CMIP7 data request: Impacts and adaptation priorities and opportunities

  • Alex C. Ruane
  • , Charlotte L. Pascoe
  • , Claas Teichmann
  • , David J. Brayshaw
  • , Carlo Buontempo
  • , Ibrahima Diouf
  • , Jesus Fernandez
  • , Paula L.M. Gonzalez
  • , Birgit Hassler
  • , Vanessa Hernaman
  • , Ulas Im
  • , Doroteaciro Iovino
  • , Martin Juckes
  • , Iréne L. Lake
  • , Timothy Lam
  • , Xiaomao Lin
  • , Jiafu Mao
  • , Negin Nazarian
  • , Sylvie Parey
  • , Indrani Roy
  • Wan Ling Tseng, Briony Turner, Andrew Wiebe, Lei Zhao, Damaris Zurell

Research output: Contribution to journalArticlepeer-review

Abstract

The Coupled Model Intercomparison Project Phase 7 (CMIP7) undertook an extensive process to gather community input and refine data requests related to impacts and adaptation applications of Earth System Model (ESM) outputs. The Impacts and Adaptation (I&A) Data Request Team worked with CMIP7 leadership to distribute an open solicitation across many communities that use climate model outputs requesting inputs for new and existing variables, the most applicable temporal characteristics, and groupings of variables that together allow for specific application opportunities. This input was then collated and translated into CMIP7 standard templates for inclusion in the broader data request, leading to 13 I&A data request opportunities, 60 variable groups and 539 unique variables sought by vulnerability, impacts, adaptation, and climate services user communities. Here, we describe these opportunities and variable groups, as well as new insights into how ESM groups can prioritize outputs that set off a chain of further analyses, ultimately informing decisions impacting society and natural systems. These include an emphasis on high-resolution outputs to allow further modeling of climate impacts at regional and local scales, improved representation of extreme weather events, enhanced accuracy of downscaling and bias-adjustment techniques, and support for more detailed assessments for decision-making in adaptation and mitigation strategies. There is also broad interest in more extensive provisioning of two-dimensional variables at the Earth's surface, prioritizing experiments that enhance our understanding of both the recent past and future scenarios, and providing outputs that allow further downscaling and bias adjustment. We emphasize that variable groups are the fundamental level at which to engage with the I&A data request, matching the scale of input and the way output provision enables specific I&A applications. Given resource constraints, we applaud CMIP7 efforts to foster strong engagement and communication between ESM groups and the I&A team to build consensus around prudent compromises in priority variables, temporal resolutions, simulation experiments, time subsets, and ensemble members.

Original languageEnglish
Pages (from-to)9497-9540
Number of pages44
JournalGeoscientific Model Development
Volume18
Issue number23
DOIs
StatePublished - Dec 4 2025

Funding

ACR contributions were supported by a NASA Community Service Grant and Earth Science Division support of the NASA GISS Climate Impacts Group. The work of CLP was supported by the National Centre for Atmospheric Science (NCAS, UK). UI acknowledges European Union's Horizon Europe Programme under CleanCloud (No. 101137639). JM was supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA) project funded through the Earth and Environmental Systems Sciences Division of the Biological and Environmental Research Office in the US Department of Energy (DOE) Office of Science. Oak Ridge National Laboratory (ORNL) is supported by the Office of Science of the DOE under Contract No. DE-AC05-00OR22725. DZ contributions were supported by the German Science Foundation DFG (Grant no. ZU 361/6-1). The work of DI was supported by the Foundation Euro-Mediterranean Center on Climate Change (CMCC, Italy). BH received funding from the European Union's Horizon 2020 Research and Innovation program under grant agreement no. 101003536 (ESM2025 - Earth System Models for the Future). The work of CB was supported by the Copernicus Climate Change Service, a programme of the European Commission implemented by ECMWF. The work of MJ was supported by UK Research and Innovation (grant no. NE/Y001729/1). The work of XL was supported by U.S. NSF #2420405. The work of LZ was supported by US NSF CAREER Award no. 2145362; US NASA no. 80NSSC25K7322. ACR contributions were supported by a NASA Community Service Grant and Earth Science Division support of the NASA GISS Climate Impacts Group. The work of CLP was supported by the National Centre for Atmospheric Science (NCAS, UK). UI acknowledges European Union's Horizon Europe Programme under CleanCloud (No. 101137639). JM was supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA) project funded through the Earth and Environmental Systems Sciences Division of the Biological and Environmental Research Office in the US Department of Energy (DOE) Office of Science. Oak Ridge National Laboratory (ORNL) is supported by the Office of Science of the DOE under Contract No. DE-AC05-00OR22725. DZ contributions were supported by the German Science Foundation DFG (Grant no. ZU 361/6-1). The work of DI was supported by the Foundation Euro-Mediterranean Center on Climate Change (CMCC, Italy). BH received funding from the European Union's Horizon 2020 Research and Innovation program under grant agreement no. 101003536 (ESM2025 – Earth System Models for the Future). The work of CB was supported by the Copernicus Climate Change Service, a programme of the European Commission implemented by ECMWF. The work of MJ was supported by UK Research and Innovation (grant no. NE/Y001729/1). The work of XL was supported by U.S. NSF #2420405. The work of LZ was supported by US NSF CAREER Award no. 2145362; US NASA no. 80NSSC25K7322.

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