Abstract
Midlatitude atmospheric blocking events are important drivers of long-lasting extreme weather conditions at regional to continental scales. However, modern climate models consistently underestimate their frequency of occurrence compared to observations, casting doubt on future projections of climate extremes. Using the prominent and largely underestimated winter blocking events in Europe as a test case, this study first introduces a spatio-temporal approach to study blocking activity based on a clustering technique, allowing to assess models’ ability to simulate both realistic frequencies and locations of blocking events. A sensitivity analysis from an ensemble of 49 simulations from 24 coupled climate models shows that the presence of a mesoscale eddy-permitting ocean model increases the realism of simulated blocking events for almost all types of patterns clustered from observations. This finding is further explained and supported by concomitant reductions in well-documented biases in Gulf Stream and North Atlantic Current positions, as well as in the midlatitude jet stream variability.
| Original language | English |
|---|---|
| Article number | 50 |
| Number of pages | 15 |
| Journal | npj Climate and Atmospheric Science |
| Volume | 6 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Dec 2023 |
Bibliographical note
Funding Information:This work was sponsored by NWO Exact and Natural Sciences for the use of SurfSARA supercomputer facilities under project 2020.022. This article is TiPES contribution No. 163; the TiPES (Tipping Points in the Earth System) project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 820970. We acknowledge the World Climate Research Program for coordinating and promoting CMIP6, including HighResMIP. We thank the different climate modeling groups for producing and making available their model output, and the Earth System Grid Federation (ESGF) for archiving the dataset and providing access through DRKZ and IPSL nodes (https://esgf-data.dkrz.de/projects/esgf-dkrz/ , http://esgf-node.ipsl.upmc.fr). We thank ECMWF for providing the ERA5 dataset in Copernicus Climate Change Service (C3S) Climate Data Store (https://cds.climate.copernicus.eu/cdsapp#!/home).
Funding Information:
This work was sponsored by NWO Exact and Natural Sciences for the use of SurfSARA supercomputer facilities under project 2020.022. This article is TiPES contribution No. 163; the TiPES (Tipping Points in the Earth System) project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 820970. We acknowledge the World Climate Research Program for coordinating and promoting CMIP6, including HighResMIP. We thank the different climate modeling groups for producing and making available their model output, and the Earth System Grid Federation (ESGF) for archiving the dataset and providing access through DRKZ and IPSL nodes ( https://esgf-data.dkrz.de/projects/esgf-dkrz/ , http://esgf-node.ipsl.upmc.fr ). We thank ECMWF for providing the ERA5 dataset in Copernicus Climate Change Service (C3S) Climate Data Store ( https://cds.climate.copernicus.eu/cdsapp#!/home ).
Publisher Copyright:
© 2023, The Author(s).
Funding
This work was sponsored by NWO Exact and Natural Sciences for the use of SurfSARA supercomputer facilities under project 2020.022. This article is TiPES contribution No. 163; the TiPES (Tipping Points in the Earth System) project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 820970. We acknowledge the World Climate Research Program for coordinating and promoting CMIP6, including HighResMIP. We thank the different climate modeling groups for producing and making available their model output, and the Earth System Grid Federation (ESGF) for archiving the dataset and providing access through DRKZ and IPSL nodes (https://esgf-data.dkrz.de/projects/esgf-dkrz/ , http://esgf-node.ipsl.upmc.fr). We thank ECMWF for providing the ERA5 dataset in Copernicus Climate Change Service (C3S) Climate Data Store (https://cds.climate.copernicus.eu/cdsapp#!/home). This work was sponsored by NWO Exact and Natural Sciences for the use of SurfSARA supercomputer facilities under project 2020.022. This article is TiPES contribution No. 163; the TiPES (Tipping Points in the Earth System) project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 820970. We acknowledge the World Climate Research Program for coordinating and promoting CMIP6, including HighResMIP. We thank the different climate modeling groups for producing and making available their model output, and the Earth System Grid Federation (ESGF) for archiving the dataset and providing access through DRKZ and IPSL nodes ( https://esgf-data.dkrz.de/projects/esgf-dkrz/ , http://esgf-node.ipsl.upmc.fr ). We thank ECMWF for providing the ERA5 dataset in Copernicus Climate Change Service (C3S) Climate Data Store ( https://cds.climate.copernicus.eu/cdsapp#!/home ).
Keywords
- Surface-temperature
- Climate
- Resolution
- Impact
- Variability
- Simulation
- Projection
- Regimes
- Region
- Stream
