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December 8, 2025Geoscientific model development4 citationsOpen Access

CMIP7 data request: impacts and adaptation priorities and opportunities

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ARAlex C. RuaneJFJesús FernándezPGPaula González

Key Points

  • Adaptation strategies improve decision-making regarding climate vulnerabilities and extreme weather events, emphasizing local action.
  • The analysis identifies key temporal resolutions relevant for effective climate modeling and impact applications.
  • Observational analysis enhances understanding of adaptation strategies, focusing on the needs of user communities and variable groups.
  • Engagement with users is crucial for refining the CMIP7 data request and addressing resource constraints in climate modeling.

Abstract

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 (IA) 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 IA 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 IA data request, matching the scale of input and the way output provision enables specific IA applications. Given resource constraints, we applaud CMIP7 efforts to foster strong engagement and communication between ESM groups and the IA team to build consensus around prudent compromises in priority variables, temporal resolutions, simulation experiments, time subsets, and ensemble members.

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Cite This Study

Ruane et al. (2025) studied this question.

synapsesocial.com/papers/693624a44fa91c937236c270https://doi.org/10.5194/gmd-18-9497-2025
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