Self-Organizing Maps (SOM) have successfully been applied to several climate research including the analysis of atmospheric circulations variability, time evolution of seasonal climate, and climate model downscaling and to access the stationary of global climate models. Several attempts have been made in the past to characterize extreme climate using machine learning methods.

The use of CA to gain insight from geographical data had more serious adoption since the 1990s. One of such techniques is Cluster Analysis (CA). The recent increase of data from ground observations, satellites, and numerical models enables the opportunity for exploring the use of data mining techniques in climatic studies. When dealing with precipitation extremes, it is important to consider their synoptic aspects and dimensions. Proper study of climate extremes depends on the quality and quantity of data, as well as on how rigorously they are analyzed. Reference evaluated how crop yield might respond to climate change in Nigeria, and discussed the challenges of agricultural adaptation to climate change. Moreover, climate projections for the 21st century show a significant increase of temperature over all the ecological zones which may have negative impacts on agriculture and food security.

The northern part of the country has been experiencing a reduction in rainfall and an increase in the rates of dryness and heat, while the rainfall amounts have been increasing in the southern part with an irregular pattern. Evidence of climate change in Nigeria has been discussed by, who reported increasing damage caused by wind and rainstorms, which are projected to increase in southern regions. According to, there is a high chance that the frequency of heavy precipitation and total precipitation will increase in several parts of the globe in the 21st century. Precipitation is one of the most important climatic parameters responsible for flood and drought in several vulnerable parts of the world. This set of indices includes both temperature and precipitation indices. The joint working group CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) ( ) has 27 standardized and recommended climate extreme indices. The use of indices to characterize the frequency, intensity, and duration of precipitation extremes is one of the ways to assess them. Д¬limate extremes, including the ones related to precipitation, can be analyzed using several approaches. However, it can also be argued that climate extremes are just a part of decadal global climate cycle and variability. There is a growing global concern that anthropogenic activities are a major cause of the variability in the intensity and frequency of weather and climate extremes. Climate extremes can result in changes in the frequency, intensity, spatial extent, duration, and timing of climatic phenomena.

A climate extreme is вЂњthe occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends of the range of observed values of the variableвЂќ. One of the visible impacts of climate change and climate variability is extreme weather events that occur from time to time in several parts of the globe. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. Precipitation properties in each cluster are discussed. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding.

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques.

1984 big weather events