Key scenarios include:
All scenarios span from 1960 to 2150, with yearly data until 2030, and data every 5 years thereafter.
Suggested overall reference for the scenario construction: Koch and Leimbach 2023 (link).
The SSP GDP per capita scenarios are constructed using:
WDI data (link) from 1990 to 2022 (missing country data filled in with MI data (link) and James data (link, specifically the WB_ID series)) extended backwards until 1960 using growth rates from MI and James,
growth rates from IMF GDP per capita projections (link) until 2029,
and SSP GDP per capita projections (SSP OECD projections link, release 3.0.1 (March 2024)) until 2100.
The scenarios are extended until 2150 using a bezier curve method that assumes that the slope in 2100 is flattened by half by 2150. For countries lacking projection data, the last historical data point is used in all future years. For more details on the harmonization, see Koch and Leimbach 2023 (link).
The SSP GDP scenarios are the product of the GDP per capita and population scenarios.
Suggested overall reference for the SDP scenarios: Bjoern Soergel et al 2024 Environ. Res. Lett. 19 124009 (link).
The SDP GDP per capita scenarios are all based off of SSP1, with different harmonization functions for the different SDPs.
The SDP GDP scenarios are the product of the GDP per capita and population scenarios.
The SSP population scenarios are constructed using:
WDI data (link) from 1960 to 2022 (missing country data filled in with UN_PopDiv data (link, 2022 revision) and MI data (link)),
growth rates from the World Bank’s Population and Projections database (link) until 2029, and
growth rates from from the SSP population projections (release 3.0.1 (March 2024) link and link), filled in with UN_PopDiv data (link, 2022 revision)) until 2100.
The scenarios are extended until 2150 using a bezier curve method that assumes that the slope in 2100 is flattened by half by 2150. For countries lacking projection data, the last historical data point is used in all future years. For more details on the harmonization, see Koch and Leimbach 2023 (link).
The SDP scenarios are all equal to the SSP1 scenario.
The SSPs labour scenarios are constructed using past WDI data (link) from 1960 to 2022 (missing country data filled in with UN_PopDiv data (link, 2022 revision)), and SSP labour projections (link) until 2100. The labor projections are glued to the data, with no further harmonization.
The SDP scenarios are all equal to the SSP1 scenario.
The tool function toolGetScenarioDefinition() can be
used to see what driver/scenario options are available.
toolGetScenarioDefinition() %>% print(n = 200)
#> # A tibble: 50 × 5
#> driver scenario pastData futureData harmonization
#> <chr> <chr> <chr> <chr> <chr>
#> 1 GDPpc SSPs WDI-MI-James SSPs GDPpcSSPs
#> 2 GDPpc SSP1 WDI-MI-James SSP1 GDPpcSSPs
#> 3 GDPpc SSP2 WDI-MI-James SSP2 GDPpcSSPs
#> 4 GDPpc SSP3 WDI-MI-James SSP3 GDPpcSSPs
#> 5 GDPpc SSP4 WDI-MI-James SSP4 GDPpcSSPs
#> 6 GDPpc SSP5 WDI-MI-James SSP5 GDPpcSSPs
#> 7 GDPpc SDPs - - GDPpcSDPs
#> 8 GDPpc ISIMIP WDI-MI-James SSPs GDPpcSSPs
#> 9 GDPpc SSP2IndiaDEAs WDI-MI-James IndiaDEAs-SSP2 GDPpcSSP2Ind…
#> 10 GDPpc SSP2IndiaMedium WDI-MI-James IndiaDEAbase-SSP2 GDPpcSSP2Ind…
#> 11 GDPpc SSP2IndiaHigh WDI-MI-James IndiaDEAopt-SSP2 GDPpcSSP2Ind…
#> 12 GDP SSPs - - GDPpcWithPop
#> 13 GDP SSP1 - - GDPpcWithPop
#> 14 GDP SSP2 - - GDPpcWithPop
#> 15 GDP SSP3 - - GDPpcWithPop
#> 16 GDP SSP4 - - GDPpcWithPop
#> 17 GDP SSP5 - - GDPpcWithPop
#> 18 GDP SDPs - - GDPpcWithPop
#> 19 GDP ISIMIP - - GDPpcWithPop
#> 20 GDP SSP2IndiaDEAs - - GDPpcWithPop
#> 21 GDP SSP2IndiaMedium - - GDPpcWithPop
#> 22 GDP SSP2IndiaHigh - - GDPpcWithPop
#> 23 Population SSPs WDI-UN_PopDiv-MI SSPs-UN_PopDiv PopSSPs
#> 24 Population SSP1 WDI-UN_PopDiv-MI SSP1-UN_PopDiv PopSSPs
#> 25 Population SSP2 WDI-UN_PopDiv-MI SSP2-UN_PopDiv PopSSPs
#> 26 Population SSP3 WDI-UN_PopDiv-MI SSP3-UN_PopDiv PopSSPs
#> 27 Population SSP4 WDI-UN_PopDiv-MI SSP4-UN_PopDiv PopSSPs
#> 28 Population SSP5 WDI-UN_PopDiv-MI SSP5-UN_PopDiv PopSSPs
#> 29 Population SDPs WDI-UN_PopDiv-MI SDPs-UN_PopDiv PopSSPs
#> 30 Population ISIMIP UN_PopDiv-MI SSPs-UN_PopDiv PopISIMIP
#> 31 Population SSP2IndiaDEAs WDI-UN_PopDiv-MI IndiaDEAs-SSP2-UN_… PopSSP2India…
#> 32 Population SSP2IndiaMedium WDI-UN_PopDiv-MI IndiaDEAbase-SSP2-… PopSSP2India…
#> 33 Population SSP2IndiaHigh WDI-UN_PopDiv-MI IndiaDEAopt-SSP2-U… PopSSP2India…
#> 34 Labour SSPs WDI-UN_PopDiv SSPs-UN_PopDiv pastAndLevel
#> 35 Labour SSP1 WDI-UN_PopDiv SSP1-UN_PopDiv pastAndLevel
#> 36 Labour SSP2 WDI-UN_PopDiv SSP2-UN_PopDiv pastAndLevel
#> 37 Labour SSP3 WDI-UN_PopDiv SSP3-UN_PopDiv pastAndLevel
#> 38 Labour SSP4 WDI-UN_PopDiv SSP4-UN_PopDiv pastAndLevel
#> 39 Labour SSP5 WDI-UN_PopDiv SSP5-UN_PopDiv pastAndLevel
#> 40 Labour SDPs WDI-UN_PopDiv SDPs-UN_PopDiv pastAndLevel
#> 41 Labour SSP2IndiaDEAs - - LabourSSP2In…
#> 42 Labour SSP2IndiaMedium - - LabourSSP2In…
#> 43 Labour SSP2IndiaHigh - - LabourSSP2In…
#> 44 Urban SSPs WDI SSPs pastAndGrowth
#> 45 Urban SSP1 WDI SSP1 pastAndGrowth
#> 46 Urban SSP2 WDI SSP2 pastAndGrowth
#> 47 Urban SSP3 WDI SSP3 pastAndGrowth
#> 48 Urban SSP4 WDI SSP4 pastAndGrowth
#> 49 Urban SSP5 WDI SSP5 pastAndGrowth
#> 50 Urban SDPs WDI SDPs pastAndGrowthThe user can create custom scenarios by creating a tibble called
“mrdivers_scenarios” in the global environment, and filling it with the
desired scenario definitions. The structure of the “mrdivers_scenarios”
object should be identical to that of the return object of
toolGetScenarioDefinition(), and the scenario building
blocks have to be available. For example, say the user wanted to create
SSP scenarios, but without using the Missing Islands data-set. The
following command executed in the global environment would make the
“nomi” (no-missing islands) scenario available.