Magnitude and Frequency of Heat and Cold Waves in Recent Decades: the Case of South America

Nat. Hazards Earth Syst. Sci., 16, 821–831, 2016 www.nat-hazards-earth-syst-sci.net/16/821/2016/ doi:10.5194/nhess-16-821-2016 © Author(s) 2016. CC Attribution 3.0 License. Magnitude and frequency of heat and cold waves in recent decades: the case of South America Guido Ceccherini1, Simone Russo2, Iban Ameztoy1, Claudia Patricia Romero3, and Cesar Carmona-Moreno1 1European Commission, Joint Research Centre (JRC), Institute for Environment and Sustainability (IES), Water Unit, Via E. Fermi 2749, 21027 Ispra, Italy 2European Commission, Joint Research Centre (JRC), Institute for the Protection and Security of the Citizen (IPSC), Financial and Economic Analysis Unit, Via E. Fermi 2749, 21027 Ispra, Italy 3Facultad de Ingeniería Ambiental, Universidad Santo Tomás, 5878797 Bogota, Colombia Correspondence to: Cesar Carmona-Moreno ([email protected]) Received: 12 November 2015 – Published in Nat. Hazards Earth Syst. Sci. Discuss.: 10 December 2015 Revised: 14 March 2016 – Accepted: 15 March 2016 – Published: 21 March 2016 Abstract. In recent decades there has been an increase in changes in extreme weather conditions such as heat waves, magnitude and occurrence of heat waves and a decrease altering the probability of experiencing major heat waves in of cold waves, both of which may be related to the an- the very near future (Field et al., 2012). This, in turn, may thropogenic influence. This study describes the extreme lead to serious implications, mainly health and health-service temperature regime of heat waves and cold waves across related (Barnett et al., 2012; Conti et al., 2005; Ostro et al., South America over recent years (1980–2014). Temperature 2009). The 2003 European heat wave (Beniston, 2004) illus- records come from the Global Surface Summary of the Day trated how infrastructures, even in highly developed coun- (GSOD), a climatological data set produced by the National tries, can fail to deal with such environmental challenges. Climatic Data Center that provides records of daily maxi- From this perspective, variability and changes in extreme mum and minimum temperatures acquired worldwide. The temperature regimes present a considerable challenge for magnitude of heat waves and cold waves for each GSOD sta- South America (Magrin et al., 2014). Different aspects of tion are quantified on an annual basis by means of the Heat the occurrence of temperature extremes – both spatially and Wave Magnitude Index and the Cold Wave Magnitude Index. temporally – are still lacking for the continent (Rusticucci, Results indicate an increase in intensity and in frequency of 2012). A complete picture, along with a robust assessment, heat waves, especially in the last 10 years. Conversely, no of temperature extreme regimes might provide essential in- significant changes are detected for cold waves. In addition, formation on the climate-related risks that society now face, the trend of the annual temperature range (i.e. yearly mean and how these risks are changing. ◦ of Tmax – yearly mean of Tmin) is positive – up to 1 C per Amongst the areas of South America most vulnerable decade – over the extratropics and negative – up to 0.5 ◦C to heat and cold waves are the so-called “megacities”, per decade – over the tropics. i.e. metropolitan areas with total populations in excess of 10 million people such as Bogota, Sao Paulo, Rio de Janeiro, and Buenos Aires. Climate change issues are thus coupled with anthropic pressure issues. 1 Introduction In order to study extreme temperature regimes, daily records are needed. This requirement is particularly hard to In the coming decades, climate change will expose hundreds meet in South America, which has a sparse sensing network. of millions of people to its impacts (Pachauri et al., 2014; To overcome this problem, the Global Surface Summary of Solomon et al., 2007; WHO, 2015). Many areas of the world the Day (GSOD) meteorological data set has been employed. – Africa and Latin America, among others (Niang et al., GSOD is a compilation of daily meteorological data pro- 2014) – will have to deal with increases in temperature and Published by Copernicus Publications on behalf of the European Geosciences Union. 822 G. Ceccherini et al.: Magnitude and frequency of heat and cold waves in recent decades duced by the National Climatic Data Center (NCDC), available from 1929 to present, which displays a reasonably dense coverage across South America. GSOD has been recently employed to show an increase in the number of heat waves in urban areas at the global scale (Mishra et al., 2015). The aim of this paper is twofold. Firstly, we calculate annual magnitudes of heat waves and cold waves during 1980– 2014 using maximum and minimum daily temperature from GSOD meteorological records. Secondly, we estimate trends of maximum, minimum temperature, and their relative range across South America. These analyses put in evidence of different aspects of temperature extremes, still largely unknown across South America. The analysis presented below follows a three-step pro- cedure that is divided as follows: (1) selection of temperature records with at least 30 years of data (see Sect. 2.2.1); (2) calculation of the Heat Wave Magnitude Index (HWMI) and Cold Wave Magnitude Index (CWMI) for the period 1980–2014; (3) estimation of the trend for annual mean of daily maximum temperature, annual mean of daily minimum temperature, and the mean temperature range D − (i.e. MTR annual mean of daily maximum annual mean Figure 1. Spatial distribution of temperature gauges used in this of daily minimum temperature; see Sect. 2.2 for further de- study. The colour of the GSOD stations refers to the elevation, ex- tails). pressed in m a.s.l. 2 Materials and methods with more than 30 % gaps have not been considered in our 2.1 Materials: GSOD data record. Note that a time series with 30 % gaps does not hinder GSOD is a product produced by the NCDC, derived from the HWMI and CWMI retrieval, and using that threshold we synoptic/hourly observations. GSOD records are mainly col- already exclude ∼ 72 % of the GSOD stations (i.e. 658 out lected at international airports. GSOD records include mean, of 912). A further decrease in that threshold will reduce ex- maximum, and minimum values of temperature, dew point, cessively the number of available temperature stations. Fig- sea level and station atmospheric pressures, visibility, and ure 1 shows the spatial distribution of the 254 temperature wind speed including maximum sustained wind speed and/or stations that satisfy these conditions with the relative eleva- wind gusts, precipitation amounts, snow depth, and indica- tion. tors for occurrences of various weather elements such as fog, rain, snow, hail, thunder, and tornado. Historical data are gen- 2.2.1 The heat and cold wave magnitude indices erally available from 1929, with data from 1973 onwards be- ing the most complete. The total number of GSOD stations Before the introduction of the HWMI (Russo et al., 2014), available across South America is equal to 912. However, not there was no consensus among researchers on the definition all of them satisfy the condition of having at least a 30-year of heat waves (Perkins and Alexander, 2012). In fact, most of timespan, as needed to calculate heat and cold wave magni- them take into account only partial aspects of the heat wave tude indices, as described in Sect. 2.2. event such as maximum temperature, duration, or frequency, without considering the broader picture. 2.2 Methods Recently, Russo et al. (2014) have introduced the HWMI able to overcome the limitation above by merging a few cli- GSOD data are quality controlled through automated quality mate measures, as duration and temperature anomalies, into checks. Most random errors are removed and further correc- a single numerical index (Hoag, 2014). Basically, the magni- tions are applied: e.g. changes in instrumentation and station tude index sums the probability scores associated to consec- displacement to new locations. However, temperature acqui- utive daily temperatures above a threshold (for further details sitions from GSOD are affected by missing data, therefore see Russo et al., 2014). The HWMI is a normalized index and preventing the computation of the HWMI and CWMI which therefore it automatically removes the effect of the different need a daily time series of at least 30 years. For this reason, elevations of GSOD stations. The HWMI computations re- the stations with records of less than 30 years and time series quire a 30-year time series of daily temperature records; the Nat. Hazards Earth Syst. Sci., 16, 821–831, 2016 www.nat-hazards-earth-syst-sci.net/16/821/2016/ G. Ceccherini et al.: Magnitude and frequency of heat and cold waves in recent decades 823 latter normally refers to the 1981–2010 timespan, taken as Table 1. Classification of heat and cold wave (i.e. HWMI and reference period. CWMI) scale categories. Because of the lack of agreement on a cold wave definition, Forzieri et al. (2015) have recently introduced the Classification Heat Wave Cold Wave CWMI. The CWMI is computed in a similar way to the Magnitude Index Magnitude Index HWMI, merging the duration and the intensity of the extreme Normal 1 ≤ HWMI < 2 −1 ≥ CWMI > −2 event into a single numerical index. Moderate 2 ≤ HWMI < 3 −2 ≥ CWMI > −3 In this work, both HWMI and CWMI indices are com- Severe 3 ≤ HWMI < 4 −3 ≥ CWMI > −4 puted to detect South American heat and cold waves in the Extreme 4 ≤ HWMI < 8 −4 ≥ CWMI > −8 present climate. For further details on HWMI computation, Very extreme 8 ≤ HWMI < 16 −8 ≥ CWMI > −16 see the relative definition in Russo et al. (2014). Regarding Super extreme 16 ≤ HWMI < 32 −16 ≥ CWMI > −32 the CWMI, it has been defined for each GSOD station by the Ultra extreme HWMI ≥ 32 CWMI ≤ −32 following steps.

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