在NCEPGDAS中同化MSG和GOES资料

首次将MSG-2（Meteosat Second Generation-2）卫星上的旋转增强可见光及红外成像仪（Spin—ning Enhanced Visibleand Infrared Imager,SEVIRI）的观测资料同化到美国国家环境预报中心（Na—tional Centers for Environmental Prediction,NCEP）全球资料同化系统（globaldataassimilationsys—tern,GDAS）中。对当前的地球静止业务环境卫星（Geostationary Operational Environmental Satel—lite,GOES）成像仪资料的同化问题也进行了进一步探讨。利用CRTM（The Community Radiative Transfer Model）模式,对SEVIRI辐射率观测资料进行了模拟。为了对红外辐射率资料进行模拟,CRTM模式中的几个关键部分得到改进,例如：动态更新地面发射率资料以及采用了快速精确的气体吸收模块。为了改进对SEVIRI和GOES成像仪辐射率资料的模拟效果,采用了GSICS（The Global Space—Based Inter—Calibration System）标定订正。初步研究结果表明,包含对SEVIRI辐射率资料的水汽通道（6．25和7．35μm）和二氧化碳通道（13．40μm）的同化对GFS（Global Forecast System）6d预报具有显著的正影响;而对其他5个SEVIRI红外窗口通道资料的同化则减小了这种正影响。通过应用GSICS标定算法,订正了SEVIRI和GOES-12成像仪观测资料的偏差,提高了对GFS预报的影响。此外,还需作进一步研究来提高对SEVIRI红外窗口通道辐射率资料同化的有效性。     

Dynamical Nighttime Fog/Low Stratus Detection Based on Meteosat SEVIRI Data: A Feasibility Study

Automated detection of fog and low stratus in nighttime satellite data has been implemented on the basis of numerous satellite systems in past decades. Commonly, differences in small-droplet emissivities at 11μm and 3.9μm are utilized. With Meteosat SEVIRI, however, this method cannot be applied with a fixed threshold due to instrument design: The 3.9μm band is exceptionally wide and overlaps with the 4μm CO₂ absorption band. Therefore, the emissivity difference varies with the length of the slant atmospheric column between sensor and object. To account for this effect, the new technique presented in this paper is based on the dynamical extraction of emissivity difference thresholds for different satellite viewing zenith angles. In this way, varying concentrations of CO₂ and column depths are accounted for. The new scheme is exemplified in a plausibility study and shown to provide reliable results.     

Operational evapotranspiration estimates from SEVIRI in support of sustainable water management

This study aimed at evaluating the accuracy of the evapotranspiration (ET) operational estimates from the Meteosat Second Generation (MSG) Spinning Enhanced Visible Infra-Red Imager (SEVIRI) at a range of selected ecosystems in Europe. For this purpose in-situ eddy covariance measurements were used, acquired from 7 selected experimental sites belonging to the CarboEurope ground observational network over 2 full years of observations (2010–2011). Appraisal of ET accuracy was also investigated with respect to land cover, season and each site(s) degree of heterogeneity, the latter being expressed by the fractional vegetation cover (FVC) operational product of SEVIRI.Results indicated a close agreement between the operational product’s ET estimates and the tower based in-situ ET measurements for all days of comparison, showing a satisfactory correlation (r of 0.709) with accuracies often comparable to previous analogous studies. For all land cover types, the grassland and cropland sites exhibited the closest agreement (r from 0.705 to 0.759). In terms of seasons the strongest correlations were observed during the summer and autumn (r of 0.714 & 0.685 respectively), and with FVC the highest correlation of 0.735 was observed for the class FVC 0.75-1 when compared against the observed values for the complete monitoring period. Our findings support the potential value of the SEVIRI ET product for regional to mesoscale studies and corroborate its credibility for usage in many practical applications. The latter is of particular importance for water limiting environments, such as those found in the Mediterranean basin, as accurate information on ET rates can provide tremendous support in sustainable water resource management as well as policy and decision making in those areas.     

Parameterization of air temperature in high temporal and spatial resolution from a combination of the SEVIRI and MODIS instruments

Some applications, e.g. from traffic or energy management, require air temperature data in high spatial and temporal resolution at two metres height above the ground (T_2m), sometimes in near-real-time. Thus, a parameterization based on boundary layer physical principles was developed that determines the air temperature from remote sensing data (SEVIRI data aboard the MSG and MODIS data aboard Terra and Aqua satellites). The method consists of two parts. First, a downscaling procedure from the SEVIRI pixel resolution of several kilometres to a one kilometre spatial resolution is performed using a regression analysis between the land surface temperature (LST) and the normalized differential vegetation index (NDVI) acquired by the MODIS instrument. Second, the lapse rate between the LST and T_2m is removed using an empirical parameterization that requires albedo, down-welling surface short-wave flux, relief characteristics and NDVI data. The method was successfully tested for Slovenia, the French region Franche-Comté and southern Germany for the period from May to December 2005, indicating that the parameterization is valid for Central Europe. This parameterization results in a root mean square deviation RMSD of 2.0 K during the daytime with a bias of −0.01 K and a correlation coefficient of 0.95. This is promising, especially considering the high temporal (30 min) and spatial resolution (1000 m) of the results.     

Contribution of the MODIS instrument to observations of deep convective storms and stratospheric moisture detection in GOES and MSG imagery

Past studies based on the NOAA/AVHRR and GOES I-M imager instruments have documented the link between certain storm top features referred to as the “cold-U/V” shape in the 10–12 μm IR band imagery and plumes of increased 3.7/3.9 μm band reflectivity. Later, similar features in the 3.7/3.9 μm band have been documented in the AVHRR/3 1.6 μm band imagery.The present work focuses on storm top observations utilizing the MODIS data. The MODIS instrument (available onboard NASA's EOS Terra and Aqua satellites) provides image data with significantly better geometrical resolution (in some of its bands) and broader range of spectral bands as compared to that from AVHRR/3 observations. One of the goals of this study is to evaluate the contribution of this new instrument to observations of convective storm tops. Besides the cloud top features linked to storm top microphysics and morphology, the paper also addresses the possibility of detection of lower stratospheric water vapor above cold convective storm tops. This issue is explored utilizing MODIS as well as GOES and MSG imagery.In addition, the paper discusses an alternative interpretation of the “cold-U/V” patterns at the top of intense storms by a mechanism of “plume masking” as suggested by some of the observations.     

A self-sufficient approach for GERB cloudy radiance detection

Geostationary Earth Radiation Budget (GERB) is the broadband radiometer onboard the Meteosat Second Generation (MSG) platform, launched at the end of August 2002 and still in commissioning phase. GERB data is planned to be used in many applications concerning Earth Radiation Budget (ERB) calculation. In order to evaluate the impact of clouds on ERB, a cloud detection is required and, at present, a cloud mask based on higher spatial and spectral resolution data acquired by Spinning Enhanced Visible and Infrared Imager (SEVIRI), the imager onboard the same MSG platform, is planned to be used in order to identify cloudy GERB soundings.As an alternative, a self-sufficient (only based on GERB data) method (OCA, the One-channel Cloudy-radiance-detection Approach) is proposed, as a time-saving and, probably, more suitable solution than the planned co-location approach.In this paper, preliminary results obtained by using several years of Meteosat data as well as GERB synthetic radiances (produced from Meteosat-7 observations) are presented. It is shown how results obtained by using GERB data alone can be comparable (and better in terms of number and spatial distribution of clear-sky GERB soundings identified) to the ones achieved if the co-location of a higher resolution cloud mask is used.     

基于地球静止气象卫星的地表参数遥感研究进展

地表参数定量遥感反演是遥感科学研究的重要环节。21世纪以来,地球静止气象卫星数据在地表参数遥感反演中受到越来越多的重视。本文对利用地球静止气象卫星进行地表参数遥感反演研究的进展进行了综述。文章首先简单介绍了当前正在运行的欧盟Meteosat、美国GOES-R、日本葵花和中国风云静止卫星系统,随后详细总结了不同卫星系统估算各种地表参数的方法。在此基础上,文章对进一步利用静止卫星估算地表参数的研究展开讨论,指出未来的研究应重点关注几个方面:(1)探索和运用新技术提高静止卫星数据获取和处理的效率和精度;(2)融合全球多颗静止气象卫星,同时与极轨卫星融合,生产覆盖全球的长时序地表参数产品;(3)探索地表参数的高效获取方法,对静止气象卫星地表参数产品开展真实性检验,满足地表过程研究和资源环境动态监测对高质量地表参数产品的需求。