Effects of land use/cover change on atmospheric humidity in three urban agglomerations in the Yangtze River Economic Belt, China

Abstract

Land use/cover change (LUCC) affects regional climate not only through its direct changes of land surface properties, but also through its further modifications of land–atmosphere interactions. Urban land expansion is a typical case of LUCC in highly populated areas and has been widely discussed about its impacts on regional air temperature, notably known as urban heat island (UHI) effects. Besides temperature, atmospheric humidity, as another key variable in hydrometeorology and climate, would be inevitably affected by LUCC as well. However, the impacts of LUCC on atmospheric humidity seem to have not been investigated as much as those on temperature. We examined atmospheric humidity changes by trend and change point analyses of humidity and heat content indicators of three representative urban agglomerations in the Yangtze River Economic Belt, China during 1965–2017, and found the evident urban dry island (UDI) effects which are characterized by significant humidity decrease and vapor pressure deficit increase. In urban cores with different levels of development, the severity of UDI is different. Furthermore, strong positive correlations between transpiration and evaporation (TEVP) and humidity, and between leaf area and TEVP were recognized during 2001–2017 when cities entered the accelerated stage of land expansion, indicating that LUCC affects regional climate through an ecohydrological way. We speculated that the UDI effect will not appear until urban land expands to a certain scale, for urbanization-induced LUCC may exert a larger influence on UDI than on UHI by considerably altering the latent heat flux in the later period of current urban expansion. The increasing impacts of urbanization on atmospheric humidity should attract wider attention in the future, so as to mitigate climate change and maintain sustainable development.

Appendix

See Figs.

Fig. 20

Annual mean of daily maximum (red solid lines), mean (black solid lines) and minimum dry bulb temperature (blue solid lines) of core cities (double circles in Fig. 1d, left in Figure) and rural areas (cross circles in Fig. 1d, right in Figure; 1965-2017) in the YRDUA

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Fig. 21

Annual mean of daily maximum (red solid lines), mean (black solid lines) and minimum dry bulb temperature (blue solid lines) of core cities (double circles in Fig. 1c, left in Figure) and rural areas (cross circles in Fig. 1c, right in Figure; 1965-2017) in the MUA

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Fig. 22

Annual mean of daily maximum (red solid lines), mean (black solid lines) and minimum dry bulb temperature (blue solid lines) of core cities (double circles in Fig. 1b, left in Figure) and rural areas (cross circles in Fig. 1b, right in Figure; 1965-2017) in the UUA

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Fig. 23

Annual mean of daily maximum (red solid lines), mean (black solid lines) and minimum equivalent temperature (blue solid lines) of core cities (double circles in Fig. 1d, left in Figure) and rural areas (cross circles in Fig. 1d, right in Figure; 1965-2017) in the YRDUA

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Fig. 24

Annual mean of daily maximum (red solid lines), mean (black solid lines) and minimum equivalent temperature (blue solid lines) of core cities (double circles in Fig. 1c, left in Figure) and rural areas (cross circles in Fig. 1c, right in Figure; 1965-2017) in the MUA

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Fig. 25

Annual mean of daily maximum (red solid lines), mean (black solid lines) and minimum equivalent temperature (blue solid lines) of core cities (double circles in Fig. 1b, left in Figure) and rural areas (cross circles in Fig. 1b, right in Figure; 1965-2017) in the UUA

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