1. Introduction
Senegal, like all West African countries that lie in the semiarid region known as the Sahel, has a highly variable rate of rainfall (Leroux 1973a). Recent decades have witnessed several significant droughts that have created socioeconomic hardships, including a scarcity of food and water. The impacts of a deficient rainy season extend over a long period, much beyond the rainy season alone, and affect the local economy, the domestic and foreign trade, and various natural resources including the tenuous water supply. For example, the Ferlo region in the country’s northern section has an ongoing problem of desertification and as a result, an annual reduction in the availability of lands suitable for crop agriculture and cattle production. Meanwhile, the very high rate of population increase (2.54% in 2002 according to the United Nations Population Fund) further aggravates the problem.
The persistence of the drought in West Africa has prompted many regional and continental investigations of tropical climate variability and predictability (Kraus 1977; Lamb 1978a, b; Lough 1986; Janowiak 1988; Semazzi et al. 1988; Parker et al. 1988; Lamb and Peppler 1991; Rowell et al. 1992; Janicot 1992; Nicholson and Palao 1993; Ward 1998; Mo et al. 2001; Niyogi et al. 2002). In contrast, localized studies involving smaller areas are rare (e.g., Camberlin and Diop 1999, 2003). Descriptive studies of the underlying climatology of smaller countries such as Senegal—which should constitute the foundations of our understanding of climate variability—are conspicuously lacking from the literature. One of the reasons for this deficiency has been the difficulty in the access of observational datasets stretching continuously over long periods and the lack of a relatively dense network of well-distributed stations.
Through the Fulbright Scholar Exchange program, an opportunity became available to access rainfall and air temperature data from surface stations across Senegal. After quality control and analysis, the dataset comprised rainfall and temperature measurements from 12 stations and 8 more for precipitation alone, and covered a period from 1971 to 1998. These data were used to construct a descriptive geospatial characterization of temperature and rainfall patterns specifically for Senegal, and the results of this project comprise the content of this study.
The analysis is presented as follows. Section 2 provides a background of the geographic and meteorological conditions in Senegal, and section 3 describes the data and methods used in this investigation. A descriptive characterization of rainfall and temperature patterns in Senegal over the study period is presented in section 4. Summary and conclusions follow in section 5.
2. Meteorological and climatological conditions in Senegal
Senegal is the westernmost country in Africa; the North Atlantic Ocean is to its western border (Figure 1). The country is located between latitudes 12°30′ and 16°30′N and longitudes 11°30′ and 17°30′W. Its topography is generally free of steep terrain—its altitude is not greater than 130 m, with the exception of a small portion in the southeast where the highest elevation is 581 m.
Two factors play an important role in determining Senegal’s climate: (i) the lack of significant topography: the country is widely open to different air masses; and (ii) the geographical position: the country lies entirely within the tropical region.
Senegal forms the westernmost part of a transitional region stretching between the moist West African zone to the south and the dry Sahara Desert to the north. The location of the country at the western edge of Africa subjects its climate to the dual influence of oceanic and continental processes. This is particularly noticeable when examining the temperature and wind fields, as described below.
Additionally, four “centers of action” can affect the local climate. Three originate in the Northern Hemisphere: the Azores anticyclone, the North African anticyclone (usually positioned over Libya in winter), and the Saharan thermal low (mainly observed during the boreal summer); one originates from the Southern Hemisphere: the Saint Helena anticyclone. The resulting winds lead to two prominent seasons, which are discussed below.
2.1. The dry season
The dry season typically lasts from 6 months in the south (November–April) to 8–10 months in the north. It occurs when the intertropical convergence zone (ITCZ) migrates southward and the country is out of reach of the moist monsoonal flow.
During the dry period, two prevailing winds generally determine the Senegalese climate: 1) the NW marine trade wind, which originates in the Azores anticyclone, typically from November to May; and 2) the east or northeast continental trade wind, also known as the “harmattan,” a very dry, warm, and dust-laden air mass that originates in the north Saharan anticyclone. A discontinuity in western Senegal separates the two fluxes (Figure 2).
Even though the period from November to April is referred to as the dry season, precipitation occurrence is not unusual, especially from December to April. Southwest–northeast-oriented cloud bands coming from the Atlantic ITCZ cause these off-season rains, which represent about 1% of the annual rainfall (De Felice and Viltard 1976; Thepenier 1981; De Brum Ferreira 1983). A southward advection of cold air coming from the midlatitudes also characterizes this type of weather.
2.2. The wet season
The ITCZ controls Senegal’s wet season. It consists of a large-scale ascendance zone onto which the NW and NE trade winds as well as the SW monsoon converge, combining air masses from both hemispheres (Dhonneur 1970; Leroux 1973b). The ITCZ is characterized by a mobile band of cloudiness and rainfall, shifting in a north–south seasonal pattern, in relation with the apparent movement of the sun (with a typical lag of 6 weeks).
Over Senegal, the ITCZ often has a NE–SW orientation and appears as a transitional branch linking the continental ITCZ with the maritime ITCZ (Figure 3). It reaches its northernmost position in August.
The migration of the ITCZ determines the onset and duration of the wet season. In Senegal, this season lasts from early May (June–July in the north) to late October (early October in the north). It begins in the south and spreads north in conjunction with the ITCZ as it migrates northward, thus reaching the whole territory and bringing moisture from the Atlantic Ocean. In low levels, this advection of the monsoon flow northward is related to the existence of a strong thermal gradient between the Gulf of Guinea and the Saharan heat low (Sultan and Janicot 2003).
During the rainy season, the most important rain events are caused by West African disturbance lines, also called squall lines or cloud clusters. These disturbances are tropical convective systems organized as lines of thunderstorms oriented roughly north–south and propagating westward (Leroux 1998). Even though many squall-line tracks have been observed throughout West Africa (Burpee 1974; Reed et al. 1977; Peters and Tetzlaff 1988; Diedhiou et al. 1999), climatologists generally agree that these systems merge into a single track located between 15° and 20°N over the Atlantic Ocean (e.g., Reed et al. 1988; Diedhiou et al. 1999). Consequently, Senegal, given its location within this range, is a point of convergence of the disturbance lines. The number of squall lines during the wet season decreases from SE to NW; as they move westward, they and most of them decay inland.
The African easterly jet (AEJ), which is a midtropospheric flow (650 mb) that results from the low-level gradient between the hot Sahara Desert and the cool and moist Guinea Coast and Atlantic regions (Rowell 1988; Lare and Nicholson 1994), is known for providing energy for the maintenance of West African disturbances (Peters and Tetzlaff 1988; Druyan 1998). Thus, the AEJ plays a key role in rainfall production and distribution over West Africa.
3. Data and methods
3.1. Data
The data used in this study were available through Météorologie Nationale, Dakar, Senegal (Office of National Meteorology). The dataset is composed of handwritten records that were digitized and reviewed for quality assurance/control. Typical checks included visual inspection of the time series plots, checks for missing values and consistency (based on knowledge of local and regional conditions), descriptive statistics of the datasets for mean and variances, and discussions with local meteorologists for unusual data values. Some stations with large data gaps and intermediate reporting were discarded. Bad data values (based on the quality checks) were eliminated from the analysis.
The dataset covers the period from January 1971 to December 1998, a time period chosen largely because of the data availability. However, this period is also significant because it covers the last West African drought epoch (beginning in 1968) and presents a complete rainfall dataset for a network of 20 stations in Senegal (Figure 4). The data consist of the measure of monthly rainfall from rain gauges and the number of rainy days per month. Additionally, 12 stations (out of the 20) also recorded monthly relative humidity, monthly solar radiation duration (day length), and monthly mean temperature [(tmax + tmin)/2].
3.2. Methods
Rainfall in West Africa is typically concentrated in the summer months. As a result, most of the studies dealing with regional climate variability in West Africa focus on the July, August, and September period. Most of the investigations focus on the larger Sahel region where most of the rain is concentrated in the July–August–September period, which justifies this choice of time period for the study.
With regards to Senegal, the Sahel lies only in the northern part of the country. The southern part of the country belongs to the Sudanian zone, which receives an appreciable amount of rains in June. Consequently, this study assumes that the wet season in Senegal lasts from June to September (JJAS).
The data were mapped using the spline method of interpolation in ArcGIS Spatial Analyst. Various methods were first tested using ArcGIS Geostatistical Analyst. Our choice was based on the following criteria: 1) the quality of the models tested assessed by a cross-validation procedure (displays charts of the different interpolated surfaces along with their root-mean-square numbers; the smaller the root-mean-square, the better the model); 2) the visual display of the models; and 3) the understanding of the data and the phenomenon that is modeled, based on local knowledge of the study area.
For the temperature dataset, an EOF analysis was performed over the study period. This method, which has been used in a number of geostatistical analyses, delineates the spatial patterns of variability, plots the time series of each eigenmode (principal component), and gives a measure of the importance of each pattern (Björnsson and Venegas 1997). In this study, the time series determined from the first EOF mode (which expresses 53% of the variance) is used as an index. Moreover, this mode is the only one that was found to be statistically significant according to Kendall’s criterion for distinctly separated eigenvalues (Kendall 1980).1
4. Analysis of mean climate conditions
The climate (rainfall and temperature) conditions in Senegal are discussed for monthly, seasonal (JJAS), and annual averages relative to the study period (1971–98).
4.1. Rainfall and number of rainy days
4.1.1. Distribution
The rainfall distribution is characterized by an increase in the amount of precipitation and the number of rainy days from north to south (Figures 5a and 5b), and a higher number of occurrences in the June–September months (Figure 6). As discussed in the earlier section, the remainder of the year can have off-season rains. For example, the rainy season can last up to October, which in some instances can record substantial amounts of rainfall (e.g., October 1991: 25.7% of the annual rainfall in Louga, 25.3% in Velingara, 24.1% in Saint-Louis). The contribution of October rains in the seasonal rainfall totals is relatively important in the south (Figure 5b). Additionally, under conditions such as SW–NE moisture transfer from the ITCZ, off-season rains also occur from December to March, as shown in Figure 7.
The spatial distribution (Figure 8) confirms the north–south gradient in the rainfall pattern: Figure 8 and Movie 1 show the progressive SE–NW development of rains throughout the wet season, with the highest values in August. This SE–NW axis of rainfall penetration, mentioned in a number of studies (e.g., Leroux 1973a, c), is due to the westward propagation of squall lines.
In August, another axis oriented SW to NE appears and is especially noticeable in western Senegal. This axis is associated with a thick monsoon layer characterized by nonstormy and continuous rains in the southwest (Casamance region). During this period, more than 60% of the seasonal rains are recorded to occur in this region.
The contribution of each month to the seasonal rainfall totals and number of rainy days is shown in Figure 9. For most of the stations, August rainfall accounts for more than 35% of the seasonal totals. September, July, and June follow this. The August and September rains are especially critical to the rainfall totals in northwestern Senegal, while the rainfall in the south is better distributed throughout the whole rainy season (Figure 9). June rainfall totals although generally low, are relatively significant in the southeast (e.g., more than 15% in the Kedougou zone). The number of rainy days exhibits similar patterns, and in general a strong correlation exists between rainfall amounts and the number of rainy days.
The temporal and spatial distribution of rainfall and the number of rainy days can be further assessed by the distribution of surface (relative) humidity. Figure 10 shows the increase of available moisture, mainly from April to September, in conjunction with the south-to-north advection of the monsoonal flow. The highest values are recorded in the south during the July–September period, with a peak in August.
4.1.2. Variability
Mapping the coefficient of variation for all stations provides a measure of the relative variability of the data according to the mean of the datasets. For both rainfall and the number of rainy days, June exhibits the greatest variability, especially in the western and northern parts of the country (Figure 11). In this sector, from one wet season to another, meteorological conditions can significantly differ, depending on the position of the ITCZ and the strength of the Azores high. The latter can block the rain-bearing systems or impose a more meridional trajectory, especially at the beginning of the wet season. Even though June is a relatively dry month, unusually heavy rainfall may sometimes occur, especially in subarid areas such as northern Senegal. This high interannual variability observed in the periods and areas with low mean precipitation is consistent with Conrad’s (Conrad 1941) findings: he pointed out an inverse relationship between the mean precipitation and the coefficient of variation; that is, as the mean precipitation increases, the relative variability decreases. August and September, which have the highest mean precipitation, exhibit a lower interannual variability.
The number of rainy days exhibits a less significant variability: with the exception of June, which records coefficients above 80% in the northern and western Senegal, moderate values (below 50%) are observed throughout the rainy season.
The seasonal variability map (Figure 12), reflecting the results obtained from monthly analysis, shows high rainfall coefficients over the north, and low values in the south. The coefficient of variation increases from less than 10% in the southeast to more than 40% in the north, which exhibits a higher variability. The spatial patterns for the number of rainy days are similar across the region, but with a smaller range; the N–S gradient is omnipresent.
The higher variability of the drier northern areas is also evident when considering the year-to-year rainfall (Figure 13). Higher-frequency fluctuations are observed in the northern stations (e.g., Saint-Louis; Figure 13a). In contrast, southern stations (e.g., Ziguinchor; Figure 13b) show less contrast in rainfall amounts from one year to the next.
Figure 14 shows the rainfall and the number of rainy days indices (normalized rainfall departures) for Senegal over the study period where a marked interannual variability is observed, with a good agreement between the two curves.
Most of the negative rainfall anomalies in the region correspond to El Niño years (e.g., 1972, 1977, 1982/83). Departures from the mean rainfall (1971–98) for some El Niño years are shown in Figure 15. Negative departures extend throughout the country. Southwestern Senegal, for example, records the highest deficits and is most affected during El Niño years, while the northern regions may exhibit a low deficit or even weakly positive anomalies in a few areas.
4.1.3. Trends
Trends in the precipitation and number of rainy days are estimated by applying a linear regression model to each station for a 28-yr period. Interpolation maps are generated from the slope values of all stations in the study area. According to the t test at the 95% confidence level, none of the stations presented a statistically significant trend. Nonetheless, the trends in seasonal rainfall (Figure 16a) show a wide SE–NW corridor of negative or weakly positive values.
The seasonal trends for the number of rainy days (Figure 16b) present more areas with weakly positive slopes, specifically in the coastal zone, central Senegal, and along the Senegal River. Similarities exist in the number of rainy days map and the precipitation map in that negative trends are observed in both the southeast and northwest.
On the whole, the analysis of the wet season’s mean conditions based on the study period reveals the strong correlation between rainfall and the number of rainy days, an omnipresent N–S gradient, and a greater rainfall variability in the northern regions. Trends for the study period are negative or weakly positive, but not significant.
4.2. Temperatures
4.2.1. Temporal and spatial distribution
The temporal variation in the temperature dataset is related to the seasonal shift. Most of the stations show two maxima (one in May or June and another in October), and two minima (in December or January and in August or September). The December–January minimum is seasonal, while the August–September secondary minimum is explained by the usual increase in cloud cover and moisture (cf. Figure 10) during this period, an increase also associated with a significant drop in solar radiation duration (Figure 17). At the end of the rainy season, the moist monsoon’s reduced inflow and the consequent decrease in cloud cover cause a secondary maximum (Figure 18a). However, a few stations’ regimes along the northern coast (Saint-Louis and Dakar) are characterized by only one maximum in September or October, and only one minimum in January or February (Figure 18b). The evolution of mean monthly temperatures throughout the year is shown in Figure 19 and in Movie 2.
The spatial distribution of mean annual temperatures for the study period, displayed in Figure 20, is mainly driven by two factors.
Oceanic: much lower temperatures occur along the coast than inland due to the cool and moist (but not rain producing) trade winds and the effects of the cold Canaries current. Thus, the coastal regions experience humid weather conditions during the November–May dry season (Figure 21). The oceanic factor causes an E–W gradient.
Continental: higher temperatures are recorded in the northeast, which is exposed to Saharan influences, more specifically to the NE trade winds (harmattan), which typically blow during the dry season. This shows in Figure 20 as a NE–SW gradient.
During the wet season, more specifically in August and September, a third factor, moisture availability, influences temperature distribution. The relative humidity decreases from south to north, and the temperature distribution follows a similar pattern.
4.2.2. Variability
From the mean annual and monthly temperatures for the 1971–98 periods, coefficients of variation for each station were computed and spatially analyzed using ArcGIS. The highest annual variability occurs in the west and north, and the values decrease from NW to SE (Figure 22a), with coefficients below 1.6% observed in the southeast.
As shown in Figures 22b and 23a, the months from January to April exhibit most of the variability. As also confirmed by Figure 16, the range between extreme maximum and minimum temperatures for a given station (indicated by the vertical lines extending in both sides of the boxes) is shown to increase during this period. During the dry season, the confluence of the relatively cool NW trade winds and the dry warm continental trade winds is a common occurrence. Depending on the predominance of either flow, temperature patterns can vary widely and cause greater fluctuation around the mean. In contrast, during the wet season, the temperature variation is relatively weak (Figure 23b). The dominance of the monsoonal flow over Senegal leads to more airmass homogeneity and reduces the amplitude between extreme temperature records. In general, the largest variability in observed temperature occurs during the dry season, especially in the subarid regions of the north and northwest.
4.2.3. Trends
Spatial and temporal trend patterns for observed air temperature are analyzed similar to the rainfall dataset. A normalized index based on the 1971–98 period is also computed, and an EOF analysis is performed. The resulting spatial patterns and corresponding time series are compared with the linear trend. The analysis is based on both monthly and annual-mean temperatures.
During the period 1971–98, most of the warming trend occurred from November to May (Figures 24a and 24b). The highest temperatures occur in February and, to a lesser extent, May. During these two months, statistically significant trends are observed for most of the stations. The southeast is the only region that experiences negative slopes throughout the year.
The trends in the annual temperature dataset are shown in Figure 25a. The temperature trend line shows positive slopes, with the exception of the southeast region. The highest values are observed in a region extending from the central north to the southwest part of the country. Most of the trends are statistically significant based on a t test (95% confidence). The annual-mean temperature for Kaolack (Figure 25b) is an example of the increasing trend of air temperature during the study period. All stations in the study area, with the exception of Kedougou, exhibit a similar mode.
A comparison between the trends map (Figure 25a) and the spatial patterns of the first EOF mode (Figure 26a) indicates similarity between the two patterns and confirms the robustness of the linear trend method. The time series for the first EOF mode (Figure 26b) also depicts a warming trend. This tendency also appears in Figure 27, which shows a comparison between the normalized temperature anomalies in Senegal (Figure 27a) and the global (worldwide) mean temperature relative to the 1951–80 period (Figure 27b). This comparison allows the evolution of temperature trends in Senegal to be placed in the broader context of the regionally observed warming trend over the past 30 yr. A moving average of the temperature time series (Figure 27a) shows two main warming phases over Senegal for the study period: 1978–83 and 1995–98. Hansen et al. (Hansen et al. 2002) have linked the record heat in 1998, which was observed throughout the world, with a strong El Niño event that raised global temperature 0.2°C above the trend line. Overall, the warming could be the result of more localized effects (e.g., land-use/land-cover change) and changes in regional meteorology (Pielke et al. 2002; Niyogi et al. 1999). Correlations between EOF1 for temperature over Senegal and Pacific SST in the El Niño zones and between the normalized temperature index for Senegal and the Southern Oscillation index (SOI) are shown in Table 1. A significant correlation exists between EOF1 for Senegal and Pacific SST during the January to April period, with the highest values (∼0.70) observed in the Niño zone (Table 1). For the remainder of the year, values are modest or weak. The normalized temperature index is inversely correlated with SOI during the first months (−0.79 in March) as shown in Table 1e.
5. Summary and conclusions
This study provides one of the first descriptive characterizations of the mean climate conditions in Senegal using in situ local observations. A relatively large dataset was compiled and digitized over the 1971–98 period. Rainfall and temperature distribution, variability, and trends were analyzed using monthly, seasonal (JJAS), and annual averages relative to the study period. Temperature and rainfall distributions were also mapped and analyzed using ArcGIS Spatial Analyst.
Rainfall over Senegal is concentrated in 3–4 months (JJAS), especially in August and September, and its distribution is dominated by a N–S gradient of decreasing amounts from south to north. June exhibits the greatest variability. Spatially, a decrease in variability occurs from north to south. Trends in precipitation are estimated using linear regression analysis and interpolation maps for the slopes. According to the t test, no statistically significant trend is shown for both rainfall and the number of rainy days.
The spatial distribution of mean annual temperatures is driven by oceanic and continental influences. Temperatures generally decrease eastward, but during the wet season, a N–S gradient is observed. Based on the coefficient of variation, the greatest variability occurs in the western and northern regions of the country, and the months from January to April are accountable for most of the variability. The greatest fluctuations of temperature occur during the dry season, especially in the semiarid areas of the north and northwest. To examine the trends, spatial and temporal patterns for all stations were analyzed with interpolated linear slopes. An index based on the 1971–98 period was also computed and an EOF analysis was performed. For the period 1971–98, most of the warming trend took place from November to May. Regarding the annual temperature trends, all slopes are positive with the exception of the southeast. According to the t test, most of the trends are statistically significant. The time series for the first EOF mode for temperature clearly depicts a warming trend. A significant correlation exists between EOF1 temperature–time series for Senegal and Pacific SST (El Niño zone) during the January–April period.
Acknowledgments
This work is part of an M.S. thesis by SF under the direction of DN and FS. SF was supported by a Fulbright fellowship from the Institute of International Education (IIE) and the NSF. Part of this work also benefited from NASA-THP grant (Dr. J. Entin). We are also grateful to the following institutions: Météorologie Nationale, Dakar, Senegal, and Centre de Suivi Ecologique, Dakar, Senegal. We extend our gratitude to Aboubacar Camara (CSE, Dakar, Senegal) and Moussa Yoro Thiam and Amadou Sene (Météorologie Nationale and ASECNA, Dakar, Senegal) for assistance in obtaining the climate data. This is the Purdue Climate Change Research Center (PCCRC) Paper 0513.
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Mean trade winds circulation during the Northern Hemisphere winter.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Mean position of the ITCZ on extreme West Africa during the Northern Hemisphere summer (adapted from Garnier 1976). The continental ITCZ is a “drift”: an anticyclone in one hemisphere faces a trough in the other. The maritime ITCZ is a “duct”: two anticyclones face each other, one in each hemisphere.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Surface meteorological/climate-monitoring stations used in this study.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Seasonal (JJAS) rainfall distribution for the period 1971–98: (a) rainfall in mm (colors) and number of rainy days (isolines); (b) monthly distribution, for the rainy months. A north–south gradient is evident. Southern Senegal is the first and the last region to receive rainfall, depending on the monsoon.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Annual rainfall cycle rainfall for Diourbel (14.65°N, 16.23°W), expressed as box plots for 12 running 3-month periods. Values are averaged over the study period (1971–98). The median is indicated by the black line inside the boxes; the upper and lower limits of each box show the 75th and 25th percentile (upper and lower quartiles). The vertical lines extending from the top and bottom of boxes indicate the maximum and minimum records of the dataset. Extremely high (or low) records, which are outside of this range, are outliers (indicated by circles in the graph). All stations in the study area exhibit a similar pattern.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Mean monthly rainfall distribution (in mm) for 1971–98. March (which recorded traces of rainfall) and April are omitted. Off-season rains are mostly observed in the north and west. The wet season starts in May, when the first tropical disturbances reach the southeast, while most of the country remains relatively dry.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Mean monthly rainfall and number of rainy days for the period 1971–98. There is a strong agreement between rainfall amounts and the number of rainy days, and the spatial patterns reveal a N–S gradient in distribution.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Contribution of each month in the seasonal totals of rainfall (expressed as a percentage). Values are averaged over the study period.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Maximum relative humidity (%) averaged over the period 1971–98. (a) Matam (15°65′N, 13°25′W); (b) Tambacounda (13°77′N, 13°68′W).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Spatial patterns of variability for rainfall and number of rainy days. Values are coefficients of variation, expressed as percentage, for all stations in the study area. Higher values indicate a greater interannual variability.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Seasonal (JJAS) variability of (a) precipitation and (b) number of rainy days.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Seasonal rainfall distribution for 1971–98: (a) Saint-Louis (16.05°N, 16.45°W); (b) Ziguinchor (12.55°N, 16.27°W). The addition of a 3-yr moving average trend line (red line) highlights the high-frequency variability of the northern stations (e.g., Saint-Louis), in contrast with lower-frequency fluctuations for the southern stations (e.g., Ziguinchor).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Time series plot of Senegal rainfall and number of rainy days indices (normalized rainfall departures) for JJAS 1971–98.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Observed mean rainfall anomaly (1971–98).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Spatial patterns of the seasonal (JJAS 1971–98) rainfall trends: (a) precipitation and (b) number of rainy days. Areas with negative trends are shown by a solid yellow line.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Monthly mean solar radiation duration (h) for Matam (15°65′N, 13°25′W), Dakar (14°73′N, 17°57′W), and Tambacounda (13°77′N, 13°68′W). Values are averaged over the study period (1971–98).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Monthly mean temperature for the period 1971–98: (a) Matam (16.65°N, 13.25°W); (b) Dakar (14.73°N, 17.57°W). Units are in °C. The lower panel shows a typical temperature regime in Senegal, with a primary minimum in January and a secondary minimum in August–September, a primary maximum in May–June, and a secondary maximum in October, with the latter corresponding to the end of the rainy season. As indicated by the vertical lines of the box plots, the greater amplitudes occur during the dry months.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(a) Spatial distribution of mean monthly temperatures. Units are in °C. During the dry season, a decreasing trend is observed with the lowest values recorded in January; the coolest temperatures are observed in the northern coastal areas and the northwest. From March to May, there is an increasing contrast in temperature between the west and east, while a heating trend is observed. The highest values are recorded in the east.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(b) Same as (a), except for May–October. From July to October, the previously observed E–W gradient is replaced by a N–S gradient. The core of the rainy season (August–September) corresponds to a relative decrease of temperatures, particularly in the south, which is more humid.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Spatial distribution of the mean annual temperature. Units are in °C. The E–W gradient denotes a double influence: (i) maritime (cool NW trade winds and cold maritime current) and (ii) continental (dry and warm trade winds: harmattan).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Maximum relative humidity (%) averaged over the period 1971–98: (a) Saint-Louis (16°05′N, 16°45′W); (b) Dakar (14°73′N, 17°57′W).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Coefficient of variation for the mean temperature: (a) spatial patterns for the mean annual temperature expressed as percentage (period 1971–98); (b) mean monthly variation for selected stations. Most of the variability is observed in a band stretching along the coastal areas and the north. The northern stations exhibit greater fluctuations, and a greater variability is observed during the dry months, especially the January–April period.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(a) Spatial patterns of variability for mean temperatures from January to June. Values are coefficients of variation, expressed as percentage, for all stations in the study area.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(b) Same as (a), except for July–December.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(a) Mean monthly temperature trends from January to June (1971–98). Slopes are multiplied by 100. Black dots represent the stations whose trends are significant at the 95% confidence level, using the t test. Black triangles represent stations with trends that are not significant.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(b) Same as in (a), except for July–December.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(a) Mean annual temperature trends relative to the period 1971–98. Negative values (in the southeast) are marked by the white solid line. Yellow dots represent the stations whose trends are significant at the 95% level, using the t test. Black triangles represent stations with trends that are not significant. (b) Mean annual temperature for Kaolack (14.13°N, 16.07°W). A linear regression line is fitted. A warming trend is observed in most of the stations in the study area.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
EOF analysis of temperatures for the period 1971–98: (a) EOF1 eigenvector patterns (loadings are multiplied by 10); (b) corresponding time series fitted with a linear trend line. The highest values occur in 1998 and 1983, which are also El Niño years.
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
(a) Normalized temperature anomalies relative to the period 1971–98 for Senegal. A 5-yr moving average trend is fitted. (b) Global mean temperature in °C relative to the mean temperature for the period 1951–80 based on measurements at meteorological stations (the mean for 1951–80 is about 14°C). The vertical lines at several dates indicate the estimated uncertainty in the annual-mean temperature due to the incomplete coverage of stations. The figure was obtained from the Goddard Institute for Space Studies (http://www.giss.nasa.gov/research/observe/surftemp/1998.html).
Citation: Earth Interactions 10, 5; 10.1175/EI158.1
Correlations between temperature indices over Senegal and Pacific Ocean features (a) between EOF1 (Temp-EOF1) and monthly SST in the Niño-1–2 zone (0°–10°S, 90°–80°W); (b) EOF1 and monthly SST in the Niño-3 zone (5°N–5°S, 150°–90°W); (c) EOF1 and monthly SST in the Niño-4 zone (5°N–5°S, 160°E–150°W); (d) EOF1 and monthly SST in the Niño-3–4 zone (5°N–5°S, 170°–120°W); and (e) normalized temperature anomaly for the period 1971–98 (T) and the SOI. SST data were obtained from the Climate Prediction Center (http://www.cpc.noaa.gov/data/indices/). Italic values are significant at the 95% confidence level, according to the t test.
Neighboring eigenvalues are statistically significant when they are distinctly separated. Kendall (Kendall 1980) proposed a test based on the following equation: δλ = λ (2/N)1/2, where δλ is the sampling error, λ is a given eigenvalue, and N is the sample size. An eigenvalue is significant when its associated sampling error is smaller than its spacing from the neighboring value.
