Decadal rainfall variability modes in observed rainfall records over East Africa and their relations to historical sea surface temperature changes.

Detailed knowledge about the long-term interface of climate and rainfall variability is essential for managing agricultural activities in Eastern African countries. To this end, the space-time patterns of decadal rainfall variability modes over East Africa and their predictability potentials using Sea Surface Temperature (SST) are investigated. The analysis includes observed rainfall data from 1920-2004 and global SSTs for the period 1950-2004. Simple correlation, trend and cyclical analyses, Principal Component Analysis (PCA) with VARIMAX rotation and Canonical Correlation Analysis (CCA) are employed. The results show decadal signals in filtered observed rainfall record with 10 years period during March - May (MAM) and October – December (OND) seasons. During June - August (JJA), however, cycles with 20 years period are common. Too much / little rainfall received in one or two years determines the general trend of the decadal mean rainfall. CCA results for MAM showed significant positive correlations between the VARIMAX-PCA of SST and the canonical component time series over the central equatorial Indian Ocean. Positive loadings were spread over the coastal and Lake Victoria regions while negative loading over the rest of the region with significant canonical correlation skills. For the JJA seasons, Atlantic SSTs had negative loadings centred on the tropical western Atlantic Ocean associated with the wet / dry regimes over western / eastern sectors. The highest canonical correlation skill between OND rainfall and the Pacific SSTs showed that El Niño-Southern Oscillation (ENSO)/La Niña phases are associated with wet/dry decades over the region

Dominant atmospheric circulation patterns associated with abnormal rainfall events over Rwanda, East Africa

The study investigated the dominant atmospheric circulation patterns associated with abnormal rainfall over Rwanda during the March–May (MAM) rainfall season in 1981–2010. The data sets used in this study include: rainfall, wind, sea surface temperature (SST), and humidity. Correlation and composite analysis and Percent of Normal Index (PNI) were deployed in this study. In the wet years (1987, 1988, and 1998), the country was dominated by moisture convergence, which is in line with wind anomalies that exhibits strong westerly winds from the Atlantic Ocean and southeasterly winds originated from the Indian Ocean. These winds carry moist air mass passing over Congo to the study area, leading to wet events. On the other hand, easterly winds were noted over the study area during the dry years (1984, 2000, 2007, and 2008). The observed wet years coincided with the El Niño events, while the dry years are noted during the La Niña episodes. The dry years exhibited a wide spread of moisture divergence anomaly at the low level and were characterized by the sinking motion as opposed to the wet years with the rising motion. The anomalies of velocity potential/divergence further showed that the wet (dry) years were characterized by convergence (divergence) at the low level. The results also show that there exists a low positive correlation between mean MAM rainfall and SST over the Indian Ocean, which shows minimum influence of the Ocean. On the other hand, it was noted that rainfall amounts is significantly correlated at 95% confidence level with the elevation (altitude) of a given station. This study improves the understanding of the occurrence of wet and dry events in Rwanda, which is helpful in future monitoring of these events

Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models

This study presents potential future variations of mean rainfall and temperature over East Africa (EA) based on five models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and representative concentration pathways (RCPs): 4.5 and 8.5. In this study, climate simulations of two timeframes, a baseline period (1961–1990) and projection period (2071–2100), are compared. The models reproduce EA's bimodal rainfall pattern but overestimate and underestimate seasonal rainfall of October–December (OND) and March–May (MAM), respectively. Rainfall is projected to increase under the two scenarios. Larger increases in rainfall will occur during the OND season than during the MAM season and in RCP8.5 than in RCP4.5. During the last half of the 21st century, EA is likely to warm by 1.7–2.8 and 2.2–5.4 °C under the RCP4.5 and RCP8.5 scenarios, respectively, relative to the baseline period. Scenario uncertainty is projected to exceed model uncertainty from the middle to the end of the 21st century. The central parts of Kenya and the Lake Victoria Basin will witness the highest increases in seasonal rainfall. The probability density functions (PDFs) of future seasonal rainfall show a positive shift and a statistically insignificant increase in variance relative to the baseline. Thus, EA is likely to experience an increase in extreme rainfall events. Understanding the future climate variability in EA is important for planning purposes but these results are based on relatively course resolution models prone to bias and therefore should be used with caution. There is a need for further research on climate projections over EA, including determining the causes of the poor performance of global models in reproducing rainfall climatology and trends over the region

Intraseasonal oscillations of the East African long rains and their connection with MJO activity over the Indian Ocean

Our understanding of the East African long rains (March-May) variability remains relatively poor. Interannual variations are quite small compared to intraseasonal vari- ations. An analysis of pentad rainfall and OLR data shows organised variations in the range of 20-75 days, though quite irregular from year to year. However, rainfall and OLR variations are strongly consistent over the highland region only. For this region, NCEP-DOE II reanalysis data are used to detect atmospheric patterns associated to wet events. Significant zonal wind anomalies, of opposite sign at 850 and 200 hPa, are found locally over East Africa. Anomalous low-level westerlies (upper-level easter- lies) are observed during wet events. Years of weakened or enhanced correlations be- tween rainfall and zonal wind tend to occur simultaneously at 850 and 200 hPa. Zonal cross-sections show that these anomalies are neither isolated in time nor in space : the wind anomalies often tend to propagate eastward, especially over the Indian Ocean. They are suggested to be associated with Madden-Julian Oscillations (MJO). To confirm this hypothesis, a MJO signal is extracted based on an EOF analysis of pentad velocity potential anomalies along the tropics, for the MAM season. The first two principal components depict MJO activity over the Indian Ocean and the Pacific Ocean, respectively, and are in quadrature. Based on Wheeler and Hendon (2004), eight different phases of the MJO signal are identified and their association with at- mospheric dynamics over the East African region is investigated. It is found that sig- nificant zonal wind anomalies occur over East Africa in conjunction with the eastward propagation of a MJO over the global tropics. These anomalies display an opposite signal in the upper and lower levels, a pattern reminiscent of that associated to wet events over the East African Highlands. However, the maximum wind, ascent and rainfall anomalies over this region occur when the MJO-induced convective activity has already settled over the central Indian Ocean. It is also found that rainfall and circulation anomalies near the East African coastal area do not follow this pattern. In particular, anomalous ascending motion occurs well before the development of deep convection over the highlands, and is restricted to the mid-troposphere. The resulting rainfall is considered to be of stratiform origin, hence the absence of a clear OLR signal for wet events along the coast

Wet periods along the East Africa Coast and the extreme wet spell event of October 1997

Extreme wet spells affect the East Africa Coast (EAC) during March to June (long rains) and October to December (short rains). While these spells are less frequent during the short rains, some of the most extreme wet spells occur at this time of the year. The present study examined the general characteristics of the wet spells during the short rains. A detailed study of the anomalous wet spell event of October 1997, with record rainfall around Mombasa (4.0°S, 39.6°E), was also carried out. Daily rainfall for 1962-1997 and NCEP2 reanalysis data for 1979-1997 were used to study the characteristics of the wet events. A high spatial coherence is found in the rainfall over the EAC. The circulation features that were common during most of the wet events were: weakening or reversal of the east-west (Walker type) circulation over the Indian Ocean, enhanced convergence between the northern and southern hemisphere trade winds and westward-moving disturbances in the low-level equatorial wind field. During the 1997 wet event, it is shown that prior to the heavy rainfall event a ridge of high pressure, on the eastern coast of southern Africa, intensified and propagated eastwards leading to the strengthening of moist easterlies reaching the EAC. The zonal wind component along longitude 40°E showed shears in the flows that were associated with the development of the Mozambique Channel low/trough in the lower troposphere round which southerlies surged northwards. These southerlies converged with the easterlies near the EAC. Thus, the warm and wet air from the east interacted with the relatively cold and mainly continental air from the south generating instability at the EAC

Oceanic and atmospheric linkages with short rainfall season intraseasonal statistics over Equatorial Eastern Africa and their predictive potential.

18 pagesInternational audienceDespite earlier studies over various parts of the world including equatorial Eastern Africa (EEA) showing that intraseasonal statistics of wet and dry spells have spatially coherent signals and thus greater predictability potential, no attempts have been made to identify the predictors for these intraseasonal statistics. This study therefore attempts to identify the predictors (with a 1-month lead time) for some of the subregional intraseasonal statistics of wet and dry spells (SRISS) which showed the greatest predictability potential during the short rainfall season over EEA. Correlation analysis between the SRISS and seasonal rainfall totals on one hand and the predefined predictors on the other hand were initially computed and those that were significant at 95% confidence levels retained. To identify additional potential predictors, partial correlation analyses were undertaken between SRISS and large-scale oceanic and atmospheric fields while controlling the effects of the predefined predictors retained earlier. Cross-validated multivariate linear regression (MLR) models were finally developed and their residuals assessed for independence and for normal distribution. Four large-scale oceanic and atmospheric predictors with robust physical/dynamical linkages with SRISS were identified for the first time. The cross-validated MLR models for the SRISS of wet spells and seasonal rainfall totals mainly picked two of these predictors around the Bay of Bengal. The two predictors combined accounted for 39.5% of the magnitude of the SST changes between the July–August and October–November–December periods over the Western Pole of the Indian Ocean Dipole, subsequently impacting EEA rainfall. MLR models were defined yielding cross-validated correlations between observed and predicted values of seasonal totals and number of wet days ranging from 0.60 to 0.75, depending on the subregion. MLR models could not be developed over a few of the subregions suggesting that the local factors could have masked the global and regional signals encompassed in the additional potential predictors