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) · Climate policy (1) · Crops and grass (5) · Ecosystem services (5) · Emissions (1) · Energy conversion (2) · Energy demand (1) · Flood risks (2) · Human development (2) · Land-use allocation (1) · Land degradation (3) · Terrestrial biodiversity (1) · Water (2)
Is output of: (Click arrow to add another value) Showing below up to 20 results in range #1 to #20.
- Bioenergy production (Total bioenergy production., type: model (from/to model))
- CO2 concentration (Atmospheric CO2 concentration., type: model (from/to model))
- Carbon storage price (The costs of capturing and storing CO2, affecting the use of CCS technology., type: model (from/to model))
- Cloudiness - grid (Percentage of cloudiness per month; assumed constant after the historical period, type: historical data)
- Energy and industry activity level (Activity levels in the energy and industrial sector, per process and energy carrier, for example, the combustion of petrol for transport or the production of crude oil., type: model (from/to model))
- Energy security indicators (Indicators on the status of energy security, such as energy self-sufficiency., type: model (end-indicator))
- 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))
- Marginal abatement cost (Cost of an additional unit of pollution abated (CO2eq). A marginal abatement cost curve (MAC curve) is a set of options available to an economy to reduce pollution, ranked from the lowest to highest additional costs., 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))
- Primary energy price (The price of primary energy carriers based on production costs., 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))
- Total primary energy supply (Total primary energy supply., 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))