A consistent and harmonized product of satellite observed fraction of absorbed photosynthetically active radiation (FAPAR). FAPAR is a biophysical variable that indicates the state and health of the vegetation. This data set provides monthly FAPAR from 1982 until 2010 at global scale and for the African continent. The construction of the data set made use of existing products from AVHRR, SeaWiFS and MERIS satellite sensors. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Length of growing season maps for maize, millet and Sorghum, for baseline (1971-2000), 2025 (2010-2039), 2055 (2040-2069), and 2085 (2070-2099). Input Parameters for Climate: Minimum and Maximum Temperature. Input Sources for Climate: 3 GCMs (MIROC5, CanESM2 and NOAA-GFDL) statistically downscaled by UCT at 0.5°, RCP 8.5. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 3 (WP3). WP3 aimed at quantifying the sensitivity of vegetation productivity and water resources to seasonal, inter-annual and decadal variability in weather and climate, using impact models on agriculture and water. The available models in combination with developed datasets of land use and climate from WP2 were used to simulate crop yield and water resources. Simulations using short-term scenarios of future climate change (5-10 years) were used to identify regional differences in the climate sensitivity of crop production etc. Scenarios for the African agricultural/pastoral sectors were also made using longer model runs. Finally, tradeoffs and areas of risk and vulnerability were identified in relation to: - Water-related hazards; - Agricultural and pastoral performance; - Soil degradation. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Suitability maps (produced through a combination of soil and climate suitability) for maize, millet and Sorghum, for baseline (1971-2000), 2025 (2010-2039), 2055 (2040-2069), and 2085 (2070-2099). Input Parameters for Climate: Minimum and Maximum Temperature, Precipitation. Input Parameters for Soil: Texture, Depth, Drainage, Slope, pH, Organic content, Ece, EXP Input Sources for Climate: 3 GCMs (MIROC5, CanESM2 and NOAA-GFDL) statistically downscaled by UCT at 0.5°, RCP 8.5. Input Sources for Soil: HWSD. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 3 (WP3). WP3 aimed at quantifying the sensitivity of vegetation productivity and water resources to seasonal, inter-annual and decadal variability in weather and climate, using impact models on agriculture and water. The available models in combination with developed datasets of land use and climate from WP2 were used to simulate crop yield and water resources. Simulations using short-term scenarios of future climate change (5-10 years) were used to identify regional differences in the climate sensitivity of crop production etc. Scenarios for the African agricultural/pastoral sectors were also made using longer model runs. Finally, tradeoffs and areas of risk and vulnerability were identified in relation to: - Water-related hazards; - Agricultural and pastoral performance; - Soil degradation. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Monthly Gross Primary Productivity (GPP) of natural vegetation (no cropland). Unit: kgC/m²/s Climate Input: MIROC5, CanESM, GFDL Downscaling method/bias correction: RCA3, QMBC, SOMD CO2 scenarios: B1 transient CO2, B2 constant CO2 at 1960 level (316.27ppm) Land use: land use is kept constant at the year 2000 distribution. Temporal Extent: 1961-2099 (monthly resolution) Spatial Extent: Africa Spatial Resolution: 0.5° grid cell This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 3 (WP3). WP3 aims at quantifying the sensitivity of vegetation productivity and water resources to seasonal, inter-annual and decadal variability in weather and climate, using impact models on agriculture and water. The available models in combination with developed datasets of land use and climate from WP2 were used to simulate crop yield and water resources. Simulations using short-term scenarios of future climate change (5-10 years) were used to identify regional differences in the climate sensitivity of crop production etc. Scenarios for the African agricultural/pastoral sectors were also made using longer model runs. Finally, tradeoffs and areas of risk and vulnerability were identified in relation to: - Water-related hazards; - Agricultural and pastoral performance; - Soil degradation. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 3 (WP3). WP3 aimed at quantifying the sensitivity of vegetation productivity and water resources to seasonal, inter-annual and decadal variability in weather and climate, using impact models on agriculture and water. The available models in combination with developed datasets of land use and climate from WP2 were used to simulate crop yield and water resources. Simulations using short-term scenarios of future climate change (5-10 years) were used to identify regional differences in the climate sensitivity of crop production etc. Scenarios for the African agricultural/pastoral sectors were also made using longer model runs. Finally, tradeoffs and areas of risk and vulnerability were identified in relation to: - Water-related hazards; - Agricultural and pastoral performance; - Soil degradation. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

The datasets represent monthly Sensible and Latent Heat Flux at 0.5 degree spatial resolution from 1982 - 2010 over the African continent. For a detailed description of the data sets see: Jung, M. et all. (2011) Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. Journal of Geophysical Research - Biogeosciences, 116, doi:10.1029/2010JG001566. request by email. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

The dataset represents different MODIS Albedo's based on MCD43C3 Albedo 8-Day L3, for the African continent at 8 daily 0.5 degree spatial resolution. The resulting data set is based on the average aof all valid 0.05 degree grid cells within a half degree grid cell. List of Albedos: BSA_nir_Albedo/ [Black Sky Albedo (Near-Infrared)] BSA_shortwave_Albedo/ [Black Sky Albedo (shortwave)] BSA_vis_Albedo/ [Black Sky Albedo (visible)] WSA_nir_Albedo/ [White Sky Albedo (Near-Infrared)] WSA_shortwave_Albedo/ [White Sky Albedo (shortwave)] WSA_vis_Albedo/ [White Sky Albedo (White Sky Albedo (Visible)isible)] This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

The dataset covers Land Surface Temperature (Day and Night) based on the MOD11C2 climate modelling grid (CMG). The resulting product is the average of all 0.05 degree grid cells, within a 0.5 degree grid cell. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Dataset with information on fractions of different crop types /CFTs at different land cover fractions based on the Synergetic Land Cover Product (SYNMAP), at global scale and for the African continent. SYNMAP is an improved global land cover product with 48 classes at 1-km spatial resolution, reflecting global land covers around year 2000. It fuses different global land cover products, including, Global Land Cover Characterization Database (GLCC), GLC2000, and the 2001 MODIS land cover product, based on fuzzy agreement, which highlights individual strengths and weaknesses of mapping approaches. The overall advantage of the SYNMAP legend is that all classes are properly defined in terms of plant functional types mixtures, which can be remotely sensed and include the definitions of leaf type and longevity for each class with a tree component. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

A consistent gapfilled 16 daily Leaf Area Index dataset at half degree spatial resolution based on the original LAI dataset retrieved with the Joint Research Centre Two-stream Inversion Package (JRC-TIP). Aggregation is based on weighted mean of valid 0.01 degree original LAI_TIP pixels. This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.