This paper investigated spatiotemporal dynamic pattern of vegetation,climate factor,and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform m...This paper investigated spatiotemporal dynamic pattern of vegetation,climate factor,and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets.First,most vegetation canopies demonstrated obvious seasonality,increasing with latitudinal gradient.Second,obvious dynamic trends were observed in both vegetation and climate change,especially the positive trends.Over 70%areas were observed with obvious vegetation greening up,with vegetation degradation principally in the Pearl River Delta,Yangtze River Delta,and desert.Overall warming trend was observed across the whole country(>98%area),stronger in Northern China.Although over half of area(58.2%)obtained increasing rainfall trend,around a quarter of area(24.5%),especially the Central China and most northern portion of China,exhibited significantly negative rainfall trend.Third,significantly positive normalized difference vegetation index(NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions,corresponding to their synchronous stronger seasonal pattern.Finally,at inter-annual level,the NDVI–climate relationship differed with climatic regions and their long-term trends:in humid regions,positive coefficients were observed except in regions with vegetation degradation;in arid,semiarid,and semihumid regions,positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature.This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process.展开更多
This study investigates the influence of interannual vegetation variability. Two sets of offline and online simulations were performed using the Community Earth System Model. The interannual Global LAnd Surface Satell...This study investigates the influence of interannual vegetation variability. Two sets of offline and online simulations were performed using the Community Earth System Model. The interannual Global LAnd Surface Satellite(GLASS) leaf area index(LAI) dataset from 1985 to 2000 and its associated climatological LAI were used to replace the default climatological LAI data in version 4 of the Community Land Model(CLM4). The results showed that on a global scale, canopy transpiration and evaporation, as well as total evapotranspiration in offline simulations were significantly positively correlated with LAI, whereas ground evaporation and ground temperature showed significant negative correlation with LAI. However, the correlations in online simulations were reduced markedly because of interactive feedbacks between albedo, changed climatic factors and atmospheric variability. In the offline simulations, the fluctuations of differences in interannual variability of evapotranspiration and ground temperature focused on vegetation growing regions and the magnitudes were smaller. Those in online simulations spread over more regions and the magnitudes were larger. These results highlight the influence of interannual vegetation variability, particularly in online simulations, an effect that deserves consideration and attention when investigating the uncertainty of climate change.展开更多
基金The authors gratefully acknowledge the financial support received for this work from the National Natural Science Foundation of China(grant number 41071267)the Scientific Research Foundation for Returned Scholars,Ministry of Education of China(grant number[2012]940)the Science Foundation of Fujian Province(grant numbers 2012I0005 and 2012J01167)。
文摘This paper investigated spatiotemporal dynamic pattern of vegetation,climate factor,and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets.First,most vegetation canopies demonstrated obvious seasonality,increasing with latitudinal gradient.Second,obvious dynamic trends were observed in both vegetation and climate change,especially the positive trends.Over 70%areas were observed with obvious vegetation greening up,with vegetation degradation principally in the Pearl River Delta,Yangtze River Delta,and desert.Overall warming trend was observed across the whole country(>98%area),stronger in Northern China.Although over half of area(58.2%)obtained increasing rainfall trend,around a quarter of area(24.5%),especially the Central China and most northern portion of China,exhibited significantly negative rainfall trend.Third,significantly positive normalized difference vegetation index(NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions,corresponding to their synchronous stronger seasonal pattern.Finally,at inter-annual level,the NDVI–climate relationship differed with climatic regions and their long-term trends:in humid regions,positive coefficients were observed except in regions with vegetation degradation;in arid,semiarid,and semihumid regions,positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature.This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process.
基金supported by Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA05110103)the National High Technology Research and Development Program of China (863 Program, Grant No. 2009AA122100)
文摘This study investigates the influence of interannual vegetation variability. Two sets of offline and online simulations were performed using the Community Earth System Model. The interannual Global LAnd Surface Satellite(GLASS) leaf area index(LAI) dataset from 1985 to 2000 and its associated climatological LAI were used to replace the default climatological LAI data in version 4 of the Community Land Model(CLM4). The results showed that on a global scale, canopy transpiration and evaporation, as well as total evapotranspiration in offline simulations were significantly positively correlated with LAI, whereas ground evaporation and ground temperature showed significant negative correlation with LAI. However, the correlations in online simulations were reduced markedly because of interactive feedbacks between albedo, changed climatic factors and atmospheric variability. In the offline simulations, the fluctuations of differences in interannual variability of evapotranspiration and ground temperature focused on vegetation growing regions and the magnitudes were smaller. Those in online simulations spread over more regions and the magnitudes were larger. These results highlight the influence of interannual vegetation variability, particularly in online simulations, an effect that deserves consideration and attention when investigating the uncertainty of climate change.
