目前太阳对地球能量平衡影响的研究大都是以太阳总辐射通量密度作为输入参数的.本文以美国航空航天局(National Aeronautics and Space Administration,NASA)太阳辐射与气候实验项目的卫星实测数据为基础,对太阳上升相(2010年上半年)和...目前太阳对地球能量平衡影响的研究大都是以太阳总辐射通量密度作为输入参数的.本文以美国航空航天局(National Aeronautics and Space Administration,NASA)太阳辐射与气候实验项目的卫星实测数据为基础,对太阳上升相(2010年上半年)和下降相(2007年12月)期间太阳光谱变化对地球能量平衡的影响进行了研究.结果表明,2010年上半年较强的太阳总辐射通量密度主要是由紫外及红外波段的能量增强引起的,其在200~400 nm和760~4000 nm波段内的平均能量分别增加了0.11%和0.05%,而在400~760 nm可见光区的能量却呈减小趋势,平均减小量为0.05%.通过对MLS 2.2全球臭氧日数据进行再分析后发现,相对于2007年12月,2010年上半年平流层臭氧浓度也有所增加,其中在太阳紫外辐射呈现较大增强的2月和3月,其臭氧增量也相对较大,最大值分别出现在33 km和40 km处,值为0.6 mL·m^(-3)和0.62 mL·m^(-3).因此,可见光区能量减弱与平流层臭氧浓度增加的双重削弱作用致使虽然2010年上半年的太阳总辐射通量密度较大,但是到达对流层顶的太阳辐射却有所减小,最大减小量出现在3月,值为0.15 W·m^(-2).这一结果说明,太阳活动或总辐射通量密度的增强也有可能对地球对流层系统起到冷却作用.展开更多
Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data wit...Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics,improve spatially extended estimates of vegetation productivity with high accuracy.In this study,the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM),which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types.The field data were collected by coordinating observations at nine stations in 2008.The results indicate that in the region during the growing season GPP was highest in cropland sites,second highest in woodland sites,and lowest in grassland sites.VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas.Further,Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas,while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation.This study demonstrates the potential of satellite-driven models for scaling-up GPP,which is a key component for studying the carbon cycle at regional and global scales.展开更多
基金supported by the National Basic Research Program of China (Grant Nos. 2009CB723904 and 2006CB400500)
文摘Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics,improve spatially extended estimates of vegetation productivity with high accuracy.In this study,the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM),which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types.The field data were collected by coordinating observations at nine stations in 2008.The results indicate that in the region during the growing season GPP was highest in cropland sites,second highest in woodland sites,and lowest in grassland sites.VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas.Further,Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas,while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation.This study demonstrates the potential of satellite-driven models for scaling-up GPP,which is a key component for studying the carbon cycle at regional and global scales.
