Asymmetry of Daytime and Nighttime Warming in Typical Climatic Zones along the Eastern Coast of China and Its Influence on Vegetation Activities

Abstract

In this dissertation, the author adopted the normalized difference vegetation index (NDVI) and meteorological data from 1982 to 2016 of the typical climate zones in coastal areas of China to analyze the influence of daytime and nighttime warming asymmetric changes in different seasons on vegetation activities during the growing season period according to the copula function theory optimized based on Markov chain Monte Carlo (MCMC). The main conclusions are as follows: (1) The seasonal daytime and nighttime warming trends of Guangdong, Jiangsu and Liaoning over the past 35 years were significant, and the daytime and nighttime warming rates were asymmetric. In spring and summer of Guangdong province, the warming rate in the daytime was higher than that at night, while, in autumn, the opposite law was observed. However, the warming rate in the daytime was lower than that at night in Jiangsu and Liaoning provinces. There were latitude differences in diurnal and nocturnal warming rate. (2) The daytime and nighttime warming influences on vegetation showed significant seasonal differences in these three regions. In Guangdong, the influence of nighttime warming on vegetation growth in spring is greater than that in summer, and the influences of daytime warming on vegetation growth from strong to weak were spring, summer and autumn. In Jiangsu, both the influences of daytime and nighttime warming on vegetation growth in summer were less than that in autumn. In Liaoning, both the influences of daytime and nighttime warming on vegetation growth from strong to weak were autumn, spring and summer. (3) In Guangdong, Jiangsu and Liaoning provinces, their maximum temperature (Tmax) and minimum temperature (Tmin) and the joint probability distribution functions of NDVI, all had little effect on NDVI when Tmax and Tmin respectively reached their minimum values, but their influences on NDVI were obvious when Tmax and Tmin respectively reached their maximum values. (4) The smaller the return period, the larger the range of climate factor and NDVI, which has indicated that when the climate factor is certain, the NDVI is more likely to have a smaller return period, and the frequency of NDVI over a certain period is higher. In addition, the larger the climate factor, the greater the return period is and NDVI is less frequent over a certain period of time. This research can help with deep understanding of the dynamic influence of seasonal daytime and nighttime asymmetric warming on the vegetation in typical coastal temperature zones of China under the background of global climate change.

Comparison between Satellite Derived Solar-Induced Chlorophyll Fluorescence, NDVI and kNDVI in Detecting Water Stress for Dense Vegetation across Southern China

“…Historical data from 2001 to 2020 show an increase in grassland areas and an upward trend in NDVI in the Tibetan Plateau, which may have partially obscured the response of NDVI to moisture changes [38]. In Guangdong province, earlier studies have identified temperature as a primary factor affecting vegetation growth [39,40]. The saturation effect in NDVI may have contributed to the high positive correlation observed between NDVI and SPEI3.…”

Responses of Bacterial Communities in Soils under Winter Wheat to Nightly Warming and Nitrogen Addition

“…Asymmetric diurnal warming is one of the main features of global warming. In the past 35 years, the trend of daytime and nighttime warming in Jiangsu province is obvious, and the rate of daytime and nighttime warming is asymmetric [7]. The rate of increase in global warming in the daytime was lower than that at night, this asymmetric warming is likely to intensify in the coming decades, ultimately leading to a drop in the day and night temperature range [8][9][10].…”

Exploring the Dynamic Impact of Extreme Climate Events on Vegetation Productivity under Climate Change

“…The variations in DTR have significant impact on the growth and development of vegetation [10]. As a crucial factor in the vegetation ecosystem, the DTR affects the growth dynamics, structures, and functions of vegetation by altering its growth environments [11]. Based on long-term remote sensing data and meteorological data, previous studies have explored the spatiotemporal distribution characteristics of NDVI and its relationship with precipitation and temperature at various time scales [12][13][14].…”