OCTOBER 2014 J U R Y 2039

Malawi’s Fluctuations and Climate

MARK R. JURY Physics Department, University of Puerto Rico, Mayaguez,€ Puerto Rico, and University of Zululand, KwaDlangezwa, South Africa

(Manuscript received 20 November 2013, in final form 14 May 2014)

ABSTRACT

Hydrological fluctuations of ’s Shire River and climatic drivers are studied for a range of time and space scales. The annual cycles of basin rainfall and river flow peak in summer and autumn, respectively. Satellite and model products at ,50-km resolution resolve the water deficit in this narrow valley. The leading climate index fitting Shire River flow anomalies is the Climatic Research Unit (CRU) Palmer drought severity index, based on interpolated gauge rainfall minus Penman–Monteith potential evapotranspiration. Climate variables anticipate lake level changes by 2 months, while weather variables anticipate river flow surges by 2 days. Global climate patterns related to wet years include a Pacific La Niña cool phase and low pressure over northeastern Africa. Shire River floods coincide with a cyclonic looping wind pattern that amplifies the equatorial trough and draws monsoon flow from Tanzania. Hot spells are common in spring: daytime surface temperatures can reach 608C causing rapid desiccation. An anticyclonic high pressure cell promotes evapo- 2 ration losses of ;20 mm day 1 over brief periods. Flood and drought in Malawi are shown to be induced by the large-scale atmospheric circulation and rainfall in the surrounding highlands. Hence, early warning sys- tems should consider satellite and radar coverage of the entire basin.

1. Introduction cumulative effect of seasonal wet and dry spells (Servat et al. 1998; Jury and Gwazantini 2002; Kumambala and is located in the African Rift Valley Ervine 2010). Rains are heaviest from December to Feb- (center: 138S, 34.58E) with a basin area of 150 000 km2.The ruary and the lake level crests at ;1mfromMarchtoMay lake is deep (.300 m) with volume of ;8.4 3 109 m3,an (Shela 2010). Evaporation losses are widespread and high area of 29 000 km2, and is 600 km north–south by ;40 km from September to November (Mandeville and Batchelor east–west at an elevation of 474 m. There are four major 1990). The Shire River outflow depends primarily on lake rivers providing inflow to the lake, while the Shire River is levels and secondarily on basin inflow and evaporation the southern outlet extending 400 km from Mangochi (Calder et al. 1995; Kumambala and Ervine 2010). (14.58S) to the Zambezi River. Over the first 130 km, the Lake Malawi level has been monitored for a century river meanders across a plateau dropping only 7 m (by (Sutcliffe and Knott 1987). Changes occur at low fre- 15.48S). Over the next 80 km (to 16.08S), there is a fall of quency due to cumulative imbalances of basin rainfall 370 m offering hydropower yield. Thereafter the Shire and evaporation, and at high frequency due to local air River runs through lowlands, joined by the Ruo River pressure, meridional winds, and storm runoff. The in- (50 m at 16.68S) and onto the confluence with the Zambezi. terdecadal fluctuation of lake level is ;3 m, which is an Lake Malawi level is maintained by annual gains from issue for boat harbors designed for use above 474 m. rainfall (1.3 m) and inflow (0.9 m) against annual losses by Runoff is affected by declining forest cover and conse- evaporation (1.8 m) and outflow to the Shire River (0.4 m) quent sediment accumulation in the floodplain (Palamuleni (Torrance 1972; Kidd 1983; Neuland 1984; Drayton 1984; and Annegarn 2011). A population growth rate of 3% Bootsma et al. 1996). Lake levels are sensitive to the (in 2010) puts pressure on the land; agricultural crops have replaced woodlands, and grasslands are overgrazed Corresponding author address: Mark R. Jury, Physics Department, and sparse. Recent studies have quantified the reduction University of Puerto Rico, Rt. 108, Mayagüez, 00681 Puerto Rico. in forest cover via satellite vegetation fraction. The Shire E-mail: [email protected] River receives outflow from Lake Malawi via Mangochi

DOI: 10.1175/JHM-D-13-0195.1

Ó 2014 American Meteorological Society Unauthenticated | Downloaded 09/28/21 11:50 AM UTC 2040 JOURNAL OF HYDROMETEOROLOGY VOLUME 15 due to topographic slope and water balance. Lake (Novella and Thiaw 2013); the National Centers for En- Malombe intersects the river in the upper catchment, while vironmental Prediction (NCEP) Climate Forecast Sys- farther downstream there is inflow from the Ruo River. tem (CFS); and the European Centre for Medium-Range Lake Malawi outflows to the Shire River are measured Weather Forecasts (ECMWF) reanalysis climate fields at at Mangochi and downstream at intervals of about 30–70-km resolution (Saha et al. 2010; Dee et al. 2011; 2 100km;flowsvaryfrom50to1000m3 s 1, averaging Meng et al. 2012). The data assimilations (GLDAS-Noah, 2 480 m3 s 1 in the upper valley. The hydrology has been NCEP-CFS, and ECMWF) have issues associated with gradually regulated by low barrages and small reservoirs inhomogeneous forcing. For example the precipitation to support hydropower, particularly since 1993. Although used in Noah changes over time, while the CFS exhibits they maintain base flow during spring and amplify lake discontinuities due to changes in satellite inputs. Grimes levels (Sene 1998), the engineering structures are still and Diop (2003) show that basin-averaged satellite cloud overtopped by floods, as seen in the results below. temperature and vegetation fraction are proxies for the The objective of this paper is to study the climatic water balance and can be fitted to daily African stream- drivers of Malawi’s Shire River using direct measure- flow records with good success. ments and model estimates, to analyze the annual to To understand regional climate influences on Mala- decadal variability, to understand the meteorological wi’s Shire River flow, cross correlations were computed forcing of wet and dry spells, and to determine which at various lags as maps and time series, similar to the atmospheric indices best correspond with the hydrology. methods of Glad (2010). For the annual cycle and con- secutive months, the degrees of freedom is 10 and 60, . 2. Data and methods respectively, so 95% significance is achieved at r 0.60 and 0.25. Of many climate indices tested, the PDSI was The southern half of Lake Malawi and Shire River closest to Shire River flow anomalies. Seasonal values of Valley encompass an area 138–178S, 33.58–36.58E(Fig. 1). Shire basin-averaged detrended PDSI were cross cor- Discharge data from the state hydrology service were related with ECMWF reanalysis fields (1957–2001) to obtained and, following quality checks and naturalization understand the global climate forcing at interannual to according to Shela (2010), a single monthly time series decadal time scales. 1953–2012 was reconstructed from the Mangochi record Inspecting the daily flow discharge at Chikwawa, a 2 (19761; 1 refers to the starting year up to 2012) extended threshold of 1200 m3 s 1 was exceeded on 13 occasions. by other gauges (Mbewe 19531 and 19651). For this group of floods, composite weather anomalies Daily values were also obtained at Mangochi and Chik- were calculated from reanalysis and satellite fields, and wawa gauges (19761) to describe flood events. Supple- their structure was examined 2 days before peak flow. menting the in situ hydrological records are National Hot spells were analyzed using MODIS satellite land Aeronautics and Space Administration (NASA) satellite surface temperatures. The warmest case was studied for altimetry of lake level (19921) and gravity measurements local structure and regional weather pattern. of soil water fraction (Tapley et al. 2004; Crétaux et al. 2011; Velpuri et al. 2012) since 2002. Satellite–gauge in- terpolated rainfall observations in the study area (Fig. 1) 3. Results at 50-km resolution derive from the Global Pre- a. Valley climate characteristics cipitation Climatology Centre (GPCC; Schneider et al. 2008, 2014) and the Climatic Research Unit (CRU; Harris Mean rainfall in the Shire Valley during the satellite era 2 et al. 2014). The Palmer drought severity index (PDSI) is is 2–3 mm day 1 corresponding to elevations of 500– used to characterize water budget anomalies, based on 1000 m, respectively (Figs. 1a,b). A tongue of lower rainfall observed precipitation minus Penman–Monteith potential extends up the Shire Valley from the Zambezi River and evapotranspiration (Hargreaves and Samani 1982; Wells its wetlands, while the surrounding Mozambique high- et al. 2004; Dai 2011). Area-averaged latent and sensible lands receive heavier rainfall. Vegetation (Fig. 1c)isrel- heat fluxes and runoff estimated by the Global Land Data atively homogeneous, having a mean annual color fraction Assimilation System (GLDAS) Noah model are em- of 0.3 in the Shire Valley, rising to 0.45 in the mountains ployed (Rodell et al. 2004). Additional datasets include and in the southeastern wetlands. Surface daytime tem- the Moderate Resolution Imaging Spectroradiometer perature (Fig. 1d) exhibits a pattern consistent with rainfall (MODIS) satellite infrared surface temperatures and and elevation with a mean annual value of 388Cinthe vegetation color fraction at 1-km resolution (Huete et al. Shire Valley indicative of high potential evaporation. 2002); African Rainfall Climatology, version 2 (ARCv2) The Shire Valley (138–178S, 33.58–36.58E) climate ex- satellite–gauge merged rainfall at 10-km resolution hibits a pronounced annual cycle (Fig. 2). Rainfall rises

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FIG. 1. Characteristics of the Shire Valley: (a) mean ARCv2 rainfall at 10-km resolution. (b) Topography with place names, white outline is Malawi border. Data is from mean 2002–12 MODIS satellite. (c) Vegetation fraction and (d) daytime surface temperature at 1-km resolution. The dashed box in (a) is the Shire Valley ‘‘local’’ area. 2 above 4 mm day 1 from December to March, generating upper 2.5 percentiles is greatest in February: 2– 2 peak runoff in February. In the May–October dry season, 12 mm day 1. CFS latent heat flux and satellite vegeta- a high pressure prevails over southern Africa and rainfall tion index exhibit a lagged response to rainfall with is absent. The rainfall difference between the lower and maxima in March and minima in October (Fig. 2a).

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FIG. 2. Mean annual cycle of local area (a) rainfall, runoff, latent heat flux, and vegetation; (b) potential evaporation and sensible heat flux; and (c) river flows and lake level. Upper and lower 2.5% averages are given for rainfall and river flow. (d) Correlation of annual cycle between climate indices at 2-month lead and lake level and its outflow (Mangochi); r . 0.6 significant.

Surface water losses in the Shire Valley are characterized until 1997. Heavier rainfall induced a rise up to 2003 and by CRU, version 3 (CRU3), potential evapo-transpiration riverflowshaveoscillatedat;10% above normal 2 2 (Fig. 2b) and exhibit values near 3 mm day 1 from January (480 m3 s 1) since then. The wavelet spectrum of river to July. From September to November evaporation ex- flow annual cycle (Fig. 3b) indicates high amplitude in 2 ceeds 5 mm day 1, so the rainy season starts with a surface 1953–65, 1976–78, and 1987–89, and low amplitude in water deficit. Sensible heat flux from Noah and CFS 1966–72 and 1992–96. Annual cycling was again prom- models follow the potential evapo-transpiration, while the inent in the recent decade. latent heat flux follows vegetation (February peak; Fig. 2a) Filtering the annual cycle, river flow anomalies (Fig. 2 and stays below 3.5 mm day 1. 3c) display oscillations that are in phase with the 12- River flows averaged over three gauges are compared month lagged sum of PDSI. There is good correspon- with lake levels in Fig. 2c. The mean annual cycle of dis- dence except when the PDSI anticipates flow decline in 2 charge peaks at 650 m3 s 1 in April, 2 months after runoff 1978–84 and rise in 1997–98. A puzzling feature is that and 1 month before lake level. Flows gradually decline to the PDSI has a downtrend (more evaporation) while the a minimum in November. Correlations between the mean river flow has an uptrend (possibly sedimentation). The annual cycle of climate and 2-month-lagged hydrology wavelet spectrum of flow anomalies (Fig. 3d) indicates indices are illustrated in Fig. 2d. Satellite vegetation and cycling at 6 years in 1953–70 and after 2003, and at 11 CFS latent heat flux exhibit significant positive values, years during 1978–98 with a low-frequency harmonic at while ECMWF/CFS sensible heat flux and CRU3 poten- ;20 years. The 6-yr signal reflects ENSO forcing (Jury tial evapotranspiration exhibit significant negative values. and Mwafulirwa 2002), while the 11-yr signal is linked with decadal fluctuations of global climate. b. Hydrology response to climate The spatial influence of the local climate is evaluated by Our reconstructed Lake Malawi record displays rela- correlating the March–May Shire flow with December– tively stationary seasonal pulses during 1953–74 (Fig. 3a). February gridded rainfall and CFS latent heat flux in The lake level rose to 477 m and river flow increased in the period 1979–2010. This indicates which parts of the 1978–82. Lake level dropped (473 m) following a pro- basin participate in multiannual climate forcing. The longed drought in 1992–95 and river flow diminished GPCC rainfall correlation is .10.4 along 148S from 348

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FIG. 3. (a) Time series of station flows and satellite data. (b) Composite flow anomalies and 12-month sum of PDSI with linear trends. Respective wavelet spectral energy in (c) annual cycle and (d) multiannual fluctuations (period is years, cone of validity indicated by the stepped line). Spectral power is shaded from 90% confidence upward to max value.

to 368E(Fig. 4a) encompassing the southeastern edge of detrended local PDSI in the December–March season Lake Malawi. However, correlations are zero in the (1957–2001). The surface temperature map (Fig. 5a) lower Shire Valley indicating that flow fluctuations are indicates a significant negative correlation in the Malawi primarily driven by the lake water balance. The correla- Shire basin, confirming that lower temperatures co- tion with CFS latent heat flux exceeds rainfall (.10.5) incide with precipitation–evaporation surplus. In the especially in the bordering highlands and upper (north- Pacific, there is a La Niña signal: cool east (r ,20.3) ern) valley (Fig. 4b). warm west (r .10.3) dipole. The Atlantic and Indian Considering lake level and downstream river gauges, the Oceans have mixed temperature signals. Yet there is a local climatic influences are studied by correlation in Fig. region of lower pressure (r ,20.3) over northeastern 4c. The cumulative PDSI affects Mangochi flow (r .10.5) Africa that extends to the North Atlantic and eastern and other locations to a lesser extent. Valley rainfall and Indian Ocean (Fig. 5b). Over the eastern Pacific the local runoff have weak negative influence at Mangochi but ECMWF pressure correlation with Shire PDSI is posi- rise to positive correlations at Mbewe downstream. Simi- tive, indicating high pressure associated with La Niña. larly the evaporative losses within the valley have a weak The 850-mb streamfunction reflects the rotational cir- negative influence that grows downstream (,20.4). culation (Fig. 5c) and is locally cyclonic, as expected. Hence, climatic conditions in the Shire Valley affect out- Thus, equatorial westerlies and subtropical easterlies flows to the Zambezi lowlands, while weather around the boost rainfall over Malawi. A key global feature at the southern edge of Lake Malawi drives inflows. Evaluating decadal time scale is opposing correlations in the the lead–lag influence of the basin-averaged monthly northeastern and southeastern Pacific where anticy- PDSI (Fig. 4d), it is evident that river flow lags the seasonal clonic winds prevail. The large-scale thermodynamic inputs (peaks at 3, 14, and 25 months) and cumulative structure and circulation reflecting the low-frequency outputs, similar to Potter et al. (2004) and Glad (2010). component of El Niño–Southern Oscillation (Jury Global climate forcing of basin hydrology is analyzed and Mwafulirwa 2002) influences Shire River flow, as by correlation of the ECMWF reanalysis fields with represented by the PDSI.

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FIG. 4. Correlation of March–May Shire River flow with December–February: (a) GPCC rainfall and (b) CFS latent heat flux; 500-m contour defines river channel. (c) Correlation of climate indices at successive downstream river gauges. (d) Lag correlation of monthly river flow and PDSI; r . 0.25 significant. c. Short-term events day 4. Low-level winds make a clockwise loop over Mozambique (Fig. 6c), joined by northerlies from Tan- Floods are studied using the daily discharge at Man- zania and easterlies from Madagascar. There is a com- gochi and Chikwawa at ;200 km downstream (Fig. 6a). posite high pressure over South Africa causing easterly The two have similar annual cycles up to 1993, where- winds there. The meridional overturning Hadley circu- after the base flow is manipulated for hydroelectric lation is moist and convergent over Malawi (Fig. 6d), 2 yield. Flood events (.1200 m3 s 1) punctuate much of while dry conditions prevail at 08 and 258S. The stream- the 32-yr record at Chikwawa due to valley runoff on top function anomaly is cyclonic in a narrow axis following of lake outflow. Storm features are analyzed as a com- the Zambezi Valley, and a low pressure is situated over posite group (13 cases) two days before peak flow (day Malawionday2(Figs. 6e,f). Station rainfall in some 2 2). Satellite convection [outgoing longwave radiation cases reached 89 mm day 1, and tropical cyclones were (OLR)] appears as a northwest–southeast axis over the prevalent near Madagascar as seen in the following Shire Valley (Fig. 6b), having developed locally since case.

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FIG. 5. Correlation of basin-averaged detrended PDSI in December–March season with global ECMWF: (a) surface temperature, (b) sea level pressure, and (c) 850-mb streamfunction with arrows highlighting rotational winds. Patterns correspond with wet seasons; r . 0.25 significant.

Although discharge at Mangochi is less variable due data during the period 24–31 October 2011. Temperatures to the buffering effects of Lake Malawi, daily surges can of 608C were observed in the central valley and CFS po- 2 2 occur: 141 m3 s 1 on 1 February 2008 (Fig. 7a). The 850-mb tential evaporation rates reached ;20 mm day 1. The heat wind map of 29 January exhibited a pair of cyclones to wave was induced by subsiding air from an anticyclonic the east and west of Malawi, which caused a line of high pressure cell located south of Malawi (Fig. 8b). thunderstorms to move over the lake (Figs. 7b,c). The Satellite soil water fraction declined sharply in November 2 ECMWF reanalysis was consistent with composite sat- 2011, and satellite altimetry recorded a 0.12 m month 1 ellite rainfall, and CFS hourly rainfall exhibited strong drop in Lake Malawi (cf. Fig. 3a). Such dessication diurnal cycling. There was a 2-day response lag, af- is common in the Shire Valley just before the rainy fording ample time for early warning. Yet rural settlers season. often encroach onto floodplains in the dry season, and then become victims when waters rise (Fig. 7d). 4. Discussion and summary Springtime dry spells are characterized by heat waves and dessication. In Fig. 8a, the Shire Valley daytime surface This study has analyzed the drivers of Malawi’s Shire temperatures are mapped from MODIS satellite infrared River flow. Past work on basin water budgets typically

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FIG. 6. (a) Daily discharge at Mangochi and Chikwawa: arrow is transition to manipulated base flow. Composite flood maps of day 2: 2 2 (b) satellite OLR anomaly (W m 2); (c) 850-mb wind (largest vector is 3 m s 1, with vertical motion exaggerated); (d) vertical slice on 358E 2 of humidity (shaded), meridional–vertical motion (largest vector is 3 m s 1, with vertical motion exaggerated); (e) 850-mb streamfunction 2 anomaly (105 m2 s 1); and (f) 850-mb geopotential height anomaly (m). use an equation for delta storage comprising gains from boundary layer, enhancing diurnal convection (cf. Fig. 7a). precipitation and inflow, losses from evaporation and out- Surface water losses are characterized by potential evapo- 2 flow, and time integration for volumetric response. Here transpiration (;1.4 m yr 1) and sensible heat flux, which the basin rainfall, lake level, and outflow are known. Actual correlate negatively with river flow (cf. Figs. 2b,d). evaporation as represented by latent heat flux has a value A statistical analysis of relationships between climate 2 of ;0.7 m yr 1 and correlates positively with river flow (cf. and hydrology at various time and space scales yielded a Figs. 2d and 4b). Latent heat flux moistens the atmospheric number of findings:

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FIG. 7. (a) Daily delta flow at Mangochi compared with area rainfall, (b) satellite rainfall 2 (mm h 1) on 29 Jan 2008, and (c) 850-mb winds. (d) Flooded homesteads along the Shire River.

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FIG. 8. (a) Daytime land surface temperatures during the period 24–31 Oct 2011 from MODIS satellite, and (b) corresponding 700-mb winds from NCEP-CFS reanalysis. d Direct measurements of lake level and river flow help surrounding highlands, then a narrow focus on Shire quantify climatic terms in the water budget at seasonal Valley impacts will not support early warning. Moni- to multiannual time scales. toring by satellite and radar is needed. Weather forecast d Modern satellite and model reanalysis products at accuracy could improve with transmission of Aircraft 50-km resolution have the ability to resolve hydrolog- Meteorological Data Relay (AMDAR) profiles from ical fluctuations in the African Rift Valley. regional airports. Further progress will require a re- d The leading climate index fitting Shire River flow is the sumption of daily Shire River flow gauging and timely CRU self-calibrating Palmer drought severity index, reporting to international centers for operational data based on interpolated gauge rainfall minus Penman– assimilation. Further research could include an analysis Monteith-calculated potential evapotranspiration. of climate change using phase 5 of the Coupled Model d Global climate variables anticipate lake level changes Intercomparison Project (CMIP5) projections. It is be- by 2 months. Regional weather variables anticipate lieved that the Shire River has reached its limit of ma- river flow surges by 2 days. nipulation and abstraction. Soil conservation is needed d Global climate patterns related to local precipitation– to control sedimentation and keep the growing rural evaporation surplus include an eastern Pacific cool population on a sustainable socioeconomic path. phase La Niña, low pressure over northeastern Africa, and rotational winds. Acknowledgments. The author thanks L. Palamuleni d Shire River floods coincide with a cyclonic looping of Northwest University, South Africa, and M. Kleynhans wind pattern that amplifies the equatorial trough and of Aurecon, South Africa, for provision of daily Shire draws monsoon flow from Tanzania. In some cases River flow and station rainfall. Satellite and model in- there is a tropical cyclone near Madagascar. terpolated data were analyzed from the Climate Ex- d Hot dry spells are a recurring feature of spring: daytime plorer, IRI Climate Library, NASA Giovanni, JPL-UC surface temperatures reach 608C causing rapid desic- Grace, and USDA altimetry websites. cation. The anticyclonic high pressure cell and its 2 subsidence lead to evaporation losses .10 mm day 1 REFERENCES over brief periods. Bootsma, H. A., M. J. Bootsma, and R. E. Hecky, 1996: The If flood and drought in Malawi are induced by the chemical composition of precipitation and its significance to large-scale atmospheric circulation and rainfall in the the nutrient budget of Lake Malawi. The Limnology, Climatology

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