Sensor lag adjustments on a mobile meteorological cart in tropical environments: a case study from an Urban Park in Singapore
2025
Moshe Mandelmilch | Sin Kang Yik | Beatrice H Ho | Graces N Y Ching | Peter J Crank | Winston T L Chow
This study adds to the growing literature on mobile platforms by examining the performance of the Singapore MaRTy (SMaRTy) in conducting mobile micrometeorological measurements along a designated route in an urban park in Singapore, reflecting a pedestrian walking experience. The main objective of the study was to calculate the sensor lag for the mobile climate measurements: Air Temperature (TA), and Relative Humidity (RH) of SMaRTy along a designated route in an urban park in Singapore based on data from fixed stations (HOBO sensors) in two significant synoptic meteorological periods during the Northeast and Southwest monsoons. Statistically significant regression models were obtained for the two study periods. For the TA, the regression models for the Southwest monsoon yielded higher R ^2 (0.85–0.99) and lower Root Mean Square Error (RMSE) (0.34–0.57) than those for the Northeast monsoon (R ^2 : 0.09–0.90, and RMSE: 0.53–0.71). However, diurnal variations in cloud cover affected the regression models of SMaRTy, with more cloudy conditions resulting in weaker correlations. Overall, results suggest that mobile climate measurements via SMaRTy along a designated route, when corrected for lag, yield accurate data that can be applied toward urban climate analysis.
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