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Spatial-temporal analysis of monthly air temperature changes from 1979—2014 in the Three Gorges Dam region

  • role： First author第一作者
  • Affiliation：

    National Satellite Meteorological Center, Beijing 100875, China

  • Introduction：王圆圆(1981—　)，女，副研究员，研究方向为生态环境遥感应用。E-mail: wangyuany@cma.gov.cn
Yuanyuan WANG,  
  • Affiliation：

    National Satellite Meteorological Center, Beijing 100875, China

Guicai LI,  
  • Affiliation：

    National Satellite Meteorological Center, Beijing 100875, China

Zheng GUO,  
  • Affiliation：

    National Satellite Meteorological Center, Beijing 100875, China

Zhaodi GUO

Resümee

The near-surface air temperature (Ta) change in the Three Gorges Dam region (TGD) has long been a popular topic in public and research fields. However, fully capturing the spatial pattern of Ta change in TGD is challenging because of the sparse observation net and complicated topographic conditions. Thermal remote sensing technology can obtain spatially contiguous observations of Land Surface Temperature (LST) in a synoptic manner, thus providing invaluable information for spatial pattern analyses of Ta change given the fact that LST and Ta are closely related. This study aims to obtain the monthly Ta from 1979-2014 and determine its trend at a spatial resolution of 1 km. We used the satellite product of LST at nighttime (LSTnight) as a covariate in the general additive model (GAM), which incorporates spline interpolation and linear regression, to ensure high quality of Ta data. First, monthly Ta estimation accuracies estimated with and without LSTnight were compared to evaluate the contribution of LSTnight. Second, the pixel-wise Ta trend was calculated with the Mann-Kendall method, and the spatial-temporal features of the Ta trend were analyzed. Finally, the effects of elevation and tree cover on the Ta trend were assessed. The main results were as follows. (1) When LSTnight was used as a covariate in GAM, temperature interpolation accuracy dramatically improved. The improvement in the cold season was more obvious than that in the warm season because Ta in the cold season is mainly influenced by LST through a strong radiative cooling effect. (2) Inter-annual variation analysis of regional mean annual Ta in TGD revealed that pronounced warming occurred after 1997, and no significant change in Ta was observed after the water level rose to 135 m in 2003. (3) Temporal-spatial analysis of monthly Ta showed that warming occurs in almost every month (except for December), and the most dramatic warming occurs in March and September. In March, pixels with significant warming trends are mainly located in the eastern mountainous TGD, whereas in September, they are mainly located in the western TGD with a relatively flat terrain. (4) The Ta range for most months has been decreasing because the minimum temperature increased at a faster speed than the maximum temperature. Consequently, the lapse rate of Ta showed a decrease. (5) The enhanced warming trend over high elevations indicated a strong positive correlation between the trend of annual Ta and elevation (r = 0.76). However, when the elevations are similar, the warming trend is less pronounced in regions with dense tree cover, suggesting that forests can restrain warming. We conclude that LSTnight information is beneficial to Ta estimation and that the change trend of Ta in TGD shows various features depending on season, region, land cover properties, and temperature metric. Further in-depth analysis of the driving factors of the Ta trend, such as land use/cover or forest cover change, should be implemented in the future to be fully prepared to meet the challenges of climate change in TGD.

Schlüsselwort

Three Gorges Dam region (TGD);warming;general additive model;land surface temperature

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