Calibration of Mobile Micrometeorological Measurements in a tropical urban park: Analysis of SMaRTy data on Urban Warming

Anthropogenic activities and land cover changes within cities can result in unique climate conditions in settlements. One of the major phenomena of the city’s climate is the “Urban Heat Island” (UHI), defined as an amplification of temperatures inside cities compared to its rural surroundings arising from the inadvertent development of cities and associated human activity. Apart from remote sensed platforms, the UHI can be measured via two different approaches; fixed meteorological stations and mobile climate measurements. Usually, fixed meteorological stations measure climate information continuously 24 hours a day. However, they are limited in number and cover relatively a small area close to them for their instrumental source area. On the other hand, mobile climate measurements are flexible in terms of instrumental source area, their quantity is greater compared to stationary stations and therefore they can cover larger areas in shorter time intervals, which makes them relevant for biometeorological research.

Recently, the development of mobile micrometeorological cars such as MaRTy (Middel et al. 2019) enables measurement of key microclimate parameters (e.g., air temperature (TA), relative humidity (RH), Wind Direction (WD), shortwave and longwave radiation across three dimensions, and wind speed (WS). That can be subsequently used to estimate outdoor thermal comfort (OTC). MaRTy is named after the key climate variable it calculates: Mean radiant temperature (MRT). Since 2019, MaRTy carts have been used in several cities worldwide mainly to assess OTC conditions, as well as to evaluate microclimate models e.g. ENVI-Met. 

This study examined, for the first time, data from the SMaRTy platform (The Singaporean version of MaRTy) to conduct mobile climate measurements along a designated route in an urban park in Singapore during different monsoon seasons. The study's aims were: (1) To test the influence of the walking speed of the SMaRTy cart on the measured climate variables e.g., TA, RH, and WS. (2) To calibrate the mobile climate measurements of the SMaRTy cart along a designated route in an urban park in Singapore based on data from fixed meteorological stations.  (3) To apply the calibration equations on SMaRTy cart data, and to create a spatial model of the climate variables in the urban park. Initial results suggest that mobile microclimate measurements via the SMaRTy platform along a designated route yield useful data that can be applied towards OTC analysis, but seasonal variations in model calibration occur across temporal measurements from SMaRTy.