**1. Introduction**

Climate is naturally variable as evidenced by the irregularity of the seasons from one year to another. Long-term climate variability is of great importance for the estimation of its impact on human activities and for predicting the future climate [1]. The need to develop science programs that, in addition to exploring long-term climate change, can meet the more immediate needs of people and organizations to begin factoring climate risks into planning and management processes [2]. Over the twentieth century, west African region continues to receive a lot of unusual disasters at unexpected moments and areas. This might be a consequence of climate change and then that change is generated on the one hand by anthropogenic activities and on the other hand by natural variation. That's why some previous studies done on West Africa regions highlight the variability of temperature and rainfall and their relationship with climate indices, as Zerbo et al. [3] who studied the relationship between the solar cycle and meteorological fluctuations in West Africa and found that temperature and rainfall are influenced by solar activity. Schulte et al. [4] analysed the influence of climate modes on streamflow in the Mid-Atlantic region of the United States. Many studies also have been done on the intra-seasonal and inter-annual variability of temperature and rainfall [5–9] over West Africa areas. Previous studies

have shown the crucial role of sea surface temperature (SST) anomalies in the tropical Atlantic region. For instance, SST induces forcing on the summer monsoon rainfall over sub-Saharan West Africa [10]. Vizy and Cook [8] highlighted that warm sea surface temperature anomalies influences positively the increase in rainfall along the Guinean coast. In their study on variability of summer rainfall over tropical north Africa during the 1906–1992 period, Rowell et al. [11] showed that the global SST variation are responsible for most of the variability of seasonal (July-August-September) rainfall from 1949 to 1990. Indeed, the annual cycle of rainfall over West Africa depends greatly on SSTs in the Gulf of Guinea [11].

However, any climatological study over West Africa could take into account at least West African Monsoon (WAM) and Inter-Tropical Convergence Zone (ITCZ). It is for the reason aforementioned that several studies have been done on the WAM influence on annual climatic variability in West Africa, [6,12] and its dynamic and onset [13–15]. Furthermore, it was also reported by Nicholson [16,17], that a major role of the WAM system is to transport moisture into West Africa from the Atlantic. In response to the onset of the African monsoon, the upwelling cooling is strongest in the east both because of the strong acceleration of the southerly winds and because the thermocline is shallow there [11].

The inter-annual variability of the WAM is mainly explained by the surface of ocean. It is worthy to note that the surface temperature of the inter-tropical Atlantic can be analysed efficiently. It constitutes an important climatic parameter, in the event of a strong anomaly, in all the coastal areas subjected to the direct impact of the WAM [18]. It is for this reason that Joly and Voldoire. Ref. [12] reported that SST anomalies are maximum in June–July, and are associated with a convective anomaly in the marine ITCZ with a spread over the Guinean coast. ITCZ is the major synoptic-scale system controlling seasonal rainfall [19]. It is well known that the distribution of temperature and rainfall through Earth surface is not homogeneous. Espinoza Villar et al. [20] pointed out the impact of mountain ranges on rainfall and specified that the long-term variability with a decreasing rainfall since the 1980s prevails in June-July-August and September-October-November in the Amazon Basin countries.

Our study area is localized in West Africa, enclosing the three major West African climate zones: Guinean zone (approximately 6–8◦ N); Soudanian zone (approximately 8–12◦ N) and Sahelian zone (approximately 12–16◦ N) [21]. It may be stated that the region of Conakry is part of the Soudanian zone (see Figure 1a). The station of Conakry is located at the international airport of Conakry at 9.34◦ N and 13.37◦ W, at 26 m height above the sea level (sl). Given that Conakry is a coastal zone that lies between the Atlantic Ocean and the Kakoulima Mountain range, which forms a barrier and promotes the Foehn phenomenon (see Figure 1b). This feature seems to be the reason that makes it the rainiest area compared to other parts of the country. This coastal site is the national socioeconomic development centre of Guinea, but is always threatened by heavy precipitations and strong heat waves causing significant economic and sanitary damages and loss of lives.

The absolute poverty of a large proportion of the African continent's people renders them highly vulnerable to changes in climate [22]. According to the increasing impact of the climate change in this area and the geo-climatic and environmental factors influences mentioned above, the purpose of our approach is to investigate with the keenest interest the climate variability as well as the forcing led by some climate indices on the temperature and rainfall at Conakry during 57 years. The aim of our study is to improve the understanding and strengthen the knowledge on the climate variability in this region of Guinea through a climatological approach coupled with a digital tool of analysis. After the station dataset description and methodology, obtained results are presented and discussed.

**Figure 1.** Geo-localisation of Conakry station in West Africa, map showing the three major west african climate zones (**a**), map showing Conakry Airport between Atlantic Ocean and Kakoulima Mountain range (**b**).

#### **2. Materials and Methods**

#### *2.1. Data*

Monthly averages of temperature and rainfall time-series are used in this study for the 1960–2016 period. They were obtained from continuous measurements at the synoptic weather station of Conakry in Guinea. A set of 684 monthly average temperature measurement during 57 years were used, for rainfall, the same data number were used too. The location of this synoptic station at the international airport of Conakry makes the data set uninterrupted and of good quality. The daily mean temperatures were calculated by averaging the daily minimum and maximum temperatures. The monthly and yearly temperature averages were calculated from the daily and monthly averages, respectively, for the complete study period. The histogram of monthly mean temperature peaks at 26 ◦C with 133 occurrences (Figure 2a).

**Figure 2.** Histograms of monthly temperature frequency, the monthly temperature mean value of 26 ◦C has higher frequency of observation (**a**) and monthly rainfall (**b**) overall frequency showing that the monthly rainfall value of 0.1–100 mm has higher frequency of observation at Conakry Airport station.

The monthly rainfall is the accumulated based on daily rainfall obtained for a particular month. The overall annual rainfall is calculated as the sum of monthly rainfall. However, measured rainfall commonly consists of discrete series of rainfall events with different durations and time intervals [23]. It is noteworthy that rainfall is a discontinuous parameter, thus, monthly rainfall accumulated values used in our study oscillate between 0.1 and 1839.3 mm. Rstudio and Matlab software were used to perform all computational tasks. The histogram of monthly accumulated rainfall peaks at 0.1–100 mm with 178 occurrences, such as values above 1500 mm, have a lower occurrence (<10), but are very quantitatively significant from disaster (flood, landslide) point of view (Figure 2b).

To achieve a better understanding of the forcing that may influence temperature and rainfall of Conakry, four climate indices were used:


In this work, the monthly average temperature (684 measurements) and monthly rainfall (684 measurements) as well as the monthly mean (684 measurements) of 4 climatic indices (Nñio 3.4, AMM, TNA and AN) were used as input data for our investigation during the period 1960–2016.
