Issues and challenges in defining a heat wave: A Mediterranean case study

Abstract

We evaluated three definitions of heat wave (HW) and demonstrate that selection of the reference period and air temperature threshold used in the definition can affect the reported frequency of HWs. First, we propose an alternative definition of HW that is based on a moving reference period and specific air temperatures threshold for each calendar date. Then, we present a case study using data from five observatories in Malaga Province (Spain) from 1971 to 2016. We assessed the effect of a moving reference period (rather than a fixed reference period) and the definition of daily air temperatures threshold on the identification of anomalies in the definition of a HW. The results indicate that HWs can occur throughout the year. Finally, we propose incorporation of minimum daily air temperatures in two alternative definitions of HW. Our results indicate a high frequency of HWs in the summer months, in which HWs are mainly due to anomalous high Tmin and more frequent HWs in which maximum and minimum daily air temperature are exceeded from 2014 onwards. These new methods of defining a HW provide more accurate assessments of thermal discomfort.

A Class of Indices and a Graphical Tool to Monitor Temperature Anomalies

“…6,10,[21][22][23][24][25][26] The structure of climate series can differ considerably among regions and locations, and exhibit variability at different scales in response to changes in direct radiative forcing and because of variations in the internal modes of the climate system. 10,24,26,27 In this article, we propose a graphical device that provides an intuitive understanding of air temperature anomalies that will facilitate communication with the general public and aid in advising policy makers. These graphs represent descriptive indices of the temperature anomalies most commonly analyzed: the frequency, intensity, and inequality (variability) of air temperature anomalies.…”

“…We then updated the reference period for subsequent years. We used a method described by Barcena-Martin et al (2019) 10 to define the daily thresholds Tmax and Tmin and to identify temperature anomalies. Below, we describe the method for computation of Tmax; Tmin thresholds can be computed similarly.…”

“…Nonetheless, several studies during the past decade have attempted to identify previous extreme events and to project future extreme events. These studies have employed diverse temperature and precipitation data for identification of return periods [10][11][12] ; calculation of frequency-duration-intensity indices 13 ; analysis by multivariate statistics 14,15 ; and development of indices based on frequency and variance. 16,17 The Intergovernmental Panel on Climate Change 18 Fourth Assessment Report (AR4) focused on 6 types of "extreme weather events" in their discussions of observed changes in extreme events and projections of future extreme events 19,20 : (1) daily maximum and minimum temperatures (coldest and hottest 10% each year); (2) heat waves; (3) heavy precipitation events; (4) droughts; (5) intense tropical cyclone activity; and (6) incidences of extreme high sea levels.…”

“…A temperature anomaly distribution describes the frequency of thermic anomalies in units of the local standard deviation. 10,21 Tebaldi et al 7 described 5 control indexes related to temperature anomalies: (1) total number of frost days, defined as the annual total number of days with an absolute minimum temperature below 0°C; (2) intra-annual extreme temperature range, defined as the difference between the highest and lowest temperature of the year; (3) growing season length, defined as the duration from the first occurrence of 5 consecutive days with mean temperature above 5°C to the last such occurrence during the year; (4) heat wave duration index, defined as the maximum period during each year in which there were at least 5 consecutive days that had maximum temperatures at least 5°C higher than the climatological norm for the same calendar days during a reference period; and (5) number of warm nights, defined as the number of times during the year when the minimum daily temperature is above the 90th percentile of the climatological distribution for that calendar day. On a global scale, Hansen et al 21 showed that as the global distribution of seasonal mean temperature anomalies shifted toward higher temperatures over time, the range of anomalies also increased.…”

Analysis of Weather-Type-Induced Soil Erosion in Cultivated and Poorly Managed Abandoned Sloping Vineyards in the Axarquía Region (Málaga, Spain)

“…Also, it is important to highlight the significant thermal variability in this region. 42 The cultivated plot follows a conventional and traditional grape production of the variety Muscat of Alexandria. It is registered by the Spanish DO (Designation of Origin) with the name of "Málaga, Sierras de Málaga, and Pasas de Málaga."…”