Identification

Title

Evaluating the accuracy of climate change pattern emulation for low warming targets

Abstract

Global climate policy is increasingly debating the value of very low warming targets, yet not many experiments conducted with global climate models in their fully coupled versions are currently available to help inform studies of the corresponding impacts. This raises the question whether a map of warming or precipitation change in a world 1.5 degrees C warmer than preindustrial can be emulated from existing simulations that reach higher warming targets, or whether entirely new simulations are required. Here we show that also for this type of low warming in strong mitigation scenarios, climate change signals are quite linear as a function of global temperature. Therefore, emulation techniques amounting to linear rescaling on the basis of global temperature change ratios (like simple pattern scaling) provide a viable way forward. The errors introduced are small relative to the spread in the forced response to a given scenario that we can assess from a multi-model ensemble. They are also small relative to the noise introduced into the estimates of the forced response by internal variability within a single model, which we can assess from either control simulations or initial condition ensembles. Challenges arise when scaling inadvertently reduces the inter-model spread or suppresses the internal variability, both important sources of uncertainty for impact assessment, or when the scenarios have very different characteristics in the composition of the forcings. Taking advantage of an available suite of coupled model simulations under low-warming and intermediate scenarios, we evaluate the accuracy of these emulation techniques and show that they are unlikely to represent a substantial contribution to the total uncertainty.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7gh9mqx

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

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Temporal reference

Temporal extent

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End position

Dataset reference date

date type

publication

effective date

2018-05-03T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact