Brunner et al. (2026) The variability atlas: how internal climate variability affects the estimation of climate extreme indices
⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.
Identification
- Journal: Environmental Research Letters
- Year: 2026
- Date: 2026-09-18
- Authors: Lukas Brunner, Varun Mithal, Leonard Borchert, Jana Sillmann, Benjamin Poschlod
- DOI: 10.1088/1748-9326/ae9c57
Research Groups
- Max Planck Institute for Meteorology (MPI-M)
Short Summary
This study investigates the impact of internal climate variability on extreme temperature and precipitation events, using a 50-member ensemble from the MPI-ESM global climate model.
Objective
- Investigate the effect of internal climate variability on the estimation of climate extremes as captured by ETCCDI indices.
Study Configuration
- Spatial Scale: Global scale with regional focus.
- Temporal Scale: Period 1995–2014.
Methodology and Data
- Models used: MPI-ESM global climate model (50-member ensemble).
- Data sources: ETCCDI indices, temperature, and precipitation data from the MPI-ESM simulations.
Main Results
- Internal climate variability significantly impacts the assessment of extreme temperature and precipitation events.
- The Variability Atlas interactive online interface allows users to investigate the effect of internal variability for flexible case-specific scenarios.
Contributions
- This study provides a comprehensive understanding of the role of internal climate variability in shaping climate extremes, complementing existing work on this topic.
- The introduction of the Variability Atlas offers practical guidance and tools for users to assess the impact of internal variability on their specific cases.
Funding
- Not specified.
Citation
@article{Brunner2026variability,
author = {Brunner, Lukas and Mithal, Varun and Borchert, Leonard and Sillmann, Jana and Poschlod, Benjamin},
title = {The variability atlas: how internal climate variability affects the estimation of climate extreme indices},
journal = {Environmental Research Letters},
year = {2026},
doi = {10.1088/1748-9326/ae9c57},
url = {https://doi.org/10.1088/1748-9326/ae9c57}
}
Original Source: https://doi.org/10.1088/1748-9326/ae9c57