REMIND - REgional Model of INvestments and Development

2.1.3

created with goxygen 1.1.0

downscaleTemperature (16_downscaleTemperature)

Description

The module downscaleTemperature downscales the global mean temperature path generated by MAGICC based on REMIND emissions to the regional level. It is a statistical population-weighted downscaling following the methodology by Burke, Hsiang, and Miguel (2015) and described in Schultes et al. (2020). The downscaling factors are currently available only for RCP2.6 and RCP8.5, for SSP2, for the 11 and 12 region versions, either for fixed 2010 populations or changing SSP2 populations. The downscaling factor is calculated based on a CMIP5 GCM ensemble.

Interfaces

Interfaces to other modules
Interfaces to other modules

Input

module inputs (A: CMIP5)
  Description Unit A
pm_globalMeanTemperature
(tall)
global mean temperature anomaly x
pm_interpolWeight_ttot_tall
(tall)
weight for linear interpolation of ttot-dependent variables x
pm_regionalTemperature
(tall, all_regi)
regional temperature x
pm_tall_2_ttot
(tall, ttot)
mapping from tall to ttot x
pm_tempScaleGlob2Reg
(tall, all_regi)
scaling factor from global to regional temperature x

Output

Realizations

(A) CMIP5

This produces the downscaled regional temperatures based on the exogenous downscaling factors and the MAGICC global mean temperature path.

Limitations Downscaling factors are currently only available for RCPs 2.6 and 8.5, for the 11 and 12 region version. They can either be based on fixed 2010 population or changing population (currently only SSP2). The input files are currently hard-coded, so the different options cannot be chosen through a switch.

(B) off

No temperature downscaling - default setting.

Limitations There are no known limitations.

Definitions

Objects

module-internal objects (A: CMIP5)
  Description Unit A
f16_tempGlobalCMIP5
(all_rcp_scen, ttot)
XXX x
f16_tempRegionalCMIP5
(all_rcp_scen, ttot, all_regi)
XXX x
p16_tempGlobalCMIP5
(tall)
global temperature x
p16_tempRegionalCalibrate2005
(all_regi)
XXX x
p16_tempRegionalCMIP5
(tall, all_regi)
regional temperature x

Sets

sets in use
  description
all_rcp_scen all possible RCP scenarios
all_regi all regions
in(all_in) All inputs and outputs of the CES function
modules all the available modules
regi(all_regi) all regions used in the solution process
tall time index
ttot(tall) time index with spin up

Authors

Anselm Schultes

See Also

core

References

Burke, Marshall, Solomon Hsiang, and Edward Miguel. 2015. “Global Non-Linear Effect of Temperature on Economic Production.” Nature 527: 235–39. https://doi.org/doi:10.1038/nature15725.

Schultes, Anselm, Gunnar Luderer, Franziska Piontek, Bjoern Soergel, Joeri Rogelj, Elmar Kriegler, and Ottmar Edenhofer. 2020. “Persistent Economic Damages Determine Social Costs of Carbon.”