Decadal predictability of late winter precipitation in western Europe through an ocean–jet stream connection

Abstract

The characteristics of the North Atlantic jet stream play a key role in the weather and climate of western Europe. Although much of the year-to-year variability in the jet stream arises from internal atmospheric processes that are inherently unpredictable on timescales beyond a few days to weeks, any low-frequency variability or long-term trends that can be considered forced by slowly varying boundary conditions offer the potential for extended range predictability of climatological conditions in western Europe. Here we demonstrate that station-based precipitation observations have displayed pronounced multidecadal variability over the past century in western Europe during the late winter. We then use these precipitation observations as an independent verification of the multidecadal Atlantic jet stream variability found in reanalysis products. Both signals are highly correlated with sea surface temperature variability in the North Atlantic that is well predicted in initialized decadal prediction experiments with a coupled general circulation model. Combining the model-based predictions of the sea surface temperature with the observed relationship between precipitation and sea surface temperature, we show that there is great potential for skilful predictions of the forthcoming decadal average of March precipitation in western Europe, with hindcasts for the UK and Portugal yielding anomaly correlation coefficients of 0.82 and 0.69, respectively.

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Fig. 1: Variability in U700 and precipitation from 1901–2016.
Fig. 2: Reconstructing variations in U700NA from precipitation.
Fig. 3: Linking March precipitation to March AMV, via the jet stream.
Fig. 4: Precipitation predictions for the UK and Portugal (Fig. 3d, grey boxes).

Data availability

All data sets used in this study are publicly available. The CESM large ensemble and DPLEs are available through NCAR’s Climate Data Gateway at www.earthsystemgrid.org/. ECMWF reanalyses are available from https://apps.ecmwf.int/datasets/. The CRU TS version 4.01 precipitation data set is available at https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.01/, GPCC precipitation is available at https://doi.org/10.5676/DWD_GPCC/FD_M_V2018_050 and ERSSTv5 SSTs are available at https://doi.org/10.7289/V5T72FNM.

Code availability

All analysis codes will be made available from I.R.S. (islas@ucar.edu) on request.

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Acknowledgements

The CESM project is supported primarily by the National Science Foundation (NSF). This material is based on work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement no. 1852977. S.G.Y. acknowledges the support of the NSF Collaborative Research EaSM2 Grant OCE-1243015. Computing and data storage resources, which include the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. NOAA_ERSST_v5 data were provided by the NOAA/OAR/ESRL PSD at www.esrl.noaa.gov/psd/. The data analysis was performed with IDL (Excelis Visual Information Solutions).

Author information

I.R.S. conceived the study and conducted the analysis. All the authors contributed to decisions regarding the methodology and contributed to the interpretation of the results. S.G.Y. led the DPLE model experiments used extensively in the analysis. I.R.S. wrote the manuscript with input from all the authors.

Correspondence to Isla R. Simpson.

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