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The role of teleconnection patterns in the variability and trends of growing season indices across Europe

Craig, P. M. ORCID: https://orcid.org/0000-0001-9213-4599 and Allan, R. P. ORCID: https://orcid.org/0000-0003-0264-9447 (2021) The role of teleconnection patterns in the variability and trends of growing season indices across Europe. International Journal of Climatology. ISSN 0899-8418

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To link to this item DOI: 10.1002/joc.7290

Abstract/Summary

Teleconnection patterns affect the weather and climate on both interannual and decadal timescales which in turn affects various socio-economic sectors such as agriculture. We use three climate indices based on E-OBS data from the INDECIS dataset (growing season onset [ogs10], growing season rainfall [gsr] and growing season temperature [ta_o]) to assess the interannual variability and trends over 1950–2017 associated with four teleconnection patterns (North Atlantic Oscillation [NAO], East Atlantic pattern [EA], Scandinavian pattern [SCA] and East Atlantic/West Russia pattern [EAWR]) using linear regression to extract the signal of each teleconnection pattern and their contribution to interannual variability. Trends towards an earlier growing season onset are found across most of Europe in low-lying regions. The NAO dominates interannual variability in northwest Europe where an NAO index of 1 is associated with earlier ogs10 of about 10 days and the EA dominates the continent with a trend towards the positive EA phase driving an earlier growing season onset of 1.1–1.7 days·decade−1 in five regions (Great Britain and Ireland, France, Italy, Poland and North Germany, Hungary, Balkans). The EA and SCA gsr signals have north/south splits of orientation: positive EA is linked to increased gsr in northern regions and reduced gsr in southern Europe, and vice versa for SCA. Correlations between gsr interannual variability and the teleconnection contributions are strongest in the Mediterranean regions and south Scandinavia with maxima of 0.41 and 0.46, respectively. Decreasing ta_o trends in Romania are explained by poor data coverage causing problems with the EOBS gridding algorithm when new stations are incorporated from 1961. The net effect is that Romanian ta_o is about 1.5°C cooler than expected compared to trends from surrounding countries. Improved spatial and temporal data coverage will benefit the EOBS dataset and prevent such erroneous trends.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:99382
Uncontrolled Keywords:climate indices growing season onset precipitation teleconnections temperature
Publisher:Wiley

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