Abstract
Existing limited understanding on the teleconnections between ocean-atmosphere coupled phenomena and drought occurrences in Ethiopia has been undermining the decisions and interventions related to climate change adaptation and mitigation. The two drought indices Standardized Precipitation Index and Reconnaissance Drought Index were used for correlation and lag correlation with global indices El-Nino Southern Oscillation, Oceanic Nino, Indian Ocean Dipole and Pacific Decadal Oscillation. The indices were obtained from their respective database websites of the National Center for Environmental Prediction. Historical EL-Nino and La-Nina years and Ethiopian drought years were collected from literatures. Meteorological data on seasonal mean rainfall, maximum and minimum temperatures from 1916-2016 were collected from Tigray regional meteorology agency. In addition, the Cru/ Model data were collected from KNMI climate explorer. The analysis results the strong correlations of global indices Nino3.4, IOD and PDO with local indices for April to June rainy season while SOI and IOD indices for July-Sep. The positive correlation of indices weakened and/or dislocated the rain-producing components for main rainy season, while those systems enhanced in low rain season. This shows global indices alter rain fall distribution & conveys Meteorological and Agricultural drought. The study revealed that, in addition to El Nino impacts, other events such as PDO, SOI and IOD are important factors for triggering meteorological and agricultural droughts in Tigray region of Ethiopia. This information has multiple implications, among others, improves seasonal forecast to make informed decisions.
Highlights
The changing climate due to anthropogenic emission and different drivers are causing climate variability and change
The positive correlation of indices weakened and/or dislocated the rain-producing components for main rainy season, while those systems enhanced in low rain season
While from 1993-200/3 moderate Reconnaissance Drought Index (RDI) was observed for April to Jun the reverse was true for July to Sept rain season and it indicates that sever RD on 1981/82, 1989, 2012/2013 at both rain seasons at the given station
Summary
The changing climate due to anthropogenic emission and different drivers are causing climate variability and change. The regional and global features that affect the kiremt rain include ITCZ, TEJ, South Atlantic Ocean and South West Indian ocean anticyclone, EALLJ or Somali Jet and ENSO. The Belg rain is affected by ITCZ, SWJ stream, Arabian High, the frequency of tropical cyclones over the Southwest Indian Ocean and ENSO. That is why at the world wide level efforts are made to investigate the climate variability and climate change in different seasons that prevail at local, regional and worldwide scales. Among this global explorations to improve the weather forecasting and climate predictions capabilities have remained on the top of the global agenda (Korecha et al, 2013)
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