Influence of the El Niño phenomena on the climate change of the Ecuadorian coast

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Introduction Since 1963, in accordance with the rainfall data recorded by the National Institute of Hydrology and Meteorology of Ecuador (INAMHI) Portoviejo-UTM meteorological station, the Province of Manabí has been experiencing an irregular behavior of the climate, reflected in the rainy periods, a primordial basis for the development of the agricultural sector. In Manabí, about 30 years ago, according to testimonies of old farmers, the rains began in the middle or end of December, extending the month of May or mid-June. Currently, the rainy periods begin in the middle or end of January and last only two and in some periods up to three months. The climatic indicators that directly affect the behavior of the climate of the coastal region of Ecuador and especially the climate in Manabí, are the cold current of the South, also known as Humboldt, and the warm current of El Niño. The Humboldt current marks the cold and dry period for Manabí, whose influence exerts from mid-June to late November or mid-December, is characterized by the lack of rain and the presence in certain regions of the so-called winter “light rain” (garúa), at this time, the surface temperature of the sea water varies between 23 and 25 °C [4; 6; 10]. From the middle to the end of December, the so-called El Niño warm current from the northwest or west gradually begins to manifest itself, so named because it appears in December, at the time of the celebration of Christmas. This current displaces the cold Humboldt current to the south, and at this time the water from the sea surface is heated with temperatures ranging between 25.5 and 27 °C, causing enough evaporation, which when transported by the wind, from the sea towards the continent, allows the formation of the clouds that cause the rains [2]. There is the so-called El Niño phenomenon, which is a difficult event to predict, characterized by a sudden change in the temperature of the surface sea water in the equatorial part of the Pacific Ocean and which has a decisive effect on the climate. In this phenomenon the hot zones near the surface move towards the east, the temperature of the ocean water exceeds 25 °C, evaporation accelerates, causing the production of rain in 5-6 times more than normal. The events of this phenomenon in the period under analysis have been 2, in the years 1983 and 1997-1998 [8; 9]. According to historical data from 1790 to the present date 7 El Niño phenomena have arisen, with intervals of occurrence of 38, 48, 15, 34, 57 and 15 years [1; 7]. These natural events, like those related to telluric movements, are considered stochastic and predicting the year of their next occurrence is impossible, but the truth is that their presence has been shown to mark the general climate, as it is demonstrated with the present investigation. Materials and Methods The basis for this work is the monthly rainfall records provided by the Ecuadorian Institute of Hydrology and Meteorology, meteorological station M005 located in the Botanical Garden of the Technical University of Manabí, latitude 01° 02’26’’ S, length 80° 27’54’’W, period 1963-2017. Figure 1 shows the geographic location of station M005 within the territory of the Manabí Hydrographic Demarcation (DHM). The total monthly precipitation records used in the investigation amount to 660. A temporal analysis of rainfall is made in 2 scenarios: 1) monthly; and, 2) annual. The analysis period consists of 55 years. For the monthly analysis scenario, in accordance with rainfall patterns, three ranges of analysis were obtained: 1963-1982, 1984-1996, 1999-2017, extraordinary events of the El Niño phenomena of the years are excluded in the analysis 1983, 1997 and 1998, since these are non-normal events whose periodicity is difficult to predict, but which mark trends of climate change. The records used here total 660. For each of the periods, the monthly variation coefficients were estimated with the help of the statistical formula [1; 3]: C = s , v x (1) where σ - standard deviation; x - arithmetic average. Figure 1. Location of the weather station M005 - Portoviejo-UTM For the scenario of the annual temporal analysis the total values are used, that is to say the sum of all the monthly precipitations, total 55 values of annual rainfall. The annual precipitation was calculated as the sum of the monthly rainfall with the formula 12 Pa = åPmi , i =1 (2) where Pa - annual rainfall; Pm - monthly rainfall. Based on El Niño phenomena arising in the period 1963-2017, 3 analysis intervals have been considered: 1963-1982, 1984-1996 and 1999-2017, this is to determine the trends of variability of climate patterns in the region coast of Ecuador, before and after said phenomena. For each of the periods considered, the average monthly rainfall values were determined with the formula n P = 1 Pm , (3) n mm å j j =1 where Pmm - average monthly rainfall; n - number of years of the period; Pmj - monthly rainfall. For the periods 1963-1982, 1984-1996 and 1999-2017, 20, 13 and 19 years have been considered, respectively. The calculations were carried out in Excel spreadsheets, to be then plotted in bars and statistical lines. Results and Discussion Of all the monthly rainfall records, the minimum value is 0.00 mm, and the maximum value is 460.20 mm. The average values of monthly rainfall for the period 1963-2017 are contained in table, where it can be noted that the minimum value corresponds to the month of August, and the maximum value to February. Table Average values of monthly rainfall in mm, Portoviejo-UMT station (M005) Period 1963-2017 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 93.0 133.0 132.0 73.4 31.9 17.2 7.3 2.7 3.7 3.0 6.6 23.8 In the monthly analysis of rainfall, in accordance with the 3 groups considered for the periods 1963-1982, 1984-1996 and 1999-2017, average monthly precipitation equal to 393.28, 456.66 and 546.80 mm was obtained, which indicates that there is a tendency to increase rainfall over time. However, by making a temporary monthly analysis of the distribution of rainfall for these periods, it has been detected that over time, the dry period has increased, becoming drier, which has a decisive impact on the agricultural sector due to the lack of enough water for the development of usual practices. Figures 2, 3 and 4 show this fact. Specifically, in figure 2, it is noted that there is greater uniformity in the distribution of precipitation, where August is the driest month with 1.16 mm and that the rainy period practically comprises 7 months: December, January, February, March, April, May and June, with a greater rainfall in the month of March, 107.69 mm. 200 1963-1982 Average rainfall (mm) 150 100 50 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0 Figure 2. Average monthly rainfall, 1963-1982 200 1984-1996 Average rainfall (mm) 150 100 50 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0 Figure 3. Average monthly rainfall, 1984-1996 200 1999-2017 Average rainfall (mm) 150 100 50 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 0 Figure 4. Average monthly rainfall, 1999-2017 Figure 3 shows a distribution scheme a little different with respect to figure 2, here the rainy season includes 6 months, from December to June with maximum precipitation in the month of February, 131.65 mm. The dry period is drier than in the previous case, where the precipitation is maintained almost equally for all months, with values that fluctuate between 1 to 2 mm per month, that is, almost nothing. Figure 4, period 1999-2017, presents a scheme almost similar to that of figure 3, with a notable difference from the increase in rainfall in the month of February, 157.98 mm. The dry period in this case, is drier than in the previous analysis with rainfall ranging between 0 and 1.5 mm per month, extreme drought. The calculated coefficients of variation Cv show that there is no uniformity of rainfall, since the values obtained fluctuate between 0.59-3.54, which reinforces the fact of the disproportion of rainfall for rainy and dry periods. Figure 5. Variability of annual rainfall, 1963-2017 Figure 5 shows the variation of annual precipitation, noting, in general, a tendency to increase average rainfall over time. From a linear dispersion analysis [5] the following trend increase formula was obtained: y = 4.3165x - 8062.3, (4) where x - year of analysis; y - average annual precipitation in mm. The appearance of El Niño phenomena, for the analysis period, shows changes in the production of rainfall patterns. Before the phenomenon happened in 1983, the minimum value of annual precipitations was of the order of 184 mm, after the phenomenon, this value had an increase of 20 mm, that is, it reached 214 mm (figure 5). After the phenomenon of 1997-1998, with respect to the previous minimum value, there was a rise of 70 mm, reaching it to be located at 284 mm per year. Conclusions The climatic conditions, as far as the production of rainfall in the city of Portoviejo is concerned, and that directly affect the basin of the river of the same name (Pfafstetter 1514), from 1963 to 2017 have changed. This situation is directly associated with the appearance of the so-called El Niño phenomena of 1983 and 1997-1998. Figure 6 summarizes the distribution of average monthly precipitation for the periods of analysis, noting the gradual increase in precipitation in the rainy season, whose maximum values for the periods 1963-1982, 1984-1996 and 1999-2017, they are 107.7, 131.6 and 1. mm, respectively. The opposite occurs with the minimum values of the average monthly precipitation in the dry period, which decrease, reaching for the periods indicated, values of 1.16, 0.44 and 0.43 mm, respectively. Average monthly rainfall (mm) 200.0 150.0 100.0 50.0 0.0 1 2 3 4 5 6 7 8 9 10 11 12 Months 1963-1982 1984-1996 1999-2017 Figure 6. Average monthly rainfall 1500.00 Annual rainfall (mm) 1000.00 757.80 945.40 878.90 500.00 184.10 213.90 284.10 0.00 1963-1982 1984-1996 1999-2017 min max Figure 7. Annual extreme rainfall The minimum values of annual rainfall (figure 7), after the events of the El Niño phenomena for the periods considered, have had an increasing character, with values equal to 184, 214 and 284 mm. Regarding the maximum values, from the period 1963- 1982 to 1984-1996 there was an increase of 187 mm, while between the periods 1984- 1996 and 1999-2017, there was a slight decrease of 66 mm. It is evident that the general panorama tends to an increase in rainfall levels but with a shortening of the rainy season time with the consequent lengthening of the dry season, which would aggravate the existing deficit problem in the province. It is imperative to design and put into operation hydrotechnical works for the storage and regulation of surface runoff.

About the authors

Antonio Fermín Campos Cedeno

Universidad Técnica de Manabí

Author for correspondence.
Email: acampos@utm.edu.ec

Ph.D., Associate Professor

Avenida Urbina y Che Guevara, Portoviejo, Ecuador, 130105

Junior Orlando Mendoza Alava

Universidad Técnica de Manabí

Email: jmendoza7865@utm.edu.ec

Associate Professor

Avenida Urbina y Che Guevara, Portoviejo, Ecuador, 130105

Evgenii K Sinichenko

Peoples’ Friendship University of Russia (RUDN University); Russian Academy of Sciences Water Problems Institute (IWP RAS)

Email: sinichenko_ek@pfur.ru

Ph.D., Associate Professor of the Construction Department, Engineering Academy

6 Mikluho-Maklaya St., Moscow, 117198, Russian Federation

Ilia I Gritsuk

Peoples’ Friendship University of Russia (RUDN University); Moscow Automobile and Road Construction State Technical University (MADI)

Email: gritsuk_ii@pfur.ru

Ph.D., Associate Professor of the Construction Department, Engineering Academy, Peoples’ Friendship University of Russia (RUDN University). Senior researcher of laboratory “Channel flow dynamics and ice thermal conditions”, Russian academy of Sciences Water Problems Institute. Associate Professor of the Hydraulic Department, Moscow Automobile and Road Construction State Technical University

6 Mikluho-Maklaya St., Moscow, 117198, Russian Federation; 3 Gubkina St., Moscow, 119333, Russian Federation; 64 Leningradsky Prospect, Moscow, 125319, Russian Federation

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