Observational records are more often than not influenced by residual non‐climatic factors which must be detected and adjusted for prior to their usage. In this work, we present a novel approach, named Radiosounding HARMonization (RHARM), providing a homogenized data set of temperature, humidity and wind profiles along with an estimation of the measurement uncertainties for 697 radiosounding stations globally. The RHARM method has been used to adjust twice daily (0000 and 1200 UTC) radiosonde data holdings at 16 pressure levels in the range 1,000–10 hPa, from 1978 to present, provided by the Integrated Global Radiosonde Archive. Relative humidity (RH) data are limited to 250 hPa. The applied adjustments are interpolated to all reported levels. RHARM is the first data set to provide homogenized time series with an estimation of the observational uncertainty at each sounding pressure level. By construction, RHARM adjusted fields are not affected by cross‐contamination of biases across stations and are fully independent of reanalysis data. Analysis of trends for temperature, RH and winds highlights increased geographical coherency of trends over 1978–2000 globally, but especially in the Northern Hemisphere and South America. RHARM shows warming trends of 0.39 K/decade at 300 hPa in the Northern Hemisphere and of 0.25 K/decade in the tropics. The RHARM adjustments also reduce differences with the European Centre for Medium‐Range Weather Forecast ERA5 reanalysis, with the strongest effect in the Northern Hemisphere for temperature and relative humidity. For wind speed, the comparison indicates a good agreement with ERA5 in the troposphere.

Anthropogenic land cover change (LCC) can have significant impacts at regional and seasonal scales but also for extreme weather events to which socio-economical systems are vulnerable. However, the effects of LCC on extreme events remain either largely unexplored and/or without consensus following modelling over the historical period (often based on a single model), regional or idealized studies. Here, using simulations performed with five earth system models under common future global LCC scenarios (the RCP8.5 and RCP2.6 Representative Concentration Pathways) and analyzing 20 extreme weather indices, we find future LCC substantially modulates projected weather extremes. On average by the end of the 21st century, under RCP8.5, future LCC robustly lessens global projections of high rainfall extremes by 22% for heavy precipitation days (>10 mm) and by 16% for total precipitation amount of wet days (PRCPTOT). Accounting for LCC diminishes their regional projections by >50% (70%) in southern Africa (northeastern Brazil) but intensifies projected dry days in eastern Africa by 29%. LCC does not substantially affect projections of global and regional temperature extremes (<5%), but it can impact global rainfall extremes 2.5 times more than global mean rainfall projections. Under an RCP2.6 scenario, global LCC impacts are similar but of lesser magnitude, while at regional scale in Amazon or Asia, LCC enhances drought projections. We stress here that multi-coupled modelling frameworks incorporating all aspects of land use are needed for reliable projections of extreme events.

Land Use Land-Cover Change (LULCC), such as deforestation, affects the climate system and land-atmosphere interactions. Using simulations carried out within the LUCID (Land Use and Climate, IDentification of robust Impacts) project framework, we first quantify the role of historical land-cover change induced by human activities on surface climate in West Africa. Focusing on two contrasted African regions, we find that climate responses of land-use changes are small but they are still statistically significant. In Western Sahel, a statistically significant near-surface atmospheric cooling and a decrease in water recycling are simulated in summer in response to LULCC. Over the Guinean zone, models simulate a significant decrease in precipitation and water recycling in autumn in response to LULCC. This signal is comparable in magnitude with the effect induced by the increase in greenhouse gases. Simulated climate changes due to historical LULCC could however be underestimated because: (i) the prescribed LULCC can be underestimated in those regions; (ii) the climate models underestimate the coupling strength between West African surface climate and leaf area index (LAI) and (iii) the lack of interactive LAI in some models. Finally, our study reveals indirect atmospheric processes triggered by LULCC. Over the Western Sahel, models reveal that a significant decrease in solar reflection tend to cool down the surface and thus counteract the atmospheric feedback. Conversely, over the Guinea zone, models reveal that the indirect atmospheric processes and turbulent heat fluxes dominate the climatic responses over the direct effects of LULCC.

Climate trends estimated using historical radiosounding time series may be significantly affected by the choice of the regression method to use, as well as by a subsampling of the dataset often adopted in specific applications. These are contributions to the uncertainty of trend estimations, which have been quantified in literature, although on specific pairs of regression methods, and in the not very recent past characterized by smaller trends in temperature than those observed over the last two decades. This paper investigates the sensitivity of trend estimations to four linear regression methods (parametric and nonparametric) and to the artificial subsampling of the same dataset using historical radiosounding time series from 1978 onwards, available in the version 2 of the Integrated Global Radiosonde Archive (IGRA). Results show that long‐term decadal trends may have not negligible uncertainties related to the choice of the regression method, the percentage of data available, the amount of missing data and the number of stations selected in the dataset. The choice of the regression methods increases uncertainties in the decadal trends ranging from −0.10 to −0.01 K⋅da^–1 for temperature in the lower stratosphere at 100 hPa and from 0.2 to 0.8% da^–1 for relative humidity (RH) in the middle troposphere at 300 hPa. Differences can also increase up to 0.4 K⋅da^–1 at 300 hPa when the amount of missing data exceeds 50% of the original dataset for temperature, while for RH, significant differences are observed in the lower troposphere at 925 hPa for almost all datasets. Finally, subsampling effects on trend estimation are quantified by artificially reducing the size of the IGRA dataset: Results show that subsampling effects on trend estimations when at least 60 stations, up to 76% of data available, are considered for temperature and at least 40 stations for RH.

COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a very contagious disease that has killed many people worldwide. According to data from the World Health Organization (WHO), the spread of the disease appears to be slower in Africa. Although several studies have been published on the relationship between meteorological parameters and COVID-19 transmission, the effects of climate conditions on COVID-19 remain largely unexplored and without consensus. However, the transmission of COVID-19 and sensitivity to climate conditions are also not fully understood in Africa. Here, using available epidemiological data over 275 days (i.e., from 1 March to 30 November 2020) taken from the European Center for Disease Prevention and Control of the European Union database and daily data of surface air temperature specific humidity and water vapor from the National Center for Environmental Prediction (NCEP), this paper investigates the potential contribution of climate conditions on COVID-19 transmission over 16 selected countries throughout three climatic regions of Africa (i.e., Sahel, Maghreb, and Gulf of Guinea). The results highlight statistically significant inverse correlations between COVID-19 cases and temperature over the Maghreb and the Gulf of Guinea regions. In contrast, positive correlations are found over the Sahel area, especially in the central part, including Niger and Mali. Correlations with specific humidity and water vapor parameters display significant and positive values over the Sahelian and the Gulf of Guinea countries and negative values over the Maghreb countries. Then, the COVID-19 pandemic transmission is influenced differently across the three climatic regions: (i) cold and dry environmental conditions over the Maghreb; (ii) warm and humid conditions over the Sahel; and (iii) cold and humid conditions over the Gulf of Guinea. In addition, for all three climatic regions, even though the climate impact has been found to be significant, its effect appears to display a secondary role based on the explanatory power variance compared to non-climatic factors assumed to be dominated by socio-economic factors and early strong public health measures.

Smallholder rainfed agriculture in West Africa is vital for regional food security and livelihoods, yet it remains highly vulnerable to climate change. Persistently low crop yields, driven by high rainfall variability and frequent climate hazards, highlight the urgent need for evidence-based adaptation strategies. This study assesses the impact of climate change on maize yields in Burkina Faso (BF) using a calibrated AquaCrop model and recent climate projections. AquaCrop was calibrated using district-level maize yields from 2009 to 2022 and a genetic optimization technique. Climate change impacts were then simulated using two socioeconomic scenarios (SSP2–4.5 and SSP5–8.5) for the periods 2016–2045 and 2046–2075. Climate projections show that Burkina Faso will experience temperature increases of 0.5–3 °C and decreased precipitation, with the most severe rainfall reductions in the country’s southern half, including the crucial southwestern agricultural zone. Maize yields will predominantly decrease across the country, with projected losses reaching 20% in most regions. The southwestern agricultural zone, critical for national food production, faces substantial yield decreases of up to 40% under the SSP5-8.5 scenario. In light of these findings, future research should employ the calibrated AquaCrop model to evaluate specific combinations of adaptation strategies. These strategies include optimized planting windows, field-level water management practices, and optimal fertilizer application schedules, providing actionable guidance for smallholder farmers in West Africa.