Analysis of the extreme and records values for temperature and precipitation in Lebanon

Abstract

Extreme natural phenomena can be damaging and very costly. Heavy rainfall, snowfall and rising temperature are some examples of these phenomena which have the potential to reproduce frequently and at an elevated scale. We are therefore interested in defining the occurrences of such extreme events and the probability of their occurrence. The extreme value theory is a useful tool to describe the statistical properties of extreme events. Lebanon is exposed to natural disasters since it boasts a long coastline which sits on the eastern Mediterranean Sea. Therefore, the database of temperature and precipitation in Lebanon, chosen as weather factors, will be simulated by two extreme distributions using R program: Weibull for the block maxima and General Pareto for the peak over a threshold to model the tail distributions of temperature and precipitation in Lebanon. Also, the theory of record-breaking data will be adopted to study the evolution of temperature and precipitation during 2003–2019. This article is to predict the intensity of the upcoming “highest” temperature and precipitation and to compute the timing probabilities for the future record. To test the increase in the highest temperature, this article presents the nonparametric test based on the number of records.

Keywords:

• Extreme weather phenomenon
• temperature
• precipitation
• extreme distributions
• extreme quartiles
• block maxima
• POT
• return level
• records theory
• nonparametric test