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This thesis has investigated land surface temperature (LST) products based on data from the Advanced Along-Track Scanning Radiometer (AATSR) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). Particular attention was paid to the long-term goal of an LST retrieval which utilises the benefits of both polar orbiting and geostationary instruments, represented by AATSR and SEVIRI, respectively. This study included an assessment of several current methods of LST retrieval, all of which were variations of the generalised split-window (GSW) algorithm. Satellite retrieved LST were compared with in situ observations at three validation sites in Europe and Africa. The results of the validation exercise suggested that for homogenous sites, Gobabeb and the “RMZ” farm in Namibia, the GSW algorithms met validation accuracies ±1-2.5 K. The accuracy of the GSW algorithms was significantly poorer at the heterogeneous site in Evora, Portugal where daytime matchups only met validation accuracies of ±5 K. Cross-platform comparisons at and around the validation sites suggested that the products were strongly correlated for night-time matchups at all sites. The daytime matchups showed greater levels of discrepancy between instruments given the combined effects of viewing geometry and sunlit/sunshade fraction observed by the satellite instruments. A novel optimal estimation (OE) method of LST retrieval has been proposed within the 1DVar framework. 1DVar is a stand-alone OE model which is based on the same architecture as 3D/4DVar systems used in a number of numerical weather prediction (NWP) and climatic models. A full diagnostic assessment of the 1DVar OE system has been presented with respect to the quality of the retrieved LST estimate based on AATSR and SEVIRI data. This demonstrated that the 1DVar OE system could reduce the LST error to 5-20% of the error associated with a priori LST estimate for both AATSR and SEVIRI. However, the implementation of the 1DVar scheme was hindered by the lack of a reliable emissivity resource; hence much of the gain in precision was compromised to the propagated emissivity error. Validation and verification of the 1DVar OE system using real data was presented in Chapter 6 of this thesis. The comparisons with in situ observations suggested only marginal improvements from the performance of the GSW products. However, the residual brightness temperatures were in much closer agreement with observations, hence the dataset was self-consistent which provided added confidence. Furthermore, this demonstration of a 1DVar scheme justifies the use of SEVIRI and AATSR data within a 3D/4DVar system which would facilitate combined platform LST retrieval. Cross-platform comparisons demonstrated that the largest sources of discrepancy were physical differences which were independent of algorithm. There was a strong seasonality, ~4K, in all the cross-platform comparisons with daytime data. Furthermore, there was a strong correlation between the cross-platform discrepancy and view-angle. This was highlighted as a major caveat of satellite LST products which are generally inferred as nadir observations by the end-user community. This is not the case and understanding the viewing geometry associated with satellite LST estimates is paramount to their various applications.

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Compte tenu de la vulnérabilité de la population rurale de la région sahélienne aux aléas pluviométriques, et devant les ambitions de certains acteurs d’utiliser le levier de l’usage des terres pour contribuer à l’atténuation du changement climatique, il est important de comprendre les facteurs contribuant à la variabilité de la couverture végétale au Sahel.Une synthèse de la littérature expliquant l’évolution récente de la végétation au Sahel est donc d’abord présentée. Les études s’intéressant au paradigme qui souligne l’impact de l’usage des terres sur les précipitations en Afrique de l’Ouest évaluent principalement ces effets par le couplage de modèles dynamiques globaux de végétation – DGVM – avec des modèles de circulation générale. C’est à l’amélioration d’un tel DGVM, ORCHIDEE, développé à l’Institut Pierre Simon Laplace, que le reste du travail cherche à contribuer.Comme d’autres études ont montré qu’il était possible d’utiliser en première approximation les steppes pâturées et les jachères pour décrire le comportement global de la surface sahélienne, les écarts entre modèle et mesures sont caractérisés pour une jachère située à proximité de Wankama (Niger). Plus précisément, les forces et faiblesses de la paramétrisation et de la structure par défaut du modèle sont diagnostiqués, et l’importance de la réduction d’erreur permise par l’optimisation de certains des paramètres est donnée. En particulier, l’emploi d’une résolution aux différences finies de la diffusion de l’eau dans la colonne de sol est évalué, dans la mesure où cela permet de mieux simuler la réponse rapide du flux évaporatoire aux événements pluvieux que le schéma conceptuel utilisé par défaut dans ORCHIDEE.Le réalisme du modèle est également mesuré à l’échelle régionale, par la comparaison d’observations de NDVI GIMMS_3G à la couverture végétale simulée par le modèle en réponse à différents forçages climatiques . Si les modifications introduites au cours du travail ne permettent pas de mieux décrire les tendances de la végétation au cours des dernières décennies, tirer partie des leçons du présent travail pourra se révéler utile. Il en est de même des conclusions de l’étude de la transitivité des biais conditionnels du modèle réalisée avec Tao Wang et présentée en annexe B. / The evolution of the land-surface conditions is often assessed through the use of “dynamic global vegetation models”, as is shown in a review of the current understanding of the factors of variability and of the recent evolution of the vegetation cover in the Sahel. Such models are also coupled to atmospheric general circulation models to evaluate the land feedback on precipitation in monsoonal climates.Thus, the improvement of the skills of such surface models to simulate the radiative and turbulent fluxes between the land of surface and the atmosphere in the Sahel over a range of scales from hourly to multi-annual has a potential to have significant implications. This is especially true considering the vulnerability of the rural population of the region, which largely relies on rainfed agriculture and the interest on the evolution of the carbon stocks of ecosystems in the context of climate change. Such a work on the ORCHIDEE model is presented here. In complement to croplands, rangelands and fallows represent a large share of the sahelian landscapes and have intermediate characteristics between erosion glacis and acacia bushes. As such, their evolution (in terms of albedo, roughness length,…) may be used to study the Sahel ecosystem behaviour as a first approximation. Differences between model outputs and field observations are quantified for a fallow close to Wankama (Niger). More precisely, some of the drawbacks of the standard parametrisation and structure of the model are diagnosed, and the range of reduction of the model-observation mismatch that results from optimizing some of the parameters are given (plant phenology,…). In particular, the use of a finite difference resolution of the soil water diffusion is considered as it enables to better simulate the fast response of evaporative fluxes to rainfall than the conceptual scheme routinely used in ORCHIDEE. The benefits of the use of such a “physical” hydrological scheme on the different outputs of the surface scheme is evaluated.The realism of the model is also measured at the regional scale, through a comparison with GIMMS_3G NDVI time series over West Africa. If the modifications that have been introduced in the model don’t improve its ability to describe the vegetation cover trends over the last decades in the region, several lessons can be kept from the analysis that has been realised, especially from the work on the transitivity of state-dependant model biases that has been conducted with Tao Wang and which is presented in annex B.

Les sols agricoles sont la principale source du gaz à effet de serre N₂O. Ces émissions sont caractérisées par une variabilité spatiale et temporelle considérable, ce qui rend très difficile leur quantification. L’UR SOLS étudie depuis 2008 les émissions de N₂O dans une zone agricole du Centre de la France. Spécifiquement, nous avons étudié au laboratoire l’effet de la température sur ces émissions et développé une méthode permettant l’estimation des émissions de N₂O à l’échelle du paysage. De façon surprenante, nous avons observé que les émissions de N₂O n’augmentent pas systématiquement avec la température. L’indicateur Q₁₀ est apparu, pour les émissions de N₂O, variable avec le temps. L’utilisation de l’acétylène, inhibiteur de la réduction de N2O, a révélé que les processus biologiques de production et de consommation de N₂O répondent différemment à la température. Les émissions de N₂O mesurées au champ à l’aide de différentes techniques ont permis d’obtenir des résultats cohérents, avec des moyennes de 43 μg N- N₂O m⁻² h⁻¹ pour la méthode par eddy covariance, 37 μg N- N₂O m⁻² h⁻¹ pour la méthode de fast-box et 71 μg N- N₂O m⁻² h⁻¹ pour la méthode des chambres automatiques sur un blé fertilisé. Des méthodes d’attribution des flux ont été développées pour déterminer de façon exhaustive les variations spatiales et temporelles des émissions de N₂O avec élaboration de cartes originales d’émissions à l’échelle du paysage. L’ensemble de ces résultats pourra être utilisé pour le développement de modèles de fonctionnement des écosystèmes. Ils vont contribuer à quantifier les émissions de N₂O aux échelles adaptées pour les inventaires et les stratégies d’atténuation. / The greenhouse gas N₂O is mainly emitted by soils. Soil emissions are characterized by considerable spatial and temporal variabilities that make their quantification very difficult. While soil N₂O emissions are studied on an agricultural area in the Central France by the UR SOLS since 2008, we specifically studied in the laboratory the effect of temperature on these emissions and also developed a method for upscaling N₂O emissions from the plot to the landscape scales. Surprisingly, N₂O emissions were observed not to increase with temperature. Q₁₀ values, describing N₂O emission sensitivity to temperature, were observed to change over time. The use of acetylene for inhibiting N₂O reduction has revealed that the biological processes involved in the N₂O production and its consumption respond differently to temperature variations. N2O fluxes measured in the field using several methods covering different scales of the landscape gave consistent results. The mean measured N₂O fluxes were 43 μg N- N₂O m⁻² h⁻¹ for the eddy covariance mast, 37 μg N- N₂O m⁻² h⁻¹ for the fast-box over a similar area, while it was 71 μg N- N₂O m⁻² h⁻¹ by the automatic chambers over a fertilized wheat field. Flux attribution methods were developed to determine both the spatial and temporal variability of the N₂O flux over a 1-km landscape, resulting in original maps of N₂O emissions at the landscape scale. All these results could be further used for developing ecosystem models. Both these ecosystems models and the methodologies hereby proposed for upscaling N₂O emissions will help in soil N₂O emission quantification at large scales, relevant to the inventories and mitigation strategies.