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FUSION OF ACTIVE AND PASSIVE MICROWAVE OBSERVATIONS TO CREATE AN ESSENTIAL CLIMATE VARIABLE DATA RECORD ON SOIL MOISTURE

机译:主动和被动微波观测的融合,以在土壤水分上创造一个基本的气候变量数据记录

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Soil moisture was recently included in the list of Essential Climate Variables (ECVs) that are deemed essential for IPCC (Intergovernmental Panel on Climate Change) and UNFCCC (United Nations Framework Convention on Climate Change) needs and considered feasible for global observation. ECVs data records should be as long, complete and consistent as possible, and in the case of soil moisture this means that the data record shall be based on multiple data sources, including but not limited to active (scatterometer) and passive (radiometer) microwave observations acquired preferably in the low-frequency microwave range. Among the list of sensors that can be used for this task are the C-band scatterometers on board of the ERS and METOP satellites and the multi-frequency radiometers SMMR, SSM/I, TMI, AMSR-E, and Windsat. Together, these sensors already cover a time period of more than 30 years and the question is how can observations acquired by these sensors be merged to create one consistent data record? This paper discusses on a high-level possible approaches for fusing the individual satellite data. It is argued that the best possible approach for the fusion of the different satellite data sets is to merge Level 2 soil moisture data derived from the individual satellite data records. This approach has already been demonstrated within the WACMOS project (http://wacmos.itc.nl/) funded by European Space Agency (ESA) and will be further improved within the Climate Change Initiative (CCI) programme of ESA (http://www.esa-cci.org/).
机译:最近土壤水分最近被视为IPCC(气候变化政府间议会政府间委员会)和“联合国气候变化框架公约”所必需的基本气候变量(ECV)列表中,并认为全球观察是可行的。 ECVS数据记录应尽可能长,完整,一致,在土壤湿度的情况下,这意味着数据记录应基于多个数据源,包括但不限于有源(散射计)和无源(辐射计)微波优选地在低频微波范围内获得的观察结果。在可用于此任务的传感器列表中,可以在ERS和Metop卫星的船上和多频辐射仪SMMR,SSM / I,TMI,AMSR-E和WINDSAT中是C波段散射计。这些传感器一起覆盖了30多年的时间段,问题是如何合并这些传感器的观察到创建一个一致的数据记录?本文讨论了融合各种卫星数据的高级别可能的方法。有人认为,不同卫星数据集的融合的最佳方法是合并来自各个卫星数据记录的2级土壤湿度数据。在欧洲航天局(ESA)资助的Wacmos项目(http://wacmos.itc.nl/)中已经证明了这种方法,并将在欧安全盟署的气候变化倡议(CCI)方案中进一步改善(http:/ /www.esa-cci.org/)。

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