High-frequency Fluctuation of Air Temperature and Building Energy Response in Coastal Urban Environment during a Heatwave Event: The Effect and Mechanism of Local Flows in Complex Terrain

Extreme temperature demands tremendous power surge for indoor space cooling during heatwave so power infrastructure would be on the verge of collapse. In this connection, the non-stationary, wide-spectrum urban climate is a challenge to power infrastructure reliability. High-frequency fluctuations in air temperature at scales of a few hours are stochastic and aperiodic. It could cause unpredictable threats to power security. In this study, the convective processes of airflow in a coastal city with mountainous terrain-Hong Kong- during a heatwave event was investigated using the mesoscale Weather Research and Forecasting (WRF) model. For the first time, we examined the collective effects of sea/land breezes, complex terrain, and the resulting local flows on urban-scale air temperature and air-conditioning load intensity (ACLI), by integrating the local climate zone (LCZ) and building categories (BCs) into WRF. Afterwards, the Hilbert-Huang transform (HHT) was unprecedentedly used to extract high-frequency temperature and wind speed signals. The physical mechanism behind was also unveiled.

It was found that mountains enhanced 2-m temperatures (T2) and ACLI by 1 °C to 2 °C and 5 W m^-2, respectively, by inhibiting urban inflow or accumulating outflow heat. ACLI in compact high-rise areas (LCZ 1) is most vulnerable to the extreme temperatures induced by the mountain blockage. Furthermore, downstream urban heat island (UHI) effects are significant that facilitate channel-flow formation by 1.66 m sec^‑1 (50.26 %). Conversely, the terrain-induced channel winds could augment heat advection and increase downstream T2 (ACLI) by 0.7 °C (2.62 W m^-2). Stronger channel winds enhance ACLI’s response to heat advection. UHI-introduced local flows interact with mountain slopes, causing sea-breeze stagnation on the leeward side of hills. It reduces wind speed and increases T2 by 0.81 m sec^-1 and 0.9 °C, respectively, in downstream urban areas. Its benefit is prominent in daytime that elevates ACLI as high as 6.41 W m^-2.

In addition, the urban-scale air temperature (IMFθ1 to IMFθ6) and wind speed (IMFW1 to IMFW6) signals were decomposed into 6 intrinsic mode functions (IMFs) using HHT. The spatio-temporal patterns, physical causes and effective ranges of high-frequency components (IMF1 to IMF4) were revealed. Temperature (wind speed) IMFθ1 to IMFθ4 (IMFW1 to IMFW4) had a temporal scale of 2.63 hours (2.53 hours), 5.88 hours (5.78 hours), 13.16 hours (9.84 hours), and 22.72 hours (19.05 hours). Their corresponding spatial scales were 2.31 km (0.99 km), 4.29 km (1.65 km), 5.94 km (2.64 km), and 6.6 km (2.97 km), respectively. The physical mechanisms of IMF1 to IMF4 consists of turbulence and heat storage/release of construction material; disturbance triggered by mountainous terrain and slope flows; land/sea breeze, along with anthropogenic heat. Moreover, the peaked amplitudes of IMFθ1 were most risky in compact/open high-rise urban (1.4 °C to 1.6 °C) rather than rural (0.6 °C to 1.0 °C) areas. IMFθ2 (1 °C to 2.1 °C) exhibited the most intense fluctuation in the foothill areas within 8-km from the mountains. IMFθ3 (0.6 °C to 3.6 °C) are effective in the coastal areas within 10-km from coastline. The urban/suburban areas were susceptible to MFθ4 (2.5 °C to 3.5 °C). The outcome offers references for policy makers to alleviate heat-related risks.