Abstract:
Manipulating the urban fabric is fundamental to mitigate and adapt to the warming trend in the growing high-density tropical cities. However, excessive data needs, weak analytical methods and the un-coordinated planning regimes pose barriers to achieving this aim.
The main aim of the research is to bridge the gap in urban design-climate links, being translated into guidelines for real-world applicability in a background climate affected by global warming. The study is limited to the warm humid tropical climate of Colombo, Sri Lanka, as the experimental context for the research.
The main research questions are related to; the microclimatic background condition under current and future warming scenario; sensitivity of the key urban morphology variables that will define and drive the decision making process; and the planning and policy implications that link climate and urban design. The study employs the Local Climate Zone (LCZ) system as a method of contextual analysis, together with LCZ-based morphology simulations (ENVI-met), utilising Mean Radiant Temperature (MRT) as the key dependent variable. Statistical analyses (SPSS) of the results test the applicability and sensitivity of urban morphological variables to help mitigate / adapt to local and global warming.
The findings indicate that the Sky View Factor is the most influential urban indicator of local climate. In general, night-time shows better correlation with MRT. The nature of the Pervious Surface Cover has little or no effect on reducing MRT. And, the correlation of variables with MRT is stronger in a climatic background affected by global warming.
The work contributes a ‘conceptual framework’ for the deeper understanding of the effect of building morphology on local level warming in the tropics. Policies that give effect to these findings are presented in a manner that requires minimal data input. Protocols for mapping of LCZs and relative warming effects, and sensitivity analysis of key design parameters for the mitigation of UHI in the tropics are presented. The socio-economic and planning practice implications of a LCZ-based planning approach are explored.
