Bivariate Extreme Value Analysis of Rainfall and Temperature in Nigeria

The rising cases of floods and the onset of drought in different parts of Nigeria require urgent attention particularly because Nigeria accommodates the largest population in Africa, hence any negative climate impact on it can easily ripple into other African regions. To understand the risk factors that drive these extreme events, we study the bivariate extreme cases of monthly precipitation and temperature observations over a period of 116 years (1901-2016). This is the first paper providing bivariate extreme value analysis of data in Nigeria. The mean rainfall and temperature variables exhibit interrelationships such as dry-cold and wet-cold associations. We further investigate whether these relationships are present at the tails by making use of the annual minimum rainfall-annual minimum temperature and annual maximum rainfall-annual minimum temperature pairs. Their extreme dependence structures are also quantified by applying the parametric bivariate extreme value models. Our results show that the compound extremes of dry-cold and wet-cold conditions exhibit a zero to weak extreme dependence at varying quantile levels. A much stronger dependence structure is present between the annual maximum rain and the total volume of rainfall. By considering both independent and dependent probability assumptions, we show that the former may lead to an underestimation of the risks associated with existing climatic hazards. The implications of these results are highlighted throughout the paper.