Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

Abstract

Rainfall variability in Ethiopia has significant effects on rainfed agriculture and hydropower, so understanding its association with slowly varying global sea surface temperatures (SSTs) is potentially important for prediction purposes. We provide an overview of the seasonality and spatial variability of these teleconnections across Ethiopia. A quasi-objective method is employed to define coherent seasons and regions of SST-rainfall teleconnections for Ethiopia. We identify three seasons (March-May, MAM; July-September, JAS; and OctoberNovember, ON), which are similar to those defined by climatological rainfall totals. We also identify three new regions (Central and western Ethiopia, CW-Ethiopia; Southern Ethiopia, S-Ethiopia; and Northeast Ethiopia, NE-Ethiopia) that are complementary to those previously defined here based on distinct SST-rainfall teleconnections that are useful when predicting interannual anomalies. JAS rainfall over CW-Ethiopia is negatively associated with SSTs over the equatorial east Pacific and Indian Ocean. New regional detail is added to that previously found for the whole of East Africa, in particular that ON rainfall over S-Ethiopia is positively associated with equatorial east Pacific SSTs and with the Indian Ocean Dipole (IOD). Also, SST-to-rainfall correlations for other season-regions, and specifically for MAM in all regions, are found to be negligible. The representation of these teleconnections in the HadGEM2 and HadGEM3-GA3.0 coupled climate models shows mixed skill. Both models poorly represent the statistically significant teleconnections, except that HadGEM2 and the low resolution (N96) version of Had-GEM3-GA3.0 better represent the association between the IOD and S-Ethiopian ON rainfall. Additionally, both models are able to represent the lack of SST-rainfall correlation in other seasons and other parts of Ethiopia.

Evaluating the CMIP5 ensemble in Ethiopia: Creating a reduced ensemble for rainfall and temperature in Northwest Ethiopia and the Awash basin

“…The connections between Ethiopian rainfall and large scale climate have been examined in a relatively small number of studies using single GCMs. Jury and Funk (2013) used the GFDL model and Degefu et al (2017) used two different versions of the HadGEM2 model. Degefu et al (2017) found that there are teleconnections with the Nino3.4 region, the Indian Ocean Dipole (IOD), and central Indian Ocean sea surface temperatures (SSTs) in observations, but found that teleconnections simulated by the models were much weaker than observations.…”

“…Jury and Funk (2013) used the GFDL model and Degefu et al (2017) used two different versions of the HadGEM2 model. Degefu et al (2017) found that there are teleconnections with the Nino3.4 region, the Indian Ocean Dipole (IOD), and central Indian Ocean sea surface temperatures (SSTs) in observations, but found that teleconnections simulated by the models were much weaker than observations. They also found that the resolution of the models did not impact on the relative strength of these teleconnections.…”

“…However the ability of GCMs to reproduce the historical climate of Ethiopia has not been widely studied, possibly because of the unique climate characteristics of the country such as the complex rainfall seasonality which render it distinct from East Africa to the south, and the Sahel to the west. The model studies that have been done, focus on a particular rainy season alone (Li et al, 2016), or a smaller sub-set of models (Diro et al, 2011;Degefu et al, 2017). Establishing the fidelity of global climate models in different regions of Ethiopia, and for different seasons could yield strategic information about why models can or cannot simulate the climate, and teleconnections.…”

An observational study of the variability of East African rainfall with respect to sea surface temperature and soil moisture

“…Rainfall is reduced over the entire EA with the exception of eastern South Sudan (Figure d). This area is scarcely affected by IOD and Niño3.4 during the short rains season, whereas weak positive and negative correlations are found with the Tropical Atlantic Ocean Dipole (TAD) and Equatorial East Atlantic (EqEAtl) indices, respectively (Degefu et al, ). On the contrary, during the JAS wet season South Sudan is strongly inversely correlated to Niño3.4, so that negative values of Niño3.4 as in La Niña or IOD−/La Niña events can be connected to positive rainfall anomalies.…”

Revisiting interannual to decadal teleconnections influencing seasonal rainfall in the Greater Horn of Africa during the 20th century

“…Focusing on the Ethiopian Kiremt Rains, some studies identified large-scale forcings important for seasonal prediction (Camberlin, 1997;Gissila et al, 2004;Korecha and Barnston, 2007;Diro et al, 2008;Segele et al, 2009a;Diro et al, 2011aDiro et al, , 2011bNicholson, 2014;Degefu et al, 2016). These studies have shown a significant simultaneous association between the summer rainfall over the Ethiopian Highlands and ENSO indices.…”