Casanueva et al. (2014) Variability of extreme precipitation over Europe and its relationships with teleconnection patterns

Identification

• Journal: Hydrology and earth system sciences
• Year: 2014
• Date: 2014-02-19
• Authors: Ana Casanueva, C. Rodríguez‐Puebla, M. D. Frías, Nube González-Reviriego
• DOI: 10.5194/hess-18-709-2014

Research Groups

• Grupo de Meteorología, Dpto. Matemática Aplicada y Ciencias de la Computación, Universidad de Cantabria, Santander, Spain
• Department of Atmospheric Physics, University of Salamanca, Salamanca, Spain

Short Summary

This study evaluates the trends of three precipitation extreme indices (consecutive dry/wet days, CDD/CWD; and contribution of very wet days, R95pTOT) and accumulated precipitation (RR) across Europe, analyzing their relationships with large-scale atmospheric and oceanic teleconnection patterns. The research reveals significant and often opposite seasonal trends in precipitation extremes across Europe, strongly modulated by various teleconnection patterns, with R95pTOT showing a consistent positive trend linked to the Atlantic Multidecadal Oscillation (AMO).

Objective

• To evaluate the trends of three precipitation extreme indices (Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), and the contribution of very wet days (R95pTOT)) and accumulated precipitation (RR) across Europe using non-parametric approaches.
• To analyze the geographically opposite trends found over different parts of Europe by considering their relationships with large-scale atmospheric and oceanic teleconnection patterns to understand the physical causes of their variability.

Study Configuration

• Spatial Scale: Europe, using a 0.5° resolution gridded dataset.
• Temporal Scale: 1950–2010 (61 years) for precipitation data; 1979–2012 for Madden–Julian Oscillation (MJO) data. Analysis performed seasonally (winter, spring, summer, autumn).

Methodology and Data

• Models used:
  • Statistical methods: Mann–Kendall test (for trend significance), Sen’s test (for trend magnitude), Empirical Orthogonal Functions (EOFs) / Principal Component Analysis (PCA) (to identify spatial and temporal variability).
  • Composite maps: Used to analyze atmospheric variables and sea surface temperature for anomalous extreme events and MJO phases.
• Data sources:
  • Gridded daily precipitation: E-OBS data set (version 5.0, 0.5° resolution) developed within the EU ENSEMBLES project.
  • Teleconnection patterns indices: Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Scandinavian Pattern (SCAND), East Atlantic Pattern (EA), East Atlantic/Western Russia Pattern (EAWRUS), Southern Oscillation Index (SOI), Atlantic Multidecadal Oscillation (AMO), and Madden–Julian Oscillation (MJO) from the Climate Prediction Center (CPC) and NCEP NOAA.
  • Atmospheric variables: Sea level pressure (SLP), wind at 850 hPa, and velocity potential at 200 hPa from NCEP/NCAR reanalysis data.
  • Sea surface temperature (SST): Extended reconstructed sea surface temperature (ERRST v3b) from the National Oceanic and Atmospheric Administration (NOAA).

Main Results

• Trends in precipitation extreme indices are generally more significant than those for mean precipitation (RR), particularly for R95pTOT.
• R95pTOT shows a consistent positive trend across all seasons over Europe, suggesting an intensification of the hydrological cycle linked to increased atmospheric moisture content due to warming.
• Winter: RR and CWD exhibit an upward trend in northern Europe and a downward trend in the south, while CDD increases across the Mediterranean Basin. The North Atlantic Oscillation (NAO) is the primary modulator for RR, CDD, and CWD, with positive NAO phases leading to increased precipitation and CWD (decreased CDD) in the north and the opposite in the south. The Atlantic Multidecadal Oscillation (AMO) shows the highest correlation with R95pTOT. Madden–Julian Oscillation (MJO) phase 3 reinforces positive NAO, causing drier conditions in southern Europe and wetter conditions in northern Europe.
• Summer: Mean precipitation decreases in western Europe and increases in the east. CDD significantly increases in southern France and northern Italy, while CWD decreases in the center. R95pTOT increases across the continent. The NAO is again the most important modulator for RR, CDD, and CWD, but with an opposite sign compared to winter. The Scandinavian Pattern (SCAND) also plays a role. AMO is highly correlated with R95pTOT.
• Spring and Autumn: The SCAND, East Atlantic (EA), and Southern Oscillation Index (SOI) patterns play more relevant roles than the NAO. SCAND is strongly related to RR, CDD, and CWD. The SOI influences precipitation over the Iberian Peninsula, with La Niña events associated with wetter springs and El Niño events with wetter autumns. AMO consistently shows the highest correlation with R95pTOT across all seasons.
• Vulnerable regions identified include the Iberian Peninsula (decreasing mean and CWD, increasing CDD in winter, increasing R95pTOT in autumn) and the Alpine region (decreasing CWD, increasing R95pTOT).
• Different seasonal patterns of variability (e.g., north–south dipole in winter, east–west in summer, southwest–northeast in spring/autumn) are found for precipitation extremes, which are explained by the influence of various teleconnection patterns.

Contributions

• Provides a comprehensive, continent-wide analysis of trends in multiple precipitation extreme indices (CDD, CWD, R95pTOT) across Europe, comparing them against mean precipitation.
• Establishes clear relationships between the observed seasonal and regional variability/trends of these precipitation extremes and various large-scale atmospheric and oceanic teleconnection patterns (NAO, SCAND, EA, EAWRUS, SOI, AMO, MJO).
• Highlights the distinct dynamical mechanisms influencing different extreme events, noting that R95pTOT (very extreme precipitation) is more strongly linked to oceanic indices like AMO and local moisture fluxes, while CDD/CWD are more related to large-scale atmospheric circulation.
• Offers insights for improving the projection of precipitation extremes in downscaling techniques by linking them to large-scale processes, addressing limitations of global climate models for hydrological applications.
• Identifies specific "vulnerable regions" in Europe based on the detected trends and their teleconnection influences.

Funding

• EXTREMBLES (CGL2010-21869)
• CORWES (CGL2010-22158-C02)
• GCL2008-04610
• CGL2011-23209 (Spanish R & D & I programme)
• SA222A11-2 (regional project JCyL)
• CLIM-RUN (7th European Framework Programme (FP7))
• FPI programme (BES-2011-047612 and BES-2009-015078) from the Spanish Government (for A. Casanueva and N. González-Reviriego)

Citation

@article{Casanueva2014Variability,
  author = {Casanueva, Ana and Rodríguez‐Puebla, C. and Frías, M. D. and González-Reviriego, Nube},
  title = {Variability of extreme precipitation over Europe and its relationships with teleconnection patterns},
  journal = {Hydrology and earth system sciences},
  year = {2014},
  doi = {10.5194/hess-18-709-2014},
  url = {https://doi.org/10.5194/hess-18-709-2014}
}