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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引用次数: 0
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.
期刊介绍:
Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques.
We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.