COLD WAVES IN THE CAPITAL CITIES OF THE BRAZILIAN SOUTH REGION - AIC 2019
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COLD WAVES IN THE CAPITAL CITIES OF THE BRAZILIAN
SOUTH REGION
ALVES M.P.A. (1), SILVEIRA R.B. (1), NASCIMENTO JR L. (1)
(1) Applied Climatology Laboratory (LabClima), Department of Geosciences, Federal University of Santa
Catarina, Trindade, Florianópolis/SC, Brazil, [maiconpassos@gmail.com]; [rafael.brito@posgrad.ufsc.br];
[lindberg.junior@ufsc.br].
Summary: A number of studies have shown that the world’s mean air temperature has been increasing. In view
of that, research on extreme heat events is usually more commonly carried out. However, it does not mean that
research on extreme cold events is less important, as such events also have impacts on society in many sectors.
This study aimed to analyze cold waves in the three capital cities of the South of Brazil, i.e. Curitiba,
Florianópolis and Porto Alegre, based on the following parameters: frequency, duration and intensity. Cold
waves were detected as per average daily air temperature within a period of 30 years. In general, the most
intense cold waves were found in Curitiba, followed by Porto Alegre and Florianópolis. A greater number of
cold waves was detected in Curitiba. It is possible to observe that, although they seem to be diminishing, the cold
waves continue to occur, which can generate negative impacts.
Key words: Cold Waves; Parameters; South Region of Brazil.
Résumé : Plusieurs études ont montré que la température moyenne de l'air augmente dans le monde. Dans cette
perspective, les recherches sur les chaleurs extrêmes sont généralement plus courantes. Toutefois, cela ne
signifie pas que la recherche sur les phénomènes de froid extrême est moins importante, puisque ces événements
ont également des impacts dans plusieurs secteurs de la société. Cette étude vise à analyser les vagues de froid
dans les trois capitales du sud du Brésil, à savoir: Curitiba, Florianópolis et Porto Alegre, sur la base des
paramètres suivants: fréquence, durée, et intensité. Les vagues de froid ont été détectées selon la température
quotidienne moyenne de l'air au cours d’une période de 30 ans. En général, les vagues de froid les plus intenses
ont été observées à Curitiba, suivies de Porto Alegre et de Florianópolis. Un plus grand nombre de vagues de
froid a été détecté à Curitiba. On peut observer que, même si elles semblent diminuer, les vagues de froid
continuent de se produire, ce qui peut générer des impacts négatifs.
Mots clés: Vagues de froid; Paramètres; Région sud du Brésil.
Introduction
Although the Brazilian territory is predominantly tropical, nearly the entire South of Brazil
is under a subtropical climate condition, which results in contrasting characteristics of air
temperature throughout the year. It is worth stressing that the highest areas of this region
sometimes sees episodes of snowfall (Grimm, 2009). Florianópolis (FLN) and Porto Alegre
(POA) are capital cities with the Cfa climate type, according to the Köppen-Geiger
classification, i.e. wet mesothermic climate with well distributed rainfall throughout the year.
Curitiba (CWB) has the Cfb climate type, which is typical of a mesothermic environment
with cool summers and typically dry winters (Danni-Oliveira, 1999).
CWB, FLN and POA (Figure 1) are the capitals of the states of Paraná (PR), Santa
Catarina (SC) and Rio Grande do Sul (RS), respectively. In the 2010 Census, these cities, in
the same order, had a population of approximately 1.7 million, 421,000 and 1.4 million
inhabitants (IBGE, 2010). CWB is located at an altitude of approximately 1000 meters,
making relief a geographic factor of great importance for the climate of the place, especially
in terms of temperature. Mendonça and Danni-Oliveira (2007) point out that CWB is the
coldest capital of the country. FLN is a coastal city, therefore, the maritime dimension is a
key factor in temperature thermoregulation (Steinke, 2012). POA is located at a higher
latitude compared to the other capitals in question. Therefore, as Cavalcanti and Kousky
(2009) emphasize, there is a greater number of cold front events (~ 40 per year).Figure 1. Location of the meteorological stations in the cities studied, and location of the South Region of Brazil in South America. The Brazilian subtropical region is influenced by atmospheric systems of polar origin coming from the Antarctic continent. The conditions associated with such air mass events occasionally persist for consecutive days, and may form a cold wave (Mendonça; Romero, 2012). Concerning the city of CWB between 1961 and 2016, Silveira et al. (2017) found 150 CW episodes, with more than 50% of the occurrences being in winter. Regarding the city of FLN from 2000 to 2010, Alves et al. (2017) identified a variation between 5 and 142 CWs when comparing ten different methods, except for the World Meteorological Organization (WMO) method. The authors observed that autumn and winter were the seasons with the greatest number of data records. As regards POA, there is no specific study counting cold waves; however, Firpo et al. (2008) studied CWs in the State of RS, Brazil, between 1967 and 2005, and detected an annual average of approximately one event per year in the cities of Torres and Encruzilhada do Sul, located near the capital. The authors also observed that winter is the season with the highest rates of cold wave occurrences. What the studies for these capitals have in common is that all the seasons of the year had cold waves even after winter. Earlier, Monteiro (1963), when studying the climate of southern Brazil, pointed to that possibility. In view of the above, this study aimed to analyze cold wave occurrences in the three capital cities of the South of Brazil through the following parameters: frequency, duration and intensity. 1. Data and Method 1.2 Data source and detection method Mean air temperature ( ̅ ) was obtained daily from the Meteorological Database for Education and Research (BDMEP) of the National Institute of Meteorology (INMET, Brazil) within the period from 1970 to 2016. The weather stations utilized for the study are conventional ones and their locations can be observed in Figure 1.
Although the data collected comprised 47 years, some of them showed considerable
failures, so the years presenting 15% or more of lack of data were excluded. Even after the
exclusion of those years, the data set remained consistent, covering 30 years in the three
cities, from 1970-1978, 1992-2000, 2002-2010 to 2012, 2014 and 2016.
For a wave to be considered a CW, ̅ must be less than or equal to the value of the daily
climatic temperature (T̅̅̅) minus two standard deviations ( ̅ , for two consecutive days or
more, thus, when ̅ ≤ (T̅̅̅ - 2 ̅) during the established period, then there is a CW (VAVRUS
et al., 2006). ̅ is given by the average annual value of the 366 (January 1 to December 31)
daily standard deviations.
1.3 Parameter analysis
After CW events were identified, based on their respective daily thresholds, the
quantitative data were grouped monthly and then annually, thus characterizing frequency.
Duration and intensity also went through the same grouping process. Duration refers to the
number of days that the event persisted. In addition, waves starting and ending in different
months were counted for the month they started. Intensity is the arithmetic mean air
temperature ( ̅ ) of the days with CWs.
2. Results
Figure 2 shows the daily temperature thresholds that indicate a cold day and possibly a
CW. Based on these thresholds, it can be seen that the three cities presented variability
between seasons, with emphasis on summer and winter. This is linked to the characteristics of
the geographical factors of each location. CWB has the lowest thresholds since it is at an
altitude of 1000 m. Fritzons et al. (2008) point out that in the State of PR, Brazil, temperature
generally decreases by 1 °C every 126 m.
FLN notably has the least stringent thresholds, demonstrating the key role of ocean
thermoregulatory action over air temperature, including when it comes to its own interannual
variability. The ocean thermoregulatory action of the State of SC, Brazil, is pointed out by
Peluso Jr. (1991) and Monteiro e Silva (2017), for example.
24
Average temperature (°C)
21
18
15
12
9 CWB
6 FLN
3 POA
0
01/jan 27/jan 22/fev 19/mar 14/abr 10/mai 05/jun 01/jul 27/jul 22/ago 17/set 13/out 08/nov 04/dez 30/dez
Days
Figure 2. Daily thresholds of ̅ (°C) for cold day classification (366 days/values).
POA is in an intermediate position with respect to the thresholds when compared to FLN
and CWB. In other words, it can be said that in this case the latitude factor does not overlap
with the altitude factor; however, during the winter the thresholds for POA and CWB are
similar. This can be explained by the fact that winter is the season and/or period of greatest
incursion of transient systems (Cavalcanti and Kousky, 2009, p. 139) and also because POAreceives a lower incidence of sunlight; even being POA under the same subtropical condition
as CWB.
2.1 Frequency
It was observed that the frequency of CW occurrences has been decreasing over the years
in all three cities (Figure 3). In CWB, 81 CWs were detected throughout the period under
study, which corresponds to an average of 2.7 CW/year. It is worth noting that the first half of
the time series shows a higher frequency of CWs, especially in the years 1971 and 1972. The
year 1971 was considerably cold, which generated a pioneering study conducted by Titarelli
(1972), who discussed the CW of April 1971, an event that reached several regions of Brazil.
Figure 3. Cold wave annual frequency (number) by city between 1970 and 2016. Note: The years 1979-1991,
2001, 2011, 2013 and 2015, although mentioned in the graphs, were excluded from the analysis as they failed to
meet the criterion adopted.
FLN is similar to CWB in terms of frequency distribution. In the same way, the first years
of the time series demonstrate higher frequencies. However, the second half of the series for
FLN shows greater amplitude compared to CWB. In FLN, the annual average of CWs is 2.6.
POA notably differs from the other cities as the general amplitude of CW frequency is
smaller, without high peaks of frequency. POA has an average of 2.3 CW/year, being the
lowest average among the three cities.
2.2 Duration
It was noted that in CWB most of the years had CWs with a duration of less than 2.5 days
on average. This demonstrates that these events in CWB last less time than in the other two
cities. The year 2007 in CWB (Figure 4) stands out for having the longest average duration (5
days) and is as well the year with the highest average duration of the three cities studied. FLN
and POA are similar in terms of CW duration. The highest average annual duration in FLN
occurred in 2016 (4.5 days) and in POA in the year 2009 (4 days).
Figure 4. Average annual duration of CWs (days) by city between 1970 and 2016. Note: the absence of markers
are years without CW occurrences rather than data failures, except for 1979-1991, 2001, 2011, 2013 and 2015.
Interestingly, the years with the highest duration are between 2007 and 2016, that is, in the
decades that are closest to present times.2.3 Intensity
The average annual intensity of the waves in FLN has low annual amplitude, varying
between 15.3 °C and 10.6 °C, which are, comparatively, the least stringent CWs among the
capitals of southern Brazil. CWB in general has CWs with the highest intensity, the year 1996
being the one with the lowest annual average, more specifically 4.6 °C.
Figure 5. Average annual intensity of CWs (ºC) by city between 1970 and 2016. Note: the absence of markers
are years without CW occurrences rather than data failures, except for 1979-1991, 2001, 2011, 2013 and 2015.
The year 1998 in the city of POA was the one that showed CWs with the lowest intensity,
that is to say, it was the year in which these events had the highest temperatures, with an
average of 18.6 °C. In that year there was only one CW, specifically in February, so the
annual average was atypical. The method used here to identify the waves and the climatic
condition of the cities allowed detecting these events throughout the year, so there are cases in
which an event can be considered a cold one for a particular season of the year, without
necessarily being rigorously cold, as discussed by Alves et al. (2017, p. 308).
Conclusions and Discussion
The daily thresholds established to compose a possible CW are preponderantly conditioned
by geographic factors. Even under a subtropical condition, it is noted that the altitude of CWB
overlaps with the highest latitudes of FLN, and especially that of POA. However, the effect of
latitude causes the city of POA to have more stringent thresholds than FLN, even taking into
account the fact that FLN is a coastal city.
The frequency analysis in the present study is in line with what has been published by the
Intergovernmental Panel on Climate Change (IPCC), which, in its 5th Assessment Report,
indicates that cold events will undergo a decrease (IPCC, 2013, p. 7, 20), as the graphics for
CWB and FLN suggest. In addition, the frequency of CWs detected in this study for CWB
confirms the findings by Silveira et al. (2017). For FLN, Alves et al. (2017) found an annual
average of 2.2 CW/year, a subtle difference from what was found here.
None of the three cities shows abrupt changes in the annual average duration of CWs.
Silveira et al. (2017) observed for CWB that approximately 90% of the CWs lasted from 2 to
3 days. Although considering the winter period, Alves and Minuzzi (2018) concluded that
almost 85% of the CWs in FLN last from 2 to 3 days. Similarly, the average annual intensity
in the three cities does not show much variation throughout the time series.
Data failures, especially in the 1980s, may have compromised the reaching of robust
results. Although much of the most current research points to elevated average air
temperature, this does not make extreme cold research less important, as such events also
have impacts on society in various sectors.Acknowledgments
The authors thank the Coordination for the Improvement of Higher Education Personnel
(CAPES, Brazil) for the doctoral scholarship granted to one of the authors (Process No.
1696632).
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