CC BY
14
Journal of Geology, Geography and Geoecology
ISSN 2617-2909 (print) ISSN 2617-2119 (online)
Journ.Geol.Geograph.
Geoecology, 28(1), 106-113 doi: 10.15421/ 111912
Lazreg Benaichata, Mahmoud Houari, Mhamed Maatoug, Mohamed Azzaoui, Naceur Khadidja
Journ.Geol.Geograph.Geoecology, 28(1), 106-113
Identification of rainfall onset for meteorological use regarding to region in the Algerian highlands
Lazreg Benaichata1, Mahmoud Houari2, Mhamed Maatoug1, Mohamed Azzaoui3, Naceur Khadidja1,
1Ibn Khaldoun university, BPP78 Zaaroura 14000, Tiaret, Algeria,, e-mail: llbb55@yahoo.com
2National Office of Meteorology, Oran.Algeria, e-mail: mahmoud_haouari@yahoo.fr
3Higher Agronomic School of Mostaganem, 27000, Kharouba - Mostaganem, Algeria, e-mail: moha-1500@outlook.com
Received 15.11.2018;
Received in revised form 11.12.2018;
Accepted 28.01.2019
Abstract. The data from several weather stations in Western Algeria show a semi-arid climate during last decades. The entire study region showed a great variability in the occurrences of the first and second rainy days in the year. This variability is associated with a positive trend, showing a continuous increasing aridity in the south Mediterranean and the late arrival of the rainy season is well marked. The rainy season in the north of Algeria, spreads from September to June. The origin of the rains differ according to the seasons. The rainfall from June to October is of localized stormy origin, whereas in winter, the rainfall comes from the classical atmospherically perturbations arriving from North or North West.
This work objective was to give a definition of the rainy season onset and to show its inter - annual variability according to the Niño and Niña years. The El - Niño phenomenon by its positive and negative phases seems to affect the start of the rainy season. The variability of the rainfall onset indices is very significant. There is a relative stability of the rainy season length over the long term period. A significant delay in the precipitation onset was observed during certain years. A method to define rainy season onset based on daily rainfall data from a weather station in the Algerian highlands was proposed. This approach is based on a climatic point of view, using a frequency analysis of precipitation and dates of their first occurrence. It delays the first heavy rain day (20 mm) when La - Niña settles. If EL-Niño settles, the first heavy rain (20 mm) day will be earlier. These results will improve the probabilistic forecasts of the beginning of the rainy seasons, the cessation as well as the lengths. This work is a preliminary confirmation that the El-Niño phenomenon really affects the Mediterranean climate.
Keywords: meteorology, weather, El-Niño, rainfall, forecast
Виявлення початку випадання опад1в для метеоролопчного використання в perioHÍ алжирського напр'я
Лазрег Бенайчата1, Махмуд Xoypi2, Мохамед Маатуг1, Мохамед АззаоР, Насер Хадщжа1
1Утверситет 1бнХалдун, BPP78 Задроура 14000, Tiapem, Алжир,, e-mail: llbb55@yahoo.com 2Нацюнальний офк МетеорологИ, Оран, Алжир, e-mail: mahmoud_haouari@yahoo. fr
Анотащя. Даш декшькох метеостанций на заходi Алжиру демонструють натвзасушливий юнмат остантх десятирiч. Повномасштабне дослвдження репону засвщчило велику мшливють у проявах першого i другого дощових дтв на протязi року. Ця мшливють пов'язана з позитивною тенденщею, що свщчить про постшне тдвищення посушливосп в поденному Середземномор'1 i про тзнш наступ сезону дощiв. Сезон дощгв на швночГ Алжиру, поширюеться з вересня по червень. Походження дощiв розрiзняеться в залежносп ввд сезону. Опади з червня по жовтень мають локальне штормове походження, в той час як взимку опади надходять з класичних атмосферних збурень, що прибувають з Пiвночi або з твшчного Заходу. Мета цiеi роботи полягала в тому, щоб надати визначення початку сезону дощгв i показати його щорiчнy мiнливiсть в залежноси вГд роюв Ель Ншьо i Ла Нгнья. Явище Ель - Нгньо своiми позитивними i негативними фазами позначаеться на початку сезону дощГв. Варiабельнiсть показникгв початку дощГв дуже значна. 1снуе вщносна стабiльнiсть тривалостi сезону дощгв в довгостроковш перспективi. В окремi роки спостерп,алася значна затримка початку випадання
Journal home page: geology-dnu-dp.ua
опад1в. Виходячи з даних про щоденш опади, отриманих з метеостанцп в алжирському напр'1, був запропонований метод визначення початку сезону дощ1в. Такий тдхвд заснований на ктматичнш точщ зору, з використанням частотного анал1зу опад1в 1 дат 1х першо1 появи. Вар1абельшсть показниюв початку дуже значна. Це затримуе перший день сильного дощу (20 мм), коли позначаеться Ла - Ншья. Якщо позначаеться Ель-Ншьо, то перший сильний дощ (20 мм) випадае на добу ранше. Ц результати дозволять полшшити 1мов1ртсн1 прогнози початку, припинення, а також тривалосп сезону дощ1в.
Ключовi слова : метеорологiя, погода, Ель-Шньо , опади, прогноз
Introduction. Knowing the beginning and end dates of the rainy season has always been a crucial issue in many parts of the world, especially countries whose agriculture depends on rainfall. A great number of works have been done on this subject for sub-Saharan and part of tropical Africa (Dodd and Joliffe, 2001; Camberlin and Diop, 2002, Balme et al., 2005). The question was not important for our regions because the crop sowing dates in the South Mediterranean were quite well mastered. This old practices was valid until the last observed fluctuations and climatic trends (Benaichata et al., 2016). However this work begins to reveal variability in the start of the rainy season. This observed disturbance of the rainy season is not without effects on crop productivity (Seck et al., 2005). During recent years it was fixed a large variability of rainfed crops yields in several regions (Essotalani et al., 2010). Naturally, these yields are well correlated with the annual rainfall variability (Marteau et al., 2010, Marega, 2016.). Hence there is an interest in knowing the dates of the beginning of the rainy season. The methods for determining these dates can be considered, from the agronomic, hydrological and atmospheric point of view by considering the installation of the meteorological action centres and the arrival of different meteorological perturbation types. It was defined the beginning of the rainy season as the first occurrence of 20 mm of rain in 2 consecutive days for the sub-Saharan regions (Stern, 1982). However, in Mediterranean region and especially in regions with arid and semi-arid climates, rains usually last less than 5 days with low intensities. The criteria applicable to sub-Saharan regions are not valid for our regions. This study is much more interested in the installation of the rainy season for the benefit of cereals and the criteria for the onset of the rainy season are based in this case on the analysis of a survey filled by farmers in the highland region of western Algeria. Several works are carried out in this direction for the sub-Saharan regions (Benoit, 1977; Cook and Heerdegen, 2001). One case study has been done for the Mediterranean regions with the exception of a synthesis (Aviad et al. 2004).The farmers of the Mediterranean regions did not worry about the variability of the rainy
season onset and work with inherited dates of sowing. At the same time the rainy season length is important in sub-Saharan regions. All the definitions used for West Africa were summarized with Fitzpatrick et al. (2015). According to Belaid (1996) and depending to the agro-climatic zone, the optimum sowing period is between 15 October and 15 November. However, following a survey analysis, we found that after the 2000s, they observed late dates of onset. Hence there is a need to study the variability of these onset dates. The determination of the beginning of the rainy season was based on (I) the occurrence and cumulative precipitation in three days after 1st September, (II) the number of days without rain between these first three days of rain and (III) the day where the cumulative rainfall amounted is equal to 20 mm. The example taken here is the for Tiaret weather station (35.34N, 1.46E). It is known that El Niño - southern oscilation (ENSO) is the dominant mode of variability over the Pacific Ocean and effects the sources of fresh water upon which millions of people rely (Curtis, 2008; Trenberth and Hoar, 1997). El Niño and La Niña event cause droughts and floods over different parts of the globe and have strong impact on the economies of the countries they affect (Hapuarachchi and Jayawardena, 2015). The objective of this work was to give a definition of the rainy season onset and to show its inter -annual variability according to the Niño and Niña years.
Materials and methods. In this study, we used archived data from international centres that collect hourly data transiting, through the Global Telecommunication System (GTS). Even though these data are not fully controlled or corrected before being transmitted in messages (METAR and SYNOP), we have found that they are acceptable for our study. To achieve this work, more than 30 years (1990-2017) daily data are downloaded from the National Oceanic and Atmospheric Administration (NOAA) website (www7.ncdc.noaa.gov/CDO/cdo). As already mentioned above, the first months of the rainy season have seen a great inter-annual variability with high coefficients of variation values and slopes signs changes (Fig.1).
Tiaret Precipitation (Sep), CV = 1301
A
0 0 O 0 O o 0
I I I 1990 1995 2000 2005 2010 2015
Time
Tiaret Precipitation (Oct),CV = 87 %
° ° Lj l\ O 0 "A-
/ » n ' ■ ' 0 » f n 0 OO On 0 O O
1990 1995 2000 2005 2010 2015 Time
Tiaret Precipitation (Nov), CV = 98 %
■'.I
1
V--S-
"T"
1990 1995 2000 2005 2010 2015 Time
Fig. 1. Changes in precipitation of SOND months
Tiaret Precipitation (Dec), cv=, CV = 76 %
o l\ \ »» o
o ,, - oo° 0° «• ; 0
1990 1995 2000 2005 2010 2015 Time
The rainy season in the north of Algeria, spreads from September to June where the origin of the rains differ according to the seasons. The rainfall from June to October is of localized stormy origin, whereas in winter, the rainfall comes from the classical atmospherically perturbations arriving from North or North West. Climate data are available mainly in meteorological services for researchers at excessive prices. We considered only
Table 1. Tiaret daily rainfall in 2015 (Data Source: NOAA)
Days Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1 * 14.9 * * * * * * * * * *
2 * * * * * 1.02 * * * * 7.11 *
3 * 0.25 * * * * * * 11.94 * 1.02 *
4 * 3.05 * * * 7.11 * * * * * *
5 * 5.08 * * * 5.08 * * * * * *
6 * 4.06 * * * * * * * * * *
7 * 1.02 * * * * * * * * * *
8 * 4.06 * * * * * * * 14.99 * *
9 * * * * * * * * * 26.92 * *
10 * * * * * 1.02 * * * 1.02 * *
11 * * * * * * * 2.03 * * * *
12 * * * * * * * * * * * *
13 * * * * * * * * * * * *
14 * 2.03 * * * 1.02 * * * 6.10 * *
15 * 0.25 * * * * * * * * * *
16 * 7.87 * * * * * * * * * *
17 0.51 2.03 * * * * * * * * * *
18 1.02 3.05 * * * * * * * 3.05 * *
19 2.03 0.2 * * * 0.25 * * * * * *
20 7.87 * * 0.51 * * * * * * * *
21 2.03 7.87 * * * * * * * 2.03 * *
22 9.91 9.91 2.03 * * * * 7.11 * 13.97 8.89 *
23 2.03 2.03 * * * * * * * * 0.51 *
24 * * * * 2.03 * * * * * * *
25 * 2.03 2.03 * 7.11 * * * * 3.05 2.03 *
26 * 2.03 5.08 * 5.08 * * 0.51 * 0.51 * *
27 * 3.05 2.03 * * * * * * 7.87 * *
28 * 6.10 * * * * * * * * 2.03 *
29 * * * * 0.76 * * * * * * *
30 * * * 0.76 * * * 6.10 * * *
31 * * * * * * *
the months starting from September to December to determine the beginning of the rainy season. The rainy season is installed only if the daily precipitation has exceeded a rainfall threshold (0.1 mm). The number of days without rain between the first three rainy days does not exceed 15 days and that the cumulative rainfall has exceeded 20 mm. Results and discussion. The amounts of daily precipitation are set out in the Table 1.
The stars represent the days without rain and the values are the daily amount of precipitation in millimetres. This table is an example of daily precipitation datasets (year 2015). We see that the first day of a quantifiable rainfall amount (> 0.1mm) corresponds to September 3 rd.
The first day exceeding 10mm matches with the first day of rain. The first day of rain exceeding 20mm corresponds to October 09 th.
The day where the cumulative rainfall exceeding 20 mm coincides with October 08 th 2015 year.
There is more than 20 dry days between the first and the second rainy days. We guess that the first rainy day does not correspond to the beginning of the rainy season and can't be considered in the 20mm cumulating.
In our example the rainy season started on the 08th or the 09th of October 2015 year (Fig. 2 and 3).
Julian Days
Fig. 2. Illustration of the 10 and 20 mm thresholds (red horizontal lines)
The black vertical lines correspond to the Julian days that coincide with the two first rainy
days and thresholds.
Fig. 3. Illustration of the cumulative 20 mm thresholds
The black vertical lines correspond to the Julian days that coincide with the threshold (red horizontal line). According to Figure 3 the cumulative 20 mm correspond to October, 8th
(starting of the rainy season).
The dates of occurrence of the first and second rainy days are shown in figures 4 and 5.
Fig. 4. Dates of occurrence of the first rainy days.
o
o j\< fj uu
—t—r o 71 o * HAM ■o 3.
\ O \1 \l o o o
1985 1990 1995 2000 2005 2010 2015 2020
Fig. 5. Dates of occurrence of the second rainy days
The analysis of the curves of the first and second days with measurable amount (>0.1mm) shows that there is a great inter-annual variability of these dates. We also found that there is a positive trend of these dates. This trend can be explained by the fact that the onsets of the rainy
seasons are later in recent years, confirming the work of Ati et al. (2002). The data on variation of the first cumulative rainfall dates reaching 20mm and dry sequences separating the 2 first rainy days are shown in figures 6 and 7.
Fig. 6. Variation and trend of the first cumulative rainfall dates reaching 20mm
The interpretation of the curves in fig.6 and 7 shows the inter-annual variability of the first and second rainy days as well as the positive trend of
their regression lines. These figures clearly show a shift after the year 2000, in the beginning of the rainy season.
Years
Fig. 7. Variation and trend of the dry sequences separating first and second rainy days.
Fig. 7, explains the time lag to reach a cumulative rainfall amount of 20 mm at Tiaret weather station. It was shown the increase in the number of false alarms of the annual precipitation onset. This great variability was reported by Reiser and Kutiel (2007).
A logistic regression was used to find a relationship between the beginning of the rainy season and the El-Nino/La-Nina phenomenon,. The logistic regression is widely used in many areas (Adams and Lawrence, 2019).
Other ways use this approach to look for association between onset variability of precipitation and equatorial ocean temperatures
Table 2. Modalities and significance of the variable ONI
Modality Signification
WE Weak El Niño
ME Moderate El Niño
SE Strong El Niño
VSE Very Strong El Niño
WL Weak La Niña
ML Moderate La Niña
SL Strong La Niña
(Joseph, 1994). This analysis aims to explain and predict the values of a dependent variable Y (starting date of the rainy season), from an independent variable X representing the Oceanic Niño Index (ONI) modalities (Cornillon et al., 2012).
The ONI index data are available at: http://ggweather.com/enso/oni.htm. Since the ONI index is considered here as an explanatory qualitative variable with 7 modalities (Table 2), we applied a logistic regression to note how modalities and significance of the variable ONI correspond to El Niño and La Nina.
The results for the two explained variables: (1) First 10 mm precipitation and (II) First 20 mm. Note that other methods are used in the search for remote connections between El niño and climatic parameters (Camberlin et al., 2001).
The logistic regression is applied to the dates of the first rainy day with 10mm as a variable to be explained and the ONI index as an explanatory variable. The results obtained from
this analysis are grouped in Table 3 using R-language.
According to Table 3, the first yearly days with 10mm precipitation are negatively affected by El-Niño and Very Strong El-Niño (WE and VSE) at 5% significance level. This can be explained as follows: The first rains up to 10mm will be relatively early in years when the El Niño phenomenon sets in.
Table 3. Analysis of the effect of El-Nino phenomenon on the dates of the first rains up to 10 mm by logistic regression
Modality Estimate ± std. error T value Pr(>|t|)
(Intercept) 300.5 ±14.3 20.99 < 0.001
ML -31.2±18.5 -1.69 0.143
SL -8.5±24.8 -0.34 0.743
VSE -48.5±20.2 -2.40 0.054
WE -47.5±18.5 -2.57 0.042*
WL -1.5±24.8 -0.06 0.954
The analysis shows that the first days with rains up to 20mm by La-Niña (Table 4)
this type of rain is positively affected for the first
Table 4. Analysis of the effect of the El-Nino phenomenon on the dates of the first rains up to 20mm by logistic regression.
Modality Estimate Estimate ± std. error T value Pr(>|t|)
(Intercept) 271.0±14.2 19.14 < 0.001
ML 17.0±20.0 0.85 0.4853
SL 59.0±20.0 2.95 0.0985
VSE 0.5±17.3 0.03 0.9796
WE -14.5±17.3 -0.84 0.4911
WL 61.0±20.0 3.05 0.093
The statistical significance is not proven at 5% threshold, but can be acceptable at 10% significant level. If we accept this result it can be
explained by the fact that the first daily heavy rains of 20mm are late when La - Niña years is set up.
Years
Fig. 8. Deviation of cumulative precipitation between SOND and JFMAM season
The Fig. 8, compares the cumulative rainfall totals for the months from September to December with the months from January to May. We note on this figure that during some years, the cumulative rainfall from January to May exceed the cumulative rainfall from September to December. During these years the start of rainy season are delayed with droughts. This figure
suggests in the future to compare this oscillation with the Nino years.
Conclusion. In general, several weather stations in Western Algeria show a semi-arid climate in their data. The entire study region showed a great variability in the occurrences of the first and second rainy days in the year. This variability is associated with a positive trend, showing a
continuous increasing aridity in the south Mediterranean and the late arrival of the rainy season is well marked. The El - Niño phenomenon by its positive and negative phases seems to affect the start of the rainy season. It delays the first heavy rain day (20 mm) when La - Niña settles. If EL-Niño settles, the first heavy rain (20 mm) day will be earlier. These results will improve the probabilistic forecasts of the beginning of the rainy seasons, the cessation as well as the lengths. Note that the bibliography is very rich in terms of definitions of the start and end of rainy seasons but the use of logistic regression is not very widely used in climatology. This work is a preliminary confirmation that the El-Niño phenomenon really affects the Mediterranean climate.
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