A
Average duration of a drought event (SSI-1) - SSP1 Lower bound
Average duration of a drought event in days as defined by the SSI-1 indicator (Standardised Streamflow Index cumulated on a 1-month window) a consecutive series of days below -1 using SSP1 Lower bound Climate change scenario.
The existing climate refers to the entire historical period of the last 40 years (1979 - 2016) the methodology employed for the computation is exhaustively explained in the Background paper.
There are reference periods for the existing climate and for the future scenarios the average duration is computed over such periods in a statistical sense (for future years from 2060 to 2100 are considered). The definition of the indicator is a series of consecutive days where the used indicator is below -1. Read More
The existing climate refers to the entire historical period of the last 40 years (1979 - 2016) the methodology employed for the computation is exhaustively explained in the Background paper.
There are reference periods for the existing climate and for the future scenarios the average duration is computed over such periods in a statistical sense (for future years from 2060 to 2100 are considered). The definition of the indicator is a series of consecutive days where the used indicator is below -1. Read More
Average duration of a drought event (SSI-1) - SSP5 Upper bound
Average duration of a drought event in days as defined by the SSI-1 indicator (Standardised Streamflow Index cumulated on a 1-month window) a consecutive series of days below -1 using SSP5 Upper bound Climate change scenario.
The existing climate refers to the entire historical period of the last 40 years (1979 - 2016) the methodology employed for the computation is exhaustively explained in the Background paper.
There are reference periods for the existing climate and for the future scenarios the average duration is computed over such periods in a statistical sense (for future years from 2060 to 2100 are considered). The definition of the indicator is a series of consecutive days where the used indicator is below -1. Read More
The existing climate refers to the entire historical period of the last 40 years (1979 - 2016) the methodology employed for the computation is exhaustively explained in the Background paper.
There are reference periods for the existing climate and for the future scenarios the average duration is computed over such periods in a statistical sense (for future years from 2060 to 2100 are considered). The definition of the indicator is a series of consecutive days where the used indicator is below -1. Read More
B
Bias Adjusted TX35
Number of days with maximum temperature above 35 degree Celsius (bias adjusted using ISIMIP3 method).
Units: days Read More
Units: days Read More
Building Exposure Model (BEM) - Non-residents
The Global Building Exposure Model, or simply BEM provides essential data for understanding the potential impact of hazards on the built environment.
An exposure model that includes a global inventory of the building stock based on a purely bottom-up approach would require considerable human and economic effort and is beyond the scope of this project.
In the absence of a bottom-up approach, a spatial disaggregation was used. This consists of a top-down or 'downscaling' approach, where information including socio-economic, building type and capital stock at national or sub-national level (statistical data) is transferred to a regular grid, using GIS data such as geographic population and Gross Domestic Product (GDP) distribution models as proxies. Read More
An exposure model that includes a global inventory of the building stock based on a purely bottom-up approach would require considerable human and economic effort and is beyond the scope of this project.
In the absence of a bottom-up approach, a spatial disaggregation was used. This consists of a top-down or 'downscaling' approach, where information including socio-economic, building type and capital stock at national or sub-national level (statistical data) is transferred to a regular grid, using GIS data such as geographic population and Gross Domestic Product (GDP) distribution models as proxies. Read More
Building Exposure Model (BEM) - Residents
The Global Building Exposure Model, or simply BEM provides essential data for understanding the potential impact of hazards on the built environment.
An exposure model that includes a global inventory of the building stock based on a purely bottom-up approach would require considerable human and economic effort and is beyond the scope of this project.
In the absence of a bottom-up approach, a spatial disaggregation was used. This consists of a top-down or 'downscaling' approach, where information including socio-economic, building type and capital stock at national or sub-national level (statistical data) is transferred to a regular grid, using GIS data such as geographic population and Gross Domestic Product (GDP) distribution models as proxies. Read More
An exposure model that includes a global inventory of the building stock based on a purely bottom-up approach would require considerable human and economic effort and is beyond the scope of this project.
In the absence of a bottom-up approach, a spatial disaggregation was used. This consists of a top-down or 'downscaling' approach, where information including socio-economic, building type and capital stock at national or sub-national level (statistical data) is transferred to a regular grid, using GIS data such as geographic population and Gross Domestic Product (GDP) distribution models as proxies. Read More
Building Exposure Model (BEM) - Total
The Global Building Exposure Model, or simply BEM provides essential data for understanding the potential impact of hazards on the built environment.
An exposure model that includes a global inventory of the building stock based on a purely bottom-up approach would require considerable human and economic effort and is beyond the scope of this project.
In the absence of a bottom-up approach, a spatial disaggregation was used. This consists of a top-down or 'downscaling' approach, where information including socio-economic, building type and capital stock at national or sub-national level (statistical data) is transferred to a regular grid, using GIS data such as geographic population and Gross Domestic Product (GDP) distribution models as proxies. Read More
An exposure model that includes a global inventory of the building stock based on a purely bottom-up approach would require considerable human and economic effort and is beyond the scope of this project.
In the absence of a bottom-up approach, a spatial disaggregation was used. This consists of a top-down or 'downscaling' approach, where information including socio-economic, building type and capital stock at national or sub-national level (statistical data) is transferred to a regular grid, using GIS data such as geographic population and Gross Domestic Product (GDP) distribution models as proxies. Read More
C
Climate adaptation
Adjustments in ecological, social, or economic systems in response to actual or expected climatic stimuli and their effects. It refers to changes in processes, practices and structures to moderate potential damages or to benefit from opportunities associated with climate change
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Climate change
Adjustments in ecological, social, or economic systems in response to actual or expected climatic stimuli and their effects. It refers to changes in processes, practices and structures to moderate potential damages or to benefit from opportunities associated with climate change (UNFCCC, https://unfccc.int/topics/adaptation-and-resilience/the-big-picture/introduction).
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Climate scenarios for hazards
Climate scenarios
The reference period for present is 1979 - 2016 while for future scenarios is 2060 - 2100.
For the future climate, the ISIMIP3b dataset has been selected as state-of-the-art climate projection. Two scenarios were chosen, adopting as criterion a statistical selection based on the percentiles of the ensemble of temperature trajectories . The Lower bound represents the 20-percentile of the ensemble of average world temperature over land of the ensemble of the entire ISIMIP3b scenario ensemble, while the Upper bound represents the 80-percentile. Read More
The reference period for present is 1979 - 2016 while for future scenarios is 2060 - 2100.
For the future climate, the ISIMIP3b dataset has been selected as state-of-the-art climate projection. Two scenarios were chosen, adopting as criterion a statistical selection based on the percentiles of the ensemble of temperature trajectories . The Lower bound represents the 20-percentile of the ensemble of average world temperature over land of the ensemble of the entire ISIMIP3b scenario ensemble, while the Upper bound represents the 80-percentile. Read More
CO2 anthro. emissions
Anthropogenic CO2 emissions. Units: kg/m**2
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