the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Vertical responses of urban heat islands to heatwaves and their local climate zones dependence: a case study of Guangzhou, China
Abstract. The interaction between urban heat island (UHI) and heatwaves (HWs) shapes urban extreme heat, but whether HW-induced UHI amplification reorganises canopy-to-boundary-layer thermal structure, and whether local climate zones (LCZs) modulate this response, remains unclear. Here, we investigated two July 2020 HW events in the Guangzhou metropolitan area in southern China, using 1 km LCZ-coupled Weather Research and Forecasting (WRF) simulations. We analysed the vertical thermal response of the urban area and individual LCZs using canopy and boundary-layer UHI intensities (CUHII, BUHII), layer-mean urban–rural air-temperature differences (Layer ∆T ), and surface-energy-balance and turbulence indicators. HWs amplified both CUHII and BUHII in a vertically non-uniform manner: CUHII increased more than BUHII, and additional warming concentrated in the canopy and lower boundary layer. Warming propagated upward as the daytime boundary layer developed but contracted toward the surface at night and during transition periods, with upper-level responses weakening or reversing. LCZ heterogeneity was largely confined to the lowest ∼250 m: LCZ 1 showed the strongest additional warming, LCZ 2 and LCZ 4 reached comparable levels through different energy–turbulence pathways, and LCZ 6 was weakest. Stronger sensible heat flux, higher Bowen ratios, sustained nocturnal heat sources, and reduced low-level stability jointly drove this diurnal reorganisation. During HW1, residual-layer warm anomalies in LCZ 1 ( 0.41 °C at 500–600 m) persisted through the night and provided an additional heat reservoir for next-day mixed-layer development, whereas LCZ 6 showed much weaker memory effects. HW2 reproduced the inter-LCZ ranking with weaker absolute amplitude.
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Status: open (until 05 Oct 2026)
- RC1: 'Comment on egusphere-2026-3392', Anonymous Referee #3, 01 Sep 2026 reply
Data sets
The 30 m annual land cover datasets and its dynamics in China from 1985 to 2025 Yang and Huang https://zenodo.org/records/18180184
Global map of Local Climate Zones Demuzere et al. https://zenodo.org/records/6364594
A Harmonized Global Continental High-resolution Planetary Boundary Layer Height Dataset Covering 2017-2021 Guo et al. https://zenodo.org/records/6498004
NCEP GDAS/FNL 0.25 Degree Global Tropospheric Analyses and Forecast Grids National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce https://gdex.ucar.edu/datasets/d083003/
Integrated Global Radiosonde Archive (IGRA), Version 2 – Qingyuan station, July 2020 subset Durre et al. https://doi.org/10.7289/V5X63K0Q
Model code and software
Weather Research and Forecasting (WRF) model Skamarock et al. https://github.com/wrf-model/WRF/tree/release-v4.4
W2W: A Python package that injects WUDAPT’s LocalClimate Zone information in WRF Demuzere et al. https://github.com/matthiasdemuzere/w2w
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This manuscript investigates the vertical structure of heatwave–UHI interactions and their LCZ dependence over Guangzhou using WRF with multi-layer urban canopy schemes. The topic is relevant and is addressed with an appropriate modelling framework and a thoughtfully designed set of diagnostics, and several results are credible. However, the paper's central conclusions on the vertical structure and its LCZ dependence are not yet adequately supported, owing to limited observational constraints, questionable comparability of the analysis periods, insufficient treatment of uncertainty, and interpretations that go beyond what the analysis design can attribute. I recommend major revision. Please see detailed comments below.
Introduction:
Method:
Result: