Impacts of Projected Urban Expansion on Rainfall and Temperature during Rainy Season in the Middle-Eastern Region in Tanzania

Abstract

Future changes of land use and land cover (LULC) due to urbanization can cause variations in the frequency and severity of extreme weather events, affecting local climate and potentially worsening impact of such events. This work examines the local climatic impacts associated with projected urban expansion through simulations of rainfall and temperature over the rapidly growing city of the middle-eastern region in Tanzania. Simulations were conducted using a mesoscale Weather Research and Forecasting (WRF) model for a period of 10 days during the rainfall season in April 2018. The Global Forecasting System data of 0.25° resolution was used to simulate the WRF model in two-way nested domains at resolutions of 12 km and 4 km correspondingly. Urban and built-up areas under the current state, low urbanization (30%), and high urbanization (99%) scenarios were taken into account as LULC categories. As the urbanized area increased, daily mean, maximum and minimum air temperatures, as well as precipitation increased. Local circulation affected the spatial irregularities of air temperature and precipitation. Results imply that urbanization can amplify the impacts of future climate changes dramatically. These results can be applicable to the city planning to minimize the adverse effect of urbanization on temperature and precipitation.

Historical and projected spatial and temporal rainfall status of Dar es Salaam, Tanzania, from 1982 to 2050

“…The results on the increase in rainfall during the OND season coincide with previous studies (Gulacha and Mulungu, 2017;Luhunga et al, 2018), which also projected an increase in rainfall over some parts of Tanzania including Dar es Salaam. Another study by Anande and Park (2021) reported a decrease in precipitation on wet days in urbanized areas including Dar es Salaam. Increased precipitation in coastal urban regions was mainly due to the strong updraft motion as there were large spatial variations in precipitation.…”

“…However, little has been carried out to determine climate variability and its associated extremes and impacts in the cities and towns with large populations and major economic activities. For example, Anande and Park (2021) examined the local climatic impacts associated with projected urban growth by simulating rainfall and temperature over the rapidly growing cities of the middle-eastern region in Tanzania. However, this study was only conducted for 10 days during the rainfall season in April 2018 and suggests further research to understand the effects of urbanization on the future climate in large cities.…”

Urban effects on precipitation: Do the diversity of research strategies and urban characteristics preclude general conclusions?

“…As shown in Figure 1, the 40 studied urban areas are mostly located in North America, Asia, and Europe, almost all of them are in the northern hemisphere, and the majority of cities are in coastal areas. Still, during the selection of articles, we found a few of them focusing on the southern hemisphere, two studying African urban areas, Nairobi in Kenya (Ongoma et al, 2015), and the Middle-Eastern Region in Tanzania (Anande & Park, 2021), one in central America (Jauregui & Romales, 1996), two south American cities, San Miguel de Tucumán in Argentina and Manaus in Brazil (Freitag et al, 2018;Sátyro et al, 2021), and one article for Oceania investigating Australian urban areas (Rosenfeld, 2000). However, these listed articles could not be selected for the analysis in this article because of their methodology or dataset types descriptions, or inexplicit conclusions.…”

“…Numerical models can induce errors but they are regularly validated against different datasets and they allow to reach fine spatial and temporal resolutions. Among the models used in the experiments, one model, in particular, is heavily used with its different possible parametrizations, the weather research and forecasting (WRF) model(Anande & Park, 2021;Argüeso et al, 2016;Debbage & Shepherd, 2019;Freitag et al, 2018;Kusaka et al, 2019;Luong et al, 2020;Miao et al, 2011;Niyogi et al, 2020;Ntelekos et al, 2008;Pathirana et al, 2014;Sarangi et al, 2018;Shem & Shepherd, 2009;Shimadera et al, 2015;Song et al, 2016;Supantha et al, 2018;Wang et al, 2016;Xiao et al, 2020;Zhong & Yang, 2015). However, the experiments using the WRF model are not directly comparable with each other because of the diversity of parametrization used.…”