Varying Responses of Vegetation Greenness to the Diurnal Warming across the Global

Abstract

The distribution of global warming has been varying both diurnally and seasonally. Little is known about the spatiotemporal variations in the relationships between vegetation greenness and day- and night-time warming during the last decades. We investigated the global inter- and intra-annual responses of vegetation greenness to the diurnal asymmetric warming during the period of 1982–2015, using the normalized different vegetation index (NDVI, a robust proxy for vegetation greenness) obtained from the NOAA/AVHRR NDVI GIMMS3g dataset and the monthly average daily maximum (Tmax) and minimum temperature (Tmin) obtained from the gridded Climate Research Unit, University of East Anglia. Several findings were obtained: (1) The strength of the relationship between vegetation greenness and the diurnal temperature varied on inter-annual and seasonal timescales, indicating generally weakening warming effects on the vegetation activity across the global. (2) The decline in vegetation response to Tmax occurred mainly in the mid-latitudes of the world and in the high latitudes of the northern hemisphere, whereas the decline in the vegetation response to Tmin primarily concentrated in low latitudes. The percentage of areas with a significantly negative trend in the partial correlation coefficient between vegetation greenness and diurnal temperature was greater than that of the areas showing the significant positive trend. (3) The trends in the correlation between vegetation greenness and diurnal warming showed a complex spatial pattern: the majority of the study areas had undergone a significant declining strength in the vegetation greenness response to Tmax in all seasons and to Tmin in seasons except autumn. These findings are expected to have important implications for studying the diurnal asymmetry warming and its effect on the terrestrial ecosystem.

Impact of Preseason Climate Factors on Vegetation Photosynthetic Phenology in Mid–High Latitudes of the Northern Hemisphere

“…Over the past 50 years, temperature data suggest that nighttime warming in northern land areas has outpaced daytime warming [32], leading to a diminished trend in DTR. This asymmetrical warming has been confirmed to impact vegetation productivity [33], and our research further suggests that changes in DTR can also have a significant effect on the SOS of vegetation. Primarily, a significant negative correlation between DTR and the SOS of vegetation exists across the vast majority of regions (Figure 5).…”

“…In our study, it was possible for multicollinearity to be present among several climate variables, such as T mean , DTR, and precipitation. To mitigate the influence of these confounding variables and obtain a clearer understanding of the relationship between individual climate factors and vegetation photosynthetic phenology metrics, we employed first-order partial correlation analysis (Equation (1)), as previously employed in studies by Du et al (2022) [1] and Huang et al (2020) [21].…”

Interannual Variations in Terrestrial Net Ecosystem Productivity and Climate Attribution in the Southern Hilly Region of China

“…As a pivotal component of the global terrestrial ecosystem, land surface vegetation plays a crucial role in energy transfer, the water balance, the carbon cycle, and climate regulation [ 1 , 2 ]. One vital indicator of ecosystem function is net primary productivity (NPP), defined as the net carbon uptake by plants through photosynthesis (the difference between the carbon assimilated during photosynthesis and that released during plant respiration) [ 3 , 4 ].…”

Remote Sensing of Poplar Phenophase and Leaf Miner Attack in Urban Forests

“…Serbia's air is extremely polluted so global dimming might cause changes in the NDVI [105]. Likewise, some oscillations are expected due to diurnal warming [106], human-associated activities [107], and an increase in CO 2 fertilization [108,109]. Medium and coarse spatial resolution sensors were most frequently used for mapping broadleaved defoliation, and researchers still found intra-annual time series analysis to be of crucial importance when studying these data sets [110,111].…”