1SEPTEMBER 2001 MCHUGH AND ROGERS 3631

North Atlantic Oscillation In¯uence on Precipitation Variability around the Southeast African Convergence Zone

MAURICE J. MCHUGH Department of Geography, University of WisconsinÐOshkosh, Oshkosh, Wisconsin

JEFFREY C. ROGERS Department of Geography, The Ohio State University, Columbus, Ohio

(Manuscript received 19 April 2000, in ®nal form 23 October 2000)

ABSTRACT The relationship between the North Atlantic oscillation (NAO) and austral summer (December±February) rainfall variability over southeastern is described. Thirty-one stations in 0Њ±16ЊS and 25Њ±40ЊE have statistically signi®cant correlations to the NAO index over varying periods of record starting since 1895 and form a regional normalized rainfall index of southeast African rainfall (SEAR) correlated to the NAO index (NAOI) at r ϭϪ0.48 over 1894/95±1989/90, although the relationship is r ϭϪ0.70 since 1958. The spectrum of the SEAR index has signi®cant amplitude at 7.6 yr, a periodicity commonly associated with the NAO, and the NAOI/SEAR cospectrum has its largest power at this periodicity. NCEP±NCAR reanalysis data, extending from 1958/59 to 1995/96 are used to evaluate moisture and circulation ®eld variations associated with both NAO and SEAR indices. Precipitable water over southeastern Africa varies signi®cantly such that anomalously high (low) convective rainfall occurs over southeast Africa when the NAO is weak (strong). Unusually wet summers are associated with anomalous equatorial westerly ¯ow originating in the subtropical Atlantic and traversing the continent. Relatively dry summers are associated with increased southeasterly monsoon ¯ow originating over the subtropical Indian Ocean. The NAO linkage to southeastern African rainfall is especially pronounced in 300-hPa zonal winds where ®ve highly signi®cant elongated bands of alternating zonal wind anomalies extend from the Atlantic Arctic to equatorial Africa. The latter 300-hPa equatorial band exhibits westerly (easterly) ¯ow during wet (dry) austral summers and undergoes regional divergence (convergence) over southeastern Africa. The westerly ¯ow, along with orographic uplift, has an element of instability due to the vertical component of the Coriolis parameter that assists rain production during wet summer. Potential interactions between the NAO and ENSO in producing regional latitudinal ITCZ shifts are discussed.

1. Introduction (northward) when the NAO westerlies are unusually strong (weak). This paper shows the characteristics, and causes, of African precipitation is characterized by an opposi- an austral summer (Dec±Feb) association between the tion in rainfall anomalies over eastern Africa south of North Atlantic oscillation (NAO) and precipitation var- the equator (Nicholson 1986; Ropelewski and Halpert iability along and north of the southeastern Africa con- 1987) in both annual data and especially the austral vergence zone. Meehl and van Loon (1979) ®rst dem- summer wet season (Janowiak 1988). Janowiak iden- onstrated that such a relationship may exist. They ti®ed an area (DJFMn) between the equator and 10ЊS showed that the air temperature seesaw between Green- where rainfall departures tended to be opposite those of land and northern Europe was linked to latitudinal shifts DJFMs, lying between 15Њ and 30ЊS, suggesting that the in January rainfall around the southeast Africa inter- out-of-phase relation implied a shift in the ITCZ. Jan- tropical convergence zone (ITCZ). Rainfall was higher owiak's DJFMn region partly corresponds to our study south (north) of 15ЊS latitude during the ``Greenland area, an area where regionally coherent rainfall anom- Below'' (``Greenland Above'') Januaries than during alies can be linked to the NAO. Januaries dominated by the opposite seesaw phase. This Other interactions occur between African precipita- implies that the southeast African ITCZ shifts southward tion and large-scale teleconnections. Lamb and Peppler (1987) demonstrated a strong NAO link to interannual precipitation variability over , driven by the Corresponding author address: Dr. Maurice J. McHugh, Depart- ment of Geography, University of WisconsinÐOshkosh, 800 Algoma southward displacement of the Atlantic storm track and Blvd., Oshkosh, WI 54901-8642. precipitation-bearing storms when the Atlantic wester- E-mail: [email protected] lies are weak. El NinÄo±Southern Oscillation (ENSO)

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Fig. 2; Janowiak 1988, his Fig. 2a). Many of the stations near the ITCZ (ϳ10Њ±15ЊS) receive over 50% of their annual rainfall in summer while 25%±50% occurs in summer at stations extending farther north near 5ЊS (McHugh 1999).

2. Data and methodology We use the National Centers for Environmental Pre- diction±National Center for Atmospheric Research (NCEP±NCAR) global reanalysis of atmospheric ®elds (Kalnay et al. 1996), which employ a global data as- similation system on a database that includes a wide variety of sources and instruments covering various spa- tial and temporal scales. Global climatological sets such as the Comprehensive Ocean±Atmosphere Data Set have been incorporated into the data assimilation system FIG. 1. The countries of equatorial and . in addition to radiosonde, satellite, aircraft, merchant shipping, and meteorological station observations. Con- has been linked to unusually wet periods in equatorial sistent usage of the global data assimilation system in eastern Africa (Davies et al. 1985; Ogallo 1988) during the reanalysis results in a climate record that avoids any months June±August, and October±December. The area major analysis discontinuities due to incorporation of around Lake Victoria has an ENSO rainfall link in Oc- new data sources. The data have been quality controlled tober±December (Ropelewski and Halpert 1987; Nich- using a variety of spatial and temporal analyses. Re- olson 1996). Ropelewski and Halpert noted that the analysis of the combined datasets has been performed Lake Victoria rainfall anomaly is often opposite that of using an operational spectral forecast model with T62 southernmost Africa, such that an equatorward shift in spectral resolution, 28 vertical levels, and a grid size of the convergence zone occurs during ENSO (warm) ep- approximately 210 km (Kalnay et al. 1996). isodes. Variables used here include u- and ␷-component In , aspects of the tendency for summers winds and sea level pressures. These are among the most to be dry (wet) during equatorial Paci®c warm (cold) reliable (class A) variables, little in¯uenced by the mod- events are explored by van Heerden et al. (1988), Jury el although statistical interpolation of observations may et al. (1994), Jury (1996), and Kruger (1999). Rope- be employed in creating the gridded ®elds. Data were lewski and Halpert (1996) similarly ®nd a statistically evaluated in this study at all mandatory pressure levels signi®cant ENSO/rainfall signal in southeastern Africa, (McHugh 1999), but only 1000-, 850-, and 300-hPa south of Lake in , Africa (see Fig. results are presented here, being representative of tro- 1) southward of 14ЊS and extending across eastern South pospheric geopotential height and u- and ␷-wind com- Africa. This area corresponds closely to Janowiak's ponent ®elds. Streamlines are calculated at each level, using the u- and -component geostrophic wind ®elds. (1988) DJFMs region. ␷ The analysis area used here is concentrated on 0Њ± Atmospheric moisture variables used here (speci®c hu- 16ЊS and 25Њ±40ЊE, covering several African countries, midity and precipitable water) are determined partially identi®able in Fig. 1, including the Democratic Republic by the model and partly by observations of that variable of Congo (D.R.C.; formerly Zaire), , , (class-B ®elds). Precipitable water is calculated as ver- , , , , Malawi, and Moz- tically integrated speci®c humidity from 1000 to 300 ambique. Per the preceding discussion, the region to hPa. 16ЊS is potentially in¯uenced by ENSO along the equa- The North Atlantic oscillation index (NAOI) is cal- tor around Lake Victoria and eastern Kenya during De- culated since 1895 from normalized values of seasonal cember, and possibly over latitudes 14Њ±16ЊS, where mean sea level pressure values at Ponta Delgada, Ropelewski and Halpert (1987, 1996) suggest an ENSO Azores, and Akureyri, Iceland (Rogers 1984). Positive impact during austral summer months. For the most part (negative) NAOI values indicate that pressure is si- however, there is little evidence of an ENSO impact in multaneously higher (lower) than normal over the our study area; it is a part of Africa where rainfall link- Azores and lower (higher) than normal over Iceland, ages to large-scale circulation disturbances are not well representing an increase (decrease) in the North Atlantic known (Nicholson 1996). The region between 10Њ and Ocean pressure gradient and zonal wind speed. The 16ЊS is especially uni®ed by having a broad rainfall Azores and Iceland pressure difference will be used here maximum during the December±January±February to measure the NAO's phase and strength, rather than (DJF) summer period (Meehl and van Loon 1979, their the air temperature seesaw (Meehl and van Loon 1979),

Unauthenticated | Downloaded 09/24/21 05:23 AM UTC 1SEPTEMBER 2001 MCHUGH AND ROGERS 3633 which is merely a response to the NAO pressure gradient This often diminishes the signi®cance of zonally and extremes. meridionally oriented streamlines, where only one of Monthly African station rainfall data are obtained the two wind components may have a signi®cant result. from both the Global Historical Climatology Network The highly signi®cant streamline con®gurations are of- (GHCN) dataset, extending through 1990 (Vose et al. ten those from directions such as southwest or northeast, 1992), and a 2.3Њϫ3.75Њ gridded precipitation dataset where both the u- and ␷-component ®elds may be in- spanning 1900±98 (Hulme 1992) obtained from the Cli- dividually signi®cant. mate Research Center at the University of East Anglia, Spectrum and cospectrum analysis are used to eval- Norwich, Norfolk, . No quantitative uate both the variance spectrum of the southeast African analysis of homogeneity has been made for the GHCN rainfall index, as well as its covariance, with the NAO station data, but gross errors and discontinuities have index from 1899 to 1989. Both analyses were performed been ¯agged in the dataset (Vose et al. 1992). The num- using the Statistical Applications Software package. The ber of stations in Africa is low compared to other data- variance spectrum was analyzed for statistical signi®- rich regions of northern Europe and eastern North cance using chi-square methods outlined in Mitchell et America, but it is comparable to the coverage over much al. (1966). The cospectrum evaluates the periodicities of the world. Eastern Africa south of the equator from primarily contributing to the covariance and correlation Kenya to South Africa is relatively well covered with between two variables, and is evaluated for signi®cance many stations having relatively long time series in com- using the spectral coherence. parison to the remainder of the continent. Stations with at least 50 years of precipitation data are clustered in 3. Aspects of the climatology of southeastern , Tanzania along Lake Tanganyika, , Africa and in northeastern South Africa. A southeast African rainfall (SEAR) index was pro- The Hulme (1992) gridded precipitation data reveal duced using a set of 31 African station rainfall time (Fig. 2a) the mean austral summer (DJF) southeast Af- series, signi®cantly correlated to the NAOI. In forming rica climatological precipitation maximum between 15Њ the SEAR index, station data were normalized by di- and 20ЊS across northern Zambia and Mozambique, Ma- viding their seasonal (DJF) departures from the long- lawi, and southern Tanzania. Precipitation decreases to term mean by the seasonal standard deviation as per the north, falling to less than 6 cm around the equator Jones and Hulme (1996). The number of normalized and to its north. Rainfall also decreases toward south- rainfall values contributing to the SEAR index varies western Africa and the Kalihari Desert. with time since station periods of record are variable. Climatologies of African circulation and climate (Tor- To illustrate the relationship between atmospheric re- rance 1972; Preston-Whyte and Tyson 1988; Nicholson analysis data and southeast African rainfall anomalies, 1996) emphasize the contribution of three very different indices for SEAR and the NAO were normalized and surface airstreams interacting to form the southeastern regressed onto the normalized NCEP reanalysis vari- Africa convergence zone (Fig. 2b). The southeast trades, ables for the 32 winters between 1958±59 and 1989± originating over the Indian Ocean to the south and east 90. Both the independent and dependent variables are of Africa, and the northeasterly monsoonal ¯ow, poten- standardized before regression analysis is performed, tially originating as far away as the Indian subcontinent, producing a standardized slope b interpreted as a stan- are both thermally stable and associated with subsiding dard deviation change in the dependent variable per a dry air (Nicholson 1996). The northeasterly monsoon one standard deviation change in the independent var- ¯ow is dry, especially when it originates over the eastern iable (McClendon 1994). Standardized beta coef®cients Sahara (illustrated in Fig. 2b), but it is more moist when are utilized because of the differences in data variance it traverses the northwestern Indian Ocean (Torrance that occur across the globe, between high and low lat- 1972). These easterly air streams dominate southeast itudes, between different levels of the atmosphere, and Africa during their respective high-sun seasons (e.g., from land to sea. They provide a basis for signal strength the northeast trades during DJF), and help to form the comparisons among these very different areas. east±west-oriented component of the southeastern Af- The Student's t test statistic is used to test the null rica ITCZ. The favored convergence zone position can hypothesis, H 0, that the population slope is not signif- vary by several degrees of latitude (Torrance 1972), but icantly different from zero. This is a two-tailed hy- typically lies between 15Њ and 17ЊS. When the ITCZ is pothesis and is tested as such. The t statistic for the null farther north, between 10Њ and 12ЊS, the comparatively hypothesis is calculated as the ratio of the slope to the dry southeast trades dominate much of Mozambique, estimated standard error of the slope t ϭ b/Sb, where b Zimbabwe, Zambia, and Malawi. The ITCZ can at times is the slope coef®cient and Sb is the estimated standard also extend unusually far south, near 20ЊS, bringing error of the slope. Statistical signi®cance of the constant heavy rains to Zimbabwe and southern Mozambique pressure surface streamlines is obtained by calculating (Torrance 1972). An area of weak mean low pressure the weighted average of the t statistics separately ob- lies over southern and northern , just tained for the u- and ␷-component ®elds of the ¯ow. southwest of the ITCZ (Fig. 2b).

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where it cools adiabatically to saturation, continually moving eastward toward the higher elevations of eastern Africa, where it brings abundant rainfall (Torrance 1972; Nicholson 1996). The three airstreams attributed to the southeast African convergence zone can be affected by movement of pressure systems at higher latitudes, and by tropical cyclones, or they can be inactive when there is little regional air¯ow convergence across them. Near-surface mean streamlines (Fig. 3a), calculated from seasonally averaged u- and ␷-component winds in the NCEP±NCAR reanalysis data, con®rm the surface airstream models of Torrance (Fig. 2b) and Nicholson. Air originating along the east ¯ank of the South Atlantic subtropical anticyclone enters Africa south of the equa- tor as a westerly current extending into the D.R.C. and Angola. The northeasterly monsoon ¯ow, which crosses the Indian Ocean in this climatology, and the south- easterly trades, originating in the subtropical Indian Ocean, converge between 15Њ and 20ЊS and ¯ow into the semipermanent summer low pressure area lying over southern Zambia and Angola, joining with the con- verging westerly Zairean air. The Northern Hemisphere ITCZ is formed by moist air originating along the east- ern ¯ank of the South Atlantic subtropical high con- verging directly into northeasterly ¯ow of the Northern Hemisphere (Fig. 3a). The 850-hPa mean ¯ow based on the NCEP±NCAR reanalyses (Fig. 3b) differs only slightly from that at 1000 hPa (Fig. 3a). Westerly ¯ow entering southern Africa from the South Atlantic is con®ned to an area north of the cyclonic convergence center lying over An- gola. East-northeast ¯ow from the Indian subcontinent enters eastern Africa in both hemispheres from roughly 10ЊNto10ЊS. An easterly ¯ow enters southern Africa from the Indian Ocean anticyclone. At 300 hPa (Fig. 3c) the mean streamline ¯ow across equatorial Africa is easterly, anchored by two time-averaged anticyclones, one over and the horn of Africa at 10Њ±15ЊN, and another over Angola and Namibia near 18Њ±20ЊS. A jet maximum (Fig. 3d) occurs over northern Africa and Saudi Arabia, to the north of the Somali high, as well as off South Africa's southern tip, in the South Atlantic and Indian Oceans, south of the Namibia high. FIG. 2. (a) Mean austral summer (DJF) southern Africa precipi- The 300-hPa equatorial easterlies, occurring between tation 1900±98, derived from Hulme's (1992) gridded 2.3Њϫ3.75Њ Ϫ1 precipitation dataset. Data are missing in this dataset over the D.R.C. the anticyclones, are relatively weak (5±10 m s ) but and Angola. Isohyets are labeled in centimeters. (b) The predominant cover much of southern Africa between 0Њ and 20ЊS. near-surface air¯ow (arrows) and convergence zones (dashed lines) over southeastern Africa (after Torrance 1972). 4. Data analysis a. Rainfall±NAO correlations The third airstream is a westerly current, originating over the South Atlantic and moving eastward to con- Correlations between seasonal (DJF) NAOI values verge with the two easterly currents. The north±south- and rainfall totals at individual African stations were oriented boundary formed between the westerly and obtained for the period of record. A cluster of stations easterly currents often extends northward and links the (Fig. 4) exhibit negative, highly signi®cant precipitation intertropical convergence zones of both hemispheres correlations to the NAOI over eastern Africa as far north (see, e.g., Fig. 2 in Nicholson 1996). The westerly air- as and includes the central African rift valley, stream is advected across the Congo basin and D.R.C. Lake Victoria, (formerly Lake Nyasa), and

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FIG. 3. Streamlines of the DJF climatological mean air¯ow along the (a) 1000-hPa, (b) 850-hPa, and (c) 300-hPa geopotential height surfaces; (d) the 300-hPa u-component zonal mean wind speed (m sϪ1) based on the 1958±95 NCEP±NCAR reanalyses. The 300-hPa wind speeds have 5 m sϪ1 isotachs with easterly winds labeled as dashed lines.

Lake Tanganyika (Fig. 1). The standardized regional The SEAR index time series is depicted in Fig. 5a. SEAR precipitation index was created using the 31 The multiplication product of the normalized NAO and Southern Hemisphere meteorological stations, between SEAR index departures is plotted over the period of 0Њ±16ЊS and 25Њ±40ЊE (Fig. 4 and Table 1), covering record (Fig. 5b). With the exception of the relatively portions of the D.R.C., Uganda, Rwanda, Burundi, Ken- large positive contribution in 1899, the period to 1923 ya, Tanzania, Mozambique, Zambia, and Malawi (Fig. is dominated by a mix of negative and positive covari- 4). It was decided at the outset that the stations com- ances. The covariances consist primarily of smaller neg- posing the index should solely lie within the high-sun ative values from 1924 to 1960. The NAOI±SEAR cor- hemisphere and facilitate comparison to Janowiak's relation is r ϭϪ0.28 from 1898±99 to 1922±23 and r

(1988) DJFMn region. Correlations using Hulme's ϭϪ0.42 for 1923±24 to 1959±60. During 1958±59 to (1992) gridded precipitation (Fig. 4b) verify the exis- 1989±90, the span of the reanalysis dataset, large neg- tence of a regional NAO signal. The most signi®cant ative covariances occur in several summers and the gridded correlation (Fig. 4b) occurs around the equator NAOI±SEAR correlation is r ϭϪ0.70. An inverse re- in the area of greatest concentration of stations with lationship between the NAO phase and southeastern Af- signi®cant NAO±rainfall correlation (Fig. 4a) in Tan- rican rainfall clearly occurs throughout the twentieth zania, Kenya, and Uganda. NAO/rainfall coef®cients are century, albeit with varying intensity and signi®cance statistically signi®cant somewhat farther to the north- but having an overall NAOI±SEAR r ϭϪ0.48, signif- west in the gridded set (Fig. 4b), compared to Fig. 4a, icant with 99.9% con®dence. The Hulme data were used and they diminish substantially in areas south of Tan- to form a separate precipitation index for the area over zania where stations with signi®cant NAO±rainfall re- the SEAR region (from the equator to 16ЊS, 25Њ±40ЊE). lationships (Fig. 4a) are more widely scattered. This grid-based index and was found to be signi®cantly

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TABLE 1. Names and locations of meteorological stations having DJF precipitation signi®cantly correlated to the NAOI. Station Name Lat Long r Naivasha Ϫ0.40 36.30 Ϫ0.43* Narok Ϫ1.13 35.83 Ϫ0.28* Machakos Ϫ1.50 37.20 Ϫ0.24* Ngara Ϫ2.40 30.60 Ϫ0.54** Musoma Ϫ1.50 33.80 Ϫ0.34* Tarime Ϫ1.40 34.40 Ϫ0.38* Ushirombo Mission Ϫ3.50 32.00 Ϫ0.61* Ngudu Ϫ2.90 33.30 Ϫ0.37* Dongobesh Mission Ϫ4.10 35.40 Ϫ0.42* Monduli Ϫ3.30 36.50 Ϫ0.51* Kibondo Mission Ϫ3.60 30.70 Ϫ0.42* Tabora Airport Ϫ5.08 32.83 Ϫ0.23* Mazumbai Estate Ϫ4.80 38.50 Ϫ0.42* Ambangulu Estate Ϫ5.10 38.40 Ϫ0.43* Ngomeni Ϫ5.20 38.90 Ϫ0.58** Manyoni, D.O. Ϫ5.70 34.80 Ϫ0.29* Mpwapwa Vet. Off. Ϫ6.30 36.50 Ϫ0.32* Singida, D.O. Ϫ4.80 34.80 Ϫ0.27* Kilosa Agric. Off. Ϫ6.80 37.00 Ϫ0.28* Mahenge Ϫ8.60 36.70 Ϫ0.31* Kabale Ϫ1.25 29.98 Ϫ0.37* Tshibinda Ϫ2.30 28.70 Ϫ0.61* Ankoro Ϫ6.70 26.90 Ϫ0.49* Rulindo Ϫ1.70 29.90 Ϫ0.50* Quelimane Ϫ17.88 36.88 Ϫ0.28* Shiwa Ngandu Ϫ11.10 31.70 Ϫ0.13* Kasempa Ϫ13.53 25.85 Ϫ0.27* Mpongwe Mission Ϫ13.50 28.20 Ϫ0.29* Kabwe Ϫ14.45 28.47 Ϫ0.27* Michinji Boma Ϫ13.80 32.90 Ϫ0.27* Mount Darwin Ϫ16.78 31.58 Ϫ0.21*

* Signi®cance at the 95% con®dence level. ** Signi®cance at the 99% con®dence level.

variances at 7.6 yr and 3.25 yr were found to be sta- tistically signi®cant at the 95% con®dence level using the chi-square tests suggested in Mitchell et al. (1966). The 5.5- and 3.25-yr spectral peaks are comparable to those known to dominate rainfall over southern and east- ern Africa (Tyson 1986; Nicholson and Entekhabi 1986, 1987). The large signi®cant SEAR index peak at 7.6 yr falls within a band of key periodicites often associated with the NAOI spectrum. For example, the normalized Azores±Iceland NAO index (Rogers 1984) was found FIG. 4. (a) Locations of GHCN stations that have signi®cant neg- ative correlation between their summer rainfall and the NAOI. (b) to exhibit a statistically signi®cant 7.3±8.0-yr period- Coef®cients of correlation between the NAO index and gridded rain- icity (1895±1983 data). Loewe and Koslowlski (1998) fall from Hulme's (1992) dataset. Shaded areas indicate the 95% and ®nd a signi®cant 7.8-yr periodicity in the NAOI over 99% signi®cant levels. the period 1879±1992. Hurrell and van Loon (1997) found a broad band of nonsigni®cant spectral variances in the 6±10-yr range in a Lisbon±Iceland index spanning correlated to the NAO index at r ϭϪ0.35, signi®cant 1865±1994, noting that the 6±10-yr band has largely with 99% con®dence, over the period of record 1900± emerged in the variance spectrum during this century. 98. This correlation is slightly lower than, but consistent The cospectrum of the negatively correlated SEAR with, the overall r ϭϪ0.48 NAOI±SEAR coef®cient and NAO indices (Fig. 6b) evaluates periodicities dom- for the SEAR index. inating the negative covariances (Fig. 5b) contributing Spectrum analysis of the SEAR index (Fig. 6) shows to the correlations. It is similarly characterized by a 7.6- a peak at 7.6 yr with smaller spectral variance peaks yr peak that is supported by high spectral coherence in occurring at about 5.5 yr, and about 3.25 yr. The spectral this NAOI±SEAR wave band (not shown; McHugh

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FIG. 6. (a) Spectrum analysis of the normalized SEAR index time series, 1899±1999 and (b) the cospectrum of the SEAR index and NAOI. The spectral and cospectral estimates are unitless, and the FIG. 5. (a) Time series of the standardized SEAR index and (b) period lengths are indicated along the x axis in years. The red noise the standardized covariances of the NAOI and the SEAR index, 1899± spectral power estimates along the thick line represent the 95% con- 1989. ®dence limit.

1999), indicating a strong link in the covariances of the ef®cients occur over virtually all of Africa, indicating two time series at this periodicity. that pressure is below normal when the index and rain- Regression of precipitable water ®elds onto the SEAR fall anomalies are positive, and are statistically signif- index (Fig. 7a) produces signi®cant positive coef®cients icant across northern Africa and the Mediterranean ba- over much of southeastern Africa as well as over the sin. Conversely, nearly all of Africa exhibits positive western Indian Ocean and northern . The coef®cients (Fig. 8b) when the NAOI is regressed onto SEAR index is also associated with above-normal pre- SLP, indicating the NAOI is positive when southeastern cipitable water in other locales known to have above- Africa has above-normal pressure and below-normal normal rainfall during the negative NAO phase, includ- rainfall over the 32 winters. The slope of the SEAR ing northwestern Africa and Morocco (Lamb and Pep- index SLP regression coef®cients (Fig. 8a) are not lo- pler 1987), the eastern Mediterranean basin and the Mid- cally statistically signi®cant over southeastern African dle East (Cullen and deMenocal 2000). A signi®cant while those of the NAOI (Fig. 8b) have weak statistical area of regression coef®cients is also obtained around signi®cance (95%) over eastern Africa from Ethiopia to Lake Malawi by regression onto the NAOI (Fig. 7b). South Africa, along with a statistically more robust The robustness of the statistical signi®cance increases NAO dipole in the northern Atlantic. over the Mediterranean basin in Fig. 7b but is smaller The SEAR coef®cients (Fig. 8a) indicate that SLP is over southeastern Africa than in Fig. 7a. lower (higher) over southern Africa than it is over the South Atlantic Ocean during the austral summers with above- (below) normal rainfall. Interpretation of the co- b. Regression analysis of rainfall-circulation ®elds ef®cients must be performed with caution due to lack over southeastern Africa of local statistical signi®cance but they suggest an The SEAR index is regressed onto the NCEP±NCAR anomalous westerly (easterly) ¯ow from (toward) the SLPs over Africa and environs (Fig. 8a). Negative co- South Atlantic Ocean during wet (dry) southeast African

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FIG. 8. Sea level pressure standardized regression coef®cients as- sociated with the (a) SEAR index, 1958±59 through 1989±90, and (b) NAOI, 1958±59 through 1995±96. Contour intervals are 0.1, and negative isolines are broken. Light and darker shading represent sta- tistical signi®cance at the 95% and 99% con®dence intervals. FIG. 7. Precipitable water standardized regression coef®cients as- sociated with the (a) SEAR index, 1958±59 through 1989±90, and (b) NAOI, 1958±59 through 1995±96. The contour interval is 0.1, erlies and the trades still occur on the mean charts, but and negative isolines are broken. Light and darker shading represent they are anomalously weak. A similar interpretation is statistical signi®cance at the 95% and 99% con®dence intervals. applied to wind ¯ow around southern Africa where an anomalous westerly ¯ow component occurs across much of tropical Africa on both sides of the equator summers. This weak continental-scale onshore-¯ow pat- between 20ЊN and 20ЊS when southeast African rainfall tern is also apparent in the NAOI ®elds (Fig. 8b) where, is unusually high. Much of southern Africa in this region although southern Africa coef®cients are the same sign experiences anomalous statistically signi®cant north- as those over the South Atlantic, they are larger, again westerly ¯ow during wet summers (Fig. 9a) converging implying weak anomalous ¯ow toward (from) the con- into cyclonic centers over South Africa near 20ЊS and tinent during the negative (positive) NAO phases. the Indian Ocean. Northeasterly summer monsoonal The 850-hPa streamlines (Fig. 9a) indicate that the ¯ow in , appears to be neither strengthened SEAR index is signi®cantly associated with an anom- nor weakened since the anomalous ¯ow represented in alous easterly component to the North Atlantic west- Fig. 9a is neither southwesterly nor northeasterly over erlies and an anomalous westerly component to the the SEAR area. Although streamlines over southern Af- trades over northwestern Africa and the subtropical rica are not signi®cant, the anomalous 850-hPa u-com- North Atlantic Ocean. Both the North Atlantic west- ponent ¯ow composing the streamlines (not shown) is

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FIG. 9. The 850-hPa streamlines associated with the (a) SEAR index FIG. 10. Same as Fig. 9 but for the 300-hPa level for (a) the SEAR and (b) NAOI. Light and dark shading represent the statistical sig- index and (b) NAOI. ni®cance of the average u- and ␷-component wind coef®cients having t scores at the 95% and 99% con®dence levels, respectively. curs with a simultaneous weakening of both 300-hPa anticyclones over Somalia (Northern Hemisphere) and by itself statistically signi®cant over Congo south of the Namibia (Southern Hemisphere; see Fig. 3c) that nor- equator, as well as over parts of Tanzania in eastern mally produce easterlies over equatorial Africa. Com- Africa. posites made during extreme high and low SEAR events The 850-hPa streamlines obtained from regression on (not shown) indicate that 300-hPa easterlies are weak- the NAOI represent the positive NAO phase when ened, but not replaced, by westerly ¯ow. An anomalous southeastern Africa rainfall is below normal (Fig. 9b). cyclonic circulation (Fig. 10a), centered over the Red The NAO-based 850-hPa (Fig. 9b) ®eld suggests a weak Sea, north of the Somalia anticyclone's normal position, nonsigni®cant anomalous southeasterly ¯ow from the produces a signi®cant southwesterly component to the Indian Ocean occurring over much of the SEAR area ¯ow from Lake Victoria along the horn of eastern Af- between the equator and 16ЊS. The weak ¯ow of Fig. rica. The anomalous southerly ¯ow west of the South 9b curls anticyclonically near 10ЊS, 20ЊE and weak Atlantic high turns cyclonically toward the east as it westerly ¯ow is limited to an area around Angola to the enters the continent, producing westerly ¯ow over Af- west. rica south of the equator. Similarly an anomalous mean The 300-hPa streamlines (Fig. 10a) based on regres- cyclonic trough over the Indian Ocean, southeast of the sion with the SEAR index indicate pronounced anom- continent, induces southwesterly ¯ow over much of the alous westerly ¯ow across Africa south of the equator country of South Africa. to roughly 20ЊS. The high rainfall, westerly phase, oc- NAOI regression onto the 300-hPa ¯ow (Fig. 10b)

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tropical jet wind maximum at 30ЊN over northwestern Africa and the Mediterranean basin is also enhanced (Fig. 11a) during the anomalously wet westerly wind periods in southeastern Africa and equatorial Africa. A similar, but statistically more robust pattern, occurs in conjunction with the NAOI regression (Fig. 11b), show- ing high consistency in the inverse relationship between the two ®elds across the globe, including equatorial Af- rica.

5. Discussion It is long known that westerly air¯ow into equatorial Africa brings rainfall (e.g., Torrance 1972; Nicholson 1996). The primary interaction taking place in the var- iability of the SEAR index and the NAOI in southeastern Africa appears to be between the westerly ¯ow from the Atlantic and the southeast trades off the Indian Ocean, with little change occurring in the northeast monsoon trades, seasonally prevailing in the back- ground. Rainfall over southeastern Africa is shown to be driven by an anomalous westerly current that occurs over large portions of the continent south of the equator, and at all levels of the troposphere. Dry conditions over southeastern Africa prevail in the southeast trade ¯ow. While the westerly ¯ow is moist and has an element of orographic uplift as it moves east, there is also a con- tribution to the uplift by the vertical component of the Coriolis parameter which, in a deep layer of westerly ¯ow near the equator, can help induce uplift and insta- bility in a neutral or weakly stable environment. The FIG. 11. 300-hPa u-component wind velocity standardized regres- anomalous 300-hPa ¯ow exhibits pronounced dif¯uence sion coef®cients associated with (a) the SEAR index and (b) the NAOI. Negative isolines are broken, the contour interval is 0.1, and around and east of Lakes Malawi and Tanganyika during negative isolines are broken. Lighter and darker shading represent rainy summers (Fig. 10a) while con¯uence occurs in statistical signi®cance at the 95% and 99% con®dence intervals. dry summers (Fig. 10b). A southeasterly 850-hPa trade ¯ow moving equatorward across the SEAR region un- dergoes divergence, encouraging subsidence (Fig. 9b) produces features similar to those of Fig. 10a. An en- during dry summers. hanced Red Sea anticyclonic circulation center occurs The sign of the SEAR rainfall anomaly is closely about 10Њ farther north of its mean position in the 300- linked to that of northwestern Africa and Morocco by hPa climatology (Fig. 3c). A 300-hPa anticyclone over the NAO. A statistically signi®cant response over north- Angola±Namibia, located about 3Њ±5Њ north of its nor- western Africa occurs in the pressure (Fig. 8), geopo- mal location, adds a southeasterly component to the ¯ow tential height (Figs. 9, 10), and 300-hPa zonal wind over much of southeastern Africa. Unusually strong up- ®elds (Fig. 11), as well as in the precipitable water ®elds per-tropospheric northeasterly ¯ow over the northwest- (Figs. 7a,b) during the SEAR index extremes. In es- ern Indian Ocean occurs over Tanzania in the northern sence, the pressure/height anomaly over northwestern SEAR region. The remainder of the SEAR region west Africa tends to be the same sign as that occurring over of Lake Tanganyika lies under the southeasterly ¯ow southeastern Africa although different synoptic mech- and is comparatively dry in the positive NAO mode anisms occur to create the rainfall anomaly similarities. represented by Fig. 10b. The linkage between the NAO and southeastern Af- A statistically signi®cant positive link exists between rica has been especially strong since 1958, the period 300-hPa zonal winds and summer SEAR index values during which the reanalysis data are evaluated. This (Fig. 11a). Overall, the equatorial African band of sta- suggests that some low-frequency change in the NAO± tistically signi®cant zonal wind coef®cients is part of a SEAR relationship may be occurring. One possible sequence of ®ve zonally oriented bands of alternating mechanism may be through the long-term east±west sign extending southeastward from the North American changes in North Atlantic centers of action. Studies by Arctic and Greenland, and is one of three representing both Hurrell (1995) and Rogers (1997) indicate a ten- an unusually strong westerly ¯ow component. The sub- dency in recent decades for an eastward migration and

Unauthenticated | Downloaded 09/24/21 05:23 AM UTC 1SEPTEMBER 2001 MCHUGH AND ROGERS 3641 intensi®cation of both the Atlantic storm track and the 6. Summary subtropical anticyclone. It may be possible that the east- ward migration of these pressure features in recent de- The purpose of this paper is to show an association cades, especially the subtropical anticyclone, has helped between the NAO and rainfall variability over south- sharpen the NAO's climatic impact on regions farther eastern Africa. The NAOI is signi®cantly correlated to east and south, with the NAO producing a weakly sig- austral summer rainfall variability over 31 stations in ni®cant response in the southeastern Africa SLP ®elds. southeastern Africa in 0Њ±16ЊS and 25Њ±40ЊE. These The best NAO±SEAR link appears to be in the upper stations south of the equator are used to form a seasonal troposphere (Figs. 10 and 11) wherein southeastern Af- standardized rainfall (SEAR) index. The SEAR index rica appears to be the most equatorward link in a sta- has negative coef®cients of correlation with the NAOI tistically signi®cantly alternating chain of zonal wind through the twentieth century with an r ϭϪ0.70 during anomaly cells extending southeastward from the north the period 1958±89. It has signi®cant spectral variance Atlantic Arctic. It appears that since 1958, at least, the near 7.6 yr, a periodicity often linked to the NAOI, and NAO strength and phase has a signi®cant impact on the NAOI±SEAR cospectrum estimate at 7.6 yr is very high-level zonal winds all the way to the African equa- large with high coherence. tor. The most coherent linkage between the North Atlantic The question of whether the ITCZ moves north or circulation and southeastern Africa rainfall occurs at 300 south in response to the NAO is of some interest. The hPa. NAO variability is linked to ®ve highly signi®cant premise of this study is that stations between the equator elongated 300-hPa bands of alternating zonal wind and 16ЊS, a region extending to the ITCZ's normal lo- strength (Fig. 11b) occurring from the North Atlantic cation, generally tend to vary uniformly in rainfall Arctic to equatorial Africa. The southernmost band pro- anomaly and are in¯uenced by the NAO phase and in- duces an anomalous westerly current over equatorial tensity. It is noteworthy that just to the south, rainfall Africa during wet summers when the NAO is negative, variability is also regionally coherent and in¯uenced and the prevailing drier easterly equatorial 300-hPa cur- signi®cantly by ENSO during summer (DJF) months rent is strengthened when the NAO is positive. The (Ropelewski and Halpert 1987; 1996). The rainfall equatorial Africa westerly air¯ow anomaly is inversely anomalies in these two regions of eastern Africa south related to the NAOI. The anomalous current, which ex- of the equator are also out-of-phase (Nicholson 1986; tends down to the 850-hPa level albeit with lower sta- Janowiak 1988) contributing to potential ITCZ move- tistical signi®cance, is laden with moisture from the ment. Janowiak's (1988) analysis indicates that the rain- tropical South Atlantic. It undergoes orographic uplift fall anomalies of each region are part of two different across southeast Africa and is potentially subject to a rotated principal components; that is, they do not form destabilizing contribution generated by the vertical com- a dipole, varying together as part of one principal com- ponent of the Coriolis parameter. The westerly current ponent. The ®rst component is that over southernmost undergoes 300-hPa divergence over southeastern Africa Africa (linked to ENSO) while the rainfall in south- during wet summers; dry summers are characterized by eastern Africa (linked to the NAO) is a separate second a convergent 300-hPa easterly ¯ow. component. The NAOI and southern oscillation index Regression analysis shows that the NAOI is signi®- (SOI) are furthermore weakly correlated. The simulta- cantly related to the precipitable water content over por- neous DJF correlation over 1921±90 is r ϭϩ0.23 be- tions of southeastern Africa in a manner suggesting that tween the NAOI and the Tahiti±Darwin SOI. The NAO heavier, convective, rainfall occurs during the negative and southern oscillation (SO) indices have the same NAO phase, when the North Atlantic westerlies are un- departure sign in 47 of these 70 winters. (The major usually weak. Sea level pressure over virtually all of 1982/83 El NinÄo winter was the biggest exception, Africa is below (above) normal when the Atlantic west- among 23; removing it from the dataset improves the erlies are unusually weak (strong), although the statis- NAOI±SOI to a signi®cant r ϭϩ0.32.) The positive tical signi®cance of this relation is strongest over north- NAOI±SOI winter correlation implies the following: western Africa and is weaker over southeastern Africa. when the NAO is negative (positive), rainfall over Southeastern Africa experiences anomalous southeast- southeastern Africa is unusually high (low), and the SOI erly ¯ow off the Indian Ocean during dry summers. The will tend to be negative (positive), the SO phase as- seasonally prevalent northeast trades do not appear to sociated with below- (above) normal rainfall over of vary signi®cantly between summers with rainfall ex- South Africa and nearby countries. Thus out-of-phase tremes in southeastern Africa. rainfall variability can occur simply because the NAO Our analysis agrees with that of Janowiak (1988) that and SO circulation patterns are acting in close proximity rainfall variability between 0Њ and 16ЊS in eastern Africa over adjacent areas of eastern Africa south of the equa- is relatively coherent. We ®nd this area to be linked with tor, and each center of coherent summer rainfall vari- NAO variability whereas those immediately to the ability in eastern Africa south of the equator (Janowiak south, including South Africa, are long known to be 1988) has a different atmospheric teleconnection linked in¯uenced by ENSO. The issue of whether the NAO to its variability. has an impact of the latitudinal position of the ITCZ

Unauthenticated | Downloaded 09/24/21 05:23 AM UTC 3642 JOURNAL OF CLIMATE VOLUME 14 might be further resolved by examining regional inter- Spectral characteristics and associations with the NAO, QBO, actions between the NAO and ENSO. The long-term and solar cycle. Tellus, 50A, 219±241. McClendon, M. J., 1994: Multiple Regression and Causal Analysis. positive correlation between the NAOI and SOI (r ϭ F. E. Peacock, 347 pp. ϩ0.23) implies that unusually high rainfall in the NAO- McHugh, M. J., 1999: Precipitation over southern Africa and global- linked north tends to occur when ENSO-linked south- scale atmospheric circulation during boreal winter. Ph.D. dis- ernmost Africa is anomalously dry, and conversely. Jan- sertation, Ohio State University, Columbus, OH, 230 pp. Meehl, G. A., and H. van Loon, 1979: The seesaw in winter tem- owiak (1988) shows that this does not occur as a co- peratures between Greenland and Northern Europe. Part III: Te- herent rainfall anomaly dipole across eastern Africa leconnections with lower latitudes. Mon. Wea. Rev., 107, 1095± south of the equator; the interactions between weakly 1106. correlated teleconnection patterns likely have an im- Mitchell, J. M., B. Dzerdzeevskii, H. Flohn, W. L. Hofmeyr, H. H. Lamb, K. N. Rao, and C. C. WalleÂn, 1996: Climatic change. portant impact over these adjacent areas in that part of WMO Tech. Note 79, WMO 195TP100, 79 pp. the continent. Nicholson, S. E., 1986: The nature of rainfall variability in Africa south of the equator. J. Climatol., 6, 515±530. Acknowledgments. This work is partly supported by ÐÐ, 1996: A review of climate dynamics and climate variability in Eastern Africa. The Limnology, Climatology and Paleoclima- the NOAA Of®ce of Global Programs±Atlantic Climate tology of the East African Lakes, T. C. Johnson and E. O. Odada, Change Program under Grant NA56GP0213. Eds., Gordon and Breach, 25±56. ÐÐ, and D. 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