Daytime variation of urban heat islands: The case study of Doha, Qatar

Yasuyo Makido, Vivek Shandas, Salim Ferwati, David Sailor

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Recent evidence suggests that urban forms and materials can help to mediate temporal variation of microclimates and that landscape modifications can potentially reduce temperatures and increase accessibility to outdoor environments. To understand the relationship between urban form and temperature moderation, we examined the spatial and temporal variation of air temperature throughout one desert city-Doha, Qatar-by conducting vehicle traverses using highly resolved temperature and GPS data logs to determine spatial differences in summertime air temperatures. To help explain near-surface air temperatures using land cover variables, we employed three statistical approaches: Ordinary Least Squares (OLS), Regression Tree Analysis (RTA), and Random Forest (RF). We validated the predictions of the statistical models by computing the Root Mean Square Error (RMSE) and discovered that temporal variations in urban heat are mediated by different factors throughout the day. The average RMSE for OLS, RTA and RF is 1.25, 0.96, and 0.65 (in Celsius), respectively, suggesting that the RF is the best model for predicting near-surface air temperatures at this study site. We conclude by recommending the features of the landscape that have the greatest potential for reducing extreme heat in arid climates.

Original languageEnglish (US)
Article number32
JournalClimate
Volume4
Issue number2
DOIs
StatePublished - Jun 1 2016

Keywords

  • Arid climate
  • Random forest
  • Spatial analysis
  • Urban heat island
  • Vehicle temperature traverse

ASJC Scopus subject areas

  • Atmospheric Science

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