Abstract
Agriculture is the backbone of Zimbabwe’s economy with the majority of Zimbabweans being rural people who derive their livelihood from agriculture and other agro-based economic activities. Zimbabwe’s agriculture depends on the erratic rainfall which threatens food, water and energy access, as well as vital livelihood systems which could severely undermine efforts to drive sustainable economic growth. For Zimbabwe, delivering a sustainable economic growth is intrinsically linked to improved climate modelling. Climate research plays a pivotal role in building Zimbabwe’s resilience to climate change and keeping the country on track, as it charts its path towards sustainable economic growth. This paper presents a simple tool to predict summer rainfall using standardized Darwin sea level pressure (SDSLP) anomalies and southern oscillation index (SOI) that are used as part of an early drought warning system. Results show that SDSLP anomalies and SOI for the month of April of the same year, i.e., seven months before onset of summer rainfall (December to February total rainfall) are a simple indicator of amount of summer rainfall in Zimbabwe. The low root mean square error (RMSE) and root mean absolute error (RMAE) values of the proposed model, make SDSLP anomalies for April and SOI for the same month an additional input candidates for regional rainfall prediction schemes. The results of the proposed model will benefit in the prediction of oncoming summer rainfall and will influence policy making in agriculture, environment planning, food redistribution and drought prediction for sustainable economic development. Keywords: sustainable economic growth, standardized Darwin sea level pressure anomalies, southern oscillation index, summer rainfall prediction, Zimbabwe. JEL Classification: Q16, Q25, Q54, Q55, Q58
Highlights
The poor economic performance of Southern Africa continues to receive considerable amount of attention in the economic literature (Chilonda and Minde, 2007)
Correlation analysis between the standardized Darwin sea level pressure (SDSLP) anomalies and the summer rainfall is used to identify the month of the previous year whose SDSLP anomalies is significantly correlated to the summer rainfall (December to February total rainfall)
We developed a simple summer rainfall predicting tool for Zimbabwe using SDSLP anomalies and southern oscillation index (SOI)
Summary
The poor economic performance of Southern Africa continues to receive considerable amount of attention in the economic literature (Chilonda and Minde, 2007). Given the importance of agriculture to a developing country such as Zimbabwe and the dependence of the sector to rainfall, as suggested by Manatsa et al, 2008 and Mangonyana and Meda, 2001, its decline and lack of prediction tools may have severe consequences for sustainable growth. This decline and lack of prediction tools poses detrimental impact on energy supply in Zimbabwe due to its heavy reliant on hydro-power for electricity generation (Kaunda et al, 2012). Large scale climatic variation that occur from one year to year (Panu and Sharma, 2002)
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