With correlation analysis and factor analysis methods, the effects of preceding Pacific SSTs on subtropical high indexes of main raining seasons are discussed. The results of correlation analysis show that the effects...With correlation analysis and factor analysis methods, the effects of preceding Pacific SSTs on subtropical high indexes of main raining seasons are discussed. The results of correlation analysis show that the effects of SSTs on five subtropical high indexes differ in seasons and regions. The variation of SSTs mostly affects the area and intensity indexes of the subtropical high, followed by the western ridge index, and the effect on the ridge line index is more remarkable than on the north boundary index. The results of factor analysis reveals that the first common factor of SST of each season reflected mainly the inverse relation of SSTs variation between the central and eastern part of equatorial Pacific and the western Pacific, which correlates better with the subtropical high indexes in the main raining seasons than other common factors of SST. The analysis of interdecadal variation indicated that the variation of SSTs was conducive to the emergence of the La Ni?a event before the end of 1970s, such that in the summer the subtropical high is likely to be weaker and smaller and located eastward and northward. After the 1980s, the opposite characteristics prevailed.展开更多
Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations(temperature and precipitation) on vegetation changes for a better understan...Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations(temperature and precipitation) on vegetation changes for a better understanding of acclimation to climatic change. In this paper, we focused on the integration and application of multi-methods and spatial analysis techniques in GIS to study the spatio-temporal variation of vegetation dynamics and to explore the vegetation change mechanism. The correlations between EVI and climate factors at different time scales were calculated for each pixel including monthly, seasonal and annual scales respectively in Qinghai Lake Basin from the year of 2001 to 2012. The primary objectives of this study are to reveal when, where and why the vegetation change so as to support better understanding of terrestrial response to global change as well as the useful information and techniques for wise regional ecosystem management practices. The main conclusions are as follows:(1) Overall vegetation EVI in the region increased 6% during recent 12 years. The EVI value in growing seasons(i.e. spring and summer) exhibited very significant improving trend, accounted for 12.8% and 9.3% respectively. The spatial pattern of EVI showed obvious spatial heterogeneity which was consistent with hydrothermal condition. In general, the vegetation coverage improved in most parts of the area since nearly 78% pixel of the whole basin showed increasing trend, while degraded slightly in a small part of the area only.(2) The EVI change was positively correlated with average temperature and precipitation. Generally speaking, in Qinghai Lake Basin, precipitation was the dominant driving factor for vegetation growth; however, at different time scale its weight to vegetation has differences.(3) Based on geo-statistical analysis, the autumn precipitation has a strong correlation with the next spring EVI values in the whole region. This findings explore the autumn precipitation is an important indicator, and then, limits the plant growth of next spring.展开更多
文摘With correlation analysis and factor analysis methods, the effects of preceding Pacific SSTs on subtropical high indexes of main raining seasons are discussed. The results of correlation analysis show that the effects of SSTs on five subtropical high indexes differ in seasons and regions. The variation of SSTs mostly affects the area and intensity indexes of the subtropical high, followed by the western ridge index, and the effect on the ridge line index is more remarkable than on the north boundary index. The results of factor analysis reveals that the first common factor of SST of each season reflected mainly the inverse relation of SSTs variation between the central and eastern part of equatorial Pacific and the western Pacific, which correlates better with the subtropical high indexes in the main raining seasons than other common factors of SST. The analysis of interdecadal variation indicated that the variation of SSTs was conducive to the emergence of the La Ni?a event before the end of 1970s, such that in the summer the subtropical high is likely to be weaker and smaller and located eastward and northward. After the 1980s, the opposite characteristics prevailed.
基金National Science & Technology Support Program,No.2012BAH31B03 National Natural Science Foundation of China,No.41301007+1 种基金No.40901101 The Fundamental Research Funds for the Central Universities,No.xjj2013079
文摘Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations(temperature and precipitation) on vegetation changes for a better understanding of acclimation to climatic change. In this paper, we focused on the integration and application of multi-methods and spatial analysis techniques in GIS to study the spatio-temporal variation of vegetation dynamics and to explore the vegetation change mechanism. The correlations between EVI and climate factors at different time scales were calculated for each pixel including monthly, seasonal and annual scales respectively in Qinghai Lake Basin from the year of 2001 to 2012. The primary objectives of this study are to reveal when, where and why the vegetation change so as to support better understanding of terrestrial response to global change as well as the useful information and techniques for wise regional ecosystem management practices. The main conclusions are as follows:(1) Overall vegetation EVI in the region increased 6% during recent 12 years. The EVI value in growing seasons(i.e. spring and summer) exhibited very significant improving trend, accounted for 12.8% and 9.3% respectively. The spatial pattern of EVI showed obvious spatial heterogeneity which was consistent with hydrothermal condition. In general, the vegetation coverage improved in most parts of the area since nearly 78% pixel of the whole basin showed increasing trend, while degraded slightly in a small part of the area only.(2) The EVI change was positively correlated with average temperature and precipitation. Generally speaking, in Qinghai Lake Basin, precipitation was the dominant driving factor for vegetation growth; however, at different time scale its weight to vegetation has differences.(3) Based on geo-statistical analysis, the autumn precipitation has a strong correlation with the next spring EVI values in the whole region. This findings explore the autumn precipitation is an important indicator, and then, limits the plant growth of next spring.