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.

Crop suitability index in classes, current cropland in grid cell for wheat, cotton and sugarcane under irrigated conditions and high input level, with and without CO2 fertilization, using different climate data source and based on different Representative Concentration Pathways (RCPs) according to the time period as follows: - climate data source CRUTS32 based on historical data for the time period 1981-2010; - climate data source ENSEMBLE based on the Representative Concentration Pathway RCP8.5 for time period 2041-2070. The Crop suitability index in classes dataset is part of the GAEZ v4 Suitability and Attainable Yield - Suitability Class. For additional information, please refer to the GAEZ v4 Model Documentation.

Simplified AEZ classification (33 classes) at about 1 km resolution at the equator, using different climate data source and based on different Representative Concentration Pathways (RCPs) according to the time period as follows: - climate data source CRUTS32 based on historical data for the time period 1981-2010; - climate data source ENSEMBLE based on the Representative Concentration Pathway RCP8.5 for time periods 2041-2070 and 2071-2100. The Simplified AEZ classification dataset is part of the GAEZ v4 Theme 1 Land and Water Resources, Agro-Ecological Zones sub-theme. The agro-ecological zones classification provides a characterization of bio-physical resources relevant to agricultural production systems. AEZ definitions and map classes follow a rigorous methodology and an explicit set of principles. The inventory combines spatial layers of thermal and moisture regimes with broad categories of soil/terrain qualities. It also indicates locations of areas with irrigated soils and shows land with severely limiting bio-physical constraints including very cold and very dry (desert) areas as well as areas with very steep terrain or very poor soil/terrain conditions. For further details, please refer to the GAEZ v4 Model Documentation.

Crop suitability index in classes, all land in grid cell for wheat, cotton and sugarcane under rain-fed conditions and high input level, with and without CO2 fertilization, using different climate data source and based on different Representative Concentration Pathways (RCPs) according to the time period as follows: - climate data source CRUTS32 based on historical data for the time period 1981-2010; - climate data source ENSEMBLE based on the Representative Concentration Pathway RCP8.5 for time period 2041-2070. The Crop suitability index in classes dataset is part of the GAEZ v4 Theme 4 Suitability and Attainable Yield, Suitability Class sub-theme. For additional information, please refer to the GAEZ v4 Model Documentation.

Production for the year 2010 for wheat, cotton and sugarcane under rain-fed, irrigated and total water supply conditions. The Crop Production dataset, at about 5 km resolution, is part of the GAEZ v4 Actual Yields and Production - Area, Yield and Production sub-theme. For additional information, please refer to the GAEZ v4 Model Documentation.

Temperature regimes, solar radiation and available soil moisture determine photosynthesis, which allows plants to accumulate dry matter throughout the plant development stages. Compilation of an AEZ agro-climatic inventory using several climatic variables (e.g. temperature, precipitation, sunshine fraction, relative humidity) gives a general characterization of climatic resources, signifies their suitability for agricultural use and provides data and indicators related to climatic requirements of crop growth, development and yield formation. The inventory includes a variety of agronomically relevant characteristics of prevailing thermal and moisture regimes, and growing periods. GAEZv4 climate data include historical (time-series and 30-year averages covering 1961-2010) and future periods (30-year average of years 2011-2040, 2041-2070, and 2070-2099) using recent IPCC AR5 Earth System Model (ESM) outputs for four Representative Concentration Pathways (RCPs). This theme 2 provides information about (1) Climate Classification, (2) Thermal Regime, (3) Moisture Regime and (4) Growing Period. Results of this theme are presented in a regular raster format of 5 arc-minute (about 9 x 9 km at the equator) grid cells. Climatic conditions are based on a time series of historical data of 1961-2010 and a selection of future climate simulations using recent IPCC AR5 Earth System Model (ESM) outputs for four Representative Concentration Pathways (RCPs). GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

The Thermal climates dataset, at about 9 km resolution, represents major latitudinal climatic zones based on monthly temperatures reduced to sea level. CRUTS32 as climate data source is used based on historical data for the time period 1981-2010. The Thermal climates dataset is part of the GAEZ v4 Theme 2 Agro-climatic Resources, Climate Classification sub-theme. For additional information on agro-climatic resources and indicators, please to Chapter 3 of the GAEZ v4 Model Documentation.

Agricultural production and land statistics are available at national scale from FAOSTAT database, but these statistical data cannot capture the spatial heterogeneity of agricultural production systems at fine resolutions within country boundaries. In this case a “downscaling” method is needed for plausible attribution of aggregate national production statistics to individual spatial units (grid cells) by applying formal methods that account for land characteristics, assess possible production options and can use available evidence from observed or inferred geo-spatial information, including remotely sensed land cover, soil, climate and vegetation distribution, population density and distribution, etc. Theme 5 spatial layers include mapped distributions of harvested area, yield and production at 5 arc-minute resolution for 26 major crops/crop groups, separately in rain-fed and irrigated cropland. Country totals are based on FAO statistics for the years 2009-2011. Also included are estimates of the spatial distribution of total crop production value and the production values of major crop groups (cereals, root crops, oil crops), all valued at year 2000 international prices, separately for rain-fed and irrigated cropland. This theme is organized into two main sub-themes: (1) Area, Yield and Production, and (2) Aggregate Crop Production Value. GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

Yield gaps provide important information for identifying causes of food insecurity and addressing rural poverty. Yield and production gaps have been estimated by comparing at a spatially detailed level of 5 arc-minutes the agro-ecological attainable yield and production of 22 major crops/crop groups (see Theme 4), simulated under the historical climate of 1981-2010, with actual yields and production obtained by downscaling for the years 2000 and 2010 statistical data of main food, feed and fiber crops (see Theme 5). Comparisons are done separately for rain-fed and irrigated cropland and are presented as crop yield achievement ratios for yields, computed as actual over potential yield, and as absolute values for the difference of potential and actual production. Theme 6 provides information about: (1) Crop Yield Achievement Ratio, (2) Production Gap, and (3) Aggregate Yield Achievement Ratio. Results of this theme are presented in a regular raster format of 5 arc-minute (about 9 x 9 km at the equator) grid cells. GAEZ methodology development, data base compilation, production of results and establishing the Data Portal were accomplished in close technical collaboration and with inputs of the International Institute for Applied Systems Analysis (IIASA). For further details, please refer to the GAEZ v4 Model Documentation.

Bias-corrected and downscaled future climate meterological forcing data for Africa, for the period 1948-2099. This dataset is derived from the Global Meteorological Forcing Dataset for Land Surface Modeling, produced by the Princeton University [Department of Civil and Environmental Engineering]. The source data is a 150-yr (1948-2099) dataset of meteorological forcings for driving land surface models and other land modeling schemes. It is derived by bias correcting and downscaling WCRP CMIP3 climate model data for the 20th century and 21st century future climate projections. The dataset is bias-corrected and downscaled using the newly developed equidistant quantile matching method (Li et al., 2010) which better represents changes in the full distribution (not just the mean change). In addition to precipitation and temperature, radiation, humidity, pressure and windspeed are also downscaled. The downsclaing is based on the observational based global forcing dataset of Sheffield et al. (2006) also available from this website. The dataset is currently available at 1.0 degree, 3-hourly resolution globally for 1948-2008. Experimental versions include a 1901-2008 version, real-time updates, higher resolution versions at 0.25deg and 0.5deg and future climate projections based on bias-corrected climate model output. The data are currently available for one climate model (NCAR-PCM1) for the 20th century historical forcing (20C3M; 1948-2000) and one future climate scenario (SRES A2; 2001-2099). This work was supported by NSF Project 0629471 "Collaborative research: Understanding change in the climate and hydrology of the Arctic land region: Synthesizing the results of the ARCSS Fresh Water Initiative Projects". Variables description Tair: 2 m air temperature (K) PSurf: 2 m surface pressure (Pa) Qair: specific humidity (kg/kg) Wind: 10m wind speed (m/s) Precip: precipitation (mm) LWdown: Downwards long-wave radiation flux (W/m-2) LWnet: Net short-wave radiation flux (W/m-2) SWdown: Downwards short-wave radiation flux (average) (W/m-2) This data set has been produced for driving land surface models and other land modeling schemes, in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1).