Investigating event‐specific drought attribution using self‐organizing maps. Issue 21 (11th November 2016)

• Record Type: Journal Article
• Authors: Harrington, Luke J.; Gibson, Peter B.; Dean, Sam M.; Mitchell, Daniel; Rosier, Suzanne M.; Frame, David J.
• Is Part Of: Journal of geophysical research. Volume 121:Issue 21(2016)
• Page Start: 12, 766
• Page End: 12, 780
• Publication Date: 2016-11-11
• Subjects: drought -- event attribution -- self‐organizing maps -- climate modeling; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2016JD025602
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Previous studies evaluating anthropogenic influences on the meteorological drivers of drought have found mixed results owing to (1) the complex physical mechanisms which lead to the onset of drought, (2) differences in the characteristics and time scales of drought for different regions of the world, and (3) different approaches to the question of attribution. For a midlatitude, temperate climate like New Zealand, strongly modulated by oceanic influences, summer droughts last on the order of 3 months, and are less strongly linked to persistent temperature anomalies than continental climates. Here we demonstrate the utility of a novel approach for characterizing the meteorological conditions conducive to extreme drought over the North Island of New Zealand, using the January–March 2013 event as a case study. Specifically, we consider the use of self‐organizing map techniques in a multimember coupled climate model ensemble to capture changes in daily circulation, between two 41 year periods (1861–1901 and 1993–2033). Comparisons are made with seasonal pressure and precipitation indices. Our results demonstrate robust (>99% confidence) increases in the likelihood of observing circulation patterns like those of the 2013 drought in the recent‐climate simulations when compared with the early‐climate simulations. Best guess estimates of the fraction of attributable risk range from 0.2 to 0.4, depending on the metric used and threshold considered. Contributions to uncertainty in these attribution statements are discussed. Key Points: Evaluating human influence on specific drought events is challenging with present generation of climate models Method of event‐specific drought attribution is proposed by using self‐organizing maps Robust anthropogenic increase found in observing daily circulation features consistent with the 2013 NZ drought