Assessing the Spatial Variability of Daytime/Nighttime Extreme Heat Waves in Beijing under Different Land-Use during 2011–2020

Xiaokang Su, Fang Wang (), Demin Zhou and Hongwen Zhang
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Xiaokang Su: College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
Fang Wang: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Demin Zhou: College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
Hongwen Zhang: Beijing Meteorological Disaster Prevention Center, Beijing 100089, China

Land, 2022, vol. 11, issue 10, 1-13

Abstract: Urban land-use affects surface air temperature; however, the impact of urban land-use on surface air temperature, particularly the extent to which it affects the duration of extreme heat waves, remains uncertain and the mechanisms of diurnal differences need to be further explored. This paper presents study of daytime/nighttime extreme heat waves duration in Beijing under different land-use changes by adopting an index of cumulative hours of extreme heat waves exceeding the certain thresholds. The urban day/night extreme heat waves cumulative hourly interpolation models were established based on high-resolution urban land-use and socioeconomic data and were assessed to have good performance. The annual average cumulative hours of extreme heat waves increased by 95% (daytime) and 116% (nighttime) in 2016–2020 compared to 2011–2015. The cumulative hours for each land-use type ranked as follows: urban land > cropland > water > grassland > woodland. We found that the cumulative hours of extreme heat waves increased significantly with the proportion of urban land and decreased significantly with the proportion of forested land and water. This research provided important information for alleviating extreme heat waves in cities and for rational land planning.

Keywords: extreme heat waves; land use/cover; interpolation models; daytime; nighttime (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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