The Minimum and Maximum Temperature Forecast Using Statistical Downscaling Techniques for Port-Harcourt Metropolis, Nigeria

Abstract

This study centers on applying the statistical downscaling technique to the daily minimum and maximum temperatures of Port Harcourt from the period 1985-2014. To select the period of calibration, the wilby and wigley assumption of 2014 was adopted. However, the Bruckner circle assumption was adopted in selecting the normal under review. Secondary data of minimum and maximum temperatures for Port Harcourt were collected from the archive of Nigerian meteorological agency (NIMET). The grid cell of the HadCM3 corresponding to the Port Harcourt meteorological station was selected from the HadCM3 website to generate the largescale predictors. Data for temperature was there after normalized for the period of calibration. To analyze data, ANOVA and Paired t tests were used. Result showed that, the model was significant at p < 0.05 implying that the largescale predictors of the HadCM3 have performed significantly and that temperature pattern in the area is significantly dependent on them. The Duncan statistics showed that in the A2 scenario Maximum temperature will rise with a mean difference of 3.1˚C from 1960-2080, while for B2 the increase will be 0.18˚C for same period. For minimum temperature, the ANOVA also showed a difference of 0.21˚C and 0.11˚C for A2 and B2 respectively. The paired t test statistics showed that these variations in temperatures for both maximum and minimum at A2 and B2 scenarios are significant at p < 0.05. Reforestation, afforestation, carbon sequestration are strongly advocated.

Validating Gauge-based Spatial Surface Atmospheric Temperature Datasets for Upper Benue River Basin, Nigeria

“…Eludoyin et al (2014) studied the changes in thermal conditions over the entire Country through temperature and relative humidity. Weli et al (2017) carried out statistical analysis on minimum and maximum temperatures in Port Harcourt metropolis. Hassan et al (2020) inter-compared basic meteorological dataset including minimum and maximum temperatures and precipitation in the Niger Delta with ground observational dataset for water resources management.…”

Application of transform software for downscaling global climate model EdGCM results in north-eastern Bangladesh

“…This technique lies in the capability to use the features of the free atmosphere as predictors of the local climate components (which are known as the predicted). Information on the large-scale predictors may be created by the direct weather observation or by some climate model result, but downscaling is essential as a method, due to the usability of climate impact results and dangers assessments [13]. Downscaling has been regarded as a significant component of climate change impact evaluation as GCMs are only accessible at coarse resolution.…”