Journal of Environmental Science and Agricultural Research

Spatiotemporal Rainfall Analysis of El Nino, Neutral and La Nina Years Across Belg and Kiremt Seasons Over Oromia Region Ethiopia 

Gezahegn Mergia Tullu

Ethiopian Meteorology Institute, Eastern and Central Oromia Meteorological Service Centre, Ethiopia

Corresponding author
Gezahegn MergiaTullu, Ethiopian Meteorology Institute, Eastern and Central Oromia Meteorological Service Centre, Ethiopia.

ABSTRACT
ENSO is the primary natural hazard that contributes to food insecurity and poverty. It has been influencing countries’ climatic regimes for decades, bringing frequent floods and droughts. There is limited knowledge on El Niño and La Niña occurrences that affect agricultural activities in the Oromia Region and occur during the Belg and Kiremt seasons when rainfall is distributed. Evaluating the spatiotemporal rainfall performance of ENSO years spanning Belg and Kiremt seasons rainfall distribution over the research area is the primary goal. For the study’s spatial and temporal analyses, satellite rainfall data from 1981 to 2021 was obtained from CHG-UCSB and https://earlywarning.usgs.gov/fews/ewx_lite/index.html, respectively. The study’s findings demonstrated a substantial association between the Belg and Kiremt seasons spanning El Niño and La Niña periods, with a range of correlation values indicating a weak, moderate, and strong relationship. Because of the spatial and temporal dynamics of this study area, ENSO phases indicate that exceptionally dry years are probably linked to El Niño occurrences in the region, whereas extraordinarily rainy years are likely linked to La Niña events. Seasonal rainfall performance and rainfall variability are impacted by ENSO events and other regional systems, with both positive and negative effects observed throughout the research area. In addition to examining the ENSO (Neutral, El Niño, and La Niña) that have a major impact on the seasonal rainfall performances in the Oromia region, this study also looked at the water availability, yield production, pastoralist and agro-pastoralist activities, and water availability. In summary, the results of this research can help us better understand the mechanisms underlying regional ENSO events and their causes, which will be especially useful when future climate conditions change.

Keywords: Belg, Kiremt, Rainfall, El Niño, La Niña

Introduction
Global climate anomalies El Niño-Southern Oscillation (ENSO) and other global climatic anomalies cause fluctuation in the agro-climate factors that affect vegetation condition and account for one-third of the variability in yearly crop production, which varies depending on crop type and location [1]. One of the most important processes in the Earth’s climate system that accounts for variations in sea surface temperatures (SST) in the tropical Pacific is the ENSO. Although they may have an impact worldwide, these differences influence tropical weather patterns [2]. ENSO occurs in three stages: El Niño, La Niña, and Neutral. El Niño occurs when SSTs in the central and eastern Pacific are much warmer than usual, while La Niña occurs when SSTs are somewhat cooler than usual. When the SSTs in the equatorial Pacific are almost average and neither El Niño nor La Niña develops, the state is referred to as neutral.

Cirino et al state that ENSO is characterized by a fluctuating transition between a neutral phase and two extreme phases, such as El Niño and La Niña [3]. Under the El Niño phase, the eastern and central equatorial Pacific region experiences a deep layer of warm ocean water in contrast to El Niño, the east-central equatorial Pacific experiences a deep layer of colder-than-average water temperatures [4]. Over the tropical Pacific region of 5°S - 5°N and 150°W - 90°W, Sea Surface Temperature anomaly (SSTa) and the index values of each month have been considered [5].

The primary environmental hazard that contributes to food insecurity and poverty is ENSO, which has been altering the climate regime of Eastern Africa by frequently producing drought in recent decades [6]. During the El Niño phase, higher sea surface temperatures warm the atmosphere, increasing convection and rainfall over Eastern Africa [7]. Rainfall variability over Ethiopia is caused by remote teleconnections systems, and ENSO events and other regional systems have an impact on seasonal rainfall performance [8-11].

El Niño ENSO phases are often linked to reduced stream flow in Ethiopia, while La Niña phases are linked to increased stream flow [12,13]. La Niña episodes are more likely to happen in extraordinarily wet years than in severely dry years in Ethiopia, according to 3]. Ethiopia experiences significant seasonal and temporal rainfall variability due to its topography and geographic location [14]. Rainfall can change temporally over time intervals ranging from days to decades, depending on the direction and size of trends spanning regions and seasons [15,16]. The seasonal cycle, quantity, beginning and ending periods, and duration of the growing season are among the spatial variances in rainfall [17]. Furthermore, these spatiotemporal variations in rainfall are caused by the different elevations in the Oromia area of Ethiopia [11,14].

Nonetheless, Ethiopia, including the Oromia region, experiences significant interannual and inter-seasonal volatility in its rainfall. The development of a thermal low over South Sudan, the generation and propagation of disturbances over the Mediterranean Sea, sometimes in conjunction with easterly waves, the development of high pressure over the Arabian Sea, the interaction between mid-latitude depressions and tropical systems accompanied by troughs and the subtropical jet, and the sporadic development of the Red Sea convergence zone (RSCZ) are the main rain-bearing systems during the Belg season [8,18]. However, the major rainy season, known as Kiremt (JJAS), spans from June to September. Major systems that produce rain during the Kiremt season include the ITCZ migrating northward, the Arabian and South Sudan thermal low developing and persisting along 20oN latitude, the development of quasi-permanent high pressure systems over the South Atlantic and South Indian Oceans, the formation of a low-level Somali jet that enhances low-level south westerly flow, and the development of tropical easterly jets [8,17]. 

Different authors have given different ratings to the impact of rainfall (ENSO events) on agricultural productivity in sub-humid regions. The risk related to climate variability has an immediate impact from the start of land preparation to the end of harvest [19,20]. The amount, time distribution, and geographic coverage of rainfall are the main elements impacting agricultural activity during the main rainy season. Getachew and Tesfaye state that crop yields and the crops that are grown are determined by the unpredictable rainfall patterns, which include the commencement and cessation dates and distribution of rainfall, necessitating careful management [21]. According to Belay, changes in rainfall can affect agricultural production either directly or indirectly by affecting the growth and development of vegetation, the emergence and spread of crop pests, livestock diseases, the frequency and distribution of unfavorable weather, the availability of water, and the severity of soil erosion [22]. Kiremt rainfall is frequently less variable than Belg rainfall, despite the fact that rainfall variability has historically been a major barrier to Ethiopian agriculture in the Oromia region [23-25]. The variability of Belg rainfall has a bigger effect on agriculture [26]. 

Thus, the objective of this research is to promote scientific knowledge regarding the effects of El Niño and La Niña phenomena on seasonal rainfall performance (Belg and Kiremt) over the Oromia region. Decision-makers’ issues simply assign grades to individuals and communities without considering how varied seasonal rainfall patterns caused by ENSO occurrences affect agricultural practices and productivity. The knowledge and gaps in the topic area are filled in by the findings of earlier national and regional investigations. Developing effective mitigation and adaptation measures need this knowledge in order to increase community resilience to climate change. Understanding how ENSO affects the rainfall distribution performance of the Belg and Kiremt seasons is necessary to develop an innovative pattern that will be included into agricultural operations to address climate change challenges in the future.

Study Area
The study region is 34.1371° to 42.9822° E longitude and 3.5119° to 10.3897° N latitude. The entire area covered was estimated to be 353,690 km2 [27,28]. It shows a great deal of physiographic heterogeneity in addition to high, rocky mountain ranges, undulating plateaus, gorges, deeply incised river basins, and rolling plains [27]. There is a range of 343 meters to 4238 meters above sea level. Small-scale farming provides the majority of the region’s population with a living [28,29]. Agriculture depends on the right amount, timing, distribution, and duration of rainfall [28,29]. The primary crops grown in the region include beans, peas, wheat, barley, teff, maize, and other types of oil seeds. The region’s principal rivers are Awash, Wabe-Shebele, Genale, Gibe, Baro, Dedessa, and Guder, to name a few. Bishoftu, Kuriftu, Ziway, Abiyata, Shala, and Langano are further significant lakes [30].

Data and Methodology
Data Sources 
For the Belg (FMAM) and Kiremt (JJAS) seasons, long-term data were acquired from the Early Warning System Network (FEWS NET) to characterize the spatial and temporal analysis of Neutral, El Niño, and La Niña situations (weak, moderate, and strong). The gridded rainfall estimate created in near-real time with a spatial resolution of 0.05 degrees (0.05◦ x 0.05◦) or (~5km) is derived from the satellite data products of Climate Hazards Group Infra-Red Precipitation with Stations (CHIRPS), a time series spanning from 1981 to 2021. The source of the data for the spatial rainfall climatology and the light, moderate, and strong El Niño, La Niña conditions for the Belg (FMAM) and Kiremt (JJAS) seasons is https://data.chc.ucsb.edu/products/CHIRPS-2.0/. The source of the monthly rainfall time series data for the study area, which is 10 km × 10 km and has a spatial resolution of 0.1 degree, is https://earlywarning.usgs.gov/fews/ewx_lite/index.html. 

Methodology
The seasonal rainfall data for Belg (FMAM) and Kiremt (JJAS) CHIRPS from 1981 to 2021 were chosen for analysis in this work and were imported into GeoCLIM Tool using CHIRPS-Prelim in the ire_ppt_dekad.climdata format. When using GeoCLIM, the spatial interpolation technique is straightforward; either the Simple (idw_s) or Ordinary (idw_s) inverse distance weighting (IDW) algorithm could be applied during the process. Tools like the Python tool for the output temporal rainfall analyzed of the Belg-FMAM and Kiremt-JJAS seasons over the study area and the GeoCLIM software for the spatial rainfall analysis were utilized in this work.

Results and Discussion
Warm ENSO periods (El Niño years) are generally associated with lower precipitation and drought years in many parts of Ethiopia, whereas cold times (La Niña years) are associated with larger quantities of precipitation. The findings demonstrate a substantial association between the Belg and Kiremt seasons in the Oromia region and the spatial study of seasonal rainfall distribution and ENSO (Neutral, El Niño, and La Niña occurrences). Positive and negative rainfall anomalies in Ethiopia are caused by the opposite SST anomalies. Based on the spatial and temporal series of this research region, ENSO phases indicate that exceptionally dry years are probably linked to El Niño events, whereas exceptionally rainy years are probably linked to La Niña events. The following scenarios are examined together with their noteworthy positive and negative effects on the distribution of seasonal Belg and Kiremt rainfall. Rainfall variability over Ethiopia is caused by remote teleconnections systems, and ENSO events and other regional systems have an impact on seasonal rainfall performance [8-11].

Spatial Rainfall Analysis of Belg and Kiremt Seasons with ENSO Phenomenon
For the majority of Ethiopia, with the exception of the southern and southeast lowlands, belg is the brief rainy season. It spans the months of February through May. Throughout the season, there is significant seasonal variation in the volume and distribution of rainfall as well as high maximum temperature values. In comparison to the Kiremt rains in the area, the Belg (FMAM) rains (February-May), often referred to as the short rains, are frequently linked to less consistent rainfall and higher regional variability (erratic rainfall distribution). There are years when the Belg rains produce very little rainfall, particularly during El Niño episodes.
 
The region has significant variations in rainfall within a single year. The annual rainfall distribution in Western Oromia is mono-modal and reaches its maximum in July and August. Rainfall is the predominant weather pattern in this area from April through November. A slightly bimodal yearly rainfall pattern is seen in Central Oromia, where June through September is when the primary rainy season occurs. The shorter period of precipitation falls in March through May. June through September is the primary rainfall period in the annual rainfall pattern over eastern Oromia, which likewise exhibits a bimodal pattern. In comparison to central Oromia, the shorter rainy period which spans from March to May has a larger rainfall peak. There is a distinct bimodal rainfall pattern in Southern Oromia, with two periods of rain followed by a dry spell. March through May is the primary rainy season; September through December is the second rainy season [30].

Belg Season Spatial Rainfall Analysis of El Niño and La Niña Years
Spatial rainfall analysis of El Niño-Belg (FMAM) across strong, moderate and weak El Niño showed that in the Figure below. Rainfall climatology of El Niño-Belg found between 400 mm up to 750 mm over Guji, few parts of Borena, southeast of Bale, Jimma and few parts of Ilubabor in different rainfall magnitudes (Figure 3 (a)). The rest zones have got below 300 mm rainfall distribution over the region. The rainfall distribution of El Niño FMAM has shown us in the Figure below a slight increment over all of Oromia region compare to mean rainfall of La Niña JJAS with the magnitude (Figure 3 (a) and (e)). At strong El Niño-Belg means rainfall has high rainfall amount and distribution than moderate and weak El Niño-Belg. In nature the effect of El Niño event has positive impact on Belg rainfall distribution over Oromia region. Weak El Niño-FMAM has better mean rainfall distribution than moderate El Niño FMAM in spatial area coverage of time scale over study area (Figure 3 (b) and (c)). From the result of study area, spatial analysis of La Niña-Belg, Strong, Moderate and Weak La Niña showed that in the Figure below in spatial coverage and distribution (Figure (e), (f), (g), (h)). The result of spatial analysis of the Figure shown as below, strong La Niña-Belg mean rainfall distribution between 400 mm up to 500 mm over some parts of Ilubabor, Jimma, few parts of east Wellega, most parts of Bale, few parts of Guji and Borena; and across 500 mm to 750 mm over few parts of Ilubabor, few parts of Bale and some parts of Guji in different rainfall distribution (Figure 3 (h)). Over north Showa and some parts of east Showa have got below 200 mm across strong La Niña-Belg season. At weak La Niña-Belg rainfall climatology was almost similar to moderate La Niña-Belg with the magnitudes at (Figure 3 (f)) and (Figure 3 (g)) respectively the region.

Kiremt Season Spatial Rainfall Analysis of El Niño and La Niña Years
Spatial rainfall analysis of El Niño-Kiremt, Weak, Moderate and Strong El Niño showed that in the Figure below over the study area with different rainfall magnitudes and the rainfall distribution decline in El Niño-Kiremt events. Mean rainfall El Niño-Kiremt show that between 1000 mm up to 1250 mm over west and east Wellega, few parts of Kelem Wellega, Ilubabor, some parts of Jimma, few parts of Horo Guduru and pocket area of west Showa (Figure 4 (i)). The rainfall distribution has shown us in the Figure below a decrement at south and southeast Oromia region due to short rainy season (JJAS). At strong El Niño-Kiremt means rainfall has less rainfall amount and distribution than moderate and weak El Niño-Kiremt. Weak El Niño-Kiremt has better mean rainfall distribution with the rainfall magnitudes (Figure 4 (j)). From the result of study area, spatial analysis of La Niña-Kiremt, Strong, Moderate and Weak La Niña showed that in the Figure below high in the strength of rainfall amount and distribution in most of Oromia region except Borena, most parts of Guji, south and southeast Bale; few parts of east Harerghe expected less rainfall. From the result study area analysis of the Figure shown as below, strong La Niña-Kiremt mean rainfall distribution in spatial area coverage extended across 1000 mm up to 1500 mm over west and east Wellega, few parts of Kelem Wellega, Ilubabor, Jimma, few parts of Horo Guduru and at pocket areas west Showa (Figure 4 (p)). At moderate La Niña-Kiremt means rainfall was slightly decrease than to strong La Niña-Kiremt with different rainfall magnitudes (Figure 4 (o)) and (Figure 4 (p)) respectively over Oromia region.

Temporal Rainfall Analysis of Belg and Kiremt Seasons for Neutral, El Niño and La Niña (Weak, Moderate and Strong) Years
The graph below shows that the rainfall pattern over the region across ENSO (Neutral, El Niño and La Niña) events including the strength of event at different magnitudes for FMAM and JJAS seasons. The graph that explains the influence of the ENSO phases (Normal, El Niño, and La Niña) over rainfall distribution of the region provided Figure 5 below with seasonal Belg-FMAM and Kiremt-JJAS in time series analysis. 

The relationships of normal, El Niño and La Niña years with Belg (FMAM) and Kiremt (JJAS) seasons rainfall distribution at different strength were presented in (Figure 5). In this figure, the amounts and distribution of weak El Niño (wk-EL) Belg rainfall (92 mm) was slightly higher than El Niño events during moderate El Niño (mod-EL) Belg rainfall (74 mm) and strong El Niño (strg-EL) phase (90 mm). In case of moderate La Niña (mod-La) event of rainfall strength show that better performance than weak La Niña (wk-LA) and strong La Niña (strg-La) phase with the magnitudes of 85 mm, 82 mm and 84 mm respectively (Figure 5). In general the performance of rainfall amount and distribution across El Niño Belg season was better than La Niña Belg season in the magnitudes as well as rainfall in spatial area coverage over the region (south and southeast Oromia region). The seasonal (FMAM) rainfall in nature erratic and varies with respect to normal, weak, moderate and strong precipitation occurred during El Niño and La Niña states on the graph shown in (Figure 5). 

From the result, at the season of Kiremt (JJAS) rainfall amount and distribution examined the association across strong La Niña (strg-La), moderate La Niña (mod-LA), weak La Niña and Neutral years the region. In Kiremt season the rainfall amount and distribution increase in area and spatial coverage across the La Niña events enhance the rainfall than El Niño events decline the seasonal rainfall. The rainfall distribution of Kiremt (JJAS) season across strong La Niña (strg-La) event was higher than moderate La Niña (mod-LA) and weak La Niña (wk-LA) with the magnitudes of 136 mm, 132 mm and 127 mm respectively over study area (Figure 5). 

However, we calculated the deviation from normal by averaging all above and below normal rainfall and comparing them to determine the influence of the strong La Niña events (strg-La) and moderate La Niña (mod-LA) with the magnitudes of 136 mm and 132 mm respectively, based on strength. Our results are similar to the notion of strong El Niño (strg-EL) being associated with below-average rainfall (115 mm), while strong La Niña (strg-La) associated with above-average rainfall (136 mm) which shown in (Figure 5) of Kiremt (JJAS) season. The influence of starting dates of the La Niña seasons were noted with respect to flood or extreme flood conditions, and when La Niña started in Kiremt June-July-August-September (JJAS) season, so there is a maximum chance for flood or extreme flood to occur. Whereas the influence of El Niño noted with respect to dry spell occurrence and drought conditions over the study area.

In the result of study area the correlation between Belg and Kiremt seasons across El Niño and La Niña events (weak, moderate and strong) showed a variation of correlation values measures the relationship between the two seasons. A correlation coefficient of zero means that the seasons have no impact on one another-increases or decreases in one season have no consistent effect on the other. A correlation coefficient of +1 indicates a perfect positive correlation, which means that as a season Kiremt increases, season Belg increases at the same rate. A correlation value -1, meanwhile, is a perfect negative correlation, which means that as a season Kiremt increases, season Belg decreases at the same rate. Correlation analysis may also return results anywhere between -1 and +1, which indicates that seasons (Kiremt and Belg) changes at similar but not identical rates.

Correlation value between neutral FMAM and neutral JJAS show that an increment with the value of -0.5101, it means the two seasons in neutral events have a high degree of negative correlation value (Table 1). A correlation value between moderate El Niño FMAM and moderate El Niño JJAS show that an increment with the value of 0.8479, it means the two seasons in moderate El Niño events have a high degree of positive correlation value. So the seasons in moderate El Niño event increases or decreases, the other season increases or decreases in the same manner. In Table 1 show that the correlation between moderate La Niña FMAM and moderate La Niña JJAS indicated the correlation value of -0860; and a correlation between strong La Niña FMAM and strong La Niña JJAS seasons of -0987, have low degree of negative correlation value

Discussion
The results indicate that most of the Belg (FMAM) and Kiremt (JJAS) seasons deficit rainfall amount and distribution during El Niño period and excess rainfall amount during La Niña period than mean rainfall over study area. El Niño Phases slight increase the rainfall distribution over Belg (FMAM) season with different rainfall magnitudes from one to other Oromia zones. In case of La Niña phases the rainfall amount and distribution enhanced over Kiremt (JJAS) season with different strength of rainfall from one place to another over study area. The largest risk of flood or extreme flood occurring was observed when La Niña started during the Kiremt June-July-August-September (JJAS) season. The influence of La Niña season starting dates on flood or extreme flood conditions was also identified. On the other hand, El Niño’s influence was observed on the prevalence of dry spells and drought conditions throughout the research area.

From the findings a correlation value between neutral FMAM and neutral JJAS show that an increment with the value of -0.5101 and high degree of negative correlation value (Table 1). A correlation value between moderate El Niño FMAM and moderate El Niño JJAS show that an increment with the value of 0.8479 and high degree of positive correlation value. The result showed that a correlation between moderate La Niña FMAM and moderate La Niña JJAS indicated the correlation value of -0860; and a correlation between strong La Niña FMAM and strong La Niña JJAS seasons of -0987, have low degree of negative correlation value.

A few studies addressed the local level effects of atmospheric circulation (e.g., geopotential height, wind velocity, and rapid warming), but the majority of previous studies concentrated on the large-scale effects of atmospheric circulation on the country’s summer rainfall [11,16,31]. Upper-level systems including the Subtropical Westerly Jet (STWJ) during small rainy and dry seasons and the Tropical Easterly Jet (TEJ) and African Easterly Jet (AEJ) during the major rainy season also affected Ethiopian rainfall, particularly that of the Oromia area [32].The intensity and distribution of the seasonal rainfall in the area are determined by the movement of the Inter Tropical Convergence Zone (ITCZ) [31].
 
El Niño, La Niña, and neutral ENSO states have all had an impact on the rainy or dry season. Numerous studies have examined the effects of ENSO on Ethiopian rainfall [8,17,33-39]. The majority of these documents demonstrated that over north and central Ethiopia, the warm phase of ENSO (El Niño) is linked to decreased precipitation during the main wet season (JJAS). Severe drought and occasionally famine may result from it. Conversely, it increases rainfall during the FMAM and ONDJ seasons, mostly affecting different regions of Ethiopia. Conversely, La Niña has the opposite effects on seasonal rainfall—drought in FMAM and flooding in JJAS. Furthermore, different parts of the region experience varying rainfall characteristics due to large-scale phenomena like ENSO. This suggests that more research is required to ascertain the extent to which ENSO influences local precipitation, which significantly affects the distribution and amount of seasonal rainfall in various zones and locations. To better assess how atmospheric circulation can affect the interaction between ENSO and other factors such as national, regional, zonal, etc., more research is required. 

Every indication has intrinsic advantages and disadvantages of its own, and its usefulness is frequently adapted to a particular application or process of decision-making. Based on the three stages of ENSO’s performance for drought and wet monitoring across the Oromia region between 1981 and 2021, the study used these phases to identify the distribution of normal, deficiency, and excess seasonal rainfall. The research area is affected negatively or positively by ENSO (El Niño, Na Nina, and Neutral) phases during the Belg and Kiremt seasons.

Conclusion
The results concluded that the ENSO Phases (neutral, El Niño and La Niña events) have an impact on seasonal (Belg and Kiremt) rainfall amount and distribution with different rainfall magnitudes over study area. From the findings a correlation value between neutral FMAM and neutral JJAS show that an increment with the value of -0.5101 and a correlation value between moderate El Niño FMAM and moderate El Niño JJAS show that an increment with the value of 0.8479 and high degree of positive correlation value. The result showed that a correlation between moderate La Niña FMAM and moderate La Niña JJAS indicated the correlation value of -0860; and a correlation between strong La Niña FMAM and strong La Niña JJAS seasons of -0987, have low degree of negative correlation value over study area.

In this study, Belg (FMAM) and Kiremt (JJAS) scales were used to analyze rainfall spatially and time series on neutral, El Niño (weak, moderate, and strong) and La Niña (weak, moderate, and strong) events across both seasons. Possible trends were also investigated, and their positive and negative significance over the study area was detected. In addition, studies were conducted on the ENSO (Neutral, El Niño, and La Niña), which has a major impact on the seasonal rainfall in the Oromia region, yield production, water availability, pastoralists and agro-pastoralists, and several other activities. The distribution and amount of seasonal (Belg and Kiremt) rainfall over the research area are influenced by the ENSO Phases, which are El Niño and La Niña events. Overall, this study’s findings can deepen our understanding of the mechanisms that cause zonal ENSO events and aid in improving ENSO event monitoring and prevention, especially as future climatic circumstances change. As a result, our water resources may be planned and managed more sustainably over the course of the research area.

Further investigation needed on ENSO events, in order to improve crop production, water availability, irrigation management, soil conservation, crop variety selection, pastoralist and agro pastoralist, and other aspects. It is advised that farmers and sectors pay attention to weather and climatic information provided by meteorological forecasts, early warning, and agro-meteorology advisory services. It is also necessary to conduct additional research on how ENSO events impact the seasonal rainfall, including the use of several El Niño and La Niña events to determine the strength and intensity of seasonal rainfall over time at the woreda, regional, and national levels.

Data Availability: The data is available as request.

Ethical Statement: The author declare that he has no known competing financial interests or personal relationships that could has appeared to influence the work reported in this paper. 

References

1. Ray DK, Gerber JS, MacDonald GK, West PC. Climate variation explains a third of global crop yield variability. Nat Commun. 2015. 6: 5989. 
2. Hanley DE, Bourassa MA, O’Brien JJ, Smith SR, Spade ER. A quantitative evaluation of ENSO indices. J Clim. 2003. 16: 1249-1258.
3. Cirino PH, Féres JG, Braga MJ, Reis E. Assessing the impacts of ENSO-related weather effects on the Brazilian agriculture. Procedia Economics and Finance. 2015. 24: 146-155.
4. Trenberth KE. “The definition of El Niño.” Bulletin of the American Meteorological Society. 1997. 78: 2771-2777.
5. Rasmusson EM, Carpenter TH. The relationship between eastern equatorial 464 Pacific sea surface temperatures and rainfall over India and Sri Lanka. Monthly Weather Review. 1983. 111: 517-528.
6. Qu C, Hao X, Qu JJ. Monitoring extreme agricultural drought over the horn of Africa (hoa) using remote sensing measurements. Remote Sens. 2019. 11: 902.
7. Mulenga H, Rouault M, Reason C. Dry summers over northeastern South Africa and associated circulation anomalies. Clim Res. 2003. 25: 29-41. 
8. National Meteorological Services Agency NMA. Climate and agro climatic resources of Ethiopia. Meteorological Research Report Series. 1996. 1: 1-37.
9. Gissila T. Rainfall Variability and Teleconnections over Ethiopia. MSc thesis (Meteorology) University of Reading UK. 2001. 109
10. Korcha D. Seasonal rainfall Prediction of Ethiopia for the Periods of September-December. DMC. 2002.
11. Korecha D, Barnston A. Predictability of June-September rainfall in Ethiopia. American Meteorological Society. 2007. 135: 625-650. 
12. Zaroug MAH, Eltahir EAB, Giorgi F. Droughts and floods over the upper catchment of the Blue Nile and their connections to the timing of El Niño and La Niña events. Hydrol Earth Syst Sci. 2014. 18: 1239-1249.
13. Abtew W, Melesse AM, Dessalegne T. El Niño-Southern Oscillation link to the Blue Nile River Basin hydrology. Hydrol Processes. 2009. 23: 3653-3660. 
14. Gamachu D. Some patterns of altitudinal variation of climatic elements in the mountainous regions of Ethiopia. Mountain Research and Development. 1988. 131-138.
15. Jury MR, Funk C. Climatic trends over Ethiopia: regional signals and drivers. International Journal of Climatology. 2013. 33: 1924-1935.
16. Seleshi Y, Zanke U. Recent changes in rainfall and rainy days in Ethiopia. International Journal of Climatology: A Journal of the Royal Meteorological Society. 2004. 24: 973-983.
17. Segele ZT, Lamb PJ. Characterization and variability of Kiremt rainy season over Ethiopia. Meteorology and Atmospheric Physics. 2005. 89: 153-180.
18. Gonfa L. Climatic Classification of Ethiopia NMSA. Addis Ababa, Ethiopia. 1996.
19. Akinseye F, Ajayi V, Oladitan T. Assessing the impacts of climate variability 374 on crop yield over Sudano- Sahelian zone in Nigeria. Access Int J Agric Sci. 2013. 1: 91-98. 
20. Mesike CS, Esekhade TU. Rainfall variability and rubber production in Nigeria Mesike. African J Environ Sci Technol. 2014. 8: 54-57.
21. Getachew H, Tesfaye K. Analysis of risks in crop production due to climate change in the Central Rift Valley of Ethiopia. African J Agric Res. 2015. 10: 1913- 1922.
22. Belay AS, Fenta AA, Yenehun A, Nigate F, Tilahun SA, et al. Evaluation and application of multi-source satellite rainfall product CHIRPS to assess spatiotemporal rainfall variability on data-sparse western margins of Ethiopian highlands. Remote Sens. 2019. 11: 1-22. 
23. Bewket W, Conway D. A note on the temporal and spatial variability of rainfall in the drought prone Amhara region of Ethiopia. Int J Climatol. 2007. 1467-1477.
24. Ayalew D, Tesfaye K, Mamo G, Yitaferu B, Bayu W. Variability of rainfall and its current trend in Amhara region, Ethiopia. African J Agric Res. 2012. 7: 1475-1486.
25. Mengistu D, Bewket W, Lal R. Recent spatiotemporal temperature and rainfall variability and trends over the Upper Blue Nile River Basin, Ethiopia. Int J Climatol. 2014. 34: 2278-2292.
26. Abebe. The onset, cessation and dry spells of the small rainy season (Belg) of Ethiopia. National Meteorological Agency Addis Ababa Ethiopia. 2006.
27. FDRE. The State of Oromia (online). The Federal Democratic Republic of Ethiopia. 2008. 
28. Hussen A, Biru D, Yadessa B. Oromia National Regional State Program of plan on Adaptation to climate change Document Feburry, 2011 Finfinne. 2011.
29. Shikur ZH, Agricultural policies, agricultural production and rural households’ welfare in Ethiopia. J Econ Struct. 2020. 9: 1-21.
30. Dufera JA, Yate TA, Kenea TT. Spatiotemporal analysis of drought in Oromia regional state of Ethiopia over the period 1989 to 2019. Natural Hazards. 2023. 1-41.
31. Segele ZT, Lamb PJ, Leslie LM. Large-scale atmospheric circulation and global sea surface temperature associations with Horn of Africa June-September rainfall. Int J Climatol. 2009. 29: 1075-1100
32. Diro GT, DIF, Grimes E, Black A, O‘Neill, et al. Evaluation of reanalysis rainfall estimates over Ethiopia. Int J Climatol. 2009. 29: 67-78.
33. Degefu W. Some aspects of meteorological drought in Ethiopia. Drought and Hunger in Africa: Denying Famine a Future, MH Glantz, Ed. Cambridge University Press. 1987. 23-36.
34. Seleshi Y, GR Demarée. Rainfall Variability in the Ethiopian and Eritrean Highlands and its Links with the Southern Oscillation Index. Journal of Biogeography. 1995. 22: 945-952.
35. Bekele F. Ethiopian use of ENSO information in its seasonal forecasts, Internet J. Afr. Studies. 1997.
36. Camberlin P. Rainfall anomalies in the source region of the Nile and their connection with the Indian summer monsoon. J Climate. 1997. 10: 1380-1392.
37. Tsegay W. The case of Ethiopia: Impacts and responses to the 1997-98 El Niño event. Once Burned, Twice Shy? Lessons Learned from the 1997-98 El Niño, M. H. Glantz, Ed., United Nations University Press. 2001. 88-100.
38. Gissila T, E Black, DIF, Grimes, JM Slingo. Seasonal forecasting of the Ethiopian summer rains. Int J Climatol. 2004. 24: 1345-1358.
39. Diro GT, DIF, Grimes, E Black. Teleconnections between Ethiopian summer rainfall and sea surface temperature: part II. Seasonal forecasting. Clim Dyn. 2011. 37: 121-131.
40. Goddard L, AG Barnston, SJ Mason. Evaluation of the IRI’S “Net assessment” seasonal climate forecasts (1997-2001). Bulletin of American Meteorological Society. 2003. 84: 1761-1782.
41. Korecha, Anthony G, Barnston. Predictability of June-September Rainfall in Ethiopia, International research institute for climate and society. Palisades New York. 2007.