Analysis of climate variability, trends, and prediction in the most active parts of the Lake Chad basin, Africa

Rashid Mahmood,Shaofeng Jia,Wenbin Zhu

doi:10.1038/s41598-019-42811-9

Abstract

An understanding of climate variability, trends, and prediction for better water resource management and planning in a basin is very important. Since the water resources of the Lake Chad basin (LCB) are highly vulnerable to changing climate, in the present study, a combination of trend analysis methods was used to examine the climate variability and trends for the period of 1951–2015 using observed and Climate Research Unit (CRU) data, and a combination of spectral analysis techniques was used for the prediction of temperature and precipitation using CRU data. Eighty-four percent of the temperature time series indicated extremely strong signals of increasing trends (α = 0.001) and 25–38% of the precipitation time series indicated strong decreasing trends (α = 0.05). Temperature is expected to increase and precipitation is expected to decrease in the future. However, surprisingly, in some regions located in the South, the temperature was predicted to decrease slightly in 2021–2030 relative to 2006–2015. This decrease might occur because these regions are highly protected natural resource areas and forests are frequently present. On the whole, the temperature was predicted to increase by 0.65–1.6 °C and precipitation was predicted to decrease by 13–11% in the next two decades (i.e., 2016–2025 and 2026–2035) relative to 1961–1990. Periodic analysis showed a 20- to 25-year cycle in precipitation in all basins and a 40- to 45-year cycle in temperature but only in the Chari-Logone basin.

Highlights

The changing climate, global warming, and global energy imbalance are considered the main consequences of the dramatic increase in the concentration of greenhouse gases due to human activities, especially industrialization, the burning of fossil fuel, and land use/land cover changes[1,2,3]
Because knowledge of climate variability and trends is important for many aspects, the accurate forecast/prediction of climate variables is important for the policymakers, planners, and other people working on water resource management and on mitigation and adaptation measures to cope with climate change
This study showed that annual and seasonal precipitations have reduced in the whole study area for the period of the 1951–2015, with moderate downward trends obtained using Climate Research Unit (CRU) precipitation and relatively strong downward trends calculated by observed precipitation

Summary

Introduction

The changing climate, global warming, and global energy imbalance are considered the main consequences of the dramatic increase in the concentration of greenhouse gases due to human activities, especially industrialization, the burning of fossil fuel, and land use/land cover changes[1,2,3]. This occurrence shows that water resources of the LCB are highly vulnerable to rapidly changing global and regional climate, especially changes in temperature and precipitation, which are considered the most important elements in climate description[14] The changes in these two variable can alter the hydrological cycle and environmental processes[15]. Because knowledge of climate variability and trends is important for many aspects, the accurate forecast/prediction of climate variables is important for the policymakers, planners, and other people working on water resource management and on mitigation and adaptation measures to cope with climate change Such predictions are important for managing water supply and demand, mitigating flood and drought, maintaining reservoir water levels, planning and preparing for disasters, reducing the uncertainty by providing information on the future availability of water, improving water resources allocation, etc.[15,17,18,19]. The spectral analysis is mostly used to study the physical processes in geophysics[33], to study the stars in astronomy[34] and to predict the weather in meteorology[35]

Results

Discussion

Conclusion