Characterization of Climate Variability and Trends Associated with Food Crises in the Horn of Africa

Project: Research

Project Details

Description

Extreme weather-related disasters are increasing in intensity by the day due to climate change and have become a threat to household food security in developing countries, especially in the horn of Africa. Sub-Saharan Africa is one of the continents where severe food insecurity is most prevalent, with more than 200 million hungry people, reaching 31% of the population and accounting for nearly one-half of all severely food insecure people in the world. Among the key factors driving the recent increase in food insecurity in the sub Saharan Africa are conflicts, overexploitation of natural resources and adverse climatic conditions such as extreme rainfall, heat-waves, and drought which are motivated by climate change. As the magnitude and impact of climate change increase the more communities and governments in this region are less able to absorb and adapt, making them increasingly vulnerable to future shocks. Climate variability may also affect outbreaks of infectious diseases like Ross River virus disease, visceral leishmaniasis, etc. Recently, several studies have provided evidence of a link between vector-borne disease outbreaks and El Nio driven climate anomalies. Of course, it is worth mentioning that a disease (infectious disease) crisis as a result of climate change in one country can and frequently does spread economic pain to other countries, for example, Ebola, MERS-CoV, COVID-19, etc. Hence, it is pertinent to study these variations in frequency or intensity of extreme weather conditions (Climate variability and trends), having observed the increasing need to achieve sustainable development goals, which include achieving a world without hunger and malnutrition. To this end, this research is geared towards characterizing the daily (or weekly, monthly, annual) variability and trends of two climatic factors, namely: extreme rainfall and drought in the horn of Africa using extreme value theory (EVT). Based on the EVT, the current study will propose new extreme value methods and spatial extreme value methods as well as Bayesian hierarchical models that can provide accurate inferences and flexibility. These models will be capable of providing times at which extremes occur (i.e. the return levels of rainfall and drought) and they will be compared with the existing models. This will address the climate risks to food security, dynamics and resilience against shocks by describing the cycle of extreme weather conditions. For example, questions such as what is the probability of a one day rainfall with depth equal or greater than 350mm occurring at a given location once in 20 years or at least once in 20 successive years? Or How will a 2C warming in the global temperature increase the chance of a 2014/15 El Nio and La Nia style of event?" will be answered.
StatusFinished
Effective start/end date1/11/2031/10/21

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