Monthly Rainfall Signatures of the North Atlantic Oscillation and East Atlantic Pattern in Great Britain

Atmosphere

Nevil Quinn¹  Michael Horswell¹  Harry West¹ 

[1]Centre for Water, Communities and Resilience, Department of Geography and Environmental Management, University of the West of England, Bristol BS16 1QY, UK

关键词: North Atlantic Oscillation (NAO);    East Atlantic Pattern (EA);    rainfall signatures;    spatio-temporal analysis;    Great Britain;   

DOI  :  10.3390/atmos12111533

来源: DOAJ

【 摘 要 】

Atmospheric-oceanic circulations (teleconnections) have an important influence on regional climate. In Great Britain, the North Atlantic Oscillation (NAO) has long been understood as the leading mode of climate variability, and its phase and magnitude have been found to influence regional rainfall in previous research. The East Atlantic Pattern (EA) is also increasingly recognised as being a secondary influence on European climate. In this study we use high resolution gridded rainfall and Standardised Precipitation Index (SPI) time series data for Great Britain to map the monthly rainfall signatures of the NAO and EA over the period January 1950–December 2015. Our analyses show that the influence of the two teleconnections varies in space and time with distinctive monthly signatures observed in both average rainfall/SPI-1 values and incidences of wet/dry extremes. In the winter months the NAO has a strong influence on rainfall and extremes in the north-western regions. Meanwhile, in the southern and central regions stronger EA-rainfall relationships are present. In the summer months opposing positive/negative phases of the NAO and EA result in stronger wet/dry signatures which are more spatially consistent. Our findings suggest that both the NAO and EA have a prominent influence on regional rainfall distribution and volume in Great Britain, which in turn has implications for the use of teleconnection forecasts in water management decision making. We conclude that accounting for both NAO and EA influences will lead to an enhanced understanding of both historic and future spatial distribution of monthly precipitation.

【 授权许可】

Unknown