利用MSU序列研究高空大气温度变化的进展   总被引：2，自引：0，他引：2  

廖蜜  张鹏  吴雪宝  邱红 《气象》2011,37(9):1151-1157

美国NOAA卫星上搭载的微波大气探测仪MSU以及后续继承改进仪器AMSU,自1978年投入运行以来,已经积累了超过30年的全球大气温度的观测资料。近年来,国外学者通过仪器定标误差订正、卫星轨道衰减订正、观测时间差异导致的温度日变化订正、仪器间的相互定标处理等技术,发现并剔除了一些影响较大的非气候因素,提高了该序列资料的质量,并用于全球气候变化研究,特别是对流层和平流层近30年的温度变化研究,研究结果是对常规地面和探空资料分析结果的重要补充。本文对目前国际上3种常用的MSU序列资料集的定标误差、偏差订正和不同卫星上仪器观测序列的一致化处理方法进行了综合介绍,并比较分析了3种资料用于30年高空大气温度变化趋势分析的异同。  相似文献   

电线积冰物理过程与数值模拟研究进展   总被引：1，自引：0，他引：1  

杨军  谢真珍 《气象》2011,37(9):1158-1165

电线积冰对人们的日常生活、电力系统、通信系统等造成了巨大的影响,人们越来越关注电线积冰的形成条件及物理过程,包括气象条件、气流动力学、液滴运动轨迹以及热力学过程。通过外场观测、室内实验和数值模拟研究的不断开展,揭示出电线积冰质量增长过程决定于云降水粒子谱分布、碰撞效率、黏性率、冻结率、碰撞速度和角度等微物理参数,这些参数又受控于降水率、云雾含水量、温度、湿度、风向、风速等宏观气象条件。通过数值模式已可进行电线积冰量和积冰持续时间的定量研究和预测,进而在开发垂冰模式和形态模式等方面也取得了新的进展。在总结过去60多年来电线积冰物理机制和数值模拟研究主要成果的基础上,对开展进一步的深入研究进行了展望。  相似文献   

利用微波辐射计AMSR-E反演陆地上空大气水汽的研究     

刘文娟  王永前 《四川气象》2011,(3):23-25

目前的大气水汽算法只适用于晴空条件,但是全球大部分时间云层覆盖都处于40%～60%之间。因此,只适用于晴空条件下的大气水汽反演算法,是不能满足应用需求的。而微波具有一定的穿透能力这一特点,使得其在全天候大气水汽探测方面具有很大的发展潜力。本文发展了基于微波辐射计AMSR-E的数据反演大气水汽的算法,利用不同波段间地表发射率之间的线性关系,消去辐射计信号中的地表信息,而AMSR-E的23.8GHz对大气水汽比较敏感,因此用其反演大气水汽,反演的结果和MODIS以及实测的数据进行对比,算法优势明显。  相似文献   

Modelling the Gross Primary Productivity of West Africa with the Regional Biomass Model RBM+, using optimized 250 m MODIS FPAR and fractional vegetation cover information     

《International Journal of Applied Earth Observation and Geoinformation》2015

Global warming associated with climate change is one of the greatest challenges of today’s world. Increasing emissions of the greenhouse gas CO₂ are considered as a major contributing factor to global warming. One regulating factor of CO₂ exchange between atmosphere and land surface is vegetation. Measurements of land cover changes in combination with modelling the Gross Primary Productivity (GPP) can contribute to determine important sources and sinks of CO₂.The aim of this study is to accurately model the GPP for a region in West Africa with a spatial resolution of 250 m, and the differentiation of GPP based on woody and herbaceous vegetation. For this purpose, the Regional Biomass Model (RBM) was applied, which is based on a Light Use Efficiency (LUE) approach. The focus was on the spatial enhancement of the RBM from the original 1000–250 m spatial resolution (RBM+). The adaptation to the 250 m scale included the modification of two main input parameters: (1) the fraction of absorbed Photosynthetically Active Radiation (FPAR) based on the 1000 m MODIS MOD15A2 FPAR product which was downscaled to 250 m using MODIS NDVI time series; (2) the fractional cover of woody and herbaceous vegetation, which was improved by using a multi-scale approach. For validation and regional adjustments of GPP and the input parameters, in situ data from a climate station and eddy covariance measurements were integrated.The results of this approach show that the input parameters could be improved significantly: downscaling considerably reduces data gaps of the original FPAR product and the improved dataset differed less than 5.0% from the original data for cloud free regions. The RMSE of the fractional vegetation cover varied between 5.1 and 12.7%. Modelled GPP showed a slight overestimation in comparison to eddy covariance measurements. The in situ data was exceeded by 8.8% for 2005 and by 2.0% for 2006. The model results were converted to NPP and also agreed well with previous NPP measurements reported from different studies. Altogether a high accuracy and suitability of the regionally adjusted and downscaled model RBM+ can be concluded. The differentiation between vegetation growth forms allows a separation of long-term and short-term carbon storage based on woody and herbaceous vegetation, respectively.  相似文献   

Evaluating the relationship between biomass,percent groundcover and remote sensing indices across six winter cover crop fields in Maryland,United States     

《International Journal of Applied Earth Observation and Geoinformation》2015

Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r² = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r² = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.  相似文献   

Reducing background effects in orchards through spectral vegetation index correction     

《International Journal of Applied Earth Observation and Geoinformation》2015

Satellite remote sensing provides an alternative to time-consuming and labor intensive in situ measurements of biophysical variables in agricultural crops required for precision agriculture applications. In orchards, however, the spatial resolution causes mixtures of canopies and background (i.e. soil, grass and shadow), hampering the estimation of these biophysical variables. Furthermore, variable background mixtures obstruct meaningful comparisons between different orchard blocks, rows or within each row. Current correction methodologies use spectral differences between canopies and background, but struggle with a vegetated orchard floor. This background influence and the lack of a generic solution are addressed in this study.Firstly, the problem was demonstrated in a controlled environment for vegetation indices sensitive to chlorophyll content, water content and leaf area index. Afterwards, traditional background correction methods (i.e. soil-adjusted vegetation indices and signal unmixing) were compared to the proposed vegetation index correction. This correction was based on the mixing degree of each pixel (i.e. tree cover fraction) to rescale the vegetation indices accordingly and was applied to synthetic and WorldView-2 satellite imagery. Through the correction, the effect of background admixture for vegetation indices was reduced, and the estimation of biophysical variables was improved (ΔR² = 0.2–0.31).  相似文献   

Assessing the Measurement Consistency Between the Jason-2/AMR and SARAL/AltiKa/DFMR Microwave Radiometers Using Simultaneous Nadir Observations     

Bin Zhang  Changyong Cao  John Lillibridge  Laury Miller 《Marine Geodesy》2015,38(3):143-155

SARAL/AltiKa has a Dual Frequency Microwave Radiometer (DFMR), and Jason-2 has an Advanced Microwave Radiometer (AMR). Both microwave radiometer sensors include a 23.8 GHz primary water sensing channel. The measurement consistencies between DFMR and AMR are important for establishing a consistent altimetry data set between SARAL/AltiKa and Jason-2 in order to accurately assess sea level rise in a long-term time series. This study investigates the measurement consistency in the 23.8 GHz channel between DFMR and AMR at the Simultaneous Nadir Overpasses (SNO's) between the two satellites and also at coldest ocean brightness temperature locations. Preliminary results show that while both instruments show no significant trends over the one year since the launch of SARAL, a consistent relative bias of 2.88 K (DFMR higher than AMR) with a standard deviation of 0.98 K is observed. The relative bias at the lowest brightness temperature from the SNO method (-3.82 K) is consistent with that calculated from coldest ocean method (-3.74 K). The relative bias exhibits strong latitude (and scene temperature) dependency, changing from -3.82 K at high latitudes to -0.92 K near the equator. There also exists an asymmetry between the northern and southern hemisphere. The relative bias increases toward the lower end of brightness temperature.  相似文献   

基于HJ-1A高光谱的黄河口碱蓬和柽柳盖度反演模型研究   总被引：3，自引：2，他引：1  

任广波  张杰  马毅 《海洋学报》2015,37(9):51-58

碱蓬和柽柳是黄河口湿地典型的盐生植物类型,是多种保护珍禽的主要栖息地,具有景观尺度较小、分布广且多混生的特点。应用覆盖黄河口北部潮滩的HJ-1A高光谱遥感影像,基于现场测量的端元光谱和从遥感影像中使用顺序最大角凸锥法(SAMCC)自动提取的端元光谱,应用线性光谱分解法(LSU)、正交子空间投影法(OSP)、匹配滤波法(MF)、最小能量约束法(CEM)和自适应一致估计法(ACE)5种不同光谱解混方法进行混合像元光谱解混,对比两种方法得到的端元光谱分别对碱蓬和柽柳盖度的反演能力,并给出相应的反演模型。结果显示:(1)现场测量端元光谱取得了较好的碱蓬和柽柳盖度反演结果,其中应用LSU方法的光谱解混结果与现场测量盖度的决定系数对于碱蓬和柽柳分别达到了0.88和0.95;(2)两种端元获取方式的光谱解混结果中,LSU和OSP方法均获得了较高的相关性,ACE解混方法的相关性都最低;(3)SAMCC方法提取端元光谱对柽柳的分解结果与现场测量盖度的相关性远高于碱蓬。  相似文献   

An assessment of arctic sea ice concentration retrieval based on “HY-2” scanning radiometer data using field observations during CHINARE-2012 and other satellite instruments     

SHI Lijiang  LU Peng  CHENG Bin  KARVONEN Juha  WANG Qimao  LI Zhijun  HAN Hongwei 《海洋学报(英文版)》2015,(3)

A retrieval algorithm of arctic sea ice concentration (SIC) based on the brightness temperature data of “HY-2” scanning microwave radiometer has been constructed. The tie points of the brightness tempe...  相似文献   

长江上游安宁河流域植被生长变化对气候条件的响应   总被引：1，自引：0，他引：1  

仙巍  邵怀勇 《国土资源遥感》2015,(3)

为探讨安宁河流域植被演变趋势及其与气候的相互作用,基于2001—2008年MODIS图像、降水量和气温数据,采用回归分析和相关分析等方法计算了安宁河流域降水、气温和归一化差值植被指数(normalized difference vegetation index,NDVI)在时间和空间上的变化情况,并对安宁河流域植被生长变化对气候条件的响应机制进行了探讨。结果表明:NDVI变化和气温、降水呈正相关;降水量和气温等气候因子的变动会直接反映在植被长势上,其中降水对安宁河流域植被生长的影响更为显著;植被长势与气温和降水存在一定的时间滞后性。  相似文献