Browse data: Variable
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- Application (39)
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Type: Is input for: Atmospheric composition and climate (2) · Carbon cycle and natural vegetation (5) · Crops and grass (6) · Ecosystem services (7) · Flood risks (2) · Human development (3) · Land-use allocation (2) · Land cover and land use (2) · Land degradation (3) · Livestock systems (2) · Terrestrial biodiversity (3) · Water (2)
Is output of: (Click arrow to add another value) Showing below up to 21 results in range #1 to #21.
- CO2 concentration (Atmospheric CO2 concentration., type: model (from/to model))
- Cloudiness - grid (Percentage of cloudiness per month; assumed constant after the historical period, type: historical data)
- Commodity price (Commodity price per sector, including various crop and livestock sectors.., type: model (end-indicator))
- Crop production (Regional production per crop., type: model (from/to model))
- Demand (all commodities) (Demand per sector including various crop and livestock sectors., type: model (end-indicator))
- Food availability per capita (Food availability per capita., type: model (from/to model))
- Global mean temperature (Average global temperature., type: model (from/to model))
- Land suitability - grid (Suitability of land in a grid cell for agriculture and forestry, as a function of accessibility, population density, slope and potential crop yields., type: model (from/to model))
- Land systems - grid (Thirty land systems as defined in CLUMondo, characterized by specific levels of built-up area, cropland area, livestock density and management intensity., type: model (from/to model))
- Livestock production (Production of livestock products (dairy, beef, sheep and goats, pigs, poultry)., type: model (from/to model))
- Management intensity crops (Management intensity crops, expressing actual yield level compared to potential yield. While potential yield is calculated for each grid cell, this parameter is expressed at the regional level. This parameter is based on data and exogenous assumptions - current practice and technological change in agriculture - and is endogenously adapted in the agro-economic model., type: model (from/to model))
- Management intensity livestock (Management intensity of livestock, expressed at the regional level. This parameter is based on data and exogenous assumptions, i.e. current practice and technological change in livestock sectors, and is endogenously adapted within the Agricultural economy component., type: model (from/to model))
- Non-CO2 GHG concentrations (Atmospheric concentration of non-CO2 greenhouse gases., type: model (end-indicator))
- Number of wet days - grid (Number of days with a rain event, per month; assumed constant after the historical period, type: historical data)
- Ocean carbon uptake (Ocean carbon uptake., type: model (from/to model))
- Precipitation - grid (Monthly total precipitation., type: model (from/to model))
- Radiative forcing (Radiative forcing of greenhouse gases, ozone, and aerosols., type: model (end-indicator))
- Regression parameters (Regression parameters of suitability assessment., type: external parameter)
- Temperature - grid (Monthly average temperature., type: model (from/to model))
- Trade (all commodities) (Bilateral trade between regions per sector, including various crop and livestock sectors., type: model (end-indicator))
- Water stress - grid (Water stress is a basin scale indicator of the mean annual water demand to availability ratio. This ratio gives an indication for the level of water stress experienced in the basin. Basins with a water demand to availability ratio above 0.2 are considered medium water stressed, basins with ratios above 0.4 are severely water stressed., type: model (end-indicator))