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La Niña 2016/2017: historical impact analysis

Hirons, L. ORCID: https://orcid.org/0000-0002-1189-7576 and Klingaman, N. ORCID: https://orcid.org/0000-0002-2927-9303, (2016) La Niña 2016/2017: historical impact analysis. Report. Evidence on Demand

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To link to this item DOI: 10.12774/eod_cr.february2016.hironsetal4

Abstract/Summary

El Niño conditions developed in the tropical Pacific during the latter half of 2015, peaking in December 2015 as one of the strongest El Niño events on record, comparable with the 1997-98 “El Niño of the century”. Conditions in the tropical Pacific are forecast to return to normal over the coming months, with the potential to transition into La Niña conditions during 2016-17. If this was to occur it would act as a further strong perturbation, or ‘kick’, to the climate system and lead to further significant socio-economic impacts affecting many sectors such as infrastructure, agriculture, health and energy. This report analyses La Niña events over the last 37 years of the satellite era (1979-present) and aims to identify regions where there is an increased likelihood of impacts occurring. It is important to note that this analysis is based on past analogous events and is not a prediction for this year. No two La Niña events will be the same – the timing and magnitude of events differs considerably. More importantly, no two La Niña events lead to the same impacts – other local physical and social factors come into play. Therefore, the exact timings, locations and magnitudes of impacts should be interpreted with caution and this should be accounted for in any preparedness measures that are taken. This report has been produced for Evidence on Demand with the assistance of the UK Department for International Development (DFID) contracted through the Climate, Environment, Infrastructure and Livelihoods Professional Evidence and Applied Knowledge Services (CEIL PEAKS) programme, jointly managed by DAI (which incorporates HTSPE Limited) and IMC Worldwide Limited.

Item Type:Report (Report)
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:58443
Publisher:Evidence on Demand

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