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  4. A global perspective on the spatial representation of climate extremes from km-scale models
 
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A global perspective on the spatial representation of climate extremes from km-scale models

Publikationstyp
Journal Article
Date Issued
2025-06-17
Sprache
English
Author(s)
Brunner, Lukas
Poschlod, Benjamin  
Dutra, Emanuel  
Fischer, Erich  
Martius, Olivia  
Sillmann, Jana  
TORE-URI
https://hdl.handle.net/11420/62554
Journal
Environmental research letters  
Volume
20
Issue
7
Article Number
074054
Citation
Environmental Research Letters 20 (7): 074054 (2025)
Publisher DOI
10.1088/1748-9326/ade1ef
Scopus ID
2-s2.0-105008506861
Publisher
IOP
Weather and climate extremes are rare manifestations of climate variability that can severely impact society and the environment. To investigate their properties and changes on a global scale, observational records are often complemented by climate models such as those from the latest Coupled Model Intercomparison Project (CMIP6). However, typical CMIP6 models have a grid spacing of about 100 km and, therefore, do not allow the representation of extremes at local scales important for impacts. Here, we provide a global view on the information lost at such resolutions, focusing on temperature and precipitation extremes. We draw on two next-generation, km-scale global climate models, run with a grid spacing of about 10 km, and regrid them to a range of coarser resolutions. From the regridded data, we then investigate the spatial sub-grid variability hidden at the CMIP6-like 100 km grid spacing to quantify the effect resolution has on the representation of extremes globally. We find clear patterns of such a resolution effect on a diverse set of temperature extremes, particularly in mountainous areas, at coastlines, and along large rivers. For the example of annual maximum temperature, the difference between the 10 km and 100 km grid spacings can exceed 10 <sup>∘</sup>C. For precipitation, globally aggregated low and high extremes are shown to be underestimated at coarse resolution, with the strongest spatial signals emerging in regions with complex topography and in the tropics. Our results quantify existing knowledge and demonstrate the importance of spatial resolution for the representation of climate extremes, in particular for hotspot regions such as coastlines, which often coincide with densely populated areas. The advent of ever higher resolved global models, hence, allows improved estimates of local climate impacts and related risk assessments with global coverage.
Subjects
climate extremes
CMIP6
km-scale models
precipitation
temperature
DDC Class
551: Geology, Hydrology Meteorology
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