Generated using version 3.2 of the official AMS LATEX template

The Annual Cycle of East African Precipitation1

Wenchang Yang ∗ Richard Seager and Mark A. Cane

Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, USA

2

Bradfield Lyon

International Research Institute for Climate and Society

Lamont-Doherty Earth Observatory, Earth Institute at Columbia University, Palisades, New York, USA.

3

∗Corresponding author address: Wenchang Yang, Lamont-Doherty Earth Observatory, Columbia Univer-

sity, 61 Route 9W, Palisades, NY 10964.

E-mail: wyang@ldeo.columbia.edu

1

ABSTRACT4

East African precipitation is characterized by a dry annual mean climatology compared to5

other deep tropical land areas and a bimodal annual cycle with the major rainy season during6

March–May (MAM, often called the “long rains”) and the second during October–December7

(OND, often called the “short rains”). To explore these distinctive features, we use the ERA-8

Interim Re-Analysis data to analyze the associated annual cycles of atmospheric convective9

stability, circulation and moisture budget. The atmosphere over East Africa is found to10

be convectively stable in general year-round but with an annual cycle dominated by the11

surface moist static energy (MSE), which is in phase with the precipitation annual cycle.12

Throughout the year, the atmospheric circulation is dominated by a pattern of convergence13

near the surface, divergence in the lower troposphere and convergence again at upper levels.14

Consistently, the convergence of the vertically integrated moisture flux is mostly negative15

across the year, but becomes weakly positive in the two rainy seasons. It is suggested the16

semi-arid/arid climate in East Africa and its bimodal precipitation annual cycle can be17

explained by the ventilation mechanism, in which the atmospheric convective stability over18

East Africa is controlled by the import of low MSE air from the relatively cool Indian Ocean19

off the coast. During the rainy seasons, however, the off-coast sea surface temperature (SST)20

increases (and is warmest during the long rains season) and consequently the air imported21

into East Africa becomes less stable. This analysis may be used to aid in understanding22

overestimates of the East African short rains commonly found in coupled models.23

1

1. Introduction24

East Africa has experienced an increased frequency of droughts in recent years, primarily25

due to the decline of rainfall during the March–May (MAM) “long rains”, threatening the26

lives of millions of people in this hydrologically and politically vulnerable region (FEWS27

NET 2011; Lyon and DeWitt 2012). Various mechanisms have been proposed for this long28

rains drying trend. Williams and Funk (2011) related it to the westward extension of the29

Indo-Pacific warm pool and associated Walker circulation while Lyon and DeWitt (2012)30

and Lyon et al. (2013) linked it to a shift of sea surface temperature (SST) over the Pacific31

basin to a La Nina-like pattern, occurring around 1998-99. A recent study (Yang et al.32

2014) demonstrated that the East African long rains exhibit variability on decadal or longer33

time scales with the recent drying trend very likely part of this Pacific-centered decadal34

variability, although droughts in recent years are somewhat unprecedented in terms of their35

severity over the past century.36

Given the recent decline of the long rains, people are inevitably wondering what will37

happen in the next few decades, particularly as the climate warms due to continued an-38

thropogenic emissions of greenhouse gases (GHGs). There is a strong consensus in model39

projections from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assess-40

ment Report (AR4) and the more recent Coupled Model Intercomparison Project Phase 541

(CMIP5, Taylor et al. (2012)) that the pattern of precipitation minus evaporation (P − E)42

will be enhanced in the warming climate (Held and Soden 2006; Seager et al. 2010; Laıne43

et al. 2014), which implies that the East African long rains will increase as they are part of44

the Intertropical Convergence Zone (ITCZ). This implies a recovery from recent dry condi-45

tions, at least in part, in the coming decades. Indeed, this is the case in the CMIP5 model46

projections as shown in Fig. 2b of Yang et al. (2014). However, some studies using high-47

resolution regional climate models forced by ensemble-mean global climate model (GCM)48

projections on the lateral and ocean boundaries indicate a reduction in the long rains (Vizy49

and Cook 2012; Cook and Vizy 2013), leaving the long rains projections more uncertain.50

2

While GCMs display some consistency in their projections of East African precipitation,51

the models’ capabilities in simulating the observed climatology and temporal variability52

are less clear. By examining the performance of both SST-forced models and the coupled53

models used in the CMIP5 historical experiment in simulating the East African long rains,54

Yang et al. (2014) showed that, while some of the SST-forced models are able to capture55

the observed decadal variability of the long rains, the coupled models, which are used for56

the 21st century climate projections, generally fail to capture the correct long rains-SST57

relationship. Moreover, the coupled models misrepresent the East African precipitation58

annual cycle by overestimating rainfall during the October–December (OND) “short rains”,59

as was also reported for the CMIP3 coupled models (Anyah and Qiu 2012).60

To understand the discrepancy between the model simulations and observations, we first61

need to better understand the observed East African precipitation climatological annual62

cycle. This has drawn little attention in the past compared to inter-annual variability but63

is a very important issue and the motivation of this study. It is also of interest to explain64

why East Africa is semi-arid and the character of its bimodal annual cycle of precipitation.65

In this paper, we investigate the atmospheric thermal condition, circulation, and moisture66

budget associated with the annual cycle of precipitation in this region and try to address67

the following questions: why is deep-tropical East Africa largely semi-arid/arid in terms of68

annual mean rainfall (Trewartha 1961; Nicholson 1996)? Why are there two rainy seasons?69

What atmospheric environment conditions set the difference between the rainy seasons and70

the dry seasons? What explains the difference between the two rainy seasons? Why are71

the long rains stronger than the short rains? The remainder of this paper is organized72

as follows: Section 2 describes the data used in the study; Section 3 briefly reviews the73

observed precipitation and topography in East Africa; analyses of the atmospheric thermal74

condition, atmospheric circulation and moisture budget are presented in Sections 4, 5 and75

6, respectively; the main conclusions of the paper and associated discussion are provided in76

Section 7.77

3

2. Data78

For precipitation, we use version 6 of Global Precipitation Climatology Centre (GPCC)79

monthly precipitation (Rudolf et al. 2010), which is a gauge-based, 0.50 longitude × 0.5080

latitude gridded global land surface dataset for the period 1901–2010 available from http://81

iridl.ldeo.columbia.edu/expert/SOURCES/.WCRP/.GCOS/.GPCC/.FDP/.version6/.0p5/82

.prcp/. For comparison, we also use version 2.2 of the Global Precipitation Climatology83

Project (GPCP) monthly precipitation dataset from 1979 to 2010 (Huffman et al. 2009),84

which combines gauge observations and satellite data into 2.50 longitude × 2.50 latitude85

global grids and is available from http://iridl.ldeo.columbia.edu/expert/SOURCES/86

.NASA/.GPCP/.V2p2/.satellite-gauge/.prcp/. The observed sea surface temperature87

(SST) is from version 3b of the NOAA National Climate Data Center (NCDC) Extended88

Reconstructed Sea Surface Temperature (ERSST) (Smith et al. 2008), which is a globally89

gridded monthly dataset with a spatial resolution of 20 longitude × 20 latitude from 185490

to the present and available from http://iridl.ldeo.columbia.edu/expert/SOURCES/91

.NOAA/.NCDC/.ERSST/.version3b/.sst/.92

To estimate the thermal condition, circulation and moisture budget, we use the European93

Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim)94

(Dee et al. 2011), which covers the post-1979 period and is the latest of the ECMWF re-95

analyses. ERA-Interim is generally considered to be improved in many aspects compared96

to its precursor, the 40-yr ECMWF Re-Analysis (ERA-40) (Berrisford et al. 2011). In this97

paper, all seasonal climatologies and annual cycles are computed based on a 1979–2009 base98

period with the seasons defined as: winter dry season(January–February, or JF); the long99

rains season (MAM), the summer dry season (June–September, or JJAS) and the short rains100

season (OND). These definitions follow the largely bimodal precipitation annual cycle found101

over much of this region.102

4

3. Precipitation and topography103

The uniqueness of East African precipitation can be seen from Fig. 1. While most tropical104

lands have a wet annual climatology, East Africa is largely dry with precipitation less than 2105

mm day−1 (Fig. 1a). Some regions (including the western and eastern coastal areas of South106

America between 00 and 120S and the northern African interior around 100N) also have a107

precipitation climatology less than 2 mm day−1, but the area is not comparable in scale108

with East Africa. The 120S-120N GPCC climatological annual mean precipitation as shown109

in Fig. 1b demonstrates that tropical land generally has less precipitation in Africa than110

South America and the Maritime continent, and East Africa is even drier than the western111

Africa. The Greater Horn region is the precipitation minimum among all longitudes. Fig.112

1c (shading) shows the normalized annual cycle of GPCP monthly climatology at 50N (the113

latitude is denoted by a blue horizontal line in Fig. 1a ). East African longitudes have a114

distinctive bimodal annual precipitation cycle, with the major and minor peaks in April and115

October, respectively. Other longitudes over land generally only have a single peak, although116

the peak months differ for different longitudes. For example, the annual cycle of precipitation117

over South America largely peaks between May and July, while for the African interior118

longitudes, the peaks are between July and October. It should be noted that the western119

end of Africa at 5N does have a bimodal annual cycle, but the two peaks are often viewed as120

one rainy season that is interrupted by the so-called midsummer drought (Karnauskas et al.121

2013). Fig. 1d shows the annual cycles of downward, top of the atmosphere (TOA) solar122

radiation at 50N (red line with circles). The two peaks of the solar radiation annual cycle123

(March and September) lead the two corresponding East African precipitation peaks by one124

month. The solar radiation is also greater in the boreal summer season than the winter125

season but precipitation over East African longitudes in boreal summer is comparable with126

or less than that in the winter.127

One of the major factors responsible for the climate in East Africa is the complex to-128

pography (Nicholson 1996; Lyon 2014). Fig. 2 shows the topographic elevation map of East129

5

Africa. The topography of East Africa can be roughly characterized by the coastal plain to130

the east and the generally north-south orientation of the interior highlands. The highlands131

to the north (the Ethiopian Highlands) and to the south (the East African Highlands) are132

separated by a narrow gap (the Turkana Channel), which connects the area of relatively low133

topography to the northwest and the eastern coastal plain. Local variations in climate over134

East Africa are greatly influenced by these topographical features as they play an impor-135

tant role in the low-level atmospheric circulations and moisture transport (Findlater 1969;136

Kinuthia and Asnani 1982; Kinuthia 1992).137

The annual cycle of precipitation over much of East Africa shows a bimodal distribution138

although in some regions a unimodal distribution dominates. In order to show the spatial139

distribution of the precipitation annual cycle types, the Fourier harmonics of the precipitation140

annual cycle are estimated in the GPCC data at each grid point and the ratio |c2/c1| of the141

amplitude of the semi-annual-period harmonic c2 (representing the bimodal distribution) to142

the annual-period harmonic c1 (representing the unimodal distribution) is calculated. Fig. 3143

shows the spatial distribution of the binary logarithm of this ratio so that positive (negative)144

values occur where the bimodal (unimodal) distribution dominates. It can be seen that the145

bimodal distribution dominates to the east of the highlands and near the equator while146

the unimodal distribution dominates over the southern and northwestern parts of the study147

domain. The average precipitation annual cycle over box 1 (shown to the right of the box)148

has the typical two rainy seasons in East Africa: the long rains in MAM and the short rains149

in OND. In contrast, boxes 2 and 3 only have one rainy season: the precipitation peaks150

during boreal summer over box 2 and during austral summer over box 3, both showing a151

typical monsoonal character.152

An even simpler way to identify the bimodal areas from the unimodal areas is to compare153

the precipitation rate during the long rains season (prMAM) with that during the boreal154

summer (prJJAS) and during the boreal winter (prJF ) and select the areas satisfying the155

criteria: prMAM > prJJAS and prMAM > prJF . The results are highlighted as gray shadings156

6

in the mini panel in the middle of Fig. 4 and mainly cover the areas to the east of the157

highlands, a similar pattern to that with the positive-values in Fig. 3. Hereafter the term158

“East Africa” is used to refer to the gray-shaded areas in Fig. 3 unless otherwise noted. The159

area-average is only computed for these areas. The area-averaged precipitation annual cycle160

over the shaded area is shown in Fig. 4 and has the typical bimodal annual precipitation161

cycle of East Africa. Both the GPCC and GPCP precipitation datasets show similar results,162

with wettest conditions during the long rains season (area average precipitation greater163

than 2 mm day−1), relatively wet conditions during the short rains season (precipitation164

between 1.5 mm day−1 and 2.5 mm day−1) and comparatively dry conditions during other165

seasons (precipitation less than 1.5 mm day−1). April is the wettest month of the year, with166

precipitation close to 4 mm day−1.167

What is the spatial distribution of precipitation during the different seasons? Fig. 5168

shows the seasonal climatologies of precipitation over East Africa. Months not covered by169

the long rains and the short rains are grouped into the boreal winter season (JF) and the170

boreal summer season (JJAS) as mentioned previously. During the long rains (Fig. 5b), the171

precipitation rate over the coastal areas to the east of the highlands peaks and in general172

exceeds 1 mm day−1 except in the northeastern extreme of the Greater Horn. The short rains173

(Fig. 5d) show a similar precipitation pattern to the long rains but with a slightly weaker174

magnitude. During the boreal winter season (Fig. 5a), the precipitation maxima appear175

over the southern extreme of the study domain, which are part of the ITCZ. The northern176

half of the region is generally dry except for some small areas over the highlands. During177

the boreal summer season (Fig. 5c), the largest rainfall amounts are found in the northwest,178

especially over western areas of the northern highlands, where they form the eastern reach of179

the west African monsoon. Moderately wet conditions are also found right on the east coast180

between 60S and 20N during JJAS, probably caused by an onshore breeze. Other regions181

are generally dry during this season.182

Fig. 5 also shows the climatological values of SSTs off the east coast and it is seen that the183

7

annual cycle of seasonal precipitation to the east of the highlands somewhat co-varies with the184

SSTs. SSTs are highest during the long rains season (greater than 28.5 0C) and are around185

1.5 0C cooler, yet with a similar pattern, during the short rains season. SSTs are coolest186

during boreal summer when the overall coastal conditions are driest. During boreal winter,187

a relatively strong north-south SST gradient is evident and there is an associated gradient188

in precipitation between the north and the south. The strong climatological precipitation-189

SST relationship suggests that SSTs might play an important role in the seasonal cycle of190

East African precipitation. Previous studies (McCreary et al. 1993; Murtugudde et al. 1996,191

2007) demonstrated that both surface heat flux and ocean dynamics play import roles in192

the annual cycle of Indian Ocean SSTs. For example, during boreal summer, the cold SSTs193

off the coast of East Africa are driven by a wide range of processes including upwelling,194

horizontal advection, mixed layer entrainment and latent flux (McCreary et al. 1993). These195

results imply that external forcings that are responsible for the East African precipitation196

annual cycle might be intrinsically complex.197

4. Atmospheric thermal condition198

Tropical precipitation is strongly connected with the thermal state of conditional insta-199

bility. One simple measurement of this instability is the difference between the surface moist200

static energy (MSE, which is defined as h = cpT +Lq+gz, where cp, T , L, q, g and z are spe-201

cific heat capacity at constant pressure, absolute air temperature, latent heat of evaporation,202

gravity acceleration and the height above the surface, respectively) and the saturated MSE203

at 700 hPa (denoted as hs−h∗700hPa). Fig. 6 shows the seasonal climatologies of hs−h∗700hPa204

(which has been normalized by the heat capacity of the air at constant pressure cp so it has205

the unit of degree Kelvin). In JF (Fig. 6a), there is a strong north-south gradient of the206

conditional instability seasonal climatology (colors). Most areas over the northern half of the207

region are also extremely stable, corresponding to the dry areas in Fig. 5a. Southern areas208

8

are less stable, favoring much wetter conditions. The north-south gradient in the seasonal209

climatology of stability and precipitation during JF arises mainly from a similar pattern of210

changes from the previous season (contours). In MAM (Fig. 6b), the stability weakens over211

northern areas and slightly strengthens over the extreme south which is accompanied by212

northward expansion of the precipitation and the occurrence of the long rains as shown in213

Fig. 5b. In JJAS (Fig. 6c), the stability continues to weaken over the northwest monsoon214

area but strengthens elsewhere, resulting in a northwest-southeast gradient of stability over215

the region, corresponding to a similar pattern of precipitation in this season (Fig. 5c). In216

OND (Fig. 6d), stability strengthens over the northwest but weakens over most of the east,217

which is accompanied by the short rains season (Fig. 5d).218

The seasonal climatologies of the conditional instability and the season-to-season changes219

over East Africa are dominated by the changes in surface MSE (hs, Fig. 7) rather than the220

700 hPa saturated MSE (h∗700hPa, not shown), as shown by the resemblance of Fig. 7 to221

Fig. 6 (colors and contours). Fig. 8 shows the annual cycles of the surface MSE and the222

saturated MSE at 700 hPa over the bimodal precipitation areas (shaded areas in Fig. 4).223

The amplitude of the surface MSE cycle is around three times stronger than that of the224

700 hPa saturated MSE cycle. As a result, the difference between the two (the gray line)225

has a pattern similar to the surface MSE. While the annual cycle of the 700 hPa saturated226

MSE is dominated by the annual harmonic, which probably arises from the dominance of227

annual harmonic of SST near the equator (Schneider 1996), the surface MSE is dominated228

by the semi-annual harmonic, similar to the precipitation annual cycle. Large surface MSE229

appears during the two rainy seasons, with values during the long rains larger than for the230

short rains. April is the month of maximum surface MSE across the year, consistent with231

the maximum precipitation rate during this month (Fig. 4).232

We further decompose the surface MSE into the component associated with temperature233

and the component associated with moisture (the component of MSE associated with geo-234

potential height has little seasonal variation and is not discussed here). The seasonal cycle235

9

of the surface MSE is dominated by the moisture component (Fig. 9) and the variation of236

the temperature component can largely be neglected (not shown here). Both the seasonal237

climatologies, and the season-to-season changes of the moisture component of the surface238

MSE, resemble those of the conditional instability in Fig. 6, suggesting that the annual cycle239

of the surface air conditional instability is largely explained by the moisture component of240

the surface MSE. Hence we need to explain the seasonal cycle of the moisture field across241

East Africa.242

5. Atmospheric circulation243

Fig. 10 shows the seasonal climatologies of 10 m winds from EAR-Interim Re-Analysis244

and their divergence. During JF (Fig. 10a), the Asian winter monsoon northeasterlies prevail245

and bring relatively cold and dry air into East Africa from the northeast. The 10 m winds246

are generally convergent to the east of the highlands, probably due to deceleration by surface247

friction as they penetrate inland. Yet most of the time these convergent winds are not able248

to bring precipitation because of the convectively stable atmosphere (as described in the249

previous section) as well as the shallowness of the convergence layer (as will be presented in250

the next paragraph). During MAM (Fig. 10b), southeasterlies replace the northeasterlies251

and bring warm and moist air from the southeast, that is, from over the southwest Indian252

Ocean, where climatological SSTs are their highest of the year (Fig. 5b). The surface winds253

are convergent over the Greater Horn of Africa and near the coastal land areas but become254

divergent near the entrance of the Turkana Channel between the northern and the southern255

highlands, due to the easterly acceleration when going through the entrance. During JJAS256

(Fig. 10c), the southeasterlies intensify and turn east slightly as they travel further north,257

while their dynamics becomes intrinsically nonlinear (Yang et al. 2013). The low level258

southerlies off the equatorial East African coast, commonly known as the East African Low259

Level Jet (Findlater 1969), are part of the Asian summer monsoon system. The 10 m winds260

10

accelerate as they travel across eastern land areas, resulting in divergence of the wind field.261

It is interesting to note that even though the winds over eastern land areas in JJAS are more262

parallel to the coast than in MAM, the onshore components are comparable. However, in263

contrast to the long rains in MAM, land areas are extremely dry in JJAS, when SSTs off the264

east coast are the coldest in the annual cycle (Fig. 5c) and the air above is comparatively265

cold and dry, resulting in cool, dry and stable air advecting over East Africa. During OND266

(Fig. 10d), the jet weakens and the magnitude of the onshore and southerly flow south of267

the Equator changes back to the MAM level. In general, the surface wind pattern resembles268

that in MAM except over the northeast, where northeasterlies or easterlies prevail in OND269

while southeasterlies prevail in MAM. The spatial distribution of precipitation in OND (Fig.270

5d) is also similar to that in MAM (Fig. 5c) although the overall rainfall rates are slightly271

weaker in the short rains season (OND), possibly due to the cooler SSTs at this time.272

The 850 hPa winds (Fig. 11) show a similar pattern to that at the surface. However,273

the divergence field is completely different from the surface, with year-round divergence over274

almost all land areas to the east of the highlands. The magnitude of the divergence of the275

wind field is stronger during the dry seasons of JF and JJAS and weaker during the wet276

seasons of MAM and OND, consistent with the precipitation annual cycle.277

Fig. 12 shows a vertical cross-section of the annual cycle of the area-averaged divergence278

over East Africa. Although convergence appears near the surface, the low level atmosphere279

immediately above is dominated by divergence across the year, especially between 850 hPa280

and 700 hPa. The annual cycle also shows a bimodal distribution, with maxima appearing at281

the beginning of the long rains and just before the short rains. Accordingly, the upper level282

atmosphere is dominated by convergence year-round, with maximum convergence appearing283

during the dry seasons and weak convergence appearing during the rainy season, in phase284

with the precipitation annual cycle.285

Consistent with the dominance of the low level divergence and convergence upper level286

convergence, the seasonal climatologies of the 500 hPa vertical pressure velocity (Fig. 13) are287

11

dominated by downward motions year-round, with larger values during the dry seasons and288

weakening during the rainy seasons. Fig. 14 shows the annual cycle of the area-averaged 500289

hPa vertical pressure velocity on different pressure levels. Although the low level atmosphere290

is dominated by upward motion, these do not penetrate into the middle atmosphere, where291

the downward motions dominate, except during the long rains season. This is consistent292

with the divergence shown in Fig. 12. The seasonal cycles of vertical motion and divergence293

are consistent with that of convective instability and derive primarily from the seasonal cycle294

of moist static energy of low level air.295

6. Moisture budget296

The vertically integrated moisture budget was evaluated based on 6-hourly data from the297

ERA-Interim Reanalysis. The equation is the same as equation (13) in Seager and Henderson298

(2013) and is rewritten here:299

P − E = − 1

gρw

∂

∂t

∫ ps

0

q dp− 1

gρw∇ ·

∫ ps

0

uq dp (1)

where P is precipitation rate; E is evaporation rate (here understood to include evapotran-300

spiration); g is acceleration due to gravity; ρw is liquid water density; ps is surface pressure; q301

is humidity; u is horizontal wind velocity. The monthly mean version of (1), after neglecting302

the local rate of change term and variations of surface pressure, is:303

P − E ≈ − 1

gρw∇ ·

∫ ps

0

uq dp

= − 1

gρw∇ ·

∫ ps

0

uq dp− 1

gρw∇ ·

∫ ps

0

u′q′ dp (2)

where the over bars and primes denote monthly mean and deviation from the monthly mean,304

respectively. If we compute a seasonal climatology of the above equation, the final moisture305

12

budget equation becomes:306

P − E ≈ − 1

gρw∇ ·

∫ ps

0

uq dp− 1

gρw∇ ·

∫ ps

0

u′q′ dp

= − 1

ρw∇ · VIqmum− 1

ρw∇ · VIqpup

= −DVIqmum−DVIqpup (3)

where307

VIqmum =1

g

∫ ps

0

uq dp

VIqpup =1

g

∫ ps

0

u′q′ dp

DVIqmum =1

gρw∇ ·

∫ ps

0

uq dp

DVIqpup =1

gρw∇ ·

∫ ps

0

u′q′ dp

and the top bar denotes seasonal climatology. Here VIqmum and VIqpup represent the308

seasonal climatologies of the vertically integrated moisture flux due to monthly mean circu-309

lation and sub-monthly eddies, respectively, with DVIqmum and DVIqpup the corresponding310

divergences. These terms were evaluated in the ERA-Interim Reanalysis as in Seager and311

Henderson (2013).312

Fig. 15 shows the seasonal climatologies of VIqmum (VIqpup has much smaller mag-313

nitude than VIqmum and its map is not shown here). These fluxes in general follow the314

pattern of the low level circulation (Fig. 11) as most of the moisture in the atmosphere is315

concentrated within the bottom layer. The estimated total moisture transport from the In-316

dian Ocean through the East African coast noted in Fig. 15 is much greater during the rainy317

seasons than the dry seasons, consistent with the precipitation annual cycle in this region.318

The total transport is low in JF (Fig. 15a) because the moisture flux is almost parallel to319

the coast in this season while during summer strong moisture flux out into the Indian Ocean320

across the northeastern coast is responsible for the lowest total moisture import into East321

Africa (Fig. 15c).322

13

We also assess the relative importance of circulation annual cycle and humidity annual323

cycle in the annual cycle of total moisture transport from the Indian Ocean into East Africa324

by estimating the moisture transport with four different combinations of q u, and v: 1)325

monthly mean q/u/v; 2) monthly mean u/v and annual mean q (to assess the importance326

of the circulation annual cycle); 3) monthly mean q and annual mean u/v (to estimate the327

importance of the humidity annual cycle); 4) annual mean q/ u/v (the base component328

without an annual cycle). With the last combination estimated as 190 ×106 kg s−1, the329

results of the first three combinations, after the base component being removed, are shown330

in Fig. 16. The moisture transport estimation based on monthly mean q/u/v (red bars) is331

consistent with the precipitation annual cycle over East Africa as shown before, with higher332

values in rainy seasons than in dry seasons. Meanwhile, both the component associated with333

the circulation annual cycle (green bars) and the component associated with the humidity334

annual cycle (blue bars) follow the total moisture transport but the magnitude of the former335

is at least two times larger than that of the later. This implies that the circulation annual336

cycle is more important than the humidity annual cycle in the annual cycle of moisture337

transport from Indian Ocean into East Africa.338

Fig. 17 shows the annual cycles of the different terms in the moisture budget equation339

averaged over East Africa. The precipitation from the ERA-Interim Reanalysis (the green340

dashed line) is able to capture the annual cycle of the GPCC data (the green solid line)341

although it also has the problem of overestimating the magnitude of the short rains. Evap-342

oration has comparable magnitude to the precipitation but much weaker season-to-season343

variations. The divergence of the vertically integrated moisture flux can be decomposed into344

the component associated with the monthly mean flow and moisture (DVIqmum) and the345

component due to sub-monthly eddies (DVIqpup). There is mean flow moisture divergence,346

indicating atmospheric exportation of moisture in all months except in April and October.347

The eddy component, DVIqpup, is much weaker and out of phase with the mean flow com-348

ponent. It should be noted here that the annual mean E is much greater than the annual349

14

mean precipitation either from GPCC or from ERA-Interim, which was also found in previ-350

ous studies and usually attributed to extensions of oceanic P − E patterns near coasts due351

to models’ low resolution (Dai and Trenberth 2002). As our focus here is on the annual cycle352

instead of the annual mean climatology, this is not a big problem. The sum of the three353

components (E, the mean and transient flow moisture convergence, the gray line) approx-354

imates the precipitation annual cycle very well, especially for the GPCC data (correlation355

coefficient 0.94). These results make clear that the two seasonal precipitation peaks are356

driven by the two periods of mean flow moisture convergence, which are themselves driven357

by the two peaks in low level mean flow mass convergence. The seasonal cycle of the area358

mean moisture convergence is in turn related to that of the moisture transport across the359

East Africa coast.360

7. Conclusion and discussion361

Recent studies have demonstrated that coupled models used in CMIP3/5 generally mis-362

represent the East African precipitation annual cycle by overestimating the short rains (rain-363

fall in OND) (Yang et al. 2014), which casts doubt on the reliability of projections of future364

East African precipitation (Waithaka et al. 2013). To understand the discrepancy between365

the model simulations and observations in this regard, a natural first step is to better under-366

stand the observed East African precipitation annual cycle. By using ERA-Interim reanalysis367

data, we have analyzed the seasonal climatologies and annual cycles of atmospheric thermal368

condition, circulation and moisture budget, which are closely related to the East African369

precipitation annual cycle. The following conclusions have been reached:370

• The off-coast SSTs (i.e. the western Indian Ocean SSTs) annual cycle is closely related371

to that for East African precipitation. These SSTs are higher during the rainy seasons372

than in the dry seasons and are highest during the long rains.373

• The atmosphere is generally conditionally stable throughout the year but the degree of374

15

instability measured as the difference between surface MSE and the saturated MSE at375

700 hPa follows the precipitation annual cycle, i.e. less stable during the rainy seasons376

and more stable during the dry seasons and least stable during the long rains season.377

• The annual cycle of the atmospheric stability is dominated by the surface MSE, and,378

in particular, by the annual cycle of surface humidity.379

• Although convergence prevails very near the surface, divergence in the low level tro-380

posphere and convergence in the upper level troposphere dominate year-round.381

• Consistent with the divergence field, the vertical velocity is predominantly downward382

in the middle troposphere and the magnitude is stronger in dry seasons than in rainy383

seasons.384

• The vertically integrated moisture flux is dominated by the monthly mean component385

with the sub-monthly eddy component much weaker. The total cross-coast moisture386

transport from the Indian Ocean into East Africa follows the precipitation annual cycle387

in this region. The annual cycle of this transport is primarily due to the circulation388

annual cycle and the role of the humidity annual cycle is secondary but augmenting .389

• The area-averaged mean flow moisture convergence follows the East African precip-390

itation annual cycle and, when combined with the transient eddy convergence and391

evaporation (E), approximates the observed East African precipitation annual cycle392

very well.393

The region of East Africa, while in the deep tropics and surrounded by the world’s394

major monsoons (the south Asian monsoon, the west African monsoon and the Australian395

monsoon), does not exhibit either a wet climate in terms of annual mean precipitation or a396

monsoonal climate in terms of precipitation annual cycle. Instead, East Africa is dominated397

by a semi-arid/arid climate with a bimodal annual cycle of precipitation. Traditionally, the398

aridity was considered to be associated with the dominant low level divergence (Trewartha399

16

1961), which in turn was assumed to be caused by a wind stress contrast between land400

and ocean (Nicholson 1996). However, the wind stress mechanism would be greatest near401

the surface and along immediate coastal areas. Our results (Fig. 10) show that the surface402

winds are mostly convergent along the east coast while the 850 hPa winds are predominantly403

divergent over much of the region to the east of the highlands (Fig. 11). This is in contrast404

to the wind stress mechanism.405

So what mechanism might be responsible for the semi-arid/arid climate in East Africa?406

Unlike extra-tropical precipitation, which is mainly driven by synoptic scale baroclinic eddies407

(Lee and Held 1993; Pierrehumbert and Swanson 1995; Chang et al. 2002; Yang et al. 2007),408

tropical rainfall mostly arises from moist convection, in which the subcloud MSE plays409

a key role in the framework of quasi-equilibrium (QE, Emanuel et al. (1994)). The QE410

framework has been applied to study the mechanisms that limit the poleward extend of411

summer monsoons (Chou and Neelin 2001, 2003), the location of monsoons (Prive and Plumb412

2007a,b), and the role of orography in monsoons (Boos and Kuang 2010). An important and413

relevant idea from these studies is that ventilation (which was defined as the import of low414

MSE air by advection from cooler oceans) depresses local convection and precipitation by415

decreasing the subcloud MSE. It should be noted that the ventilation mechanism in these416

studies is generally applied only in the subtropics because SST is usually cooler there but417

warm over tropical oceans. However, in the case of East Africa, there are strong low-level418

cross-equatorial monsoonal winds during the dry seasons, especially in summer, which can419

bring much lower MSE air from the winter hemisphere into East Africa and stabilize the420

atmosphere. The north-south orientated highlands act to block the import of high MSE air421

from the west as well as leading to the formation of the East African low-level jet (Findlater422

1969). Indeed, numerical experiments without topography (Fig. 1a in Chou and Neelin423

(2003)) demonstrated that East Africa is much wetter during the boreal summer season424

due to the fact that the low-level jet in observations is now replaced by westerlies in the425

simulation, which bring high MSE air from the interior of Africa to the west. Furthermore,426

17

SSTs near the coast are generally cool compared to values further offshore (Fig. 5) and a427

west-east SST gradient off the coast exists year-round. Therefore, even in the rainy seasons428

when the air is imported from the western tropical Indian Ocean by the weak onshore winds,429

it is still difficult for East Africa to develop high subcloud MSE as in regions with high coastal430

SSTs. Since the saturated MSE above the boundary layer is near uniform across the tropics,431

and influenced by the warmest of tropical regions, low subcloud MSE in East Africa ensures432

overwhelming stable conditions to moist convection.433

The bimodal annual cycle is therefore the result of the annual cycle of monsoonal winds434

combining with the annual cycle of the Indian Ocean SST. During boreal winter precipitation435

over East Africa is suppressed due to advection of low-MSE air from the cold northern Indian436

Ocean. During boreal summer the precipitation is suppressed due to even stronger advection437

from the cool Indian Ocean with the cool Indian Ocean resulting from both winds coming438

from the winter hemisphere and the coastal upwelling associated with the Somali Jet. During439

the two rainy seasons, the low-level winds are much weaker and thus have less impact on the440

surface air MSE over East Africa. Moreover, the SSTs off the coast are higher during the441

two rainy seasons and are the highest of the year during the long rains season. These are442

the reasons why there is more precipitation during the two rainy seasons and the long rains443

are stronger than the short rains. For all seasons, the off-coast SSTs are still lower than that444

of the eastern interior of the Indian Ocean, i.e. there is a west-east SST gradient over the445

Indian Ocean within the East African latitudes. The cooler SSTs off the East African coast,446

when combined with the year-round onshore winds, prevent land areas over East Africa from447

developing high subcloud MSE and therefore suppress the overall precipitation in this region.448

This might explain the largely semi-arid/arid climate over East Africa.449

Recent studies demonstrated that simulations from coupled climate models tend to have450

a west-east SST gradient that is too weak, i.e. simulated SST over the western Indian Ocean451

(including the SST nearby the East African coast) is higher than observed while the eastern452

Indian Ocean SST is close to or lower than observed. This is especially so during the boreal453

18

late autumn/early winter months (Conway et al. 2007; Han et al. 2012; Liu et al. 2013;454

Cai and Cowan 2013). This might one of the reasons why coupled models generally have a455

tendency to overestimate the short rains. We will next look at SSTs as well as circulation456

patterns in those CMIP coupled models that are crucial in the East African subcloud MSE457

development and moisture flux in order to better understand the overestimation of the458

short rains in coupled models and the consequent misrepresentation of the East African459

annual cycle of precipitation. This understanding should lead to improvements in the model460

representation which could further lead to greater confidence in model projections of future461

East African climate.462

Acknowledgments.463

This work was supported by NOAA award NA10OAR4310137 (Global Decadal Hydro-464

climate Variability and Change). Funding for BL was provided by the National Science465

Foundation under award AGS 12-52301.466

19

467

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24

List of Figures575

1 a) GPCC climatological annual mean. The vertical and horizontal blue lines576

are at the 30E and 52E longitudes and the 5N latitude, respectively. b) 12S-577

12N averaged GPCC climatological annual mean in panel a. The shaded578

rectangle marks the longitudinal range of East Africa (30E-52E). c) Normal-579

ized annual cycle of GPCP monthly climatology at 5N (shading). Vertical580

blue solid lines indicate 30E and 52E and dashed lines indicate the longitudi-581

nal edges of South America and Africa at 5N. d) Annual cycle of the monthly582

climatology of downward top of the atmosphere solar radiation at 5N from583

NCEP/NCAR reanalysis. All climatologies are estimated based on the period584

of 1979-2009. 28585

2 Topographic elevation map of East Africa. The insert shows the topographic586

elevation for all of Africa and a box indicating the East African region of focus587

in this paper. 29588

3 Distribution of precipitation (from GPCC) annual cycle type, which is mea-589

sured by log2 |c2/c1|, where c1 and c2 are the Fourier harmonics of the annual590

period and the semi-annual period, respectively. Positive (negative) values591

occur when the semi-annual (annual) period mode dominates. Boxes 1, 2 and592

3 have ranges of [40E, 44E] × [1N, 5N], [31E, 35E] × [6N, 10N] and [32E,593

36E] × [8S, 4S] respectively. Bar graphs next to the boxes show the annual594

cycle of precipitation averaged over the corresponding boxes. 30595

25

4 The annual cycle of East African area-averaged precipitation from GPCC596

and GPCP. The grid points to be averaged are chosen by the criteria that the597

precipitation rate during the long rains (MAM) is greater than that during598

both boreal summer (JJAS) and boreal winter (JF) so that the areas with599

bimodal precipitation annual cycle are focused on. The mini panel in the600

middle shows the areas satisfying the criteria (gray shading), which resemble601

the areas with positive values in Fig. 3. The thick black lines are the 1000 m602

topographical elevation contours. 31603

5 Seasonal climatologies of precipitation (mm day−1) from GPCC over East604

Africa and SST (0C) from ERSST off the east coast. The red lines are the605

smoothed contours of the 1000 m topographical elevation. 32606

6 Seasonal climatologies of the surface moist static energy (MSE) minus the607

saturated MSE at 700 hPa (colors) and their changes from the previous season608

(contours), both from the ERA-Interim reanalysis. The MSE is normalized by609

the heat capacity of the air at constant pressure so that it has the unit of degree610

Kelvin. The thick red lines are the contours of the 1000 m topographical611

elevation. 33612

7 Seasonal climatologies of the surface MSE (colors) and its change from the613

previous season (contours) from the ERA-Interim reanalysis. The MSE is614

normalized by the heat capacity of the air at constant pressure so that it has615

the unit of degree Kelvin. The thick red lines are the contours of the 1000 m616

topographical elevation. 34617

8 Annual cycles of surface MSE and the saturated MSE at 700 hPa pressure618

averaged over the shaded area shown in Fig. 4 . 35619

9 Same as Fig. 7 except it is only for the component of MSE associated with620

moisture. 36621

26

10 Seasonal climatologies of the 10 m wind (vectors, units are 10−6 s−1) and its622

associated divergence (colors) and from ERA-Interim. The thick red lines623

show the smoothed 1000 m elevation contours. 37624

11 Seasonal climatologies of 850 hPa wind (vectors, units are 10 −6 s−1) and its625

associated divergence (colors) and from ERA-Interim. The thick red lines626

show the smoothed 1000 m elevation contours. 38627

12 Annual cycles of wind divergence averaged over the shaded area shown in Fig.628

4 . 39629

13 Seasonal climatologies of 500 hPa vertical pressure velocity (ω) from ERA-630

Interim. The thick red lines show the smoothed 1000 m elevation contours. 40631

14 Annual cycles of vertical pressure velocity (ω) from ERA-Interim averaged632

over the shaded area shown in Fig. 4. 41633

15 Seasonal climatologies of the vertically integrated moisture flux of the monthly634

circulation and humidity from ERA-Interim. The stepwise numbered red635

lines approximate the coast and the moisture transports (westward/eastward636

transports are positive/negative ) through these lines are listed in the box to637

the right. 42638

16 Vertically integrated moisture transports from the Indian Ocean into East639

Africa through the coast between 100S and 120N in the four seasons (the640

annual mean q/u/v component, which is estimated as 190 ×106 kg s−1, has641

been removed to emphasize the annual cycle). Different colors show results642

from different cases with red bars using monthly mean q/u/v, green bars using643

annual mean q and monthly mean u/v, and blue bars using annual mean u/v644

and monthly mean q. 43645

17 Annual cycles of the moisture budget terms averaged over the areas shown in646

Fig. 4 from ERA-Interim. 44647

27

a GPCC climatologyical annual mean (mm/day)

150W 90W 30W 30E 90E 150E

10S

0

10N

0 2 4 6 8 10

150W 90W 30W 30E 90E 150E02468

1012

mm

/day

b GPCC 12S−12N mean

mo

nth

c GPCP annual cycle at 5N (normalized)

150W 90W 30W 30E 90E 150E

2

4

6

8

10

12 W/m

2

d

380 420

−2 −1 0 1 2

Fig. 1. a) GPCC climatological annual mean. The vertical and horizontal blue lines areat the 30E and 52E longitudes and the 5N latitude, respectively. b) 12S-12N averagedGPCC climatological annual mean in panel a. The shaded rectangle marks the longitudinalrange of East Africa (30E-52E). c) Normalized annual cycle of GPCP monthly climatologyat 5N (shading). Vertical blue solid lines indicate 30E and 52E and dashed lines indicatethe longitudinal edges of South America and Africa at 5N. d) Annual cycle of the monthlyclimatology of downward top of the atmosphere solar radiation at 5N from NCEP/NCARreanalysis. All climatologies are estimated based on the period of 1979-2009.

28

Fig. 2. Topographic elevation map of East Africa. The insert shows the topographic eleva-tion for all of Africa and a box indicating the East African region of focus in this paper.

29

Fig. 3. Distribution of precipitation (from GPCC) annual cycle type, which is measured bylog2 |c2/c1|, where c1 and c2 are the Fourier harmonics of the annual period and the semi-annual period, respectively. Positive (negative) values occur when the semi-annual (annual)period mode dominates. Boxes 1, 2 and 3 have ranges of [40E, 44E] × [1N, 5N], [31E, 35E]× [6N, 10N] and [32E, 36E] × [8S, 4S] respectively. Bar graphs next to the boxes show theannual cycle of precipitation averaged over the corresponding boxes.

30

Fig. 4. The annual cycle of East African area-averaged precipitation from GPCC andGPCP. The grid points to be averaged are chosen by the criteria that the precipitation rateduring the long rains (MAM) is greater than that during both boreal summer (JJAS) andboreal winter (JF) so that the areas with bimodal precipitation annual cycle are focused on.The mini panel in the middle shows the areas satisfying the criteria (gray shading), whichresemble the areas with positive values in Fig. 3. The thick black lines are the 1000 mtopographical elevation contours.

31

Fig. 5. Seasonal climatologies of precipitation (mm day−1) from GPCC over East Africaand SST (0C) from ERSST off the east coast. The red lines are the smoothed contours ofthe 1000 m topographical elevation.

32

2

2

2

4

−16

−14

−12

−10

−8−8

−8

−6

−6

−6 −6

−4

−4

−4 −4

−2

−2

−2

00

JF

a

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2

2

2

4

4

4

4 4

6

6

66

8

8

8

8

10

10

101214

−2

0

0

0

MAM

b

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2 2

2

4

4

68

101214

−6

−6

−6

−6

−4

−4

−4

−4

−4−4

−4

−2

−2

−2

0

0

0

0 JJAS

c

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2

2

2

2

2

4

4

4

4

4

4

6

−8

−8

−6

−6

−4 −4

−2

−2

−2 −2

−2

0

0

0

OND

d

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

K

−20 −10 0 10 20

Fig. 6. Seasonal climatologies of the surface moist static energy (MSE) minus the saturatedMSE at 700 hPa (colors) and their changes from the previous season (contours), both fromthe ERA-Interim reanalysis. The MSE is normalized by the heat capacity of the air atconstant pressure so that it has the unit of degree Kelvin. The thick red lines are thecontours of the 1000 m topographical elevation.

33

2

2

2

4

4

−14

−12

−10

−8

−6

−6

−4

−4

−4

−4

−2

−2

−2−2

−2

0

0 0

0

JF

a

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

4

4

4

6

6 6

8 8

810

10

10

10

10

12

12

1416

18

−4 −2

0

0

0

MAM

b

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

24

4

6

6

810

−12

−12

−10

−8

−8

−8

−6

−6

−6

−6

−4

−4

−4

−2

−2

−2

0

0

JJAS

c

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2

2

4

4

4

6

6

6

8

8

10

12

−12

−10−10

−10−8

−8

−8

−6

−6

−6

−4

−4

−4

−2

−2

−2

0

0 0

OND

d

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

K

320 330 340 350 360

Fig. 7. Seasonal climatologies of the surface MSE (colors) and its change from the previousseason (contours) from the ERA-Interim reanalysis. The MSE is normalized by the heatcapacity of the air at constant pressure so that it has the unit of degree Kelvin. The thickred lines are the contours of the 1000 m topographical elevation.

34

2 4 6 8 10 12−7

−6

−5

−4

−3

−2

−1

0

1

2

3

Month

K

EA hs − h∗

700hP a (K) from ERA-Inte rim

(h s − h ∗

700h P a)/c p

332

333

334

335

336

337

338

339

340

341

342

K

h s/c ph ∗

700h P a/c p

Fig. 8. Annual cycles of surface MSE and the saturated MSE at 700 hPa pressure averagedover the shaded area shown in Fig. 4 .

35

2

2

2

2

4

4

66

8

−16

−14

−12

−10

−8

−8

−8

−6

−6

−6−4

−4

−4

−4

−4

−2

−2

−2

−2

0

0

0

0

0

JF

a

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2

2

2

4

4

4

4

4

4

46

6

6

6

6

6

8

8

8

8

8

10

10

10

10

12 12

1416

−4

−2

0

0

0

MAM

b

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2

4

4

68

10121416

−12 −

10

−10

−8

−8

−8

−6

−6

−6

−6

−6

−6

−4

−4

−4

−4

−4

−4

−2

−2

−2−

2

−2

0

0

0

0 0

0

JJAS

c

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

2

2

2

2

2

2

4

4

4

4

4

4

6

6

6

6

8

810

10

−10

−10

−8

−8

−8

−6

−6

−6

−4

−4

−4

−2

−2

−2

−2

−2

0

0

0

0

0

OND

d

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

K

10 20 30 40 50

Fig. 9. Same as Fig. 7 except it is only for the component of MSE associated with moisture.

36

JF

a

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

10 m/s MAM

b

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

JJAS

c

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

OND

d

30E 34E 38E 42E 46E 50E 10S

6S

2S

2N

6N

10N

10−6

s−1

−20 −10 0 10 20

Fig. 10. Seasonal climatologies of the 10 m wind (vectors, units are 10−6 s−1) and itsassociated divergence (colors) and from ERA-Interim. The thick red lines show the smoothed1000 m elevation contours.

37

JF

a

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

10 m/s MAM

b

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

JJAS

c

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

OND

d

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

10−6

s−1

−20 −10 0 10 20

Fig. 11. Seasonal climatologies of 850 hPa wind (vectors, units are 10 −6 s−1) and itsassociated divergence (colors) and from ERA-Interim. The thick red lines show the smoothed1000 m elevation contours.

38

0.030.03

0.03 0.03

0.03

0.03

0.03

0.03

0.0

3 0.03

0.06 0.06

0.06 0.06

0.06

0.06

0.06

0.06

0.0

60.09

0.090.09 0.09

0.09

0.09

0.09

0.12

0.12

0.12 0.12

0.120.12

0.12

0.15

0.15 0.15

0.150.15

0.15

0.18

0.18 0.180.18

0.18

0.21 0.2

1

0.2

4

−0.21

−0.21

−0.18

−0.18

−0.18

−0.15−0.15

−0.15

−0.15

−0.12 −0.12

−0.1

2

−0.12

−0.09 −0.09

−0.09

−0.09

−0.09

−0.06 −0.06

−0.06

−0.0

6−0.06

−0.06

−0.0

6

−0.03 −0.03

−0.03

−0.03

−0.03−0.03

−0.03

−0.03

0 0 0

0

0 0

0

0

00

0 0

Month

Pre

ssure

(hP

a)

EA Div ( 10−5

s−1

) from ERA−Interim

2 4 6 8 10 12

100

200

300

400

500

600

700

800

900

1000

Fig. 12. Annual cycles of wind divergence averaged over the shaded area shown in Fig. 4 .

39

JF

a

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

MAM

b

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

JJAS

c

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

OND

d

30E 34E 38E 42E 46E 50E

10S

6S

2S

2N

6N

10N

10−2

Pa s−1

−10 −5 0 5 10

Fig. 13. Seasonal climatologies of 500 hPa vertical pressure velocity (ω) from ERA-Interim.The thick red lines show the smoothed 1000 m elevation contours.

40

0.005

0.005

0.0050.005

0.0

05

0.005

0.0

05

0.0

1

0.0

1

0.0

1

0.01

0.0

1

0.01

0.01

5

0.01

50.0

15

0.015

0.02

0.02

0.02

−0.0

4

−0.04

−0.035

−0.0

35

−0.03 −0.03−0.025 −0.025−0.02

−0.02

−0.02−0.015

−0.015

−0.015−0.01

−0.0

1

−0.01

−0.01

−0.0

05 −

0.0

05

−0.005

−0.005

0

0

00

0

0

0

Month

Pre

ssure

(hP

a)

EA vertical pressure velocity (Pa/s) from ERA−Interim

2 4 6 8 10 12

100

200

300

400

500

600

700

800

900

1000

Fig. 14. Annual cycles of vertical pressure velocity (ω) from ERA-Interim averaged overthe shaded area shown in Fig. 4.

41

200kg/m/s

30E 40E 50E 60E10S

5S

0

5N

10N

1

2

3

Units: 106 kg/s1: 192: 473: 85Total: 151

(a) JF 200kg/m/s

30E 40E 50E 60E10S

5S

0

5N

10N

1

2

3

Units: 106 kg/s1: 742: 1283: 37Total: 239

(b) MAM

200kg/m/s

30E 40E 50E 60E10S

5S

0

5N

10N

1

2

3

Units: 106 kg/s1: 602: 1913: -173Total: 78

(c) JJAS 200kg/m/s

30E 40E 50E 60E10S

5S

0

5N

10N

1

2

3

Units: 106 kg/s1: 892: 883: 52Total: 229

(d) OND

Fig. 15. Seasonal climatologies of the vertically integrated moisture flux of the monthlycirculation and humidity from ERA-Interim. The stepwise numbered red lines approximatethe coast and the moisture transports (westward/eastward transports are positive/negative) through these lines are listed in the box to the right.

42

JF MAM JJAS OND150

100

50

0

501

06

kg/s

monthly q/u/vmonthly u/v; annual mean qmonthly q; annual mean u/v

Fig. 16. Vertically integrated moisture transports from the Indian Ocean into East Africathrough the coast between 100S and 120N in the four seasons (the annual mean q/u/vcomponent, which is estimated as 190 ×106 kg s−1, has been removed to emphasize theannual cycle). Different colors show results from different cases with red bars using monthlymean q/u/v, green bars using annual mean q and monthly mean u/v, and blue bars usingannual mean u/v and monthly mean q.

43

1 2 3 4 5 6 7 8 9 10 11 12

−2

−1

0

1

2

3

4

Month

mm

/day

EA moisture budget annual cycle

P(GPCC)

P(ERA−Interim)

E − DVIqmum − DVIqpup

E

−DVIqmum

−DVIqpup

Fig. 17. Annual cycles of the moisture budget terms averaged over the areas shown in Fig.4 from ERA-Interim.

44