HWF (sum of days satisfying definition criteria) Globally averaged trends (trends in bold are significant, averaged across all regions with data) HWA (amplitude of hottest event) INDICES A wide range of indices published in the scientific literature employed for heatwave/warm spell measurement were surveyed (see Perkins and Alexander, 2012). By balancing a range of “definitions” and “components”, the framework seeks to satisfy the requirements of many users, as well as enabling the measurement of events from a climatological standpoint. Definitions – a heatwave/warm spell exists when at least 3 consecutive days satisfy the below criterion: 1) CTX90pct: Tmax exceeds the calendar day 90 th percentile, based on a 15-day moving window. 2) CTN90pct: Tmin exceeds the calendar day 90 th percentile, based on a 15-day moving window. 3) EHF: Positive Extreme Heat Factor based on average temperature, derived from: EHI(accl.) = (T i + T i−1 + T i−2 )/3 − (T i−3 + …+ T i−32 )/30 EHI(sig.) = (T i + T i−1 + T i−2 )/3 − T 95 EHF = max[1,EHI(accl.)]x EHI(sig.) Where T i = (Tmax i +Tmin i )/2; T 95 =95 th percentile of time period Aspects (annually per definition): HWN: Total number of events. HWD: Length of longest event. HWF: Sum of days satisfying definition criteria. HWM: Average magnitude of all events. HWA: Hottest day of hottest event. Trends estimated by Sens’ Kendall slope method, significant at 5% level. Closing the Gap on Measuring Heat Waves and Warm Spells Sarah E. Perkins 1,2 and Lisa V. Alexander 1,2 1. Climate Change Research Centre, University of New South Wales, Sydney, Australia. 2. ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, Australia. INTRODUCTION Due to a wide range of impacted sectors (e.g. Coumou and Rahmstorf, 2012), the definition of a heatwave remains is very broad in describing a period of consecutive days where conditions are excessively hotter than normal. This has resulted in a plethora of metrics that seek to measure heatwaves, however are generally only suited to a specific sector or study (e.g. Matzarakis and Mayer, 1997; Deo et al., 2007). This inconsistency creates great difficulty in ascertaining observed changes in heatwaves. Annual warm spells (which include non-summertime events) may also be of interest and need to be measured appropriately DATA Australia: AWAP gridded dataset of daily Tmin and Tmax at 0.5 o X 0.5 o resolution (Jones et al., 2009). Time period All data consistent through space and time. 5-month summer (i.e. heatwaves only) Global: Updated HadGHCND (Donat and Alexander, 2012) daily Tmin and Tmax at 3.75 o x2.5 o resolution. Time period Grid points included with at least 65% of data for the entire period, 5% of which is after month summer for heatwaves (Austral=Nov-Mar; Boreal=Jun-Sep); all months for warm spells. CONCLUSIONS Increasing trends in HWF are driving increases in HWN and HWD. Small-scale differences in changes of event magnitude (HWA, HWM). Tmin (night-time) events increasing fastest, agreeing with other studies. Warm spell trends larger than heatwaves – non-summertime events driving this annual trend more than summertime only events. Qualitatively, all definitions agree on changes of aspects. Framework allows for a consistent measure of events, while permitting the user to “cherry pick” the most appropriate definitions/aspects for their purpose. KEY OBJECTIVE To define a framework in which heatwaves/warm spells can be measured, giving justice to the geographical regions affected, the communities impacted, and the climatic fields involved. REFERENCES Coumou, D. and Rahmstorf, S., 2012: A decade of weather extremes. Nature Climate Change, DOI: /NCLIMATE1452 Donat, M. G., and Alexander L.V., 2012:The shifting probability distribution of global daytime and night-time temperatures, GRL, DOI: /2012GL Deo, R. C., McAlpine C. A., Syktus J., McGowan, H. A. and Phinn, S., 2007: On Australian heatwaves: time series analysis of extreme temperature events in Australia, L. Oxley and D. Kwasiri (eds), Proceedings of the International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand. Jones, D. A., Wang W. and Fawcett R., 2009: High-quality spatial climate data-sets for Australia. Australian Meteorological and Oceanographic Journal, 58, Matzarakis, A. and Mayer, H. 1997: Heat stress in Greece. Int. J, Biometeorol., 41, For more information please see: Perkins, S.E., Alexander L.V. and Nairn J.R., Increasing intensity, frequency and duration of observed global heatwaves and warm spells. GRL, doi: /2012GL Perkins, S.E. and Alexander L.V., On the Measurement of Heatwaves, submitted to J. Climate. %/decade CTN90pct EHF HWD HWA Warm Spells Definition HWN Number /decade HWD Days /decade HWF % days /decade HWA Magnitude/ decade HWM Magnitude /decade WarmCTX90pct SpellCTN90pct EHF HeatCTX90pct WaveCTN90pct EHF Length (days) Magnitude (degrees C/ degrees C 2 Globally averaged time series of CTX90pct, CTN90pct and EHF warm spell HWA (top) and HWD (bottom). Global (warm spells) Global (heatwaves) Australia (heatwaves) CTX90pct days/decade CTN90pct EHF CTX90pct Australia (heatwaves) Global (warm spells) Degrees C/decade Degrees C (C 2 for EHF)/decade