THE INFLUENCE OF LA NINA ON AFRICAN RAINFALL

Transcription

1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 20: (2000) THE INFLUENCE OF LA NINA ON AFRICAN RAINFALL S.E. NICHOLSON* and J.C. SELATO Florida State Uni ersity, Department of Meteorology, Tallahassee, FL 32306, USA Recei ed 15 December 1999 Re ised 12 May 2000 Accepted 12 May 2000 ABSTRACT This article examines the influence of La Nina/cold events on rainfall over the African continent, using a harmonic analysis method. As with El Nino, there is a general association between wet conditions continentally and cold temperatures in the Atlantic and Indian Oceans, and dry conditions in association with warm sea-surface temperatures (SSTs) in these oceans. La Nina appears to have the greatest influence on rainfall in southern Africa and wet episodes tend to occur throughout the subcontinent during the first few months of the post-la Nina year. There is a somewhat weaker tendency for below-normal rainfall in eastern equatorial Africa at this time. Our results provide further confirmation of an earlier conclusion that SSTs in the Atlantic and Indian Oceans are a primary influence on African rainfall. La Nina s influence tends to be exactly opposite that of El Nino: reduced rainfall over much of the continent in the first half of the episode, abnormally high rainfall in the second half. The documented El Nino/La Nina associations with African rainfall reflect the impact of these episodes on SSTs in the oceans. Copyright 2000 Royal Meteorological Society. KEY WORDS: Africa; air sea interaction; climatic variability; harmonic analysis; La Nina; El Nino; rainfall 1. INTRODUCTION It has long been recognized that the Pacific El Nino has a close association with rainfall variability in many parts of Africa. Geographically specific studies indicated a tendency for droughts in southern Africa during El Nino events (Lindesay et al., 1986; van Heerden et al., 1988) and above-normal rainfall in much of equatorial eastern Africa (e.g. Farmer, 1988; Camberlin, 1995; Nicholson, 1996; Camberlin, 1997). Several studies have suggested an influence on continental-scale patterns of variability (Nicholson and Entekhabi, 1986; Ropelewski and Halpert, 1987; Janowiak, 1988; Nicholson and Kim, 1997), with particularly strong signals in eastern and southern Africa. These continental-scale studies have suggested a remarkable lack of influence in Sahelian West Africa, a region of marked variability. However, other studies looking more specifically at that region and/or considering only recent years have concluded that El Nino tends to reduce rainfall (e.g. Semazzi et al., 1988; Wolter, 1989). Ward (1998) has reconciled the various views by demonstrating that El Nino forces high frequency variability in the region (i.e. on time scales less than about 10 years) and has had a greater impact during the protracted dry episode of the last three decades than earlier. In view of the strong El Nino signal over much of the continent, a pronounced influence of La Nina might also be anticipated. However, the only continental-scale study of its influence on African rainfall was that of Ropelewski and Halpert (1989), who found a consistent La Nina signal in two sectors. An area of equatorial East Africa tended to experience low rainfall during the period from November of the La Nina year to March of the following year. An area of southeastern Africa experienced positive rainfall anomalies during this same period, up to the April of the year following La Nina. Kiladis and Diaz (1989), who looked at composite differences between cold and warm events, showed an influence in * Correspondence to: Florida State University, Department of Meteorology, Tallahassee, FL 32306, USA; nicholson@met.fsu.edu. Copyright 2000 Royal Meteorological Society

2 1762 S.E. NICHOLSON AND J.C. SELATO Table I. La Nina years utilized in this study roughly the same areas, but the analysis method did not permit them to distinguish between the influence of La Nina and El Nino. Here, La Nina s association with African rainfall is further examined, using an additional 10 to 15 years of data and regionally-averaged rainfall anomalies instead of station data. The study follows the approach of Nicholson and Kim (1997), which is an adaptation of the harmonic method developed and applied by Ropelewski and Halpert (1987, 1989). This methodology is described in detail in Section 2. A robust La Nina signal is found over much of the continent and is generally out-of-phase with the El Nino signal in the regions where it occurs. As with the El Nino signal (Nicholson, 1997; Nicholson et al., 2000), La Nina s influence on African rainfall appears to be confined to those events that produce strong sea-surface temperature (SST) anomalies (in this case, a cold phase) in the Atlantic and Indian Oceans. 2. DATA This study utilizes monthly rainfall data from an historical archive of nearly 1400 stations, as described in numerous other publications (e.g. Nicholson, 1986, 1993). To describe the evolution of SST patterns in the Atlantic and Indian Oceans during the course of a typical La Nina episode, SST data from the Comprehensive Ocean-Atmosphere Data Set (COADS) are analysed. The years in which La Nina events are assumed to have occurred are indicated in Table I. This includes those years since 1901 identified by Ropelewski and Halpert (1989) as La Nina events and the La Nina event of Thus, this study is based on 17 episodes during the period , eight of which (1909/1910, 1916/1917, 1955/1956 and 1970/1971) occurred in consecutive years. From the station rainfall archive, standardized regional time series (monthly, seasonal and annual) were produced for the 90 regions shown in Figure 1. Regions were defined using rainfall characteristics and linear correlation; homogeneity of the regions with respect to interannual variability was confirmed using an F-test (see Nicholson, 1986). Most regional series commence around 1901 and extend through the last Figure 1. Map of 90 homogeneous rainfall regions in Africa

3 LA NINA AND AFRICAN RAINFALL 1763 Figure 2. Key to the depiction of rainfall fluctuations via harmonic analysis. The time series represents a rainfall anomaly averaged over all regions in the chosen sector and over all 17 La Nina events in the period The ( 1, 0, +1) refer to months in the years prior to, during and following a Pacific La Nina event. The data are ranked anomalies, so that the vector length is arbitrary. The harmonic dial illustrates the vector convention for displaying the amplitude and phase of the fitted harmonic, with the arrow pointing in the direction of the month of highest positive rainfall anomalies year of the study period, Further details on the regional series are given in Nicholson and Kim (1997). The study of La Nina SST patterns is based on fewer years. The COADS data set (Woodruff et al., 1987) covering the time period is utilized. As in Nicholson (1997), the analysis sector extends from 40 N to 40 S and from the western Atlantic to the central Indian Ocean at about 100 E. Although the data are available with a 2 2 resolution, most of the variance is captured in 4 4 averages (Nicholson and Nyenzi, 1990), hence these are used here to facilitate computations. Although the COADS data set extends back to the last century, only the years since 1948 are considered here, in order to reduce biases due to changes in observing procedures and density of observations. The choice of 1979 as the end of the analysis period was made for several reasons. The main one is that this will permit a direct comparison with the El Nino Southern Oscillation (ENSO) study of Nicholson (1997), which eliminated the post-1979 period. A second reason for the choice is that extensive use of satellite data creates a discontinuity in the COADS data set at about that time. Finally, the SST analysis period is comparable to that of numerous papers studying the global El Nino phenomenon (e.g. Deser and Wallace, 1990; Ropelewski et al., 1992). In some studies later years were eliminated because of the well-recognized global warming of the oceans in the late 1970s and because El Nino events of the 1980s were quite unlike earlier episodes in terms of timing, intensity and duration (Gill and Rasmusson, 1983; Rasmusson and Mo, 1993). This leaves open the possibility that relationships between La Nina and African rainfall might be different during the post-1979 period than those identified in this article. That issue can be examined in a separate study. 3. METHODOLOGY The methodology of identifying a La Nina signal has several steps, described in greater detail in Ropelewski and Halpert (1987, 1989), Halpert and Ropelewski (1992) and Nicholson and Kim (1997). The first step is to derive a typical, 2-year La Nina episode by forming a composite of all 17 episodes during the analysis period. Using the convention generally applied to El Nino, an episode is defined as the 2-year period commencing in July prior to the La Nina (or high index) year (designated at July ( 1)) and continuing until June of the year after La Nina (designated as June (+1). The composite episode is derived from the regional rainfall series and consists of 24 monthly values representing rainfall anomalies. The La Nina signal in rainfall is then detected by performing harmonic analysis on the composite for each region. This yields a phase and amplitude, based on the first harmonic. These represent, respectively, the time of maximum rainfall in each region and the total magnitude of rainfall variation during the 2-year period. Vectors depicting the phase and amplitude at each grid-point, as illustrated in Figure 2, are plotted on a map. From this map, multiregion sectors that appear to have a coherent La Nina signal are selected and the coherence within each sector is assessed, following Ropelewski and Halpert (1987). For each sector, a

4 1764 S.E. NICHOLSON AND J.C. SELATO 24-month composite is then derived with the value for each month calculated as the arithmetic average of the values for all regions within the sector. This is a 24-month La Nina aggregate response for the sector. The composites are then examined to ensure that rainfall anomalies of the same sign persist for multimonth periods and to identify the 3-month seasons with the largest negative and positive anomalies. Finally, rainfall time series for each of these seasons are derived as the anomaly averaged over all regions within the sector. These time series, covering the period , show the consistency of the rainfall response associated with La Nina. As in Nicholson and Kim s (1997) analysis of the El Nino signal, the rainfall analysis is based on anomaly rank. This procedure is used because of the large number of absolutely dry months and the skewed distribution of rainfall in arid and semi-arid regions. Rank is used to delineate the La Nina signal, but the subsequently derived seasonal time series and composites are based on standardized departures. 4. RESULTS OF HARMONIC ANALYSIS The results of the harmonic analysis are presented in Figure 3. The strongest La Nina signals occur in southern Africa and in extra-tropical North Africa. Some influence also appears along the Guinea Coast of West Africa. Contrary to the El Nino case, this approach does not indicate a strong influence in eastern equatorial Africa. These results also seem to suggest a lack of influence in most of West Africa, consistent with the findings of Ropelewski and Halpert (1989) for La Nina and the findings of Ropelewski and Halpert (1987) and Nicholson and Kim (1997) for El Nino events. However, caution is in order in drawing these last two conclusions, because this method only detects those signals with a temporal structure that can be represented by a first harmonic. Also, high and low-frequency domains are not separately analysed, so that a signal might be overridden by strong low-frequency variability in the Sahel, as with El Nino (Ward 1998). In Figure 3, six sectors are identified as candidates for consistent La Nina-induced fluctuations in rainfall. The 24-month La Nina composites for each sector are presented in Figure 4. In contrast to the El Nino case, the response indicated by the composites is not particularly well described by the first harmonic. Nevertheless, in the six sectors selected, there appears to be a strong La Nina signal in rainfall. In all cases, strong positive anomalies occur toward the end of the La Nina year and/or the beginning of Figure 3. Results of harmonic analysis of 24-month La Nina rainfall composites, representing an average of 17 La Nina events. See Figure 2 for interpretation of notation. Sectors selected for further analysis are outlined and numbered

5 LA NINA AND AFRICAN RAINFALL 1765 Figure 4. La Nina-composite rainfall anomalies for six African sectors identified in Figure 3. Time series commence in July in the year prior to La Nina and continue to June of the year following it. Shadings indicate seasons of possible La Nina-related rainfall response, with light shading indicating seasons of maximum negative rainfall anomalies and dark shading indicating seasons of maximum positive rainfall anomalies. Amplitude is an index based on rank. (a) North and West African sectors. (b) Western sectors of Southern Africa. (c) Eastern sectors of Southern Africa the post-la Nina year and the positive anomaly is evident throughout a 6- to 8-month period. This is roughly the timing of the maximum negative anomaly in these regions during the El Nino cycle. Unlike the positive anomalies, the negative anomalies are generally relatively weak and are not temporally persistent. The strongest negative anomalies generally occur toward the end of the La Nina year or the end of the year preceding it. From the composite time series in Figure 4, the 3-month seasons of maximum negative and positive anomalies are selected. These seasons are indicated in Table II. Selection was guided by the need to minimize the use of dry months in the choice of season. Although a dry-season response to La Nina might Table II. Seasons of maximum negative rainfall anomalies and maximum positive rainfall anomalies for the six sectors shown in Figure 3 Sector Positive anomalies Negative anomalies 1 FMA (+1) SON (0) 2 JFM (+1) 2 SON ( 1) 3 DJF (+1) ASO ( 1) 4 FMA (+1) SON (0) 5 DJF (+1) SON ( 1) 6 JFM (+1) JAS ( 1)

6 1766 S.E. NICHOLSON AND J.C. SELATO occur, this analysis procedure would exaggerate it, because very small changes in rainfall produce large percent anomalies during relatively dry months. An exception to the above convention occurs in the case of Sector 2. In this sector there is no 3-month period with pronounced negative anomalies, but two 3-month periods with strong positive anomalies are apparent. Hence, both are evaluated. Time series of standardized rainfall anomalies are given in Figure 5 for the seasons indicated in Table II. The consistency of response is indicated in Table III and is defined simply as the number of events, out of 17, with a rainfall anomaly of the anticipated sign. In many cases, the anomaly is relatively small, but in this simple index magnitude is not taken into account. In almost all cases, a rainfall anomaly of the anticipated sign occurs quite consistently in the indicated seasons. The most consistent response is in Sector 3, which includes most of the eastern half of southern Africa (large areas of Mozambique, Malawi, Zambia, Zimbabwe and Botswana). In 13 of the 17 events, a positive rainfall anomaly appears in the December February (DJF) (0) season, but in most cases, the anomaly is weak. In 14 of 17 events, a negative anomaly appears in the August October (ASO) ( 1) season. The magnitude of the anomalies is generally large, but these 3 months occur prior to the heart of the rainy season and August is generally dry in most regions comprising Sector 3. The strongest response is evident to the west of this sector, in Sectors 4 and 5 (mostly Namibia and South Africa). In Sector 4, the positive anomaly appears in February April (FMA) (+1) in 14 of 17 events and the negative anomaly appears in September November (SON) (0) in 12 of 17 events. The response in Sector 5 is similar and occurs at roughly the same time: positive anomalies in DJF (+1) in 12 of 17 events and negative anomalies in SON ( 1) in 14 of 17 events. Particularly evident is the high rainfall in association with the La Nina events of the 1970s. In the remaining sectors, the consistency of the responses is somewhat lower but the magnitude is generally strong. In Sector 1 (North Africa), it is 12 of 17 for positive anomalies in the FMA (+1) season and 11 of 17 for negative anomalies in the SON (0) season. In Sector 2 (Guinea Coast) it is 12 of 17 for positive anomalies at this time (January March (JFM) ( +1)). Positive anomalies also occur in 11 of 17 events during SON ( 1). In Sector 6, (southeastern Africa) rainfall anomalies were positive in 10 of 17 La Nina events during the JFM season of the year following La Nina. The negative anomalies during July September (JAS) of the year preceding La Nina occurred more consistently, in 13 of 17 events, but a huge positive anomaly occurred in this season of the 1988 event. These months are relatively dry in most of the regions comprising Sector 6, so that this exception may not be particularly meaningful. It should be noted that eight of the 17 events considered in this study occurred in consecutive years. Ropelewski and Halpert (1989) handled this problem by considering only the event of the first year, but in our study both were utilized. To see if this had an impact on the results, we visually examined Figure 6 to see whether the sign of the anomaly was the same in both pairs of events 1909/1910, 1916/1917, 1955/1956 and 1970/1971. Except for the 1909/1910 pair, there are few cases of opposite anomalies occurring in the 2 years of the pair. Also, elimination of either the first or the second year of the pairs does not significantly alter the consistency of the resultant rainfall anomalies. Table III. Number of La Nina episodes (out of 17 episodes) with rainfall anomalies of the expected sign during the appropriate season (see Table II for season) Sector Positive anomalies Negative anomalies (JFM (+1)) 12 2 (SON ( 1))

7 LA NINA AND AFRICAN RAINFALL 1767 Figure 5. Time series of seasonal rainfall anomalies (standardized departures) for six African sectors shown in Figure 3. These represent the 3-month periods (as indicated) in which positive or negative rainfall anomalies are anticipated during La Nina events, as identified in Figure 4. Units are regionally-averaged standard deviations. Shading represents La Nina events, but may represent year 0, year +1 or year 1, depending on the timing of the anomaly in that particular region (see Table II). (a) North and West Africa. (b) Western sectors of Southern Africa. (c) Eastern sectors of Southern Africa. In each case, the top set of diagrams represents time series for the seasons in which positive anomalies are anticipated; the bottom set of diagrams represents time series for the seasons in which negative anomalies are anticipated, execpt for sector 2

8 1768 S.E. NICHOLSON AND J.C. SELATO 5. CONTINENTAL COMPOSITES OF RAINFALL DURING THE VARIOUS PHASES OF LA NINA To look at La Nina s influence on a continental scale and to identify additional areas with a strong La Nina signal, the rainfall anomaly patterns for the continent as a whole are examined. These are composited for each of the 3-month seasons of the episodes (Figure 6). The composites utilize only the first year in cases of 2 consecutive La Nina years, consistent with the approach of Ropelewski and Halpert (1989). This step had little influence on the overall patterns, but enhanced the magnitude of anomalies in areas where they appeared to be significant. During the first four seasons (JAS ( 1) to April June (AMJ) (0)), the anomalies are predominantly negative. However, positive anomalies prevail in the western half of the continent during October December (OND) ( 1) and in a various other sectors in the other seasons. For western equatorial regions, the pattern is predominantly positive in all four seasons. This contrasts strongly with similar composites for El Nino events. For one, the spatial continuity is much lower in the La Nina case. During El Nino, anomalies of one sign affect most of the continent in each season of the episode. Also, anomalies are predominantly positive during the first four seasons of El Nino episodes, compared to negative during La Nina. During the following four seasons, a pronounced shift to negative anomalies occurred in El Nino episodes. No such shift is evident in the La Nina composites for the continent as a whole, but strong positive anomalies developed regionally. This was the case for the Sahel and parts of equatorial Africa during the JAS (0) season. By OND (0), strong negative anomalies developed in this same region and in Figure 6. Continental maps of rainfall anomalies corresponding to 3-month segments of the 24-month La Nina composite for each of 90 regions. Units are regionally-averaged, standard departures multiplied by 100

9 LA NINA AND AFRICAN RAINFALL 1769 Figure 7. The seasonal cycle of rainfall in two sectors of eastern Africa selected for further analysis. This is calculated by averaging for all stations in each sector the percent contribution of each month to the annual mean. The location of sectors is shown East Africa, while positive anomalies developed over Southern Africa. Roughly the same pattern prevailed in the subsequent JFM ( +1) season, except along the Guinea Coast, where positive anomalies developed. A pattern of negative anomalies in the northern hemisphere and positive in the southern continued into the AMJ (+1) season. 6. THE LA NINA SIGNAL IN EAST AFRICA The harmonic analysis failed to identify a strong and coherent La Nina rainfall signal in East Africa. This is surprising in view of El Nino s strong effect on rainfall in this region and in view of studies such as that of Camberlin (1995) showing a strong influence in parts of the region. The composites in Figure 6 suggest that the signal was not initially picked up because the seasonal pattern of anomalies does not fit the harmonic model particularly well and because the signal is reasonably weak. Figure 6 nevertheless suggests that La Nina modulates rainfall in some seasons. For example, there are strong positive anomalies in JAS (0) and strong negative anomalies in the subsequent season. To further examine this question, the analyses shown in Figures 4 and 5 are carried out for two regions of East Africa. These are chosen on the basis of the patterns in Figure 6, but with a multi-region aggregation guided by rainfall seasonality and previous analyses of interannual variability. Several regions were chosen for further analysis. These were aggregated into a summer rainfall area that includes the Ethiopian highlands and the western Rift Valley highlands (regions 22, 27, 31, 85 and 88 of Figure 1) and an area with two rainy seasons that includes the Horn of Africa, parts of Kenya and northern Tanzania (regions 33, 38, 87 and 89). Figure 7 shows the annual cycle for both areas, expressing this as a percent contribution of each month to the annual mean. In the western region (EA1), August is the wettest month, but significant rainfall occurs in most months of the year. In the eastern region (EA2), both the summer and the winter are relatively dry. Region 32 is aggregated into EA1, despite its bi-modal rainfall seasonality, because the La Nina composite (Figure 6) shows strong summer rainfall anomalies extending into this region. Figure 8 shows the monthly composited rainfall for the two areas during La Nina events. In EA1 there are strong positive anomalies during the JAS (0) season. In EA2, the strongest negative rainfall anomalies occur during the OND (0) season, but a multi-month period of negative anomalies also occurs during the FMA ( +1) season. Figure 9 shows time series of rainfall anomalies for these seasons. The most consistent

10 1770 S.E. NICHOLSON AND J.C. SELATO Figure 8. La Nina-composite rainfall anomalies, as in Figure 4, for the two eastern African sectors shown in Figure 7. EA1 represents the summer rainfall area and includes regions 22, 27, 31, 85 and 88 of Figure 1. EA2 represents the equatorial rainfall regime with a bi-modal seasonal cycle and includes regions 33, 37, 87 and 89 La Nina association is in the JAS (0) season for EA1; positive anomalies occur in 15 of 17 events. The association with EA2 is less consistent, with negative anomalies in OND (0) and in FMA (+1) in 13 of 17 events. It is interesting to note that for the year as a whole EA1 and EA2 are very highly correlated (Figure 10), despite the contrast between a summer rainfall regime and a bi-modal one. This underscores the fact that the controls on interannual variability are not necessarily the same ones that produce the climatological Figure 9. Time series of seasonal rainfall anomalies (standardized departures) for the sectors shown in Figure 8. The season JAS (0) is shown for EA1 and the seasons OND (0) and FMA (+1) are shown for EA2. La Nina years are shaded

11 LA NINA AND AFRICAN RAINFALL 1771 Figure 10. Time series of annual rainfall averaged for the EA1 and EA2 sectors. Rainfall is expressed as standardized departures mean patterns. In view of the strong correlation between the two regions, it is meaningful to evaluate for both areas all three identified seasons of possible La Nina influence. Figure 11 thus presents the JAS (0) season for EA2 and the OND (0) and FMA (+1) seasons for EA1. La Nina s influence in the OND Figure 11. Time series of seasonal rainfall anomalies (standardized departures) for the sectors shown in Figure 8. The season JAS (0) is considered for EA2 and the seasons OND (0) and FMA (+1) are considered for EA1. La Nina years are shaded

12 1772 S.E. NICHOLSON AND J.C. SELATO Figure 12. SST evolution in the Atlantic and Indian Oceans during La Nina events. Composites are for 36-month seasons commencing JAS of the year prior to La Nina. Positive anomalies are shaded, with progressively darker shading indicating anomalies of , and greater than 0.5 C. Negative anomalies are shown via right hatching (0 0.25), left hatching ( ) and dots (greater than 0.5 C) (0) season clearly extends to EA1, with negative anomalies occurring in 11 of 17 events and strong positive anomalies occurring in none of the La Nina events. In the FMA (+1) season, no association is evident between La Nina and rainfall in EA1. La Nina s influence in EA2 in JAS (0) appears to be marginal, with negative anomalies occurring in 12 of 17 cases. It is nonetheless clear that associations with La Nina and El Nino (Nicholson and Kim, 1997) play a role in producing the similar patterns of interannual variability in the two regions. 7. RELATIONSHIP TO SSTS IN THE ATLANTIC AND INDIAN OCEANS Figure 12 presents the mean SST anomaly patterns for the various seasons of the La Nina episodes occurring between 1948 and A strong contrast is apparent, season by season, between the first half and second half of the episodes. The first three seasons (from JAS ( 1) to JFM (0)) show strong positive anomalies throughout most areas of the Atlantic and Indian Ocean within the analysis domain. In AMJ (0), strong positive anomalies continued in the equatorial Atlantic, but cooling had commenced throughout most of the Indian Ocean. The following three seasons (JAS (0) to JFM (+1)) are dominated by cold anomalies in both oceans, but two pronounced warm sectors remained in the equatorial Atlantic during the first of these seasons. By AMJ (+1), warming had again begun in many areas of the Atlantic and in the southern Indian Ocean. Thus, there is a tendency for a warm phase in the Atlantic and Indian Oceans early in the La Nina episodes and a cold phase in these oceans late in the episode. The end of the cold phase is approximately AMJ of the post-la Nina year. It is interesting to compare the SST patterns with those identified earlier (Nicholson 1997) for El Nino episodes (Figure 13). During El Nino episodes, there is likewise both a cold phase and warm phase in the Atlantic and Indian Oceans, but the sequence is exactly the opposite that of La Nina: the cold phase prevails in the first half of the episode, the warm phase in the second half. Moreover, there is a

13 LA NINA AND AFRICAN RAINFALL 1773 season-by-season reversal, with the distribution of positive SST anomalies in the first half of the La Nina episode bearing a strong resemblance to the distribution of negative SST anomaly patterns in these seasons of El Nino episodes. Similarly, the distribution of negative SST anomalies in the second half of La Nina is similar to that of the positive SST anomalies in the second half of the 2-year El Nino episodes. The several month phase shift observed during El Nino between the Atlantic/western Indian Oceans and the Pacific is also apparent in La Nina. It should be noted that 2 of the 8 La Nina years in the composite followed an El Nino year and 5 of the La Nina years preceded one. Thus, some of the semblance to the El Nino patterns can be so explained. However, the pattern is robust for the remaining years. This provides further confirmation of the tendency for warm conditions in the ocean sectors surrounding Africa to promote abnormally dry conditions over much of Africa and for cold conditions in these sectors to promote abnormally wet conditions over Africa. This tendency is, however, much weaker for La Nina events than for El Nino events. This is consistent with the much weaker SST anomalies during La Nina (Figure 12) compared to El Nino (Figure 13). It is interesting to note that 2 of the wettest years on record over Southern Africa, 1974 and 1976, were post-la Nina years (Figure 14). These anomalies were linked to both the JFM and AMJ seasons. Regionally-averaged rainfall was % above normal in much of the region, especially in southwestern regions near the Atlantic Ocean. An examination of SST patterns during the JFM rainy season of these 2 years (Figure 15) shows unusually strong cold anomalies in both cases in the Indian Ocean. During this season in 1974, SSTs were unusually high in the southeastern Atlantic, a condition which also favours high rainfall in this region (Nicholson and Entekhabi, 1987; Nicholson and Kim, 1997). During the AMJ season, generally the same SST pattern was maintained, except for an area of positive SST anomalies expanding into the central Indian Ocean. Figure 13. SST evolution in the Atlantic and Indian Oceans during El Nino events. Composites are for 3-month seasons commencing during JAS of the year prior to El Nino (from Nicholson 1997). Shading represents positive anomalies, with progressively darker shading indicating anomalies of , and greater than 0.5 C. Negative anomalies are indicated by right hatching (0 0.25), left hatching ( ) and dots ( 0.5 C)

14 1774 S.E. NICHOLSON AND J.C. SELATO Figure 14. Regionally-averaged rainfall anomalies during the years 1974 and 1976, expressed as a percent departure from normal. Regions are shown in Figure 1 8. SUMMARY AND CONCLUSIONS The harmonic analysis used in this study served to identify six sectors of Africa where La Nina appears to modulate rainfall in a predictable fashion. As with El Nino, the La Nina signal is strongest during the second half of the episode (i.e. the cold phase), but in contrast to El Nino, rainfall is abnormally high. La Nina s influence on rainfall occurs most consistently in southwestern Africa (Namibia and western South Africa, from 15 S to 32 S), with increased rainfall occurring in the first few months of the post-la Nina year in 14 of 17 events. Further east, in a sector stretching from southern Tanzania (10 S) to South Africa (32 S), positive anomalies occurred at roughly the same time but less consistently. In the two northern African sectors, positive anomalies occurred in this same season just as consistently, but were generally weak. In the western highlands of equatorial Africa positive anomalies also occurred in the second half of La Nina episodes, but during the summer season. La Nina episodes are generally less temporally symmetric than El Nino episodes, so that the first half of the episode is not a mirror image of the second half. Thus, the harmonic analysis is a less than optimal representation of the La Nina signal. Nevertheless the analysis demonstrates a tendency for anomalously dry conditions in most of these sectors some time during the first half of La Nina episodes (i.e. during the warm phase). The negative anomalies occur less consistently than the subsequent positive ones. The timing of the negative anomalies is quite disparate, ranging from JAS ( 1) to OND (0). A dry phase is not at all evident in the Guinea Coast sector. As in the case of El Nino, anomalously dry conditions tend to occur in conjunction with relatively warm SSTs in the Atlantic and Indian Oceans and anomalously wet conditions tend to occur during the cold phase of La Nina in these oceans. Our results further suggest that La Nina s influence on rainfall occurs much more consistently during the cold phase (second half of La Nina) than during the warm phase. The opposite was found to be the case for El Nino, with the rainfall response occurring more consistently in the warm phase (second half of El Nino episodes). Figure 15. SST anomalies averaged for the JFM and AMJ seasons for the years 1974 (left) and 1976 (right), as in Figure 12, but with a contour added to show negative SST anomalies exceeding 1 C

15 LA NINA AND AFRICAN RAINFALL 1775 A departure from the warm/dry cold/wet associations is apparent in eastern equatorial Africa. This is also the case for El Nino events. There is a tendency for dry conditions during the cold phase of La Nina, but these occur less consistently than do the positive anomalies at this time in southern Africa. Thus, La Nina also contributes to the well-documented dipole in rainfall anomalies between equatorial and southern Africa (Nicholson, 1986), but less so than El Nino does. Our results are consistent with those of Ropelewski and Halpert (1989), the most extensive study of La Nina s influence on African rainfall. They show the tendency for reduced rainfall in equatorial regions and above-normal rainfall in southeastern Africa early in the post-la Nina year. However, our study shows a considerably broader impact of La Nina, geographically speaking. La Nina s influence on rainfall is apparent throughout Southern Africa and its influence in equatorial Africa is considerably more complex and more spatially extensive than suggested by Ropelewski and Halpert. In general, our results confirm the conclusion of Nicholson (1997) and Nicholson et al. (2000) that SSTs in the Indian and Atlantic Oceans, rather than El Nino/La Nina, have the dominant control on rainfall variability over Africa. The observed El Nino/rainfall relationships are manifestations of the influence of El Nino and La Nina on these oceans. A similar conclusion was reached by Goddard and Graham (1999), using model simulations. This study has not attempted to quantify the forecast potential of La Nina events, but the rainfall/la Nina associations clearly have some prognostic value. In most of the regions evaluated, drought conditions are extremely unlikely during the first half of the post-la Nina year. Likewise, wet conditions are extremely unlikely in the eastern equatorial region late in the La Nina year or early in the following year. Since the Pacific La Nina commences several months prior to changes in the Atlantic and Indian Oceans, a more detailed statistical evaluation of the relationships shown in this study can provide some long-range forecasting skill. Finally, it should be noted that the analysis is based only on the period The El Nino events of the 1980s were quite unlike earlier episodes in terms of timing, intensity and duration (Gill and Rasmusson, 1983; Rasmusson and Mo, 1993). Thus, the relationships between La Nina and African rainfall that are summarized above may be different during the post-1979 period. This produces a limitation in the forecast value of the results. However, that issue can be examined in a separate study. ACKNOWLEDGEMENTS This work was carried out with the support of National Science Foundation (NSF) Grant No. ATM and NIBA-ATM The government of Botswana supported the participation of J. Selato in this study. The authors would like to thank D. Klotter for his assistance in the preparation of figures utilized in the article. REFERENCES Camberlin P June September rainfall in northeastern Africa and atmospheric signals over the tropics: A zonal perspective. International Journal of Climatology 15: Camberlin P Rainfall anomalies in the source region of the Nile and their connection with the Indian summer monsoon. Journal of Climate 10: Deser C, Wallace JM Large-scale atmospheric circulation features of warm and cold episodes in the tropical Pacific. Journal of Climate 3: Farmer G Seasonal forecasting of the Kenya coast short rains, Journal of Climatology 8: Gill AE, Rasmusson EM The climate anomaly in the equatorial Pacific. Nature 306: Goddard L, Graham NE Importance of the Indian Ocean for simulating rainfall anomalies over eastern and southern Africa. Journal of Geophysical Research 104: Halpert MS, Ropelewski CF Surface temperature patterns associated with the Southern Oscillation. Journal of Climate 5: Janowiak J An investigation of interannual variability in Africa. Journal of Climate 1: Kiladis GN, Diaz HF Global climatic anomalies associated with extremes in the Southern Oscillation. Journal of Climate 2: Lindesay JA, Harrison MSJ, Haffner MP The Southern Oscillation and South African rainfall. South African Journal of Science 82:

16 1776 S.E. NICHOLSON AND J.C. SELATO Nicholson SE The spatial coherence of African rainfall anomalies interhemispheric teleconnections. Journal of Climate and Applied Meteorology 25: Nicholson SE An overview of African rainfall fluctuations in the last decade. Journal of Climate 6: Nicholson SE A review of climate dynamics and climate variability in eastern Africa. In The Limnology, Climatology and Paleoclimatology of the East African Lakes, Johnson TC, Odada E (eds). Gordon and Breach: Amsterdam; Nicholson SE On the characteristics of warm episodes in the tropical Atlantic and Indian Oceans. International Journal of Climatology 17: Nicholson SE, Entekhabi D The quasi-periodic behavior of rainfall variability in Africa and its relationship to the Southern Oscillation. Journal of Climate and Applied Meteorology 34: Nicholson SE, Entekhabi D Rainfall variability in equatorial and southern Africa. Relationships with sea-surface temperatures along the southwestern coast of Africa. Journal of Climate and Applied Meteorology 26: Nicholson SE, Kim J The relationship of the El Nino Southern Oscillation to African rainfall. International Journal of Climatology 17: Nicholson SE, Nyenzi BS Temporal and spatial variability of SSTs in the tropical Atlantic and Indian Oceans. Archi es for Meteorology, Geophysics and Bioclimatology, Series A 42: Nicholson SE, Leposo D, Grist JR On the relationship between El Nino and drought over Botswana. Journal of Climate (in press). Rasmusson EM, Mo K Linkages between 200-mb tropical and extratropical circulation anomalies during the El Nino cycle. Journal of Climate 6: Ropelewski CF, Halpert MS Global and regional scale precipitation associated with El Niño/Southern Oscillation. Monthly Weather Re iew 115: Ropelewski CF, Halpert MS Precipitation patterns associated with the high index phase of the Southern Oscillation. Journal of Climate 2: Ropelewski CF, Halpert MS, Wang X Observed tropospheric biennial variability and its relationship to the Southern Oscillation. Journal of Climate 5: Semazzi FHM, Mehta V, Sud YC An investigation of the relationship between sub-saharan rainfall and global sea surface temperatures. Atmosphere and Ocean 26: van Heerden J, Terblanche DE, Schulze GC The Southern Oscillation and South African summer rainfall. Journal of Climatology 8: Ward NM Diagnosis and short-lead time prediction of summer rainfall in tropical North Africa at interannual and multidecadal timescales. Journal of Climate 11: Wolter K Modes of tropical circulation, southern oscillation, and Sahel rainfall anomalies. Journal of Climate 2: Woodruff SD, Slutz RJ, Jenne RL, Steurer PM A comprehensive ocean-atmosphere data set. Bulletin of the American Meteorological Society 68: