16 resultados para Ethiopia

em CentAUR: Central Archive University of Reading - UK


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There is a pressing need for good rainfall data for the African continent both for humanitarian and climatological purposes. Given the sparseness of ground-based observations, one source of rainfall information is Numerical Weather Prediction (NWP) model outputs. The aim of this article is to investigate the quality of two NWP products using Ethiopia as a test case. The two products evaluated are the ERA-40 and NCEP reanalysis rainfall products. Spatial, seasonal and interannual variability of rainfall have been evaluated for Kiremt (JJAS) and Belg (FMAM) seasons at a spatial scale that reflects the local variability of the rainfall climate using a method which makes optimum use of sparse gauge validation data. We found that the spatial pattern of the rainfall climatology is captured well by both models especially for the main rainy season Kiremt. However, both models tend to overestimate the mean rainfall in the northwest, west and central regions but underestimate in the south and east. The overestimation is greater for NCEP in Belg season and greater for ERA-40 in Kiremt Season. ERA-40 captures the annual cycle over most of the country better than NCEP, but strongly exaggerates the Kiremt peak in the northwest and west. The overestimation in Kiremt appears to have been reduced since the assimilation of satellite data increased around 1990. For both models the interannual variability is less well captured than the spatial and seasonal variability. Copyright © 2008 Royal Meteorological Society

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Despite an emerging body of work on youth transitions, research has yet to explore the often unconventional routes to adulthood for young people marginalised through poverty. By drawing on interviews with 60 young commercial sex workers in Ethiopia, this paper explores the connections between poverty, migration and sex work and demonstrates that sex work provides a risky alternative, but often successful, path to independence for some rural-urban migrants. The paper concludes by offering recommendations for policies that seek to support young sex workers by enabling them to maintain their independence while seeking different employment.

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Since the emergence of the AIDS pandemic in sub-Saharan Africa, male mobility has been highlighted as one of the reasons for the spread of the disease with men employing the services of commercial sex workers while away from home. However, sex workers' mobility and the implications of this for their access to prevention services, has largely been ignored. This paper, based on multi-method qualitative research with 60 young sex workers in two Ethiopian towns, reveals that sex workers are highly mobile, moving in order to attract a wider or different client base, for adventure and to conceal illnesses which might be associated with AIDS. In addition, sex workers are affected by restrictions on their movements, with girls working in bars and red-light areas having little free time to access projects. This paper advocates that policy approaches need to take account of this mobility in three ways: first, by exploring ways for girls to access information and maintain contact with support structures while moving between places of work; second, by building the capacity of sex workers to take greater control over decision-making in their day-to-day lives and third, by developing outreach strategies for taking services into bars and red-light areas.

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Despite an emerging body of work on youth transitions, research has yet to explore the often unconventional routes to adulthood for young people marginalised through poverty. By drawing on interviews with 60 young commercial sex workers in Ethiopia, this paper explores the connections between poverty, migration and sex work and demonstrates that sex work provides a risky alternative, but often successful, path to independence for some rural-urban migrants. The paper concludes by offering recommendations for policies that seek to support young sex workers by enabling them to maintain their independence while seeking different employment.

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An annually laminated, uranium-series dated, Holocene stalagmite from southeast Ethiopia has been analysed for growth rate and δ13C and δ18O variations at annual to biennial resolution, in order to provide the first long duration proxy record of decadal-scale rainfall variability in this climatically sensitive region. Our study site (10°N) is climatically influenced by both summer (June—August) and spring (March—May) rainfall caused by the annual movement of the Inter-Tropical Convergence Zone (ITCZ) and modulated by large-scale anomalies in the atmospheric circulation and in ocean temperatures. Here we show that stalagmite growth, episodic throughout the last 7800 years, demonstrates decadal-scale (8—25 yr) variability in both growth rate and δ 18O. A hydrological model was employed and indicates that this decadal variability is due to variations in the relative amounts of rainfall in the two rain seasons. Our record, unique in its combination of length (a total of ~1000 years), annual chronology and high resolution δ18O, shows for the first time that such decadal-scale variability in rainfall in this region has occurred through the Holocene, which implies persistent decadal-scale variability for the large-scale atmospheric and oceanic driving factors.

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Development policies in the pastoral areas of Africa assume that pastoralists are poor. Using the Afar pastoralists of Ethiopia as the focus of research this article challenges this depiction of pastoralism by exploring pastoral livelihood goals and traditional strategies for managing risk. Investment in social institutions to minimise the risk of outright destitution, sometimes at the cost of increased poverty, and significant manipulation of local markets enable the Afar to exploit a highly uncertain and marginal environment. Improved development assistance and enhanced targeting of the truly vulnerable within pastoral societies demands an acceptance that pastoral poverty is neither uniform nor universal.

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Climate data are used in a number of applications including climate risk management and adaptation to climate change. However, the availability of climate data, particularly throughout rural Africa, is very limited. Available weather stations are unevenly distributed and mainly located along main roads in cities and towns. This imposes severe limitations to the availability of climate information and services for the rural community where, arguably, these services are needed most. Weather station data also suffer from gaps in the time series. Satellite proxies, particularly satellite rainfall estimate, have been used as alternatives because of their availability even over remote parts of the world. However, satellite rainfall estimates also suffer from a number of critical shortcomings that include heterogeneous time series, short time period of observation, and poor accuracy particularly at higher temporal and spatial resolutions. An attempt is made here to alleviate these problems by combining station measurements with the complete spatial coverage of satellite rainfall estimates. Rain gauge observations are merged with a locally calibrated version of the TAMSAT satellite rainfall estimates to produce over 30-years (1983-todate) of rainfall estimates over Ethiopia at a spatial resolution of 10 km and a ten-daily time scale. This involves quality control of rain gauge data, generating locally calibrated version of the TAMSAT rainfall estimates, and combining these with rain gauge observations from national station network. The infrared-only satellite rainfall estimates produced using a relatively simple TAMSAT algorithm performed as good as or even better than other satellite rainfall products that use passive microwave inputs and more sophisticated algorithms. There is no substantial difference between the gridded-gauge and combined gauge-satellite products over the test area in Ethiopia having a dense station network; however, the combined product exhibits better quality over parts of the country where stations are sparsely distributed.

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Tropical Applications of Meteorology Using Satellite and Ground-Based Observations (TAMSAT) rainfall estimates are used extensively across Africa for operational rainfall monitoring and food security applications; thus, regional evaluations of TAMSAT are essential to ensure its reliability. This study assesses the performance of TAMSAT rainfall estimates, along with the African Rainfall Climatology (ARC), version 2; the Tropical Rainfall Measuring Mission (TRMM) 3B42 product; and the Climate Prediction Center morphing technique (CMORPH), against a dense rain gauge network over a mountainous region of Ethiopia. Overall, TAMSAT exhibits good skill in detecting rainy events but underestimates rainfall amount, while ARC underestimates both rainfall amount and rainy event frequency. Meanwhile, TRMM consistently performs best in detecting rainy events and capturing the mean rainfall and seasonal variability, while CMORPH tends to overdetect rainy events. Moreover, the mean difference in daily rainfall between the products and rain gauges shows increasing underestimation with increasing elevation. However, the distribution in satellite–gauge differences demon- strates that although 75% of retrievals underestimate rainfall, up to 25% overestimate rainfall over all eleva- tions. Case studies using high-resolution simulations suggest underestimation in the satellite algorithms is likely due to shallow convection with warm cloud-top temperatures in addition to beam-filling effects in microwave- based retrievals from localized convective cells. The overestimation by IR-based algorithms is attributed to nonraining cirrus with cold cloud-top temperatures. These results stress the importance of understanding re- gional precipitation systems causing uncertainties in satellite rainfall estimates with a view toward using this knowledge to improve rainfall algorithms.

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In this study, the oceanic regions that are associated with anomalous Ethiopian summer rains were identified and the teleconnection mechanisms that give rise to these associations have been investigated. Because of the complexities of rainfall climate in the horn of Africa, Ethiopia has been subdivided into six homogeneous rainfall zones and the influence of SST anomalies was analysed separately for each zone. The investigation made use of composite analysis and modelling experiments. Two sets of composites of atmospheric fields were generated, one based on excess/deficit rainfall anomalies and the other based on warm/cold SST anomalies in specific oceanic regions. The aim of the composite analysis was to determine the link between SST and rainfall in terms of large scale features. The modelling experiments were intended to explore the causality of these linkage. The results show that the equatorial Pacific, the midlatitude northwest Pacific and the Gulf of Guinea all exert an influence on the summer rainfall in various part of the country. The results demonstrate that different mechanisms linked to sea surface temperature control variations in rainfall in different parts of Ethiopia. This has important consequences for seasonal forecasting models which are based on statistical correlations between SST and seasonal rainfall totals. It is clear that such statistical models should take account of the local variations in teleconnections.

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A seasonal forecasting system that is capable of skilfully predicting rainfall totals on a regional scale would be of great value to Ethiopia. Here, we describe how a statistical model can exploit the teleconnections described in part 1 of this pair of papers to develop such a system. We show that, in most cases, the predictors selected objectively by the statistical model can be interpreted in the light of physical teleconnections with Ethiopian rainfall, and discuss why, in some cases, unexpected regions are chosen as predictors. We show that the forecast has skill in all parts of Ethiopia, and argue that this method could provide the basis of an operational seasonal forecasting system for Ethiopia.

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An account of Wingate's time in the UK, from his return to Palestine to his departure for Ethiopia.

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Major General Orde Wingate was a highly controversial figure in his time and remains so among historians. However, his eccentric and colourful personality has drawn attention away from the nature of his military ideas, the most important of which was his concept of long-range penetration, which originated from his observations of his operations in Italian-occupied Ethiopia in 1941, and evolved into the model he put into practice in the Chindit operations in Burma in 1943-44. A review of Wingate's own official writings on this subject reveals that long-range penetration combined local guerrilla irregulars, purpose-trained regular troops and airpower into large-scale offensive operations deep in the enemy rear, with the intention of disrupting his planning process and creating situations regular forces could exploit. This evolved organically from Major General Colin Gubbins' doctrine for guerrilla resistance in enemy occupied areas, and bears some resemblance to the operational model applied by US and Allied forces, post September 2001.

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Rainfall can be modeled as a spatially correlated random field superimposed on a background mean value; therefore, geostatistical methods are appropriate for the analysis of rain gauge data. Nevertheless, there are certain typical features of these data that must be taken into account to produce useful results, including the generally non-Gaussian mixed distribution, the inhomogeneity and low density of observations, and the temporal and spatial variability of spatial correlation patterns. Many studies show that rigorous geostatistical analysis performs better than other available interpolation techniques for rain gauge data. Important elements are the use of climatological variograms and the appropriate treatment of rainy and nonrainy areas. Benefits of geostatistical analysis for rainfall include ease of estimating areal averages, estimation of uncertainties, and the possibility of using secondary information (e.g., topography). Geostatistical analysis also facilitates the generation of ensembles of rainfall fields that are consistent with a given set of observations, allowing for a more realistic exploration of errors and their propagation in downstream models, such as those used for agricultural or hydrological forecasting. This article provides a review of geostatistical methods used for kriging, exemplified where appropriate by daily rain gauge data from Ethiopia.

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Cultural comparisons enjoy increasing popularity in economics. Since cultural comparison must abandon random allocation to treatments, it is unclear whether differences found between countries can be attributed to country characteristics or are merely driven by differences in subject pools. In experiments in two Chinese cities and at two campuses in Ethiopia, we show that within-country differences are negligible. Differences between the two countries, on the other hand, are large.