Accuracy of Local Knowledge in Prediction Seasonal Weather: Empirical Evidence from North eastern Nigeria

A. Jajere, Joshua, Jonah Kunda, U. M. Bibi, Yusuf Maina-Bukar
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Abstract

Over the years, West African Sahel’s people developed some strategies for predicting the seasonal weather using meteorological indicators to plan for extreme weather events. This study used information on local indicators of seasonal weather prediction and mean monthly rainfall and temperature record (1981-2017) from Nguru weather station located at Latitude 14°N in achieving the aim of the study. Both qualitative and quantitate (descriptive and inferential) statistical tools were employed in analysing the collected data. The study found that the local population of the study area used meteorological indicators in predicting the seasonal weather. The results of the analysis revealed that the variability of the annual rainfall during the study period was large. An increasing trend of 3.1mm annually was observed. While decreasing trend in the cold, dry and hot dry season temperature and an increasing trend in warm moist temperature by 0.025°C, 0.05°C and 0.0004°C respectively, was observed. Annual rainfall amount accounts for 31% and 2% variability in cold dry and warm moist season temperature, respectively. Cold, dry season and warm moist season temperature respond to any 1mm increase in annual rainfall by decreasing by 0.012°C and 0.002°C, respectively. The Hot, dry season temperature also accounts for 4% of the variability in annual rainfall. The model’s result revealed anyone 1°C increase in hot dry season temperature lowers the annual rainfall by 10mm. This study confirmed that the observed relationship between seasons weather conditions by local population exist. Therefore annual rainfall is the major determinant of cold dry seasonal temperature in the study area.
当地知识在季节天气预测中的准确性:来自尼日利亚东北部的经验证据
多年来,西非萨赫勒地区的人们制定了一些利用气象指标预测季节性天气的策略,以规划极端天气事件。为了实现研究目的,本研究利用了位于北纬14°N的Nguru气象站的季节性天气预报和平均月降雨量和温度记录(1981-2017)的当地指标信息。定性和定量(描述性和推断性)统计工具被用于分析收集的数据。研究发现,研究区当地居民利用气象指标预测季节天气。分析结果表明,研究期间年降雨量的变异性较大。年增加幅度为3.1mm。冷、干、热干季气温分别下降0.025℃、0.05℃和0.0004℃,暖湿期气温呈上升趋势。年降雨量分别占冷干季和暖湿季温度变化的31%和2%。年降雨量每增加1毫米,冷季、旱季和暖湿季温度分别下降0.012°C和0.002°C。干热季节的温度也占年降雨量变化的4%。该模型的结果显示,旱季温度每升高1°C,年降雨量就会减少10毫米。该研究证实了观测到的季节气候条件与当地人口之间的关系。因此,年降雨量是研究区冷干季温度的主要决定因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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