Kiremt Season Research Articles

Impacts of land use/land cover detection on climate variability of Gumara Watershed, Ethiopia

Land use/land cover (LU/LC) detection on climate variability has been conducted using satellite image and weather data in the study area. LU/LC analysis was done using supervised classification and the categories used were built-up area, forest, grassland, agriculture and waterbody. From the analysis, built-up area is shown as increasing from 1997 to 2017. Climate variability assessment done using the Mann-Kendall and Sen's slope estimator shows that average annual maximum temperature and mean temperature have positive trends, average annual minimum temperature shows a decreasing trend. Annual rainfall showed positive trend in the Bega season and decreasing trends in, Belg season and Kiremt season. Percentage changes were observed as 0.4%, 2.4% and 2.6% for average annual minimum, maximum and average annual temperature, respectively. Average annual rainfall, in Bega season, Belg season and Kiremt seasons was −1.7%, 3.5%, 6.5% and −6.4% respectively. Hence percentage changes show LU/LC change affects climate.

Impact of Climate Change on Seasonal Rainfall Patterns over Bale Highlands, Southeastern Ethiopia

The objective of this study was evaluates the impact of climate change on seasonal rainfall patterns over Bale Highlands by using climate data from National Meteorology Agency and downscaling Coordinated Regional Climate Downscaling Experiment (Cordex) output data from cordex Africa. In order to estimate the climate change signal scenarios of rainfall and temperature were developed for periods of 30 years (2011 to 2100). The outputs GCM model for the RCP4.5 and RCP8.5 emission scenarios were used to produce the future scenarios. Instat V3.7 software was governed for this study. The sample size for this study was 768 respondents randomly selected. Results of R 2=0.58 for temperature over study area which shows that there is a good correlation between downscaled and observed data. The study shows that there is an overall increasing trend in seasonal maximum and minimum temperatures and decreasing of seasonal rainfall from the base period. The onset, cessation and Length of Growing Periods in both Belg and Kiremt season shifts from the base years. Observational data, GCM date and farmer’s perception showed similar result and there is a shift of seasons over Bale highlands form 2 days to dekade. During Kiremt season there was decreasing of LGP from 109 to 101. Similarly, the LGP of Belg was reduced from 84 days to 48 days at the end of 21st century. The onset of Belg season at the end of 21st century will shifts to May. The anticipated shift of Kiremt season will merging to Bega (dry season) with this the author recommended the local farmers or any concerned body uses this information which is significant amount of rainfall require appropriate acclimatization strategies to minimize risks, increase crop productivity, and avert food insecurity of the area.

Spatio-Temporal Analysis of Rainfall Variability and Meteorological Drought: A Case Study in Bilate River Basin, Southern Rift Valley, Ethiopia

Rainfall always plays a deciding role in sustainable agricultural production. This research attends to analyzes variation of rainfall, examine trends of rainfall, evaluate the relationship between ENSO and rainfall variability, and analyzes meteorological drought in Bilate River Basin. The Bilate River Basin includes the portion of SNNPRS regional zones; Hadiya, Kanibate Tembaro, Gurage, Silte, Wolaita, Sidama, and Alaba special woreda and small parts of the South-central Oromiya Regional states. The analysis was done based on historical recorded rainfall data, 26 to 40 years (1974-2013) and ENSO data. Rainfall variability were analyzed through using basic statistics like mean, standard deviation, and coefficients of variation and trend were analyzed by non-parametric Mann-Kendall test methods. From the analysis Butajira both in Belg and Kiremt season rainfall were significant at I±=.1, I±=.05, I± =.01 level with critical statistic table value 1.645, 1.96, and 2.576 respectively. In addition to this, in Shone annual and Belg seasons were significant. In the study area El NiA±o enhances rainfall activities and La NiA±a periods lowering rainfall.

Innovative Trend Analysis of Annual and Seasonal Rainfall Variability in Amhara Regional State, Ethiopia

This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen’s slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = −0.37) and Adet (Z = −0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980–2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies.

Characteristics of Seasonal Rainfall and its Distribution Over Bale Highland, Southeastern Ethiopia

Agricultural productivity heavily depends on onset and cessation of rainfall and Length of Growing Period (LGP). Determining these variables is useful for early warning and preparedness. Therefore, the objective of this study was to show the onset, cessation and LGP of the seasons over Bale Highlands. Bale Highland is characterized by bi-modal rainfall types. In order to find Onset, Cessation and LGP of both Belg and Kiremt seasons, 30 years of rainfall data for periods of (1985 to 2014) in daily format from NMA (National Metrological Agency) Bale robe branch directorate was used. Additionally, for this study, 12 meteorological stations in the Bale Highlands were used. The study shows that there is high variability of onset and cessation in Belg season than kiremt season. The mean onset and mean cessation of Belg season over Bale Highland is March 28 and June 10 with mean standard deviation of 19 days, respectively. On the other hand, in kiremt season, mean onset and mean cessation were July 12 and October 31 with mean standard deviation of 16 and 12 days, respectively. During the major growing season (Kiremt) the mean LGP is 110 days with mean standard deviation of 19 days and for Belg season the mean LGP is 73 days with mean standard deviation of 26 days. The short in LGP and the variation of onset and cessation of the seasons will be considered by the concerned body to aware the local community on the onset and cessation as well as Length of growing period for both seasons. The result found more likely lead the traditional rain-fed agricultural practice in both seasons to shift to irrigation system.

Spatio-temporal variability and trends of precipitation and extreme rainfall events in Ethiopia in 1980–2010

This article summarizes the results from an analysis conducted to investigate the spatio-temporal variability and trends in the rainfall over Ethiopia over a period of 31 years from 1980 to 2010. The data is mostly observed station data supplemented by bias-corrected AgMERRA climate data. Changes in annual and Belg (March–May) and Kiremt (June to September) season rainfalls and rainy days have been analysed over the entire Ethiopia. Rainfall is characterized by high temporal variability with coefficient of variation (CV, %) varying from 9 to 30% in the annual, 9 to 69% during the Kiremt season and 15–55% during the Belg season rainfall amounts. Rainfall variability increased disproportionately as the amount of rainfall declined from 700 to 100 mm or less. No significant trend was observed in the annual rainfall amounts over the country, but increasing and decreasing trends were observed in the seasonal rainfall amounts in some areas. A declining trend is also observed in the number of rainy days especially in Oromia, Benishangul-Gumuz and Gambella regions. Trends in seasonal rainfall indicated a general decline in the Belg season and an increase in the Kiremt season rainfall amounts. The increase in rainfall during the main Kiremt season along with the decrease in the number of rainy days leads to an increase in extreme rainfall events over Ethiopia. The trends in the 95th-percentile rainfall events illustrate that the annual extreme rainfall events are increasing over the eastern and south-western parts of Ethiopia covering Oromia and Benishangul-Gumuz regions. During the Belg season, extreme rainfall events are mostly observed over central Ethiopia extending towards the southern part of the country while during the Kiremt season, they are observed over parts of Oromia, (covering Borena, Guji, Bali, west Harerge and east Harerge), Somali, Gambella, southern Tigray and Afar regions. Changes in the intensity of extreme rainfall events are mostly observed over south-eastern parts of Ethiopia extending to the south-west covering Somali and Oromia regions. Similar trends are also observed in the greatest 3-, 5- and 10-day rainfall amounts. Changes in the consecutive dry and wet days showed that consecutive wet days during Belg and Kiremt seasons decreased significantly in many areas in Ethiopia while consecutive dry days increased. The consistency in the trends over large spatial areas confirms the robustness of the trends and serves as a basis for understanding the projected changes in the climate. These results were discussed in relation to their significance to agriculture.

Seasonal predictability of Kiremt rainfall in coupled general circulation models

The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June–September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985–2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

Climate Projection Outlook in Lake Haramaya Watershed, Eastern Ethiopia

Smallholder farmers in Ethiopia generally face widespread problems driven by climate change. For this reason, the study of climate change at watershed level might be critical to solve the problem from its root. The study was conducted in Lake Haramaya Watershed, Eastern Ethiopia to project ad characterize the climatic condition of the coming thirty years (2020-2050). Thirty-four years of rainfall, maximum and minimum temperature baseline data were collected from National Meteorological Agency of Ethiopia. Whereas, thirty years (2020-2050) projected rainfall, maximum and minimum temperatures were downscaled from MarkSim web version for IPCC AR5 data (CMIP5) using five climate models namely: BCC-CSM1-1, CSIRO-Mk3-6-0, HadGEM2-ES, MIROC-ESM, MIROCESM- CHEM, and MIROC5 under two Representative Concentration Pathways (RCPs): RCP4.5 and RCP8.5. The results of the study revealed that the annual mean rainfall will be increased by 20.70 and 24.14% under RCP4.5 and RCP8.5, respectively compared to baseline average value of 777.51 mm/yr. The annual rainfall under RCP4.5 ranges from 769.6 to 1090 mm/yr having the CV value of about 11%; whereas, under RCP8.5, it will range from 771.9 to 1129 mm/yr with the CV value of 13.17%. Kiremt (JJAS) season rainfall will increase from the baseline of 107.55 mm/yr to 135.79 and 136.27 mm/yr under RCP4.5 and RCP8.5, respectively. Moreover, a study indicated that the annual and seasonal temperature under RCP4.5 and RCP8.5 will be expected to increase during 2020-2050 period. Under high emission scenario of RCP8.5, the annual maximum temperature could rise from 24.73°C baseline to 25.41°C.

The El Ni\xf1o effect on Ethiopian summer rainfall

While El Niño is known to cause failure of Kiremt (boreal summer) rainfall in Ethiopia, the mechanisms are not fully understood. Here we use the ECHAM5 Atmospheric General Circulation Model to investigate the physical link between Pacific sea surface temperature (SST) anomalies and Kiremt rainfall. We compare ECHAM5 simulations forced with reconstructed SST data, to gauge-based rainfall observations and atmospheric reanalysis for the time period of 1961–2009. We perform composite analysis and sensitivity experiments driven only with equatorial Pacific SST anomalies. Our results show warm SST anomalies in the equatorial Pacific drive a corresponding large-scale circulation anomaly with subsidence over Ethiopia in dry Kiremt seasons. Horizontal wind fields show a slow-down of the whole Indian monsoon system with a weaker Tropical Easterly Jet and a weaker East African Low-Level Jet in these summers. These changes can be seen as an anomalous circulation cell over northern Africa with westerlies at 100–200 hPa and easterlies below 500 hPa. Surface easterlies might reduce the moisture inflow from the Atlantic and Congo basin into Ethiopia. This and the general subsidence over the region could explain the reduction in Kiremt rainfall. Our results suggest up to 50% of the Kiremt rainfall anomalies is driven by equatorial Pacific SST variability.

Analysis of rainfall trend and variability for agricultural water management in Awash River Basin, Ethiopia

The national economy and food security of many sub-Saharan countries relies on rain-fed agriculture, hence the impact of rainfall variability is highly significant. The intent of this study is to characterize rainfall variability and trend in Awash River Basin for agricultural water management using standard rainfall statistical descriptors. Long-term climate data of 12 stations were analyzed. Onset and cessation dates, length of growing period (LGP) and probability of dry spell occurrences were analysed using INSTAT Plus software. The Mann–Kendall test and the Sen's slope method were used to assess the statistical significance of the trend. The results show high variability of rainfall (38–73%), LGP (30–38 days) and high probability of dry spell occurrence (up to 100%) during the Belg season (the short rainy season from March to May) compared with the Kiremt season (the main rainy season from June to September) in all stations. Belg season showed a non-significant decline trend in most of the stations, whereas the Kiremt season indicated the contrary. The finding also revealed that supplementary irrigation is vital, especially in the Belg season to cover up to 40% of the crop water requirement deficit.

Spatial and temporal variability of dry spell lengths and indication of climate change in rainfall extremes at Tekeze River Basin, Ethiopia

Understanding weather extremes and climate variability both in space and time based on historical surface observed climate data at watershed is very crucial as it is used as in put for applying the seasonal forecast given by National Hydrological and Meteorological Agencies, in decision making in agricultural activities, water resources projects, rainfall-runoff modeling, and for drought risk identification and assessment. This study examined the spatio-temporal variability of dry spell length in Kiremt (June to September) season and trend detection, as a means of indication for climate change, in rainfall extremes over Tekeze river basin, Ethiopia. Daily rainfall indices were used over the basin based on data available from 24 meteorological stations having variable record length spanning from 1960-2009 with available data from 1992-2009 for most of the stations. Data quality control was done for infilling missing values and main quality tests of outliers and homogeneity tests. Temporal variability was analyzed by coefficient of variability and temporal trends were analyzed using Mann-Kendall method. Spatial distribution and variability was investigated using ordinary kirging interpolation technique. The results showed that: (1) The dry spell lengths for the months of kiremt season showed high temporal variability; (2) The dry spell lengths in the months of Kiremt season were shown to be higher in north-east and north-west of the river basin than the other parts; (3) The dry spell lengths were higher in the months of June and September and changed more rapidly in the basin than dry spell lengths in July and August; and (4) A significantly increasing trend on the 95th percentile of daily rainfall was found at Gonder meteorological station and significantly decreasing trend on the 90th percentiles of daily rainfall was found at Mekelle meteorological station. Key words: Dry spell lengths, extreme rainfall, climate change, spatial variability.

Searching for evidence of changes in extreme rainfall indices in the Central Rift Valley of Ethiopia

Extreme rainfall events have serious implications for economic sectors with a close link to climate such as agriculture and food security. This holds true in the Central Rift Valley (CRV) of Ethiopia where communities rely on highly climate-sensitive rainfed subsistence farming for livelihoods. This study investigates changes in ten extreme rainfall indices over a period of 40 years (1970–2009) using 14 meteorological stations located in the CRV. The CRV consists of three landscape units: the valley floor, the escarpments, and the highlands all of which are considered in our data analysis. The Belg (March–May) and Kiremt (June–September) seasons are also considered in the analysis. The Mann-Kendall test was used to detect trends of the rainfall indices. The results indicated that at the annual time scale, more than half (57 %) of the stations showed significant trends in total wet-day precipitation (PRCPTOT) and heavy precipitation days (R10mm). Only 7–35 % of stations showed significant trends, for the other rainfall indices. Spatially, the valley floor received increasing annual rainfall while the escarpments and the highlands received decreasing annual rainfall over the last 40 years. During Belg, 50 % of the stations showed significant increases in the maximum number of consecutive dry days (CDD) in all parts of the CRV. However, most other rainfall indices during Belg showed no significant changes. During Kiremt, considering both significant and non-significant trends, almost all rainfall indices showed an increasing trend in the valley floor and a decreasing trend in the escarpment and highlands. During Belg and Kiremt, the CDD generally showed increasing tendency in the CRV.

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42), the Global Satellite Mapping of Precipitation (GSMaP_MVK+), and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN) at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain) and Kiremt (long rain) seasons, the TRMM did better than the others by far. However, during Bega (dry) season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

English

This study was conducted to investigate historical climate dynamics and the resultant risks at four sites (Meki, Melkassa, Miesso and Ziway) in the Central Rift Valley of Ethiopia. It involved analysis of rainfall and temperature data in the study areas. The results showed the existence of high inter-annual rainfall variability within seasons and sites. The number of rainy days exhibited a declining trend at Meki in both belg (FMAM) and kiremt (JJAS) seasons and an increasing trend at Melkassa in the belg season; while an increasing trend was observed at Miesso and Ziway in the kiremt season, and no change in trends was observed in the belg season at both sites. The minimum and maximum temperature showed an increasing trend at Miesso and Ziway, whereas no change was observed at Melkassa. As opposed to the cessation of the rainfall, onset dates of rainfall were highly variable at all sites. The median length of the growing period was found to be 101, 88, 118 and 104 days at Meki, Melkassa, Miesso and Ziway, respectively. The obtained results will certainly help the farming community and the agricultural sector to make a decision for the best management scheme in the central rift valley of Ethiopia. Key words: Climate change, risk, rainfall, temperature, crop production, Central Rift Valley, Belg, Kiremt.

Analysis of Climate Variability (ENSO) and Vegetation Dynamics in Gojjam, Ethiopia

This study analyses the regional climate variability, especially La Nina or El Nino Southern Oscillation events and their impact on rainfall variability and vegetation coverage. The temporal and spatial distributions of temperature, precipitation, and vegetation coverage have been investigated for the two agricultural productive seasons from (2000–2008), using data from 11 meteorological station and MODIS satellite data in Gojjam, Ethiopia. The normalized difference vegetation index (NDVI) is widely accepted as a good indicator for providing vegetation properties and associated changes for large spatial scale. The analyses indicated that climate variability is quite common particularly in the small rainy season, Belg and continues to affect the vegetation condition in the region. The statistical correlation analysis indicated that there is a strong positive correlation between NDVI and the seasonal rainfall in most years, whereas, the temperature increase decreases the vegetation coverage in both seasons. The effect of ENSO, climate variability has been high to the regional rainfall variability in mostly of the months or years. In the fully strong El Nino or La Nina episode years like 2000 and 2002 the SST and rainfall showed positive correlation with r2 values 0.75 and 0.63, respectively. The NDVI anomaly pattern is almost similar to that of the main documented precipitation and temperature anomaly pattern associated with ENSO. The spatial and temporal analyses of basic climate elements and NDVI values for the growing season showed that NDVI and rainfall are highly variable during the 9 years period. The ENSO analyses showed an increase in seasonal vegetation coverage during El Nino episodes contrasting to La Nina episodes. However, there has been a rainfall delay during El Nino episodes in the first one or two months of Kiremt season.

Regional perspective on rainfall change and variability in the central highlands of Ethiopia, 1978–2007

Rain-fed agriculture is the most common farming strategy in rural Ethiopia. A short rainy period called Belg (February–May) is caused by easterly winds from the Indian Ocean and a longer rainy season (Kiremt) which occurs between July and October is the result when the inter-tropical convergence zone (ITCZ) is located over the horn of Africa. The staple food is Injera preferably made from Tef (Eragrostis tef) but it is common to mix it with other cereals like Sorghum or Barley. The aim of this study is to analyse regional differences in yearly precipitation, seasonal, variability, intensity and the start of the short and the long rainy in the central highlands during the period 1987–2007. The analysis is done by comparing the three decades between 1978 and 2007. Analyses of total rainfall, seasonal changes, rainfall variability and rainy days were conducted from daily rainfall data from seven stations. Daily temperature data from two stations were used to calculate potential evaporation. Rainfall results show an increase in the annual rainfall and also in Kiremt season. The Belg rainfall has, on the other hand, declined during the 30 year period that has been analysed. High rainfall variability, more extreme rainfall during the start of the Kiremt season and more rainy days during the Kiremt season were found. The Belg season shows an increase in temperature and potential evaporation as well. The possibility to grow cereal during Kiremt season is considered to be more or less the same during the past 30 years but in the last decade it has become impossible in the southern part of the study area due to a shortening of the Belg season. Cereal production is considered to be a bigger problem in the last decade around some rainfall stations especially in South Wollo where population numbers are high and land is under greater pressure than the southern areas of the study region.

Evaluation of reanalysis rainfall estimates over Ethiopia

AbstractThere 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

Rainfall change and its implications for belg harvest in south wollo, ethiopia

Most farmers in the Ethiopian highlands depend on rain‐fed agriculture. Some areas have the favourable situation of having two rainy seasons, Belg (February‐May) and the long rainy season Kiremt (June‐October), which is the case in some parts of South Wollo. Tef (Eragrostis tef) is the staple crop that farmers prefer to grow and the 90‐day variety is suitable for growing during the short rainy season. One out of eight Ethiopians lives in tef potential areas which have Belg rainfall. The aim in this study is to analyse rainfall variation in South Wollo, in particular the area east of the small town of Hayk, and to study its effect on the ability to grow tef during the Belg season. Results from interviews showed that a more difficult farming situation had emerged during the past 40 years, largely due to deterioration of physical resources such as rainfall. Rainfall is analysed by comparing daily rainfall data from four stations in two periods, 1963 to 1982 and 1984 to 2003, for changes in totals, seasonal distribution and variability. Coefficient of variance, rainy days, rainfall intensity and dry spells were analysed. Results from this study show that there have been minor rainfall changes but greater rainfall variability. During fieldwork key informants were asked if they were able to harvest tef during the past nine years, a period that has been used in a model of rainfall influence on tef cultivation during the Belg season. In both 20–year periods, farmers were able to grow tef every second year. In spite of a greater variability in rainfall the farmers proved their knowledge and flexibility and were able to harvest tef in the same number of years during both periods.

Interannual Variability and Ensemble Forecast of Upper Blue Nile Basin Kiremt Season Precipitation

AbstractEthiopian agriculture and Nile River flows are heavily dependent upon the Kiremt season (June–September) precipitation in the upper Blue Nile basin, as a means of rain-fed irrigation and streamflow contribution, respectively. Climate diagnostics suggest that the El Niño–Southern Oscillation phenomenon is a main driver of interannual variability of seasonal precipitation in the basin. One-season (March–May) lead predictors of the seasonal precipitation are identified from the large-scale ocean–atmosphere–land system, including sea level pressures, sea surface temperatures, geopotential height, air temperature, and the Palmer Drought Severity Index. A nonparametric approach based on local polynomial regression is proposed for generating ensemble forecasts. The method is data driven, easy to implement, and provides a flexible framework able to capture any arbitrary features (linear or nonlinear) present in the data, as compared to traditional linear regression. The best subset of predictors, as determined by the generalized cross-validation (GCV) criteria, is selected from the suite of potential large-scale predictors. A simple technique for disaggregating the seasonal precipitation forecasts into monthly forecasts is also provided. Cross-validated forecasts indicate significant skill in comparison to climatological forecasts, as currently utilized by the Ethiopian National Meteorological Services Agency. This ensemble forecasting framework can serve as a useful tool for water resources planning and management within the basin.