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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Detection of large-scale climate signals in spring vegetation index (normalized difference vegetation index) over the Northern Hemisphere - art. no. 4498
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Detection of large-scale climate signals in spring vegetation index (normalized difference vegetation index) over the Northern Hemisphere - art. no. 4498

机译:北半球春季植被指数(归一化植被指数)中大规模气候信号的探测-艺术。没有。 4498

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Climate is one of the determinants driving ecosystems on both local and global scales. During the last two decades, there has occurred a dramatic temperature increase in the northern midlatitudes to high latitudes. The rapid warming has resulted in the promotion of bioactivity and an early growing season. However, the temperature and vegetation changes are not uniform in geographical distribution. In the present study, we analyze the spatial features in the normalized difference vegetation index (NDVI)-temperature relationship over Eurasia and North America in spring for the period 1982-2000. The NDVI data are derived from the Earth Observing System Pathfinder advanced very high resolution radiometer data sets. A singular value decomposition analysis is applied to the covariance matrix of the NDVI and temperature. Most of the squared covariance, 91.6%, is captured by the first seven paired modes. The result clearly indicates that the temperature is a focal factor influencing vegetation activity. Furthermore, those seven paired modes show large-scale features and well-defined patterns. The atmospheric circulation systems, such as the Southern Oscillation, North Atlantic Oscillation/Arctic Oscillation, Pacific/North American pattern, Eurasian pattern, western Pacific pattern, western Atlantic pattern, eastern Atlantic pattern, and North Pacific index, are found to be associated with that. The time coefficient corresponding to the first paired modes, centered on western Siberia, is correlated significantly with the Eurasian teleconnection pattern. Their correlation coefficients are 0.72 and 0.78 for vegetation and temperature, respectively, for the data period. Other modes are also correlated with one or more circulation indices. This implies that the large-scale circulation is essential for understanding the regional response of vegetation to global climate change. Taking all nine circulation indices and time lags into account, a large portion (71%) of the satellite-sensed variance in NDVI could be explained. The temperature-NDVI relationships did not change significantly when the NDVI was rescaled from 1 to 5 degrees, indicating that the singular value decomposition analysis is an appropriate technique for detecting the degree of coupling between vegetation and climate and that the vegetation-temperature relationship presented in this study is robust. [References: 39]
机译:气候是在本地和全球范围内推动生态系统的决定因素之一。在过去的二十年中,北中纬度地区到高纬度地区的气温急剧上升。快速变暖导致生物活性的提高和生长季节的提前。但是,温度和植被变化在地理分布上并不统一。在本研究中,我们分析了1982-2000年春季欧亚大陆和北美春季归一化植被指数(NDVI)-温度关系的空间特征。 NDVI数据来自“地球观测系统探路者”高级超高分辨率辐射计数据集。将奇异值分解分析应用于NDVI和温度的协方差矩阵。前七个配对模式捕获了大多数平方协方差,即91.6%。结果清楚地表明温度是影响植被活动的焦点因素。此外,这七个配对模式显示了大规模特征和定义明确的模式。大气循环系统,如南方涛动,北大西洋涛动/北极涛动,太平洋/北美格局,欧亚格局,西太平洋格局,西大西洋格局,东大西洋格局和北太平洋指数,都与那。以西伯利亚西部为中心的对应于第一对模式的时间系数与欧亚遥相关模式显着相关。在数据周期内,植被和温度的相关系数分别为0.72和0.78。其他模式也与一个或多个循环指标相关。这意味着大规模的环流对于了解植被对全球气候变化的区域响应至关重要。考虑到所有九个环流指数和时滞,可以解释NDVI中卫星感知变化的很大一部分(71%)。当将NDVI从1调整为5度时,温度与NDVI的关系没有显着变化,这表明奇异值分解分析是检测植被与气候之间耦合程度的一种合适技术,并且植被与温度之间的关系如图5所示。这项研究是可靠的。 [参考:39]

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