In order to catch more process details in chemical processes, adynamic model for prediction of process trends is proposed bymodifying traditional time-series ANN (artificial neural networks)model with impulse response...In order to catch more process details in chemical processes, adynamic model for prediction of process trends is proposed bymodifying traditional time-series ANN (artificial neural networks)model with impulse response identification means. The applicationresults of the model is briefly discussed.展开更多
Aims Recent warmer and wetter climate in northern China remains a hot topic in recent years,yet its effect on vegetation growth has not been fully understood.This study investigated the temporal change of vegetation c...Aims Recent warmer and wetter climate in northern China remains a hot topic in recent years,yet its effect on vegetation growth has not been fully understood.This study investigated the temporal change of vegetation cover and its correlations with climatic variables from 1982 to 2018 for grasslands in northern China.Our aim is to clarify whether the warmer and wetter climate in recent years drives the greening of the vegetation in this region.Methods We investigated the temporal dynamic of vegetation normalized difference vegetation index(NDVI)and its driving forces based on long time-series data.Piecewise regression was used to examine whether there was a turning point of the trend of NDVI and climatic variables.Pearson correlation analyses were conducted to quantify the relationship between NDVI and climatic factors.Stepwise multivariable regression was used to quantify the contributions of climate variables to the temporal variations in NDVI.Important Findings We found a turning point of NDVI trend in 2008,with GIMMS NDVI indicating a slight increase of 0.00022 yr?1 during 1982–2008 to an increase of 0.002 yr?1 for GIMMS NDVI during 2008–2015 and 0.0018 yr?1 for MODIS NDVI during 2008–2018.Precipitation was the predominant driver,and air temperature and vapor pressure deficit exerted a minor impact on the temporal dynamics of NDVI.Overall,our results suggest a turning point of NDVI trend,and that recent warmer and wetter climate has caused vegetation greening,which provides insights for better predicting the vegetation cover in this region under changing climate.展开更多
文摘In order to catch more process details in chemical processes, adynamic model for prediction of process trends is proposed bymodifying traditional time-series ANN (artificial neural networks)model with impulse response identification means. The applicationresults of the model is briefly discussed.
基金This research was supported by the National Natural Science Foundation of China(31922053,31570437)the National Key Research and Development Program of China(2017YFA0604801).
文摘Aims Recent warmer and wetter climate in northern China remains a hot topic in recent years,yet its effect on vegetation growth has not been fully understood.This study investigated the temporal change of vegetation cover and its correlations with climatic variables from 1982 to 2018 for grasslands in northern China.Our aim is to clarify whether the warmer and wetter climate in recent years drives the greening of the vegetation in this region.Methods We investigated the temporal dynamic of vegetation normalized difference vegetation index(NDVI)and its driving forces based on long time-series data.Piecewise regression was used to examine whether there was a turning point of the trend of NDVI and climatic variables.Pearson correlation analyses were conducted to quantify the relationship between NDVI and climatic factors.Stepwise multivariable regression was used to quantify the contributions of climate variables to the temporal variations in NDVI.Important Findings We found a turning point of NDVI trend in 2008,with GIMMS NDVI indicating a slight increase of 0.00022 yr?1 during 1982–2008 to an increase of 0.002 yr?1 for GIMMS NDVI during 2008–2015 and 0.0018 yr?1 for MODIS NDVI during 2008–2018.Precipitation was the predominant driver,and air temperature and vapor pressure deficit exerted a minor impact on the temporal dynamics of NDVI.Overall,our results suggest a turning point of NDVI trend,and that recent warmer and wetter climate has caused vegetation greening,which provides insights for better predicting the vegetation cover in this region under changing climate.
