Abstract

This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash–Sutcliff efficiency (0.98) and percentage bias (4.4% and −8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.

Highlights

  • Climates in different parts of the world are characterized by their variability with impacts on varied sectors

  • This paper examines the trend in annual rainfall and temperature extreme indices over the

  • The study revealed that the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data was able to mimic both the seasonal and annual rainfall pattern of the study area reasonably well indicating its capability for further usage in other analysis at the study location

Read more

Summary

Introduction

Climates in different parts of the world are characterized by their variability with impacts on varied sectors. This variability has increased since the 1950s, and during the latest decade [1]. The IPCC (Intergovernmental Panel on Climate Change) report [4] attests to the fact that there is the likelihood of increases in extreme climate events due to the observed global warming over recent decades This makes studying climate extremes at the spatial and temporal scale relevant due to the fact that its impact is very devastating and can lead to loss of life and economic damages

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call