scholarly journals Impact of rainfall variability on crop yields and its relationship with sea surface temperature in northern Ethiopian Highlands

2021 ◽  
Vol 14 (22) ◽  
Author(s):  
Getie Gebrie Eshetie
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Crop Yields ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Ethiopian Highlands

scholarly journals Spatio-Temporal Variability and Trend of Rainfall and Its Association with Pacific Ocean Sea Surface Temperature in West Harerge Zone, Eastern Ethiopia

2020 ◽  
Author(s):  
Getachew Bayable Tiruneh ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw
Keyword(s):  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Variability ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Annual Rainfall ◽  
Eastern Ethiopia ◽  
Spatio Temporal ◽  
Annual Time

Abstract Background: Rainfall variability is a common characteristic in Ethiopia and it exceedingly affects agriculture particularly in the eastern parts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatio-temporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.Method: The coefficient of variation (CV) and standardized anomaly index (SAI) was employed to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by the Pearson correlation coefficient (r).Results: The annual rainfall CV ranges from 12-19.36% while the seasonal rainfall CV extends from 15-28.49%, 24-35.58%, and 38-75.9% for average Kiremt (June-September), Belg (February-May), and Bega (October-January) seasons, respectively (1983-2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends of rainfall were not statistically significant (α = 0.05), unlike November. The annual rainfall trends showed a non-significant decreasing trend. On a seasonal basis, the trend of mean Kiremt and Belg seasons rainfall was decreased. But, it increased in Bega season although it was not statistically significant. Moreover, the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, the correlation between rainfall and Pacific Ocean SST was negative at annual time scales.Conclusions: High spatial and temporal rainfall variability on monthly, seasonal, and annual time scales was observed in the study area. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall was increased annually and in the Bega season rather than other seasons. Generally, the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

scholarly journals Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

2014 ◽  
Vol 11 (3) ◽  
pp. 3111-3136 ◽  
Author(s):  
C. Funk ◽  
A. Hoell ◽  
S. Shukla ◽  
I. Bladé ◽  
B. Liebmann ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Southern Ethiopia ◽  
East African ◽  
Central Pacific ◽  
Boreal Spring ◽  
Central Indian Ocean

Abstract. In southern Ethiopia, Eastern Kenya, and southern Somalia, poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009, and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers implement disaster risk reduction measures while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts in that region to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we show that the two dominant modes of East African boreal spring rainfall variability are tied, respectively, to western-central Pacific and central Indian Ocean SST. Variations in these rainfall modes can be predicted using two previously defined SST indices – the West Pacific Gradient (WPG) and Central Indian Ocean index (CIO), with the WPG and CIO being used, respectively, to predict the first and second rainfall modes. These simple indices can be used in concert with more sophisticated coupled modeling systems and land surface data assimilations to help inform early warning and guide climate outlooks.

scholarly journals What is the Role of the Sea Surface Temperature Uncertainty in the Prediction of Tropical Convection Associated with the MJO?

2015 ◽  
Vol 143 (8) ◽  
pp. 3156-3175 ◽  
Author(s):  
Wanqiu Wang ◽  
Arun Kumar ◽  
Joshua Xiouhua Fu ◽  
Meng-Pai Hung
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Rainfall Variability ◽  
Lower Boundary ◽  
Ocean Model ◽  
Sea Surface ◽  
Climatic Data ◽  
Sst Variability ◽  
National Climatic Data Center ◽  
Convection Schemes

Abstract This study investigated the influence of the uncertainty in the sea surface temperature (SST) on the representation of the intraseasonal rainfall variability associated with the Madden–Julian oscillation (MJO) and how this influence varies with convection parameterization. The study was motivated by the fact that there exist substantial differences in observational SST analyses, and by the possibility that lacking sufficient accuracy for SSTs in dynamical models may degrade the MJO simulation and prediction. Experiments for the DYNAMO intensive observing period were carried out using the NCEP atmospheric Global Forecast System (GFS) with three convection schemes forced by three SST specifications. The SST specifications included the widely used National Climatic Data Center (NCDC) daily SST analysis, the TRMM Microwave Imager (TMI) SST retrieval, and an SST climatology that only contains climatological seasonal cycle. The experiments show that for all convection schemes, the advantage of using observed (TMI and NCDC) SSTs over the climatology SSTs can be seen as early as 5 days to 1 week after the start of the forecast. Further, the prediction with TMI SSTs was more skillful than that with the NCDC SSTs, indicating that the current level of SST uncertainties in the observational analyses can lead to large differences when they are used as the lower boundary conditions. The results suggest that the simulation and prediction can be improved with an atmosphere-only model forced by more accurate SSTs, or with a coupled atmosphere–ocean model that has a more realistic representation of the SST variability. Differences in the prediction among the convection schemes are also presented and discussed.

scholarly journals Spatiotemporal variability and trends of rainfall and its association with Pacific Ocean Sea surface temperature in West Harerge Zone, Eastern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Getachew Bayable ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw
Keyword(s):  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Seasonal Rainfall ◽  
Spatiotemporal Variability ◽  
Annual Rainfall ◽  
Eastern Ethiopia ◽  
Enso Events

Abstract Background Rainfall variability exceedingly affects agriculture in Ethiopia, particularly in the eastern region where rainfall is relatively scarce. Hence, understanding the spatiotemporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatiotemporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia. Method The coefficient of variation (CV) and standardized anomaly index (SAI) were used to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by Pearson correlation coefficient (r). Results The annual rainfall CV during 1983–2019 periods is between 12 and 19.36% while the seasonal rainfall CV extends from 15–28.49%, 24–35.58%, and 38–75.9% for average Kiremt (June–September), Belg (February–May), and Bega (October–January) seasons, respectively (1983–2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends were not statistically significant (α = 0.05), unlike in November. On a seasonal basis, the trends of mean Kiremt and Belg seasons rainfall decreased while it increased in Bega season although it is not statistically significant. Moreover, the annual rainfall showed a non-significant decreasing trend. The findings also revealed that the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, annual rainfall and Pacific Ocean SST was negatively correlated. Conclusions High spatial and temporal rainfall variability was observed at the monthly, seasonal, and annual time scales. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall decreased in the annual, Belg and Kiremt season while increased in the Bega season. The study also indicated that the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

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