eCommons

 

Data from: Scenarios for modeling solar radiation modification

dc.contributor.authorVisioni, Daniele
dc.date.accessioned2022-07-07T19:03:37Z
dc.date.available2022-07-07T19:03:37Z
dc.date.issued2022-07-07
dc.description.abstractMaking informed future decisions about solar radiation modification (SRM, also known as solar geoengineering) – approaches such as stratospheric aerosol injection (SAI) that would cool the climate by reflecting sunlight – requires projections of the climate response and associated human and ecosystem impacts. These projections in turn will rely on simulations with global climate models. As with climate change projections, these simulations need to adequately span a range of possible futures, describing different choices such as start date and temperature target as well as risks such as termination or interruptions. SRM modeling simulations to date typically consider only a single scenario, often with some unrealistic or arbitrarily chosen elements (such as starting deployment in 2020), and have often been chosen based on scientific rather than policy-relevant considerations (e.g., choosing quite substantial cooling specifically to achieve a bigger response). This limits the ability to compare risks both between SRM and non-SRM scenarios, as well as between different SRM scenarios. To address this gap, we begin by outlining some general considerations on scenario design for SRM. We then describe a specific set of scenarios to capture a range of possible policy choices and uncertainties and present corresponding SAI simulations intended for broad community use. This dataset includes all data used for the figures in this paper.en_US
dc.identifier.doihttps://doi.org/10.7298/xr82-sv86
dc.identifier.urihttps://hdl.handle.net/1813/111357
dc.language.isoen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectclimate changeen_US
dc.subjectsulfateen_US
dc.subjectgeoengineeringen_US
dc.titleData from: Scenarios for modeling solar radiation modificationen_US
dc.typedataseten_US

Files

Original bundle
Now showing 1 - 5 of 10
No Thumbnail Available
Name:
Visioni_PNAS2022_Readme.txt
Size:
3.68 KB
Format:
Plain Text
Description:
No Thumbnail Available
Name:
Visioni_PNAS2022_AODVISstdn.zip
Size:
5.17 MB
Format:
Data Compression Utility
Description:
No Thumbnail Available
Name:
Visioni_PNAS2022_ICEFRAC.zip
Size:
2.7 MB
Format:
Data Compression Utility
Description:
No Thumbnail Available
Name:
Visioni_PNAS2022_MOC.zip
Size:
2.29 GB
Format:
Data Compression Utility
Description:
No Thumbnail Available
Name:
Visioni_PNAS2022_O3_column.zip
Size:
9.77 MB
Format:
Data Compression Utility
Description: