Laban Ogallo

ENSO signals in East African rainfall seasons

The evolutions of ENSO modes in the seasonal rainfall patterns over East Africa are examined in this study. The study covers the period 1961–1990. Both rotated empirical orthogonal function (EOF) and simple correlation analyses were used to delineate a network of 136 stations over East Africa into homogeneous rainfall regions in order to derive rainfall indices. Time series generated from the delineated regions were later used in the rainfall/ENSO analyses. Such analyses involved the development of composite rainfall map patterns for El Nino and post-ENSO (+1) years in order to investigate the associations between seasonal evolution of El Nino–Southern Oscillation (ENSO) signals and the space-time evolution of rainfall anomalies over the region. Analyses based on both EOF and simple correlation techniques yielded eight homogeneous rainfall regions over East Africa. The results showed unique seasonal evolution patterns in rainfall during the different phases of the ENSO cycles. East African rainfall performance characteristics were stratified to identify distinct rainfall anomaly patterns associated with ENSO and post-ENSO (+1) years. These can be applied in conjunction with skilful long lead (up to 12 months) ENSO prediction to provide guidance on likely patterns of seasonal rainfall anomalies over the region. Such information can be crucial for early warning of socio-economic disasters associated with extreme rainfall anomalies over East Africa. Copyright

Application of the NCAR Regional Climate Model to eastern Africa: 2. Simulation of interannual variability of short rains

We have applied the NCAR RegCM2 to the simulation of the interannual variability of precipitation over eastern Africa for the short-rains season by performing a set of experiments for the years 1982 to 1993. The model reproduced the observed interannual variability of precipitation in most of the years. The results show that remote factors play a dominant role in determining the precipitation anomalies. Interannual variability of precipitation over Tanzania is closely related to El Nino events in their mature phase and sea surface temperature (SST) anomalies over the Indian and Atlantic Oceans. The southward shift of the Arabian High results in a southward shift of the zonal component of the Intertropical Convergence Zone (ITCZ), which is responsible for early onset of the rainy season (e.g., 1982 and 1986). The enhanced St. Helena High and weaker Mascarene High lead to the eastward shift of the meridional branch of the ITCZ for the wet years. Model simulations confirmed a strong positive correlation between precipitation anomalies over Lake Victoria and the warm El Nino-Southern Oscillation events, by which enhanced moist westerly flow from the Atlantic Ocean and the mainly easterly flow from the Indian Ocean converge over Lake Victoria during wet years. The interannual variability of precipitation over Lake Victoria and the western Kenya Highlands (WKH) are strongly coupled. Positive precipitation anomalies over the WKH region are usually associated with weaker Arabian High and Mascarene High, which weaken the large-scale divergence over the WKH region and favor the development of convection. The interannual variability of precipitation over eastern Kenya Highlands (EKH) is not directly related to the El Nino events, but the association with a warm SST anomaly pattern over the western Indian Ocean is evident during wet years. An El Nino signal is, however, evident for wet years over the Turkana Channel, warm SST anomalies over the northern Indian Ocean contribute enhanced water vapor transport over the region.

Application of the NCAR regional climate model to eastern Africa: 1. Simulation of the short rains of 1988

The National Center for Atmospheric Research (NCAR) Regional Climate Model (RegCM2) is employed to investigate the physical mechanisms that govern the October-December rains over eastern Africa. The model employs the Mercator conformai projection, with a domain of 5580 km × 5040 km centered at 31°E, 4°S, and a horizontal grid point spacing of 60 km. The simulation period is October-December 1988, and the model initial and lateral boundary conditions are taken from ECMWF reanalysis. A number of month-long simulations have been conducted to optimize various parameterizations of the model which include the following factors: cumulus convection, moisture parameterization, radiative transfer formulation, surface processes, boundary layer physics, and the lateral boundary conditions. The model was successfully customized over eastern Africa. The model simulates the large-scale circulation characteristics over the region as well as local features such as the dominant precipitation maxima, the Turkana low-level jet, and the diurnal reversal in the lake/land breeze circulation over Lake Victoria. Several model deficiencies are also identified. They include a negative rainfall bias over the western portions of the domain and the Kenya Highlands and a temperature bias over the tropical forest regions. Systematic analysis of surface water budget reveals that evapotranspiration is a major sink in the water budget over the regions where precipitation is moderate or small, while the role of runoff and drainage becomes important over the regions where precipitation is abundant. The model simulations also suggest that during the short-rains season, the large-scale circulation anomalies play the most important role in shaping the precipitation anomalies.

Mechanistic Model Simulations of the East African Climate Using NCAR Regional Climate Model: Influence of Large-Scale Orography on the Turkana Low-Level Jet

Abstract The National Center for Atmospheric Research regional climate model (RegCM) is employed to study the dynamics of the Turkana low-level jet that lies between the Ethiopian and the East African highlands, and also investigate the mechanisms responsible for the observed dry conditions over the Lake Turkana basin that lies in the wider section of the Turkana channel. The role of the large-scale orography and two other forcing factors namely the large-scale monsoonal flow and the Turkana channel depth are investigated in order to understand the kinematics of the jet. The simulated patterns of the Turkana easterly low-level jet compares well with its observed characteristics. Strong winds are indicated in the channel throughout the study period of October to December, with the wind speed decreasing in the middle and wider region of the channel. A split in the jet core is also shown in the middle of the channel. The level of maximum winds (∼11 m s−1) occurs in the layers 930-hPa and 650-hPa levels. The ...

Predictability of the Normalized Difference Vegetation Index in Kenya and Potential Applications as an Indicator of Rift Valley Fever Outbreaks in the Greater Horn of Africa

In this paper the progress made in producing predictions of the Normalized Difference Vegetation Index (NDVI) over Kenya in the Greater Horn of Africa (GHA) for the October–December (OND) season is discussed. Several studies have identified a statistically significant relationship between rainfall and NDVI in the region. Predictability of seasonal rainfall by global climate models (GCMs) during the OND season over the GHA has also been established as being among the best in the world. Information was extracted from GCM seasonal prediction output using statistical transformations. The extracted information was then used in the prediction of NDVI. NDVI is a key variable for management of various climate-sensitive problems. For example, it has been shown to have the potential to predict environmental conditions associated with Rift Valley Fever (RVF) viral activity and this is referred to throughout the paper as a motivation for the study. RVF affects humans and livestock and is particularly economically important in the GHA. The establishment of predictability for NDVI in this paper is therefore part of a methodology that could ultimately generate information useful for managing RVF in livestock in the GHA. It has been shown that NDVI can be predicted skillfully over the GHA with a 2–3-month lead time. Such information is crucial for tailoring forecast information to support RVF monitoring and prediction over the region, as well as many other potential applications (e.g., livestock forage estimation). More generally, the Famine Early Warning System (FEWS), a project of the U.S. Agency for International Development (USAID) and the National Aeronautics and Space Administration (NASA) and other specialized technical centers routinely use NDVI images to monitor environmental conditions worldwide. The high predictability for NDVI established in this paper could therefore supplement the routine monitoring of environmental conditions for a wide range of applications.

The Characteristics of Wet Spells in Tanzania

In Tanzania where the bulk of economy depends largely on rain-fed agriculture, the study of daily rainfall patterns is of paramount importance. It is well known that wet or dry spells lasting for long duration may impose unbearable moisture stress on crops. The dry and wet spells will also influence the day-to-day agricultural operations which include seedbed preparations, weeding, fertilizer applications, harvesting and many others. These weather events also influence the occurrence and spread of many plants and animal diseases, and pests, together with the wind and water erosions. It is therefore important to investigate the spatial and temporal characteristics of wet and dry spells. The characteristics which should be investigated include: (a) The length of dry / wet spell that can be expected in any given month or season. (b) The chances of a dry/wet spell lasting for a given number of days. (c) Persistence of the weather events. This will indicate whether the occurrences of dry / wet spells are functions of the rainfall events in the previous days. (d) Statistical distribution of the wet / dry spells. Spatial and temporal characteristics of the dry fwet spells have been investigated by many scientists. Some of these authors include Williams (1952), Gabriel and Neuman (1957, 1962), Longley (1957), Jorgenson (1964), Weiss (1964), Basu (1971), Feyerhem et al. (1965), Hopkins et al. (1964), Katz (1977), Swift et al. (1981), Kamte et al. (1979), Stern (1982) and Agnihotri et al. (1983). Results from these studies indicated the tendency for wet f dry spells to be followed by dry / wet spells in some regions of the world. Many statistical models have also been used to describe the temporal patterns of the wet / dry spells. The statistical distributions which have been used include geometric, gamma, log-normal, Markovchain and SB models. In East Africa Alusaand Gwage (1978) examined the frequency of dry spells during the rainy months for the whole of East Africa. In this study we will investigate the spatial and temporal characteristics of the wet spells in Tanzania during the months of November through to May.

Stochastic modelling of regional annual rainfall anomalies in East Africa

ARIMA (p, d, q) models were fitted to areal annual rainfall of two homogeneous regions in East Africa with rainfall records extending between the period 1922–80. The areal estimates of the regional rainfall were derived from the time series of the first eigenvector, which was significantly dominant at each of the two regions. The first eigenvector accounted for about 80% of the total rainfall variance in each region. The class of ARIMA (p, d, q) models which best fitted the areal indices of relative wetness/dryness were the A R M A (3, 1) models. Tests of forecasting skill however indicated low skill in the forecasts given by these models. In all cases the models accounted for less than 50% of the total variance. Spectral analysis of the indices time series indicated dominant quasi-periodic fluctuations around 2.2–2.8 years, 3–3.7 years, 5–6 years and 10–13 years. These spectral bands however accounted for very low proportion of the total rainfall variance.

Statistical characteristics of the surface wind speeds over Kenya

In this study attempts were made to fit several statistical distributions to the surface maximum, minimum and mean daily wind speed records at 24 Kenyan sites. The statistical distributions fitted included the 2 and 3 parameter Lognormal, Pearson type III, Log Pearson type III, the 2 and 3 parameter Weibull distributions. The various parameters for these distributions were obtained from the methods of moments and maximum likelihood. The goodness of fit of the various distributions were investigated at each of the 24 sites using the Kolmogorov-Smirnov and x2 tests. The corresponding standard errors were also computed.