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1.
尝试以单星多角度卫星观测数据同时反演晴空陆地的气溶胶光学厚度和地表反射率,并选取2009年5月的MODIS(Moderate Resolution Imaging Spectroradiometer)1B资料进行了反演试验.结果表明:单星多角度法反演得到的气溶胶光学厚度结果与MODIS气溶胶产品(MOD04)平均值的相关系数为0.7914;反演的地表反射率结果与MODIS地表反射率产品(MOD09)也具有较好的一致性.对直接利用单星多角度观测数据反演获得一段时间内平均的气溶胶光学厚度进行了有益的尝试.  相似文献   

2.
李雪  钟仕全 《贵州气象》2013,37(Z1):37-41
以典型岩溶地貌区为研究区,HJ-1B遥感数据为数据源,通过分别采用覃志豪单窗算法、普适性单通道算法、基于影像的Artis反演算法,并对其中的经验关系式进行修订,最后反演出研究区的地表温度,与MODIS温度产品(MOD11_L2)进行对比分析,探寻适用于岩溶地貌区利用HJ卫星遥感数据进行干旱监测的地表温度反演算法。结果表明,修订后的普适性单通道算法优于其他两种算法,其与MODIS温度产品平均温差相差0.36 K,反演精度达到1 K之内,说明该算法经过修订后适用于反演岩溶地貌区的地表温度。  相似文献   

3.
海表温度是研究海洋表面海气相互作用的一个至关重要的物理参数。为建立长时间序列海表温度数据集,在海表温度反演模型建立过程中还需要考虑卫星之间的差异、卫星仪器随时间的衰减、所采用反演算法模型建立过程中人的主观因素的影响等。为此,针对1989—2008年间NOAA/AVHRR数据特点,发展了统一的海表温度反演模型,并生成了20年时间序列海表温度数据集,空间分辨率达到1km。利用船舶浮标资料和OISST数据对该数据集进行了验证,验证结果表明该数据集均方根误差在1℃左右。最后针对1997/1998年厄尔尼诺事件,用反演的海表温度分析了西太平洋暖池区海表温度距平对这次事件的响应。  相似文献   

4.
利用FY-2C卫星数据反演云辐射特性   总被引:2,自引:0,他引:2       下载免费PDF全文
周青  赵凤生  高文华 《大气科学》2010,34(4):827-842
本文利用FY-2C静止卫星提供的可见光、中红外和热红外观测数据, 开展了水云光学厚度、粒子有效半径和云顶温度的云参数遥感探测理论和反演方法研究。基于FY-2C可见光、中红外(3.75 μm)与热红外(11 μm)通道辐射率对云光学厚度、 云滴有效半径、云顶温度辐射参数的敏感性分析, 提出三通道同时反演云的光学厚度、云滴有效半径及云顶温度的迭代方案; 通过个例分析进行了云参数反演试验, 并将结果与MODIS的云反演产品进行了对比, 最后对反演误差进行了分析。主要结论如下:(1) 个例反演得到的云参数与各通道探测数据有着较好的对应关系, 迭代计算标准偏差在允许的计算精度范围内(<0.89%), 反演结果具有合理性; (2) 通过与MODIS云反演产品的对比可以看到, 两者云光学厚度、云滴有效半径的均值和直方图分布都非常一致, 而MODIS的云顶温度比FY-2C反演值要高, 考虑到FY-2C的 11 μm通道测量的辐射值与MODIS相比偏小, 因此认为我们的反演方法与MODIS方法的精度是相当的。  相似文献   

5.
利用ENVI4.5软件对2007年7—9月间23 d的MODIS 1B晴空数据进行水汽的反演,从中提取乌鲁木齐地区水汽含量并与地基GPS水汽数据进行对比分析,发现经过MODIS 1B反演的近红外水汽相对于地基GPS水汽偏小,但两者的变化趋势基本一致。通过MODIS近红外水汽的订正公式对反演的水汽进行订正,可使乌鲁木齐地区MODIS晴空像元大气水汽含量精度明显提高。  相似文献   

6.
针对MODIS数据的分裂窗算法进行了简要介绍,通过ENVI(ENvironment for Visualizing Images)二次开发,实现了直接利用MODIS lB数据进行雪面温度反演。在ENVI二次开发环境下,编程实现了该算法,并给出了具体的数据反演处理流程。以我国新疆北部为例,将反演结果与气象站雪面温度观测资料对比。结果表明:系统反演得到的雪面温度分布规律与观测资料一致,反演的平均误差为1.73℃,基本反映了北疆地区的雪面温度分布情况;利用ENVI二次开发可以实现遥感数据的批量处理,从而快速准确地得到一个长时间序列的结果。  相似文献   

7.
第10卷第2期(总第34期)2011年8月全球海表温度(SST)数据集简介本期介绍大气资料服务中心目前存放的3套全球海表温度(sea surface tem perature,简称SST)资料,分别是NOAA最优差值海表温度数据集、NOAA延长重建的海表温度数据集以及MODIS海表温度温度数据集。  相似文献   

8.
基于MODIS数据的金塔绿洲地表温度反演   总被引:5,自引:2,他引:3       下载免费PDF全文
武坚  孟宪红  吕世华 《高原气象》2009,28(3):523-529
地表温度(LST)是气象、水文、生态等研究领域中的一个重要参数.本文对MODIS数据的分裂窗算法进行了简要的介绍,并利用MODIS数据计算反演了地表温度所需的关键参数:大气透过率和地表比辐射率,然后运用分裂窗算法反演了金塔绿洲地区的地表温度,并与地面实测数据进行了对比分析.结果表明,这一方法能获得较合理的地表温度,符合金塔绿洲的实际地表状况.  相似文献   

9.
陆面温度是研究地表和大气之间物质交换和能量交换的重要参数。本文通过NASAMODIS地表温度产品与常规资料的分析,发现利用MODIS资料反演的地表温度在山西省分布情况与实测资料基本一致,但应用MODIS资料反演的地表温度要小于实测数据。  相似文献   

10.
以辽宁地表温度为研究对象,采用普适性单通道算法,利用FY-3A/MERSI数据,并结合MODIS 1000 m分辨率数据,反演了2009年和2010年4-9月间10个时次晴空或局部晴空时的地表温度。结果表明:计算验证了模型的反演精度与同期NASA所发布MODIS地表温度产品的精度相当,其结果与相应的56个气象站点的实际观测数据相一致。多源遥感数据的综合应用,可获得较合理的地表温度反演结果;不同土地覆盖类型间地表温度的高低在相同时间内存在显著差异;研究期内,林地、水田、旱地和建设用地的NDVI与地表温度具有负相关性。综合利用遥感、地理信息系统技术,可以表征地表温度与土地利用类型以及地表温度与归一化植被指数(NDVI)之间的关系。  相似文献   

11.
基于MODIS数据的台湾海峡SST区域遥感监测模型研究   总被引:2,自引:1,他引:1  
采用SeaDAS模型开展基于MODIS数据的台湾海峡海洋表面温度SST遥感监测时,发现SeaDAS模型在台湾海峡中部SST的监测精度能够满足要求,但在台湾海峡近岸SST的监测误差明显偏大。为此根据2003—2006年台湾海峡近岸观测站点和台湾海峡中部浮标的实测SST数据,采用线性多通道算法建立台湾海峡SST区域遥感监测统计模型,并选择2007年30个SST数据样本对区域统计模型的监测效果进行验证分析。结果表明:在台湾海峡海域采用SeaDAS模型监测SST绝对误差的平均值是1.2 ℃,标准差是0.69 ℃,而采用区域统计模型监测SST绝对误差的平均值下降到0.89 ℃,标准差下降到0.52 ℃,区域统计模型优于SeaDAS模型。  相似文献   

12.
A dense sea fog episode that occurred near the coastal city of Qingdao in the Shandong Peninsula of China on 1 August 2003 is investigated by using all of the available observational data and high-resolution modeling results from the Regional Atmospheric Modeling System (RAMS). This fog event reduced the horizontal visibility to be less than 60 m in some locations and caused several traffic accidents locally. In this paper, all of the available observational data, including visible satellite imagery of Geostationary Operational Environmental Satellite (GOES)-9 and MODerate-resolution Imaging Spectroradiometer (MODIS), objectively reanalyzed Final Analysis (FNL) data issued by the National Centers for Environmental Prediction (NCEP), sounding data at the Qingdao and Dalian stations, and the latest 4.4 version of the RAMS model, were employed to study this sea fog case. We begin with the analyses of the environmental conditions of the sea fog event, including the large-scale conditions, the difference between T 2m (air temperature at 2 m altitude) and sea surface temperature (SST), and the atmospheric sounding profiles of the two stations. The characteristics of this sea fog event was documented by using visible satellite imagery of GOES-9 and MODIS. In order to better understand the fog formation mechanism, a high-resolution RAMS model of dimensions 4 km × 4 km was designed, which was initialized and validated by FNL data. A 54-h modeling period that started from 18 UTC 31 July 2003 reproduced the main characteristics of this sea fog event. The simulated lower visibility area agreed well with the sea fog area identified from the satellite imagery. It is shown that advection cooling effect plays a significant role in the fog formation.  相似文献   

13.
Matlab对基于HDF格式的MODIS 1B数据的提取方法与实现   总被引:4,自引:1,他引:4  
陈林  牛生杰  仲凌志 《气象科学》2006,26(6):676-681
基于HDF文件格式的MODIS数据的应用越来越广泛,MODIS数据开发应用的前提是对MODIS 1B数据的提取。本文详细介绍了利用Matlab对HDF文件进行读写操作的过程,在此基础上给出了提取MODIS 1B数据的流程图,实现了对MODIS 1B数据的提取,为MODIS二级产品的开发打下了基础。  相似文献   

14.
FY-3B/VIRR海表温度算法改进及精度评估   总被引:2,自引:0,他引:2       下载免费PDF全文
该文介绍了卫星观测海表温度 (SST) 算法的发展历程,给出了所用SST算法的回归模型,并在FY-3B/VIRR业务SST算法的基础上进行了改进。基于NOAA-19/AVHRR匹配数据集,进行多算法建模分析及精度评估,白天最优算法为非线性SST (NL) 算法,夜间最优算法为三通道SST (TC) 算法,最优算法的确定与NESDIS/STAR一致。建立2012年8月—2013年3月FY-3B/VIRR匹配数据集,并在此基础上进行多算法回归建模及精度评估,白天和夜间的最优均为NL算法,分析发现夜间TC算法采用匹配数据集版本2(MDB_V2) 时,3.7 μm通道存在类似百叶窗的条带现象。以2012年10—12月FY-3B/VIRR匹配数据集计算回归系数,以2013年1—3月独立样本进行精度评估,与浮标SST相比,NL算法白天和夜间的均方根误差分别为0.41℃和0.43℃。与日平均最优插值海温 (OISST) 相比,NL算法白天和夜间的均方根误差分别为1.45℃和1.5℃; 选择与OISST偏差在2℃以内的样本,NL算法白天和夜间均方根误差分别为0.82℃和0.84℃。  相似文献   

15.
Observational analysis and purposely designed coupled atmosphere–ocean (AOGCM) and atmosphere-only (AGCM) model simulations are used together to investigate a new mechanism describing how spring Arctic sea ice impacts the East Asian summer monsoon (EASM). Consistent with previous studies, analysis of observational data from 1979 to 2009 show that spring Arctic sea ice is significantly linked to the EASM on inter-annual timescales. Results of a multivariate Empirical Orthogonal Function analysis reveal that sea surface temperature (SST) changes in the North Pacific play a mediating role for the inter-seasonal connection between spring Arctic sea ice and the EASM. Large-scale atmospheric circulation and precipitation changes are consistent with the SST changes. The mechanism found in the observational data is confirmed by the numerical experiments and can be described as follows: spring Arctic sea ice anomalies cause atmospheric circulation anomalies, which, in turn, cause SST anomalies in the North Pacific. The SST anomalies can persist into summer and then impact the summer monsoon circulation and precipitation over East Asia. The mediating role of SST changes is highlighted by the result that only the AOGCM, but not the AGCM, reproduces the observed sea ice-EASM linkage.  相似文献   

16.
A stochastic model of SST for climate simulation experiments   总被引:1,自引:0,他引:1  
 This study describes the implementation of a statistical method to simulate a multi-century sequence of global sea surface temperature (SST) fields. A multi-variable auto-regressive (AR) model is trained on the observed time series of SST from the data set compiled at the Hadley Centre (GISST 2.0). To reduce the dimensionality of the model, the stochastic process is in practice fitted to empirical orthogonal function (EOF) time coefficients of the SST series, retaining the first 14 EOFs. Selected lag cross-covariances among the EOF time series are retained, based on the structure of the cross-correlation matrix and lags up to 64 months are included. Though the resulting system is quite large (a 14-dimensional AR process, with 400 parameters to be determined) the calculation is possible and a stable process is obtained. The process can then be used to investigate some statistical properties of the SST data set and to generate synthetic SST data that could be used in very long numerical experiments with atmospheric or ocean models in which only the main features of the observed statistics of the SST must be retained. Results indicate that the synthetic SST data set seems to be of usable quality as boundary condition for the atmosphere or the ocean in climate experiments. Analysis of extreme events and extreme decades in the synthetic SST data confirms the exceptional character of the 1980s, but also provides circumstantial evidence that the 1980s were indeed within the limits of the statistics of the previously observed record. Received: 6 August 1996 / Accepted: 29 September 1997  相似文献   

17.
利用1950~1998年太平洋海温资料进行分析,得出太平洋海温对春季冷暖环流的遥相关,并得出海温影响大气冷暖环流的过程,进一步分析得到太平洋海温影响亚欧中高纬环流及西太平洋副高的时间.从而得出太平洋海温影响我国南方春温的过程为:前2年10月到前一年3月赤道东太平洋海温持续暖(冷)→前1年3月西太平洋副高持续强(弱)→春...  相似文献   

18.
Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets show consistency in statistically significant trends, with a warming trend of 0.07—0.08 ℃ per decade from 1890 to2013. However, in shorter epochs(such as 1961—2013 and 1981—2013), HadISST1 exhibits stronger warming rates than those of COBE SST2. Both datasets experienced a sudden decrease in the global hiatus period(1998—2013), but the cooling rate of HadISST1 is lower than that of COBE SST2. These differences are possibly caused by the different observations sources which are incorporated to fill with data-sparse regions since 1982. Different data sources may lead to higher values in HadISST1 from 1981 to 2013 than that in COBE SST2. Meanwhile, the different data sources and bias adjustment before the World War II may also cause the large divergence between COBE SST2 and HadISST1,leading to lower SST from 1891 to 1930. These findings illustrate that the long-term linear trends are broadly similar in the centennial-scale in the China Seas using different datasets. However, there are large uncertainties in the estimate of warming or cooling tendency in the shorter epochs, because there are different data sources, different bias adjustment and interpolation method in different datasets.  相似文献   

19.
ENSO 循环各阶段东亚夏季风特征的诊断研究   总被引:2,自引:6,他引:2  
陈月娟  简俊  周任君 《高原气象》2002,21(5):441-446
利用NCEP/NCAR再分析资料和NCAR海温资料及中国测站地温资料,对ENSO循环不同阶段东亚夏季风强弱变化进行了分析.并从此期间的海陆热力差异和季风低压变化来探讨海温异常对东亚夏季风的影响,结果表明:东亚夏季风指数有明显的年际变化和年代际变化,且与赤道东太平洋SST有较好的负相关关系,其中又以与三个月前的海温变化关系最好.在Ninol 2区为冷、暖水之后的三个月中,冷水期对应的东亚夏季风指数大于暖水期对应的东亚夏季风指数,东亚夏季风比暖水期强。赤道东太平洋SST变化期间亚洲大陆的地面温度和地面气压也有明显变化,这是引起ENSO不同阶段东亚夏季风变化的主要原因。  相似文献   

20.
In this paper,climatic features of sea temperature of western Pacific warm pool and the relationship with sea surface temperature (SST) of its adjacent regions are analyzed based on the observed sea temperature on vertical cross section along 137°E in western Pacific,the monthly mean SST of Xisha Station in South China Sea and the global monthly mean SST with resolution of 1°×1° (U.K./GISST2.2).The results indicate that (1) in a sense of correlation.SST of western Pacific warm pool can represent its sea subsurface temperature from surface to 200 m-depth level in winter,and it can only represent sea temperature from surface to 70 m depth in summer.The sea subsurface temperature anomaly of warm pool may be more suitable for representing thermal regime of western Pacific warm pool.The sea subsurface temperature of warm pool has a characteristic of quasi-biennial oscillation.(2)Warm pool and Kuroshio current are subject to different ocean current systems (3)Furthermore,the relationship between SST of Xisha Station and SST of warm pool has a characteristic of negative correlation in winter and positive correlation in summer,and a better lag negative correlation of SST of Xisha Station with sea subsurface temperature of warm pool exists.(4)Additionally,oscillation structure of sea temperature like "a seesaw" exists in between warm pool and Regions Nino3 and Nino4.January (June) maximum (minimum) sea subsurface temperature anomaly of warm pool may serve as a strong signal that indicates maturity phase (development phase) of La Nina (El Nino) event,it also acts as a strong signal which reveals variations of SST of Regions Nino3 and Nino4.  相似文献   

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