Data Snack - From Data to Action: How Climate Data Inform Decisions

Climate data are widely used to study climate change and its impacts, and increasingly play a role in decision-making across science, policy, and society. These datasets originate from a range of sources – including observations, reanalyses (e.g., ECMWF), and global and regional climate model simulations (e.g., CMIP and CORDEX). However, their size, complexity, and diversity often make them difficult to access, compare and interpret, especially for non-specialists. Working with climate data therefore involves more than analysis alone. It requires finding and selecting suitable datasets, preparing them through subsetting, regridding, and harmonization, and deriving meaningful indicators for specific regions or applications. At the same time, ensemble approaches are essential to assess robustness and to account for uncertainties inherent in climate projections. While these technical steps are important, the challenge does not end there. Climate data must ultimately be translated into accessible and usable information. This Data Snack focuses on how climate data are turned into products such as fact sheets or decision-support tools, and highlights key considerations for their interpretation and communication across disciplines.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-21
DOI
https://doi.org/10.5281/zenodo.20320887
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00
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article

Data Snack - From Data to Action: How Climate Data Inform Decisions

Lars Buntemeyer
Zenodo (CERN European Organization for Nuclear Research)
Climate variability and models
article

Data Snack - From Data to Action: How Climate Data Inform Decisions

Lars Buntemeyer
article en

Abstract

Climate data are widely used to study climate change and its impacts, and increasingly play a role in decision-making across science, policy, and society. These datasets originate from a range of sources – including observations, reanalyses (e.g., ECMWF), and global and regional climate model simulations (e.g., CMIP and CORDEX). However, their size, complexity, and diversity often make them difficult to access, compare and interpret, especially for non-specialists. Working with climate data therefore involves more than analysis alone. It requires finding and selecting suitable datasets, preparing them through subsetting, regridding, and harmonization, and deriving meaningful indicators for specific regions or applications. At the same time, ensemble approaches are essential to assess robustness and to account for uncertainties inherent in climate projections. While these technical steps are important, the challenge does not end there. Climate data must ultimately be translated into accessible and usable information. This Data Snack focuses on how climate data are turned into products such as fact sheets or decision-support tools, and highlights key considerations for their interpretation and communication across disciplines.

Zenodo (CERN European Organization for Nuclear Research)
Helmholtz-Zentrum Hereon (DE)
Climate action
Openalex Percentile: Top 6%
Climate variability and models
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