A rapid application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)

Mathison, Camilla Therese; Burke, Eleanor J.; Kovacs, Eszter; Munday, Gregory; Huntingford, Chris ORCID: https://orcid.org/0000-0002-5941-7770; Jones, Chris D.; Smith, Chris J.; Steinert, Norman J.; Wiltshire, Andy J.; Gohar, Laila K.; Varney, Rebecca M.. 2024 A rapid application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME). EGUsphere, egusphere-2023-2932. https://doi.org/10.5194/egusphere-2023-2932

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Abstract/Summary

Climate policies evolve quickly, and new scenarios designed around these policies are used to illustrate how they impact global mean temperatures using simple climate models (or climate emulators). Simple climate models are extremely efficient although limited to showing only the global picture. Within the Intergovernmental Panel on Climate Change (IPCC) framework, there is a need to understand the regional impacts of scenarios that include the most recent science and policy decisions quickly to support government in negotiations. To address this, we present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), a new flexible probabilistic framework which aims to provide an efficient means to run new scenarios without the significant overheads of larger more complex Earth system models (ESMs). PRIME provides the capability to include the most recent models, science and scenarios to run ensemble simulations on multi-centennial timescales and include analysis of many variables that are relevant and important for impacts assessments. We use a simple climate model to provide the global temperatures to scale the patterns from a large number of the CMIP6 ESMs. These provide the inputs to a weather generator and a land-surface model, which generates an estimate of the land-surface impacts from the emissions scenarios. Here we test PRIME using known scenarios in the form of the Shared Socioeconomic Pathways (SSPs) to demonstrate that PRIME reproduces the climate response to a range of emissions scenarios, as shown in the IPCC reports. We show results for a range of scenarios including the SSP5-8.5 high emissions scenario, which was used to define the patterns; SSP1-2.6, a mitigation scenario with low emissions and SSP5-3.4-OS, an overshoot scenario. PRIME correctly represents the climate response for these known scenarios, which gives us confidence that PRIME will be useful for rapidly providing probabilistic spatially resolved information for novel climate scenarios; substantially reducing the time between the scenarios being released and being used in impacts assessments.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/egusphere-2023-2932
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
NORA Subject Terms:	General > Science Policy Meteorology and Climatology Data and Information
Related URLs:	Dataset Dataset Other Other
Date made live:	01 Mar 2024 11:50 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537005

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