Spatiotemporal trend analysis of changing rainfall characteristics in Guinea Savanna of Nigeria

Buba, Luka Fitto; Kura, Nura Umar; Dakagan, John Bathrobas

doi:10.1007/s40808-017-0356-2

Cited by 14 publications

(3 citation statements)

References 33 publications

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“…Knowing the temporal variation of temperature and its relationship with other climate variables is very important for climate planning [28]. e precipitation and temperature have very high temporal variations [29,30]. e dependence of precipitation to temperature causes its high variation over the time [27].…”

Section: Introductionmentioning

confidence: 99%

Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran)

Mesbahzadeh

Miglietta

Mirakbari

et al. 2019

Advances in Meteorology

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Precipitation and temperature are very important climatic parameters as their changes may affect life conditions. Therefore, predicting temporal trends of precipitation and temperature is very useful for societal and urban planning. In this research, in order to study the future trends in precipitation and temperature, we have applied scenarios of the fifth assessment report of IPCC. The results suggest that both parameters will be increasing in the studied area (Iran) in future. Since there is interdependence between these two climatic parameters, the independent analysis of the two fields will generate errors in the interpretation of model simulations. Therefore, in this study, copula theory was used for joint modeling of precipitation and temperature under climate change scenarios. By the joint distribution, we can find the structure of interdependence of precipitation and temperature in current and future under climate change conditions, which can assist in the risk assessment of extreme hydrological and meteorological events. Based on the results of goodness of fit test, the Frank copula function was selected for modeling of recorded and constructed data under RCP2.6 scenario and the Gaussian copula function was used for joint modeling of the constructed data under the RCP4.5 and RCP8.5 scenarios.

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Section: Introductionmentioning

confidence: 99%

Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran)

Mesbahzadeh

Miglietta

Mirakbari

et al. 2019

Advances in Meteorology

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“…Temperatures have increased from 0.2 to 0.5 o C in the high ground areas of Jos, Yelwa and Ilorin in the north and Shaki, Iseyin and Ondo in the southwest to 0.9 to 1.9 o C over the rest parts of the country. Aiyelokun & Odekoya (2016) (Umar et al, 2019) Thezhighzvariationszofzrainfallzatzhigherzlatitudeszrevealzthezunreliableznaturezofzrain fallzaszonezprogressesztowardszNorthern Guineazandzvicezversa (Buba et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Spatio-Statistical Analysis of Rainfall and Temperature Distribution, Anomaly and Trend in Nigeria

Adeleke

Orebayo

2020

Geos. Ind.

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This study aims to examine the variability of rainfall and temperature based on spatio-statistical analysis. Data for the study was gotten from the Nigerian Meteorological Agency and subjected to statistical analysis using mean, standard deviation, time series analysis, t-test and correlation. The results of the study revealed that the mean rainfall in the area is 108.6 mm, mean temperature is 28o C and mean sunshine is 4.7 hours. The result further revealed that mean onset date in the state is 13th march, mean cessation date is 10th October while the mean length of rainy season is 223 days. The result also showed that rainfall anomaly index in the area ranged between -2.12 and 2.28 while temperature anomaly ranged between -2.31 and 1.73. The correlation coefficient showed that cessation (0.408) and Length of rainy season (0.406) is significantly related to rainfall, sunshine hours (0.380) and Average temperature (0.867) is significantly related to minimum temperature, sunshine hours (-0.389) and average temperature (0.749) is significantly related to maximum temperature while onset (-0.642) and cessation (0.509) is significantly related to length of rainy season. However,there is a significant difference in onset dates, cessation dates and length of rainy season in the area. The area is experiencing a significant increase in temperature, rainfall and sunshine hours and recommends that more tress should be planted in the area and Nigerian meteorological agency should also inform farmers about the onset of the rains so as to help the farmers prepare for the planting season. Keywords: Climate; Rainfall; Anomaly; Temperature; Cessation; Onset Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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“…A thorough understanding of the temporal trends in temperature and their correlation with other climatic factors becomes pivotal in the formulation of adaptive climate strategies (Balyani et al, 2017). Among these fundamental climatic influences on agriculture, rainfall exhibits significant fluctuations over time (Sethi et al, 2015;Buba et al, 2017).…”

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confidence: 99%

Estimation of the Correlation Between Temperature and Precipitation in Bafra Plain Using Copula

Sözen,

Sağlam,

Sözen

et al. 2023

Preprint

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Temperature and precipitation are two critical climate parameters that influence agricultural productivity and various extreme hydrological and meteorological phenomena. Both temperature and precipitation have non-normal marginal distribution and have varying correlation over time. In many cases, while the marginal distributions of these two variables are known, their joint distributions remain unknown. Modelling the potential dependence under varying correlation and non-normal distribution can be achieved using Copula. In this study, we analysed the relationship between total precipitation and temperatures within the Bafra Plain using the Copula method considering maximum, minimum and average temperature, and total precipitation. First, the assumption of autocorrelation was tested using Ljung-Box unit root, Mann-Kendall trend, and Ollech-Webel seasonality tests. Then, the presence of autocorrelation was verified through autocorrelation functions (ACF). To mitigate autocorrelation, appropriate SARIMA and NNAR models were determined based on ACF. A multivariate analysis was conducted on residuals by examining the marginals distributions and copula dependency. Parameters of the marginal distributions and copula families were estimated by maximizing log-likelihood. The suitable copula families were determined based on Bayesian information criteria (BIC). Copula Kendall correlations (τCK) together with Spearman (ρs) and Pearson correlation coefficient (ρp) calculated to show the effect of copula in revealing correct relationship. As a result, the Copula method demonstrated moderate negative correlation of minimum and maximum temperature with precipitation which is higher compared to low negative correlation of ρs and ρp. For average temperature and precipitation, all three methods showed similar low negative correlation. The outcomes contribute to establishing more robust foundations for implementing measures to preserve and strengthen the region's agricultural sustainability.

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Spatiotemporal trend analysis of changing rainfall characteristics in Guinea Savanna of Nigeria

Cited by 14 publications

References 33 publications

Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran)

Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran)

Spatio-Statistical Analysis of Rainfall and Temperature Distribution, Anomaly and Trend in Nigeria

Estimation of the Correlation Between Temperature and Precipitation in Bafra Plain Using Copula

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