Abstract
Rwanda has experienced high temperature rising phenomena over the last decades and hence, highly vulnerable to climate change. This paper examined the spatial and temporal variations of daily maximum and minimum surface air temperature (Tmin and Tmax) and diurnal temperature range (DTR). It studied variables at monthly, seasonal and annual time-scales from 1961 to 2014. The study applied various statistical methods such as ordinary least-square fitting, Mann-Kendall, Sen’ slope and Sequential Mann-Kendall statistical test to the new reconstructed ENACTS dataset that cover the period from 1983 to 2014 while pre-1983s recorded data from 24 meteorological stations have been added to complete the lengthiness of ENACTS data. The January to February season did not show a significant trend at seasonal time-scales. The authors decided only to consider March-to-May, June-to-August and October-to-December seasons for further analyses. Topography impacts on temperature classified stations into three regions: region one (R1) (1,000–1,500 m), region two (R2) (1,500–2,000 m) and region three (R3) (≥2,000 m). With high confidence, the results indicate a significant positive trend in both Tmin and Tmax in all three regions during the whole study period. However, the magnitude rate of temperatures change is different in three regions and it varies in seasonal and annual scale. The spatial distributions of Tmax and Tmin represent a siginificant warming trend over the whole country notably since the early 1980s. Surprisingly, Tmin increased at a faster rate than Tmax in R3 (0.27 vs. 0.07°C/decade in March-to-May) and (0.29 vs. 0.04°C/decade in October-to-December), resulting in a significant decrease in the DTR. This is another confirmation of warming in Rwanda. The mutation test application exhibited most of the abrupt changes in the seasonal and annual Tmax and Tmin trends between 1984 and 1990. The present work mainly focus on the spatial and temporal variability of Tmin, Tmax and DTR in Rwanda and their relationship with elevation change, leaving a gap in other potential cause factors explored in the future.
Highlights
The harmful impacts of climate change on human life, infrastructure and ecosystem have led to increased studies on the subject globally (IPCC, 2001a; Alexander et al, 2006; Myoung et al, 2013)
It is likely agreed that Tmax and Tmin trends and variability play an essential role in detecting climate change impacts on human health such as vector-borne disease (Ren et al, 2016; Sun et al, 2017)
The impacts of extreme temperature on mortality have been confirmed in a number of other studies (Barreca et al, 2016; Heal and Park, 2016; Ndenga et al, 2006) revealed that unusual high maximum temperatures positively correlate with many malaria cases
Summary
The harmful impacts of climate change on human life, infrastructure and ecosystem have led to increased studies on the subject globally (IPCC, 2001a; Alexander et al, 2006; Myoung et al, 2013). The studies mentioned above have reported significant results in terms of dynamic variability of Tmax and Tmin over some regions of Rwanda. Most of those previous studies were limited to a specific area, which may fail to cover country’s general representation. Safari, 2012 used the same observed data to examine the trend of mean annual temperature from five observatories during 1958–2010 Trend analyses on monthly, seasonal and annual time-scales were performed in order to capture changes in temperature series for Rwanda. The method has been used in related studies in East Africa (Nsubuga et al, 2014; Ongoma and Chen 2017) as well as over Rwanda by Safari (2012)
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