ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

REVUE INTERNATIONALE D'HÉLIOTECHNIQUE N° 46 (2018) 46-53

http:\\www.comples.org ___________________________________________________________________________________

TREND IN TEMPERATURE AVERAGE AS A PARAMETER TO QUANTIFY IN CLIMATOLOGY

Mohamed NIA

High school, Ibn Chabira, Bousaada, 28200, M'sila, Algeria

Email : mohamed_nia@yahoo.fr

Reçu 02-08-2018, Revu 30-09-2018, en ligne 27-10-2018

Résumé Les mesures des variations de la température de l'air nous donnent des indications sur les activités quotidiennes humaines. Cette étude

montre que les températures moyennes sur plusieurs années sont liées aux modifications climatiques ce qui permet d'introduire les tendances

dans les températures moyennes comme paramètre pour les évaluations climatiques. Ce paramètre est d’une grande importance pour la

compréhension des origines des changements climatiques afin de réduire leurs impacts. Ce travail s’est concentré sur la détection des tendances dans les données de température de huit stations en Algérie sur la période 1973-2015 en utilisant le test statistique de Mann-

Kendall appliqué à un niveau de signification de 5% et l’estimateur de Sen pour connaitre la pente d’une éventuelle tendance. Dans la

plupart des huit stations l’étude a mis en évidence une hausse dans la température moyenne que ce soit la température moyenne mensuelle; la

température moyenne saisonnière ou la température moyenne annuelle.

Abstract Measurements of air temperature variations give indications for human daily activities.

This study shows that seasonal and annual temperature averages along many years are related to climatic modifications. It allows to introduce trends in temperature averages as a parameter for climatic evaluations. This parameter is of importance for the understanding in

climatology of origins, prevision, and evolution in order to reduce impact effects.

This work has focused on detecting trends of temperature data from eight stations in Algeria from 1973 to 2015 using statistical tests such as

Mann-Kendall test applied at a level of 5% of significance (for trend) and Sen’s estimator (for slope of trend). In most of the eight stations the study has brought to light an increase in the temperature average whether monthly average, seasonal average or annual average.

Keywords: climate, parameter, statistical data, trend test, Mann-Kendall, Sen’s estimator.

I. INTRODUCTION

Studies of climate variability are of particular interest in scientific research, water resources, for the economy and for the

people themselves.

Most parts of the world has seen a sharp rise in temperatures which we live today its consequences (floods, ice melt, fires,

droughts, desertification etc.). These phenomena have caused massive population displacement, economic disruption, and in

some cases, famine and even loss of life. It is therefore necessary to explain temperature trend and seek subsequently causes to

take precautions to minimize the dangers that can result in order to be in shelter (Anwer., 2015 ; Cécile., 2007-2008 ; Ceppi et

al. 2012 ; Domroes and El-Tantawi., 2005 ; Fan et al. 2011; Fossou et al. 2015; GIEC., 2007; Xu et al. 2005).

In order to reach our goal of this work and quantify the evolution of temperature series data the use of mathematical statistic

was an indispensable tool. Determination of trend in the temperature series is performed in the mean of Mann-Kendall test and

the slope of a possible trend is determined by the Sen’s slope estimator.

II. DATA AND STUDY AREAS

II.1.Area

In Algeria the northern region is characterized by a Mediterranean climate, with hot, dry and mild summers, rainy

winters, with annual rainfall between 400 mm and 1000 mm. Summer and winter average temperatures are 25°C and 11°C

respectively. Annual precipitation in the highlands and the Saharan Atlas do not exceed 200 mm to 400 mm.

The Sahara is a very windy and arid region, where temperature variations are often considerable; these variations can be

explained by the total absence of humidity. Across the Algerian desert the height of the annual rains is less than 130 mm.

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ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

II.2. Data

Data used are the averages of monthly, seasonal and annual temperatures; they have summers provided by the website

(http://meteo-climat-bzh.dyndns.org/mete19-1154-1965-2016.php), table 1.

Table 1 : Characteristics of stations

III. METHODS

III.1. Mann-Kendall test

Mann-Kendall test is a non parametric test for trend detection. The null hypothesis of the test is H0 (no trend), against the

alternative hypothesis Ha (presence of trend) (Esterby., 1993; Goula et al. 2012; Jose and Claudia., 2008 ; Longobardi and

Villani., 2010; Mateescu., 2011; Nasri and Modarres., 2009; Qin et al. 2010; Scherrer et al. 2016). Statistic (Z) of the test is

calculated as follows.

𝑆 = 𝑠𝑔𝑛 𝑥𝑗 − 𝑥𝑖 𝑁𝑗=𝑖+1

𝑁−1𝑖=1 (1)

𝑍 =

(𝑆−1)

𝑣𝑎𝑟 (𝑆) 𝑖𝑓 𝑆 > 0

0 𝑖𝑓 𝑆 = 0(𝑆+1)

𝑣𝑎𝑟 (𝑆) 𝑖𝑓 𝑆 < 0

(2)

where

𝑣𝑎𝑟(𝑆) = 𝑁(𝑁 − 1)(2𝑁 + 5)/18 . (3)

For equal values in the series, var(S) was substituted in the above equation by

𝑣𝑎𝑟 𝑆 = 𝑁 𝑁−1 2𝑁+5 − 𝑡𝑝 𝑡𝑝−1 2𝑡𝑝+5

𝑞𝑝=1

18. (4)

where (tp) denotes the number of equality in the series involving (p) values and (q) is the number of equalities groups. The null

hypothesis is rejected at significance level (α) if 𝑍 > Z 1−

α

2 where Z

1−α

2 is 1 −

α

2 quantile of the standard normal

distribution.

III.2. Sen estimator of the slope

If a linear trend is present in the time series its slope (a) (change per unit time) can be estimated using an non parametric

procedure developed by Sen (1968) (Drápela., Drápelová., 2011; Fossou et al., 2014 ; Gajbhiye et al., 2015; Ghasemi., 2015;

Miro et al., 2006; Partal and Kahya., 2006); this means that the trend may be expressed by a function f(t) such as

𝑓 𝑡 = 𝑎𝑡 + 𝑏 . (5)

In order to obtain the slope (a), the slopes of all data pairs are calculated ; If there are (N) values (xj) in serie we get n = N(N-

1)/2 slope estimates (ai). Sen estimator of the slope is the median of these values (ai). The (n) values (ai) are ranked from

smallest to largest and Sen estimator of the slope is.

𝑎 =

1

2𝑎𝑛+1 𝐼𝑓 𝑛 𝑖𝑠 𝑜𝑑𝑑

1

2 𝑎𝑛

2+

𝑎𝑛+2

2 𝑖𝑓 𝑛 𝑖𝑠 𝑒𝑣𝑒𝑛 .

(6)

IV. RESULT AND DISCUSSION

Statistical values of the Mann-Kendall test applied at 95% significance level for the eight stations are given in table 2; It

showed that an upward trends have existed since 1973 in the monthly average temperatures for all stations except in

December and February.

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Station Biskra Annaba Alger Ghardaïa El Goléa Tamanrasset In-Amenas In-Salah

Longitude 05°43'12"E 07°48'36"E 03°15'E 03°47'24"E 02°52'E 05°26'E 09°38'E 02°27'36"E

Latitude 34°51'N 36°49'12"N 36°43'N 32°22'48"N 30°34'N 22°48'N 28°03'N 27°13'48"N

Elevation 125m 5m 24m 461m 397m 1362m 561m 269m

ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

For El-Goléa, Tamanrasset and In-Amenas the upward trend was for 75% of months and the magnitudes of the increase

trend varies from 0.02°C/year to 0.09°C/year and the largest slopes are for El-Goléa and In-Amenas ; for Biskra, Ghardaïa

and In-Salah the increase trend was for 67% of months where the slopes of the upward trends were from

0.04°C/year to 0.09°C/year and the largest slopes are for Ghardaïa and In-Salah; the upward trend detected in

monthly average temperatures for the two coastals stations of Annaba and Algiers was in 58% of months and the

magnitudes of trend where from 0.03°C/year to 0.07°C/year and the highest are for Algiers.

In seasonal average temperatures it was found that El-Goléa, Tamanrasset and In-Amenas were touched by an

increase trend in all seasons with slopes that varied from 0.02°C/year to 0.07°C/year; for the rest of stations the

trend was in 75% of seasons and slopes were from 0.03°C/year to 0.06°C/year ; the largest slopes were for El-

Goléa and Ghardaïa. whereas for average annual temperatures all stations were affected by an upward trends

whose slopes were 0.05°C/year for El-Goléa, Ghardaïa, and In-Amenas; 0.04°C/year for Algiers and 0.03°C/year

for the rest of stations; generally the upward trends are in almost of 1°C/year to 4°C/year on the study period that

spans 43 years. This remarkable temperature increase is related to greenhouse gases; these anthropogenic emissions

are mainly due to carbon dioxide (CO₂) coming in first from the consumption of fossil fuels; the biggest of the gas

emission sources are traffic ( affects most large cities like Algiers, Annaba, Biskra and Guardaia), households,

industry (the steel complex of El Hadjar and asmidal factory that manufactures phosphate and nitrogen fertilizers,

oil and natural gas fields in southern Algeria and the in Algerian-Libyan border), services, agriculture, forestry and

cattle breeding are an important source of methane production, deforestation caused by land use, energy

transformation (Refinery crude, power plants) ( Ministère de l’Aménagement du Territoire et de l’Environnement.,

2001; Ministère de l’Energie et des Mines.,2007).

For January it’s only in 25% of stations where a trend were obseved with 0.04°C/year in El-Goléa and In-Amenas.

Regarding seasonal average temperatures upward trends were manifested in 100% of stations for Summer and

Autumn, in 87.5% of stations for Spring and in 37.5% of stations for winter. The largest slopes were

0.06°C/year in Summer for Ghardaïa and El-Goléa, 0.07°C/year in Autumn for El-Goléa and In-Amenas and

0.06°C/year in Spring for Ghardaïa and El-Goléa.

For annual average temperature all stations studied were affected with an upward trends. Slopes for these

stations were 0.05°C/year in Ghardaïa , El-Goléa and In-Amenas , 0.04°C/year in Algiers and 0.03°C/year in

Biskra, Annaba, Tamanrasset and In-Salah.

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ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

49

Figure 1: Largest slopes in the average temperature of March and April

Figure 1 : Trends in the average temperature of March in El-Goléa,

In-Amenas

1970 1975 1980 1985 1990 1995 2000 2005 2010 201517

18

19

20

21

22

23

24

25El-Goléa

Year

Ave

rag

e te

mp

era

ture

in

Ap

ril (°

C)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201514

15

16

17

18

19

20

21

22In-Amenas

Year

Ave

rag

e te

mp

era

ture

in

Ma

rch

(°C

)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201517

18

19

20

21

22

23

24

25

26

27Biskra

Year

Ave

rag

e te

mp

era

ture

in

Ap

ril (°

C)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201517

18

19

20

21

22

23

24

25

26Guardaia

Year

Ave

rag

e te

mp

era

ture

in

Ap

ril (°

C)

ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

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Figure 2: Largest slopes in the average temperature

of May, July and August

1970 1975 1980 1985 1990 1995 2000 2005 2010 201522

23

24

25

26

27

28

29

30

31Biskra

Year

Ave

rag

e te

mp

era

ture

in

Ma

y (

°C

)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201515

16

17

18

19

20

21

22Algiers

Year

Ave

rag

e te

mp

era

ture

in

Ma

y (

°C

)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201530

31

32

33

34

35

36

37Guardaia

Year

Ave

rag

e te

mp

era

ture

in

Ju

ly (

°C

)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201529

30

31

32

33

34

35

36Guardaia

Year

Ave

rag

e te

mp

era

ture

in

Au

gu

st(

°C

)

ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

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Figure 3: Largest slopes in the average temperature of September, October and November

1970 1975 1980 1985 1990 1995 2000 2005 2010 201526

27

28

29

30

31

32

33

34In-Amenas

Year

Ave

rag

e te

mp

era

ture

in

Se

pte

mb

er

(°C

)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201531

32

33

34

35

36

37In-Salah

Year

Ave

rag

e te

mp

era

ture

in

Se

pte

mb

er

(°C

)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201518

19

20

21

22

23

24

25

26

27El-Goléa

Year

Ave

rag

e te

mp

era

ture

in

Octo

be

r (°

C)

1970 1975 1980 1985 1990 1995 2000 2005 2010 201513

14

15

16

17

18

19

20In-Amenas

Year

Ave

rag

e te

mp

era

ture

in

No

ve

mb

er

(°C

)

ISSN 0378-1305 Rev. Int. Hél. N° 46 (2018) Mohamed Nia.

Table 2: Trends in average temperature with the values of Mann-Kandall test and Sen’s slope (°C/year).

Figure 1, Figure 2 and Figure 3 illustrate the largest slopes highlighted for the average monthly temperatures and table 2

summarizes the results of the application of statistical tests.

V. CONCLUSION

Measurements of the mean values of air temperatures, whether monthly, seasonal or annual for eight stations in Algeria have

shown upward trends in the period 1973-2015.

This phenomenon could be a result of human activities which are related to industry and agriculture developments.

A temperature average is introduced as a parameter for quantifying climatic evaluations.

This parameter is of importance for the understanding in climatology of origins, prevision, and evolution in order to reduce

impact effects.

Remerciement

Le professeur Pierre MIALHE a bien voulu relire ce travail: MERCI.

_____________________________________________________________________________________________________

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Month Biskra Annaba Alger Ghardaïa El-Goléa Tamanrasset In-Amenas In-Salah

1 2.60; 0.05 2.39 ; 0.05

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4 3.85; 0.07 3.63 ; 0.04 4.66; 0.06 3.50 ; 0.07 3.43; 0.07 2.65 ; 0.05 2.48 0.05 2.16 ; 0.05

5 2.62; 0.06 2.76 ; 0.03 3.50; 0.06 2.61 ; 0.06 1.97; 0.04 2.96 ; 0.04 2.00 0.03 2.13 ; 0.05

6 1.97; 0.04 2.58; 0.03 3.80; 0.05 2.72 ; 0.02

7 2.80 ; 0.04 2.43; 0.03 3.33; 0.05 4.51; 0.09 4.00 ; 0.07 4.36 ; 0.04 3.82 ; 0.06 3.86 ; 0.05

8 3.44 ; 0.05 2.73 ; 0.04 3.27 ; 0.05 4.56 ; 0.08 4.83 ; 0.07 4.17 ; 0.04 4.34 ; 0.06 3.73 ; 0.04

9 2.02 ; 0.04 3.65 ; 0.07 5.05 ; 0.05 4.25 ; 0.07 3.92 ; 0.07

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Summer 3.41 ; 0.05 3.22 ; 0.03 3.95 ; 0.05 4.75 ; 0.06 4.86 ; 0.06 4.81; 0.03 4.39 ; 0.05 3.59 ; 0.03

Autumn 3.29 ; 0.04 3.66 ; 0.04 3.04 ; 0.04 4.88; 0.06 5.18 ; 0.07 5.96 ; 0.05 5.96 ; 0.07 4.87 ; 0.05

Winter 2.18 ; 0.03 1.99 ; 0.02 2.62 ; 0.03

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