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The mean climatology, inter‐model variability and spatio‐temporal patterns of temperature and precipitation over West Africa from Coupled Model Intercomparison Project 5 (CMIP5), CMIP5_SUBSET [ensemble of global climate models driving COordinated Regional climate Downscaling EXperiment (CORDEX)] and CORDEX multi‐model ensembles are evaluated and intercompared for the monsoon season (June–September). We find that, while CORDEX fails to outperform the simulated mean climatology of temperature by the CMIP5 ensembles, it substantially improves precipitation and provides more realistic fine‐scale features tied to local topography and landuse. This improved performance over the region is found to depend more on the internal models physics than the driving boundary conditions and results from a more consistent and realistic simulation of monsoon precipitation across the various regional climate models (RCMs). Rotated empirical orthogonal function (REOF) analysis indicates that the CORDEX ensemble captures better the spatio‐temporal variability of both temperature and precipitation (first REOF mode), in particular depicting the warming and Sahel precipitation recovery in recent decades over West Africa. On the other hand, the spatial patterns and associated time series of the last two REOF modes in CORDEX mostly follow the CMIP5_SUBSET pointing towards a strong role of the boundary forcing in the RCM simulation of precipitation variability.

This study focuses on the ability of the global Land Data Assimilation System, LDAS-Monde, to improve the representation of land surface variables (LSVs) over Burkina-Faso through the joint assimilation of satellite derived surface soil moisture (SSM) and leaf area index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced by the latest European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis ERA5 as well as ERA-Interim former reanalysis, leading to reanalyses of LSVs at 0.25° × 0.25° and 0.50° × 0.50° spatial resolution, respectively. Within LDAS-Monde, SSM and LAI observations from the Copernicus Global Land Service (CGLS) are assimilated with a simplified extended Kalman filter (SEKF) using the CO2-responsive version of the ISBA (Interactions between Soil, Biosphere, and Atmosphere) land surface model (LSM). First, it is shown that ERA5 better represents precipitation and incoming solar radiation than ERA-Interim former reanalysis from ECMWF based on in situ data. Results of four experiments are then compared: Open-loop simulation (i.e., no assimilation) and analysis (i.e., joint assimilation of SSM and LAI) forced by either ERA5 or ERA-Interim. After jointly assimilating SSM and LAI, it is noticed that the assimilation is able to impact soil moisture in the first top soil layers (the first 20 cm), and also in deeper soil layers (from 20 cm to 60 cm and below), as reflected by the structure of the SEKF Jacobians. The added value of using ERA5 reanalysis over ERA-Interim when used in LDAS-Monde is highlighted. The assimilation is able to improve the simulation of both SSM and LAI: The analyses add skill to both configurations, indicating the healthy behavior of LDAS-Monde. For LAI in particular, the southern region of the domain (dominated by a Sudan-Guinean climate) highlights a strong impact of the assimilation compared to the other two sub-regions of Burkina-Faso (dominated by Sahelian and Sudan-Sahelian climates). In the southern part of the domain, differences between the model and the observations are the largest, prior to any assimilation. These differences are linked to the model failing to represent the behavior of some specific vegetation species, which are known to put on leaves before the first rains of the season. The LDAS-Monde analysis is very efficient at compensating for this model weakness. Evapotranspiration estimates from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled carbon uptake from the FLUXCOM project and sun-induced fluorescence from the Global Ozone Monitoring Experiment-2 (GOME-2) are used in the evaluation process, again demonstrating improvements in the representation of evapotranspiration and gross primary production after assimilation.

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Agrometeorological services, as part of weather and climate services, are expected to play a key role in supporting sub-Saharan agriculture facing climate change and variability. In the Sahel, smallholder farmers relying on rainfed crop production systems are particularly vulnerable to climate change and variability because of low resilience and coping capacity. The provision of agrometeorological services is growing across Africa, but they often remain inaccessible for the majority of smallholder farmers or are not very relevant to support on-the-ground decision-making. Our work aims to demonstrate the hypothesis that agrometeorological services can effectively improve agricultural productivity and sustainability provided that appropriate mechanisms are put in place to ensure access, uptake and action. The paper illustrates the case study of Burkina Faso, where the National Meteorological Service, with the support of the World Meteorological Organization, engaged in the provision of accessible, reliable and relevant agrometeorological services for farmers. The study demonstrates that farmers, even in remote rural areas, are willing to profit from weather and climate services for strategic and tactical decisions in agricultural management because of relevant economic benefit. These benefits can be summarized as a 40% reduction in production costs and a 41% increase in income. Results also highlight environmental positive impacts such as the reduction by 50% in the use of fertilizers. Nevertheless, the study concludes that in order to scale-up weather and climate services in West Africa, a new business model released from the development projects approach should be explored.