I am writing to request a clarification regarding the interpretation of the Urban Cooling model’s outputs.
My understanding from the documentation is that the maximum possible temperature reduction (ΔT) the model can simulate is, by definition, limited by the “urban heat island magnitude” (UHI_max) input parameter. This would mean that, for example, if a UHI_max of 2°C is provided as input, the maximum cooling effect simulated by the model will not exceed 2°C, even for a massive greening intervention, and even if the empirical, localized cooling effect of an urban forest might be greater.
Therefore, I would like to confirm if this interpretation is correct: should the model’s cooling result be understood as the relative mitigation of the provided UHI_max, rather than a prediction of the absolute cooling that trees can generate in a specific microclimate?
Thank you in advance for your time and for your excellent work on this tool.
Thank you for your question. In forming my response, I had to reconfirm my understanding of the model.
Yes, you are correct in that the model’s cooling result is simply a relative mitigation of the user-specified UHI_max value and NOT a mechanistic prediction of the absolute number of degrees that trees will cool the air at a specific site. HMI cannot exceed 1, so this model’s predicted air temperature for any given pixel will never be less than rural reference air temperature, based on equation 120.
Because HMI is a relative index of mitigation potential and temperature is calculated as a linear interpolation between the reference air temperature and UHI_max, neither are a physical simulation of microclimate. One implication of this is that if UHI_max doubles, for example, all degree differences would also double, even though HMI remains constant. HMI is not based on a mechanistic energy-balance and does not capture detailed micrometeorology. It is simply reliant upon the relative effects of shade, albedo, and ET and the spatial configurations of your study area.
HMI alone (or service metrics derived from it) is often sufficient when users only need to compare relative rankings between scenarios. This would not require committing to a single UHI_max value. But for questions like ‘How many degrees would a specific grove cool the air 2m above the ground at 1pm under given wind and radiation?’, users should turn to a microclimate/urban canopy model (e.g., ENVI-met, SOLWEIG, SUEWS, or an energy-balance approach) or empirical models calibrated to local measurements.