A method for estimating the effect of climate change on monthly mean temperatures: September 2023 and other recent record‐warm months in Helsinki, Finland.
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| Title: | A method for estimating the effect of climate change on monthly mean temperatures: September 2023 and other recent record‐warm months in Helsinki, Finland. |
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| Authors: | Rantanen, Mika1 (AUTHOR) mika.rantanen@fmi.fi, Räisänen, Jouni2 (AUTHOR), Merikanto, Joonas1 (AUTHOR) |
| Source: | Atmospheric Science Letters (John Wiley & Sons, Inc. ). Jun2024, Vol. 25 Issue 6, p1-9. 9p. |
| Subject Terms: | *Global warming, *Climatologists, *Temperature, *Meteorologists, Temperature distribution |
| Geographic Terms: | Helsinki (Finland) |
| Abstract: | We describe a method for quantifying the contribution of climate change to local monthly, seasonal, and annual mean temperatures for locations where long observational temperature records are available. The method is based on estimating the change in the monthly mean temperature distribution due to climate change using CMIP6 (Coupled Model Intercomparison Project Phase 6) model data. As a case study, we apply the method to the record‐warm September 2023 in Helsinki, and then briefly examine all record‐warm months of the 21st century. Our results suggest that climate change made the record‐warm September in Helsinki 9.4 times more likely and 1.4°C warmer. Thus, the new monthly mean record in September 2023 would probably not have been set without the observed global warming. The presented and provided tool allows operational meteorologists and climatologists to monitor and report the impact of climate change on local temperatures in near real time. [ABSTRACT FROM AUTHOR] |
| Copyright of Atmospheric Science Letters (John Wiley & Sons, Inc. ) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
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| Abstract: | We describe a method for quantifying the contribution of climate change to local monthly, seasonal, and annual mean temperatures for locations where long observational temperature records are available. The method is based on estimating the change in the monthly mean temperature distribution due to climate change using CMIP6 (Coupled Model Intercomparison Project Phase 6) model data. As a case study, we apply the method to the record‐warm September 2023 in Helsinki, and then briefly examine all record‐warm months of the 21st century. Our results suggest that climate change made the record‐warm September in Helsinki 9.4 times more likely and 1.4°C warmer. Thus, the new monthly mean record in September 2023 would probably not have been set without the observed global warming. The presented and provided tool allows operational meteorologists and climatologists to monitor and report the impact of climate change on local temperatures in near real time. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 1530261X |
| DOI: | 10.1002/asl.1216 |
