiramets and Maytsebri stations, while the Debarik and Ketema Niguse stations exhibit superior performance in the HadReg4-7 simulation and the Zarima station shows better representation in the CCLM ensemble simulations. The majority of the model simulations exhibit good representation of mean annual minimum temperature at Adiramets, Debarik, and Zarima stations. Specifically, CanESM-RCM, HadReg4-7, REMOOensemble, multi-model ensemble, and Regensemble simulations perform better at Adiramets, Debarik, Ketema niguse, Maystebri and Zarima stations respectively. This suggests that these models may have biases or shortcomings in capturing the temperature values in the subbasin. Furthermore, NorESM-CCLM at Adiramets, Ketema niguse, and Zarima stations, NorESM-REMOO at Debarik station, and HadReg4-7 at Maystebri station demonstrate poor performance in representing the observed mean minimum temprature. Majority of the RCMs, all institutional based ensemble means and the multi-model ensemble mean simulations overestimate the observed mean annual rainfall of the Zarima subbasin with minimum bias of 0.02 mm at Ketema niguse HadReg4-7and maximum bias of 2.81 mm at Maytsebri MPI-CCLM simulation. Similarly, HadReg4-7 simulation of Ketama Niguse MPI-CCLM showed a minimum 0.02 mm and Maytsebri simulation kiremit season mean rainfall showed a maximum bias of and 2.99 mm. Regarding mean annual and kiremit season maximum and minimum temperature of the Zarima subbasin were overestimated by majority of the simulation and the ensemble means. The correlation (r) of observed and model simulated mean annual and kiremit season rainfall was strong (0.60–0.79) and very strong (0.80–0.99) in the majority of the simulations except Ketema niguse station mean annual and kiremit season rainfall simulations of MPI-REMOO, NorESM-Reg4-7; Debarik station kiremit season rainfall of NorESM-CCLM and NorESM-REMOO, MPI-Reg4-7 and MPI-REMOO, which showed moderate correlation. The performance of the RCMs, institutional based ensemble means and multi-model ensemble mean were different in statistical metrics (BIAS, RMSE, r, CV and KGE) and Taylor diagram. Among the simulations and ensemble means, the multi-model ensemble mean was superiors in two or more of statistical metrics at each station of the Zarima subbasin except Maytsebri station kiremit season rainfall, where the CCLM ensemble was better. Consistently, the Taylor diagram showed that the multi-model ensemble was better in the replication of the areal annual and kiremit season rainfall, maximum and minimum temperature of the subbasin. This finding evidenced that selecting the best RCMs and ensemble mean is necessary for climate projection and climate change impact assessment study. [ABSTRACT FROM AUTHOR]

Despite the enormous potential of precipitation forecasts to save lives and property in Africa, low skill has limited their uptake. To assess the skill and improve the performance of the forecast, validation and postprocessing should continuously be carried out. Here, we evaluate the quality of reforecasts from the European Centre for Medium-Range Weather Forecasts over equatorial East Africa (EEA) against satellite and rain gauge observations for the period 2001–18. The 24-h rainfall accumulations are analyzed from short- to medium-range time scales. Additionally, 48- and 120-h rainfall accumulations were also assessed. The skill was assessed using an extended probabilistic climatology (EPC) derived from the observations. Results show that the reforecasts overestimate rainfall, especially during the rainy seasons and over high-altitude areas. However, there is potential of skill in the raw forecasts up to 14-day lead time. There is an improvement of up to 30% in the Brier score/continuous ranked probability score relative to EPC in most areas, especially the higher-altitude regions, decreasing with lead time. Aggregating the reforecasts enhances the skill further, likely due to a reduction in timing mismatches. However, for some regions of the study domain, the predictive performance is worse than EPC, mainly due to biases. Postprocessing the reforecasts using isotonic distributional regression considerably improves skill, increasing the number of grid points with positive Brier skill score (continuous ranked probability skill score) by an average of 81% (91%) for lead times 1–14 days ahead. Overall, the study highlights the potential of the reforecasts, the spatiotemporal variation in skill, and the benefit of postprocessing in EEA. [ABSTRACT FROM AUTHOR]

Gridded SST products developed particularly for offshore regions are increasingly being applied close to the coast for biogeographical applications. The purpose of this paper is to demonstrate the dangers of doing so through a comparison of reprocessed MODIS Terra and Pathfinder v5.2 SSTs, both at 4 km resolution, with instrumental in situ temperatures taken within 400 m from the coast. We report large biases of up to +6°C in places between satellite-derived and in situ climatological temperatures for 87 sites spanning the entire ca. 2 700 km of the South African coastline. Although biases are predominantly warm (i.e. the satellite SSTs being higher), smaller or even cold biases also appear in places, especially along the southern and western coasts of the country. We also demonstrate the presence of gradients in temperature biases along shore-normal transects — generally SSTs extracted close to the shore demonstrate a smaller bias with respect to the in situ temperatures. Contributing towards the magnitude of the biases are factors such as SST data source, proximity to the shore, the presence/absence of upwelling cells or coastal embayments. Despite the generally large biases, from a biogeographical perspective, species distribution retains a correlative relationship with underlying spatial patterns in SST, but in order to arrive at a causal understanding of the determinants of biogeographical patterns we suggest that in shallow, inshore marine habitats, temperature is best measured directly. [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]

This paper describes a new gridded, daily 29-yr precipitation estimation dataset centered over Africa at 0.1° spatial resolution. Called the African Rainfall Climatology, version 2 (ARC2), it is a revision of the first version of the ARC. Consistent with the operational Rainfall Estimation, version 2, algorithm (RFE2), ARC2 uses inputs from two sources: 1) 3-hourly geostationary infrared (IR) data centered over Africa from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and 2) quality-controlled Global Telecommunication System (GTS) gauge observations reporting 24-h rainfall accumulations over Africa. The main difference with ARC1 resides in the recalibration of all Meteosat First Generation (MFG) IR data (1983-2005). Results show that ARC2 is a major improvement over ARC1. It is consistent with other long-term datasets, such as the Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), with correlation coefficients of 0.86 over a 27-yr period. However, a marginal summer dry bias that occurs over West and East Africa is examined. Daily validation with independent gauge data shows RMSEs of 11.3, 13.4, and 14, respectively, for ARC2, Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis 3B42, version 6 (3B42v6), and the CPC morphing technique (CMORPH) for the West African summer season. The ARC2 RMSE is slightly higher for Ethiopia than those of CMORPH and 3B42v6. Both daily and monthly validations suggested that ARC2 underestimations may be attributed to the unavailability of daily GTS gauge reports in real time, and deficiencies in the satellite estimate associated with precipitation processes over coastal and orographic areas. However, ARC2 is expected to provide users with real-time monitoring of the daily evolution of precipitation, which is instrumental in improved decision making in famine early warning systems. [ABSTRACT FROM AUTHOR]

This paper examines the factors governing rainfall variability in western equatorial Africa (WEA) during the April-June rainy season. In three of the five regions examined some degree of large-scale forcing is indicated, particularly in the region along the Atlantic coast. Interannual variability in this coastal sector also demonstrates a strong link to changes in local sea surface temperatures (SSTs) and the South Atlantic subtropical high. To examine potential causal mechanisms, various atmospheric parameters are evaluated for wet and dry composites. The results suggest that the intensity of the zonal circulation in the global tropics is a crucial control on rainfall variability over WEA. A La Niña (El Niño)-like signal in both SSTs and zonal circulation over the Pacific is apparent in association with the wet (dry) conditions in the western sector. However, remote forcing from the Pacific modulates the circulation over Africa indirectly by way of synchronous changes in the entire Indian or Atlantic Ocean. Anomalies in the local zonal winds are similar in all three regions: the wet (dry) composite is associated with an intensification (weakening) of the upper-tropospheric easterlies and low-level westerlies, but a weakening (intensification) of the midlevel easterlies. This work also suggests that, in most cases, the relationship between local SSTs and rainfall reflects a common remote forcing by the large-scale atmosphere-ocean system. This forcing is manifested via changes in the zonal circulation. Thus, the statistical associations between rainfall and SSTs do not indicate direct forcing by local SSTs. One point of evidence for this conclusion is the stronger association with atmospheric parameters than with SSTs. [ABSTRACT FROM AUTHOR]

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Africa is most vulnerable to climate change, although it makes the least contribution to factors that result in global and regional climatic changes. High levels of vulnerability and low adaptive capacity across the continent have been linked to, among other things, poverty. This paper discusses and analyses the relationship between climate change and poverty in Africa. It investigates the relationship between climate change and poverty patterns in Africa, analyses the resultant impact, and discusses potential adaptation policies for moderating the consequences of climatic changes on poverty in the region. The record shows that climate change is happening. What is not discussed or is little researched is the potential devastating impact of climate change on socio-economic development in Africa and the policy measures available to the continent for adaptation. [ABSTRACT FROM AUTHOR]

Understanding the underlying processes causing large-scale dust storms and their transport in North Africa is essential for their accurate prediction. Different atmospheric mechanisms have been identified to govern the emission of dust and its transport, ranging in scale and season, from Rossby wave breaking to local, low-level cold and dry jets. Connecting these features in a Lagrangian sense is a coherent airflow from the midlatitude upper troposphere to the surface where dust concentrations peak. Such dry intrusions (DIs) are linked to reduced static stability and strong, dry winds and indeed have been recently shown to play a central role in four of the largest dust storm in the region. Yet, the climatological link between DIs and dust storms over a long time period has not been studied yet. The aim of this paper is to identify objectively dust events that co-occur with DIs, and understand their spatio-temporal characteristics and underlying dynamical drivers. Combining Lagrangian-based DI identification in ERA-Interim and dust optical depth data in CAMS reanalyses, 325 events during 2003–2018 are identified. The events occur mostly in late winter and spring, when they are also larger in size and last longer, compared to summer events. When occurring with DIs, dust optical depth is generally higher, compared to events that are not accompanied by DIs. We focus on March events, and find coherent large-scale precursors and atmospheric conditions of dust-DI events: a northward jet shift over the North Atlantic with anticyclonic Rossby wave breaking occurs on average 4–5 days prior to the events. The lower troposphere responds with dry and cold conditions in northwest Africa, coinciding with the outflow of the DI airstream that is initially guided by the upper trough. Finally, elevated near-surface dust concentrations prevail on the leading edge of the DI in tropical west Africa, and in northeast Africa, where dust is exported to the Mediterranean in association with a Mediterranean cyclone. • 325 dust storms related to DIs in North Africa were compiled using objective identification and a matching algorithm. • The largest, longest and most frequent events occur in February and March. They are more intense compared to non-DIs events. • Large-scale precursor jet anomalies related to anticyclonic Rossby wave breaking exist 4–5 days prior to the events. • DIs descend from upper-tropospheric anomalies towards the surface in Africa where the highest dust concentrations prevail. [ABSTRACT FROM AUTHOR]

The tropical cloud forest ecosystem in western equatorial Africa (WEA) is known to be sensitive to the presence of an extensive and persistent low-level stratiform cloud deck during the long dry season from June to September (JJAS). Here, we present a new climatology of the diurnal cycle of the low-level cloud cover from surface synoptic stations over WEA during JJAS 1971-2019. For the period JJAS 2008-19, we also utilized estimates of cloudiness from four satellite products, namely, the Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting (SAFNWC) cloud classification, the Day and Night Microphysical Schemes (DMS/NMS), and cross sections from CALIPSO and CloudSat (2B-GEOPROF-lidar). A comparison with surface stations reveals that the NMS at night together with SAFNWC at daytime yield the smallest biases. The climatological analysis reveals that low-level clouds persist during the day over the coastal plains and windward side of the low mountain ranges. Conversely, on their leeward sides, i.e., over the plateaus, a decrease of the low-level cloud frequency is observed in the afternoon, together with a change from stratocumulus to cumulus. At night, the low-level cloud deck reforms over this region with the largest cloud occurrence frequencies in the morning. Vertical profiles from 2B-GEOPROF-lidar reveal cloud tops below 3000 m even at daytime. The station data and the suitable satellite products form the basis to better understand the physical processes controlling the clouds and to evaluate cloudiness from reanalyses and models. [ABSTRACT FROM AUTHOR]

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy. [ABSTRACT FROM AUTHOR]

This paper examines the co-construction of global and local views of the weather and climate at the turn of the twentieth century through a history of data gathering efforts in the German colonies in Africa. While both governmental officials and metropolitan practitioners aimed at producing standardized – and thus globally comparable and economically useful – data in different environments, these efforts often tended to break down in practice. Rather than being able to turn the field into a finely tuned laboratory, both European and African data gatherers were confronted with complex and challenging environmental and institutional realities. Faced with these difficulties, colonial practitioners tended to embrace alternative strategies of recording weather conditions, which placed a higher value on individual sensory perception and qualitative descriptions. Thus, in a seemingly paradoxical dynamic, the attempts to gather quantitative colonial data for global maps and models also facilitated the development of a particular colonial approach to climatology that highlighted local specificities and direct embodied experience. [ABSTRACT FROM AUTHOR]

There is an increasing recognition of the role of climate change adaptation among smallholder farmers in rain-fed agriculture in Africa. Collective action among smallholder farmers has been suggested as influencing local adaptation processes hence the need to evaluate its impact in different contexts. This paper provides evidence of collective action in enhancing local adaptation to climate variability. It determines the importance of different forms of collective action for enhancing adaptation. Through simple random sampling, a survey of 240 households in Embu County in Kenya and 200 households from Kapchorwa district of Uganda was undertaken. Focus-group discussions involving farmer groups and local government representatives were performed to triangulate information collected through the surveys. The results show a positive relationship between membership in farmer groups and adaptation to climate variability in both sites. Four main components of collective action were identified in Embu and these included the development of internal group capacities, assets mobilization and management, collective marketing, and management of human and natural capital. In Kapchorwa, the development of internal group capacities, risk spreading, and financial resources were significant. We argue that local-level governance and institutional arrangements for collective action are critical for successful adaptation to climate variability. [ABSTRACT FROM PUBLISHER]

Climate change adaptation now occupies central stage on the agenda of most environmental initiatives in Africa. Our current understanding on the state of adaptation is limited, however, both globally and in Africa in particular. This study examines the status of adaptation in the Sahel by reviewing the primary peer review literature that reports concrete climate change adaptation actions. Based on an analysis of 70 peer review papers that document 414 discrete adaptations, we create a snap shot of adaptations developed between 1975 and 2015, and also calculate the percentages of adaptation. The results show that from a country to country perspective, Kenya has the highest number of reported adaptation actions (75 or 18.1%). The percentages indicate that the adaptive capacity of the entire study area is generally low for all the countries being that the highest country-level percentage is recorded in Kenya and it is 18%. Regionally, West Africa has more adaptation actions (261 or 63%) when compared to other regions of the Sahel. Regional level percentages suggest a higher level of adaptation at the regional level being that the percentage falls within the high scale range. The most commonly used adaptation actions reported are income diversification and water harnessing respectively. When categorized, technically related adaptation actions dominate the adaptation charts. The decade 2008–2016 recorded the highest number of adaptations (65.2%). Adaptation actions are also reported to be triggered by climatic and non-climatic drivers which both record high frequencies but the climatic drivers (98%) of adaptation are slightly dominant relative to the non-climatic drivers (95%). These results should be viewed as proxies of climate change adaptation as much information may be found in grey literature and non-peer review national communications which are left out here because of their relative low standardization and acceptability due to the absence of peer review. [ABSTRACT FROM AUTHOR]

Malaria is a climate sensitive disease that is causing rampant deaths in sub-Saharan Africa (SSA) and its impact is expected to worsen under climate change. Thus, pre-emptive policies for future malaria control require projections based on integrated models that can accommodate complex interactions of both climatic and non-climatic factors that define malaria landscape. In this paper, we combined Geographical Information System (GIS) and Bayesian belief networks (BBN) to generate GIS-BBN models that predicted malaria hotspots in 2030, 2050 and 2100 under representative concentration pathways (RCPs) 4.5 and 8.5. We used malaria data of children of SSA, gridded environmental and social-economic data together with projected climate data from the 21 Coupled Model Inter-comparison Project Phase 5 models to compile the GIS-BBN models. Our model on which projections were made has an accuracy of 80.65% to predict the high, medium, low and no malaria prevalence categories correctly. The non-spatial BBN model projection shows a moderate variation in malaria reduction for the high prevalence category among RCPs. Under the low prevalence category, an increase in malaria is seen but with little variation ranging between 4.6 and 5.6 percentage points. Spatially, under RCP 4.5, most parts of SSA will have medium malaria prevalence in 2030, while under RCP 8.5, most parts will have no malaria except in the highlands. Our BBN-GIS models show an overall shift of malaria hotspots from West Africa to the eastern and southern parts of Africa especially under RCP 8.5. RCP 8.5 will not expand the high and medium malaria prevalence categories in all the projection years. The generated probabilistic maps highlight future malaria hotspots under climate change on which pre-emptive policies can be based. [ABSTRACT FROM AUTHOR]

This study evaluated the historical precipitation simulations of 49 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in reproducing annual and seasonal precipitation climatology, linear trends, and their spatial correlation with global SST across Africa and the Arabian Peninsula during the period of 1980–2014, using Global Precipitation Climatology Centre (GPCP) data as a reference. Taylor's diagram was used to quantify the strengths and weaknesses of the models in simulating precipitation. The CMIP6 multi-mean ensemble (MME) and the majority of the GCMs replicated the dominant features of the spatial and temporal variations reasonably well. The CMIP6 MME outperformed the majority of the individual models. The spatial variation of the CMIP6 MME closely matched the observation. The results showed that at annual and seasonal scales, the GPCP and CMIP6 MME reproduced a coherent spatial pattern in terms of the magnitude of precipitation. The humid region received >300 mm and the arid region received <50 mm across Africa and the Arabian Peninsula. The models from the same modeling centers replicated the precipitation levels across different seasons and regions. The CMIP6 MME and the majority of the individual models overestimate (underestimate) in humid (arid and semi-arid)-climate zones. The annual and pre-monsoon seasons (i.e., DJFMA) were better replicated in the CMIP6 GCMs than in the monsoon-precipitation model (MJJASON). The CMIP6 MME (GPCP) showed stronger wetting (drying) trends in the northern hemisphere. In contrast, a strong drying trend in the CMIP6 MME and a weak wetting trend in the GPCP were shown in the Southern Hemisphere. The CMIP6 MME captures the spatial pattern of linear trends better than individual models across different climate zones and regions. The relationship between precipitation and sea-surface temperature (SST) exhibited a high spatial correlation (−0.80 and 0.80) with large variability across different regions and climate zones. The GPCP (CMIP6 MME) exhibited a heterogenous (homogeneous) spatial pattern, with higher correlation coefficients recorded in the CMIP6 MME than in the GPCP in all cases. Individual models from the same modeling centers showed spatial homogeneity in correlation values. The differences exhibited by the individual GCMs highlight the significance of each model's unique dynamics and physics; however, model selection should be considered for specific applications. [ABSTRACT FROM AUTHOR]

Changes in the terrestrial total water storage (TWS) have been estimated at both global and river basin scales from the Gravity Recovery and Climate Experiment (GRACE) mission and are still being detected from its GRACE Follow-On (GRACE-FO) mission. In this contribution, the sixth release of GRACE-FO (RL06) level-2 products applying DDK5 (decorrelation filter) were used to detect water mass variations for the Nile River Basin (NRB) in Africa and the Mega Aquifer System (MAS) in Asia. The following approach was implemented to detect the mass variation over the NRB and MAS: (1) TWS mass (June 2018–June 2021) was estimated by converting the spherical harmonic coefficients from the decorrelation filter DDK 5 of the GRACE-FO Level-2 RL06 products into equivalent water heights, where the TWS had been re-produced after removing the mean temporal signal (2) Precipitation data from Global Precipitation Climatology Project was used to investigate the pattern of change over the study area. Our findings include: (1) during the GRACE-FO period, the mass variations extracted from the RL06-DDK5 solutions from the three official centers—CSR, JPL, and GFZ—were found to be consistent with each other, (2) The NRB showed substantial temporal TWS variations, given a basin average of about 6 cm in 2019 and about 12 cm in 2020 between September and November and a lower basin average of about −9 cm in 2019 and −6 cm in 2020 in the wet seasons between March and May, while mass variations for the MAS had a relatively weaker temporal TWS magnitude, (3) the observed seasonal signal over the NRB was attributed to the high intensity of the precipitation events over the NRB (AAP: 1000–1800 mm yr−1), whereas the lack of the seasonal TWS signal over the MAS was due to the low intensity of the precipitation events over the MAS (AAP:180–500 mm yr−1). [ABSTRACT FROM AUTHOR]

The Paris Agreement of COP21 set a goal of holding global average temperature increases to below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C. This is particularly relevant for the African context where temperatures are likely to warm faster than the global average and where the magnitude of change will be regionally heterogeneous. Most studies that provide information over Africa under specific global warming levels have used data from global models, however global models poorly resolve local scale forcing (e.g. topography) nor the internal climate variability of a region. Although downscaling using regional climate models can address these issues, we found only one paper that had used downscaled data for GWL studies over Africa. During 2018 the CORDEX-Africa campaign investigated the impact of 1.5 and 2 degrees of global warming over many regions of sub-Saharan Africa and compiled the results for a special issue of nine papers in ERL. This paper reports on some of the key regional findings of the analysis of 25 CORDEX downscalings, including the impact of the extra 0.5 degrees of warming between 1.5 and 2 degrees on particular extremes and the differences noted between the driving GCMs and downscaled results. We also briefly discuss the impact of the papers in the IPCC SR15 and their contribution to the development of adaptation and mitigation policies. [ABSTRACT FROM AUTHOR]

Background: This paper provides an insightful quantitative ethnoecological analysis and affirms that agro-pastoralists have a multiplicity of criteria for valuating their natural forage resources. Rural households in West Africa are not only confronted with water resource scarcity but also have to cope with limited forage resources to feed livestock in both wet and dry seasons based on local knowledge. Local agro-pastoral social-ecological systems (SESs) in the study areas stem from the daily utilization of available forage resources by dominant domestic livestock (cattle, goats, and sheep) over the years. However, there is very little systematic knowledge documentation on forage-related valuation criteria in this part of the world. Hence, this study aimed at examining (1) forage resources used for different seasons and livestock types, (2) explicit forage-related valuation criteria and associated salience, and (3) effects of socio-demographic and climatic aridity on local valuation criteria. Methods: To address these aims, a total of 526 individual ethnoecological interviews (encompassing Dagbani, Gurunsi, and Mossi ethnic groups) were conducted in 16 villages coupled with vegetation sampling of 144 plots in Ghana and Burkina Faso. Rigorous model selection, generalized linear mixed-effects models, cognitive salience indices, and descriptive statistics were applied. Results: The results revealed that majority (73%) of the agro-pastoralists regarded herbaceous forage plants to be very palatable for livestock consumption in the rainy season and for cattle while woody vegetation and crop-related forage plants were rather perceived to be more important in the dry season and for goats and sheep. The findings also indicated that climatic aridity significantly influenced the number of forage-related valuation criteria cited by agro-pastoralists for different seasonal and livestock types (p < 0.001). It was also found out that agro-pastoralists did not only judge forage plants based on their availability but also on other criteria such as palatability, stimulation of milk production, and healthy growth of livestock. Conclusion: Local agro-pastoralists' knowledge on natural forage resources and their valuation criteria is geared towards sustainable domestic livestock production. This study is thus interesting and crucially important for fellow scientists, policy-makers, and other stakeholders in the agricultural production sector in local farming landscapes within West Africa and beyond. [ABSTRACT FROM AUTHOR]

While considerable attention has been given to how convectively coupled Kelvin waves (CCKWs) influence the genesis of tropical cyclones (TCs) in the Atlantic Ocean, less attention has been given to their direct influence on African easterly waves (AEWs). This study builds a climatology of AEW and CCKW passages from 1981 to 2019 using an AEW-following framework. Vertical and horizontal composites of these passages are developed and divided into categories based on AEW position and CCKW strength. Many of the relationships that have previously been found for TC genesis also hold true for non-developing AEWs. This includes an increase in convective coverage surrounding the AEW center in phase with the convectively enhanced ("active") CCKW crest, as well as a buildup of relative vorticity from the lower to upper troposphere following this active crest. Additionally, a new finding is that CCKWs induce specific humidity anomalies around AEWs that are qualitatively similar to those of relative vorticity. These modifications to specific humidity are more pronounced when AEWs are at lower latitudes and interacting with stronger CCKWs. While the influence of CCKWs on AEWs is mostly transient and short lived, CCKWs do modify the AEW propagation speed and westward-filtered relative vorticity, indicating that they may have some longer-term influences on the AEW life cycle. Overall, this analysis provides a more comprehensive view of the AEW–CCKW relationship than has previously been established, and supports assertions by previous studies that CCKW-associated convection, specific humidity, and vorticity may modify the favorability of AEWs to TC genesis over the Atlantic. [ABSTRACT FROM AUTHOR]

Climate change is expected to have important implications for human mobility. This article discusses and contextualizes key insights from a recently published study by Thalheimer, Williams, van der Geest, and Otto in Earth's Future (2021), https://doi.org/10.1029/2020EF001958. The authors synthesize findings from the climate science and impact literature, among others from the IPCC Special Report on Global Warming of 1.5 °C, to explore the role of climatic drivers for human mobility in African drylands. Facing a number of economic, social, and political challenges, these areas are highly vulnerable to global warming and related risks. Climate mobility in this region is the outcome of complex interactions between individual and contextual factors shaping peoples' needs and incentives to move as well as their constraints. As the authors highlight, climate change can influence mobility outcomes through a number of channels, including impacts on food and water security, poverty and livelihood risks, and conflicts. These impacts are relevant for both rural areas and cities, with the latter representing a primary destination for climate‐induced migration in Africa. The complexity and diversity of the climate mobility nexus call for integrative approaches in science and policy that bridge different disciplines and policy sectors. These approaches should be based on fair, equal, and inclusive processes of knowledge production, transfer, and implementation that involve a number of stakeholders. Inclusive deliberations and partnerships across fields and sectors are key elements to comprehensively studying and addressing the realities and manifold challenges faced by both mobile and immobile populations. Key Points: Drylands in Africa are highly exposed and vulnerable to climate change impacts with important implications for human mobilityClimate mobility is the outcome of complex interactions between individual and contextual factors shaping mobility decisions, outcomes, and risksIntegrative approaches in science and policy are needed to address the complex nexus between climate change and human mobility [ABSTRACT FROM AUTHOR]

This 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 0.~96 between 0 and 1 month lead time. With the same time scale, just over 85% 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 0:~12 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. [ABSTRACT FROM AUTHOR]

This systematic review analyzes all 260 studies published in the Web of Science on gender and climate change in Africa. While there is no strong methodological bias, comparative case studies and sex disaggregated analyses predominate from a limited set of countries. Many articles covered the agrarian sector by comparing women's and men's on-farm vulnerability to a changing climate based on their adaptation behaviours. Though this literature recognizes women's important conservation, farming, and food responsibilities, it oftentimes generalized these contributions without providing evidence. A number of themes were covered by a very limited number of articles, including coastal areas, conflict, education, energy, migration, urban areas, and water. Overall, more justice-oriented research is needed into the socioeconomic structures that intersect with social identities to make certain people, places, and institutions more vulnerable. Investigations into the power dynamics between (social) scientists and African institutions are also needed as most articles reviewed stem from North America and Europe and are locked beyond paywalls. [ABSTRACT FROM AUTHOR]

In this viewpoint I argue for a perspective on climate change in African cities that focuses on challenges and also opportunities for action. Delivering climate change adaptation in cities in the first instance requires addressing immediate infrastructure and service provision needs, because increasing climate change resilience in cities also requires improving the delivery of services to all citizens. However, there is a risk that climate change discourses facilitate the deployment of technocratic, expert-led forms of planning, particularly when climate change is used as an excuse to facilitate the intervention of international planning consultants who most often know little about the local context of planning. This paper advocates instead approaches to climate change action that harness opportunities on the ground to engage with the creative potential that urban citizens already have and to draw attention to the need to develop planning skills from within the city. [ABSTRACT FROM AUTHOR]

This study examines the seasonal forecast of the North American Multi-Model Ensemble (NMME) over Central Africa (CA), which encompasses a region of the world where the economies of the countries are highly dependent on agriculture and livestock breeding. Following many regional climate perspectives, we evaluated the seasonal forecast over the 4 seasons: December to February (DJF), March to May (MAM), June to August (JJA), September to November (SON) between 0 and 5 months lead time before the beginning of each season. Deterministic and categorical approaches which focus on the rainfall variable were used to assess NMME ensemble mean (MME). The observed and predicted rainfalls have been divided into three categories: below normal, normal, and above normal. The results show that for 0 to 2 months lead time, the MME reproduces well the peak rainfall of the Atlantic coast and in the East of Democratic Republic of Congo in MAM and SON between 9 and 10 mm/day. Again in the same lead time interval, values of correlation coefficients (R) between the MME and the Global Precipitation Climatology Center (GPCC) reference observation of all seasons are greater than 0.72. For 3 to 5 months lead time, lower values of R are observed. It follows that probabilities of detection (POD) are greater than 50% for all different normal seasons and less than 45% for below and above normal seasons. On the other hand, high false alarm (FAR) values and low Critical Success Index (CSI) values are observed for both below and above normal seasons. From our results, one can argue that the NMME seems to be an interesting tool during the first three forecasting lead times in CA capable of providing important seasonal characteristics before the start of each season, which will allow proper consideration of meteorological phenomena. [ABSTRACT FROM AUTHOR]

ENSEMBLES stream 2 single-model and multimodel ensemble seasonal precipitation forecasts are evaluated over the African continent with respect to Global Precipitation Climatology Centre (GPCC) precipitation data for the 1960-2005 time period using deterministic and probabilistic skill scores. Focus is set on three regions of Africa during main precipitation seasons: West Africa during boreal summer, southern Africa during austral summer and the Greater Horn of Africa during the 'long rains' and 'short rains' transition seasons. The 45-member multimodel improves the ensemble spread-skill ratio over all regions, which translates into enhanced skill in terms of anomaly correlation and ranked probability skill scores for climatological precipitation deciles over West Africa and southern Africa. Results are contrasted depending on the region and probabilistic formulations of the ensemble predictions after a quantile-quantile calibration give valuable information essentially over areas where deterministic skill is found. Probabilistic skill scores illustrate the range of possibilities for more user-related applications of ensemble seasonal forecasts. A simple illustration using a cost-loss model shows that model potential economic values can reach over 10% depending on the regions and occurrences studied. [ABSTRACT FROM AUTHOR]

Aim This study investigates inter-annual variability in burnt area in southern Africa and the extent to which climate is responsible for this variation. We compare data from long-term field sites across the region with remotely sensed burnt area data to test whether it is possible to develop a general model. Location Africa south of the equator. Methods Linear mixed effects models were used to determine the effect of rainfall, seasonality and fire weather in driving variation in fire extent between years, and to test whether the effect of these variables changes across the subcontinent and in areas more and less impacted by human activities. Results A simple model including rainfall and seasonality explained 40% of the variance in burnt area between years across 10 different protected areas on the subcontinent, but this model, when applied regionally, indicated that climate had less impact on year-to-year variation in burnt area than would be expected. It was possible to demonstrate that the relative importance of rainfall and seasonality changed as one moved from dry to wetter systems, but most noticeable was the reduction in climatically driven variability of fire outside protected areas. Inter-annual variability is associated with the occurrence of large fires, and large fires are only found in areas with low human impact. Main conclusions This research gives the first data-driven analysis of fire-climate interactions in southern Africa. The regional analysis shows that human impact on fire regimes is substantial and acts to limit the effect of climate in driving variation between years. This is in contrast to patterns in protected areas, where variation in accumulated rainfall and the length of the dry season influence the annual area burnt. Global models which assume strong links between fire and climate need to be re-assessed in systems with high human impact. [ABSTRACT FROM AUTHOR]

Abstract: Several regions of the world have developed capability in providing services on climate information for risk management, but there are still gaps in service delivery due to inadequate information regarding the needs within the regions. This paper highlights the role of Regional Climate Outlook Forums, assesses the needs for some regions and extracts examples of how regional associations could benefit through the provision of better climate services. Problems are given for Africa, South-East Asia, South America, the Pacific and Europe. Different geographical climate features lead to different climate phenomena and in turn determine the type of climate delivery needs for risk management. Short discussions of regional socio-economic factors that shape the needs for climate information provide further context for the unique character of delivery services. Recommendations and future plans follow this assessment. [ABSTRACT FROM AUTHOR]

Abstract: The inclusion of CO2 capture and storage (CCS) in the Kyoto Protocol''s Clean Development Mechanism (CDM) is still subject to controversy and discussion. A myriad of barriers prevents CCS in the CDM. Apart from political barriers, economic, social and procedural barriers play a role. This paper discusses relevant new results on the human capacity, procedural feasibility and economic potential of CCS in the CDM. The conclusions of a capacity building effort in Africa show that awareness and knowledge are low but that capacity building efforts are well received. A reality check on methodologies for hypothetical CCS projects shows that most of the issues can be resolved, and the CDM institutional arrangements can accommodate CCS. A bottom-up estimate of the potential of natural gas processing CCS in the CDM, based on a previously proprietary database from the oil and gas industry, suggests that there is an annual potential of about 174MtCO2 in 2020 in that sector. Most of that potential can be realized at CER prices between $20 and $30/tCO2 but there is no sign of flooding the CDM market with cheap credits from CCS projects. Despite these results and more open information, the CCS and CDM debate, progress in the negotiations on CCS in the CDM is slow and there is no clear view on a solution. [Copyright &y& Elsevier]

Past studies of the relationships between economic activity and geography have been hampered by limited spatial data on economic activity. This study presents revised data on global economic activity, the G-Econ database, which measures economic activity for the entire globe, measured at a 1° latitude by 1° longitude scale. The methodologies for the study are described. We show several graphical applications, including an "output globe." The study shows the location of economic deserts. The study indicates the importance of geophysical variables for Africa and questions whether the importance of latitude in economic-growth studies in fact reflects geophysical variables. [ABSTRACT FROM AUTHOR]

Climate change is one of a complex array of risks facing the planet and society. It is argued that adaptation to and mitigation of climate change will be required to avert or reduce adverse impacts. Governments are developing climate change adaptation (CCA) strategies. The business community is also stirring to the need to adapt to as well as mitigate climate change, but progress has been slow, particularly in the case of adaptation. This paper explores emerging perceptions of the need for adaptation and some initial adaptation actions within a 'business as usual' economic mode of operation. It also identifies constraints to further action among a cross-section of actors in the business community in South Africa. Data from semi-structured interviews and scrutiny of reports reveals that there are a number of constraints preventing business from engaging more fully in CCA. These findings correspond with findings in other business-sector and CCA studies. They include: issues of terminology (adaptation versus risk management); uncertainty over climate-change projections and scenarios; and concerns about how such information can be used effectively in decision making, particularly long-term business planning. Despite these challenges, some potential synergies between policy, planning and the business community for promoting adaptation are suggested. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the impact of climatic change on the level of total agricultural production of Sub-Saharan Africa (SSA) and non-Sub-Sahara Africa (NSSA) developing countries. In doing so it uses a new cross-country panel climatic dataset in an agricultural production framework. The results show that climate, measured as changes in country-wide rainfall and temperature, has been a major determinant of agricultural production in SSA. In contrast, NSSA countries appear not to be affected by climate in the same manner. Simulations using the estimates suggest that the detrimental changes in climate since the 1960s can account for a substantial portion of the gap in agricultural production between SSA and the rest of the developing world. [Copyright &y& Elsevier]