Comparison of Multiple Maximum and Minimum Temperature Datasets at Local Level: The Case Study of North Horr Sub-County, Kenya

Giovanni Siciliano,Ingrid Vigna,Elena Comino,Velia Bigi,Alessandro Demarchi,Maurizio Rosso,Alessandro Pezzoli,Elena Cristofori

doi:10.3390/cli9040062

Abstract

Climate analyses at a local scale are an essential tool in the field of sustainable development. The evolution of reanalysis datasets and their greater reliability contribute to overcoming the scarcity of observed data in the southern areas of the world. The purpose of this study is to compute the reference monthly values and ranges of maximum and minimum temperatures for the eight main inhabited villages of North Horr Sub-County, in northern Kenya. The official ten-day dataset derived from the Kenyan Meteorological Department (KMD), the monthly datasets derived from the ERA-Interim reanalysis (ERA), the Observational-Reanalysis Hybrid (ORH) and the Climate Limited Area Mode driven by HadG-EM2-ES (HAD) are assessed on a local scale using the most common statistical indices to determine which is more reliable in representing monthly maximum and minimum temperatures. Overall, ORH datasets showed lower biases and errors in representing local temperatures. Through an innovative methodology, a new set of monthly mean temperature values and ranges derived from ORH datasets are calculated for each location in the study area, in order to guarantee to locals an historical benchmark to compare present observations. The findings of this research provide insights for environmental risk management, supporting local populations in reducing their vulnerability.

Highlights

Several studies have classified Africa as the most vulnerable continent to the impacts of climate change, due to its dependence on agricultural activities as well as its poor financial, technical and institutional resilience capacities [1,2,3,4]
Kenyan Meteorological Department (KMD), ERA-Interim reanalysis (ERA), Observational-Reanalysis Hybrid (ORH) and HAD datasets were evaluated against the TMAX and TMIN observations recorded by the land-based meteorological stations of Lodwar, Marsabit and Moyale in the selected period of 1983–2014
KMD showed higher CC results compared to other TMAX datasets; differently mixed results were found for TMIN CCs

Summary

Introduction

Several studies have classified Africa as the most vulnerable continent to the impacts of climate change, due to its dependence on agricultural activities as well as its poor financial, technical and institutional resilience capacities [1,2,3,4]. Local sustainable development in Africa is heavily threatened by the impacts that climate change has on livelihood activities, ecosystem services and water supply [5]. Among African countries, Kenya is one of the most vulnerable to climate change. 182 countries, Kenya was ranked as the 38th most vulnerable country in the world to the effect of climate change and the 23rd least ready to face future impacts in 2020 [6]. Monitoring, forecasting and early warning systems are the best strategies to mitigate negative socio-economic impacts and strengthen the resilience of the communities [10,11]

Objectives

Results

Conclusion