Trend-preserving blending of passive and active microwave soil moisture retrievals
Trend-preserving blending of passive and active microwave soil moisture retrievals
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DOI：
10.1016/j.rse.2012.03.014
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发表时间：
2012-08-01
影响因子：
13.5
通讯作者：
van Dijk, A. I. J. M.
中科院分区：
文献类型：
--
作者：
Liu, Y. Y.;Dorigo, W. A.;van Dijk, A. I. J. M.
一系列星载无源和有源微波仪器提供了总共跨越30多年的土壤湿度反演。这提供了一个机会，以产生一个结合了两种微波技术的优点，并跨越1979年开始的观测期的组合产品。然而，在开发这样的数据集时存在若干挑战，例如，仪器规格的差异导致土壤湿度绝对值不同，全球被动和主动微波反演方法产生的数值在概念上不同，产品的相对性能也因植被密度而异。本文介绍了一种方法，结合四个被动微波产品从阿姆斯特丹自由大学/美国国家航空航天局和两个有源微波产品从维也纳技术大学。首先，被动微波土壤水分反演从扫描多通道微波辐射计（SMMR），特殊传感器微波成像仪（SSM/I），和热带降雨测量使命微波成像仪（TMI）仪器的气候学的高级微波扫描辐射计-地球观测系统（AMSR-E）的衍生产品，然后所有四个合并成一个单一的合并被动微波产品。第二，从欧洲遥感（ERS）散射仪仪器的主动微波土壤湿度估计缩放到高级散射仪（ASCAT）的气候学派生的估计。两者合并成合并的活性微波产物。最后，这两个合并的产品被重新缩放到一个共同的全球可用的参考土壤水分数据集提供的陆面模型（GLDAS-1-诺亚），然后混合成一个单一的被动/主动产品。主动和被动数据集的混合是根据其各自对植被密度的敏感性。虽然这种三步方法将陆地表面模型数据集的绝对值强加给最终产品，但它保留了相对动态（例如，季节性和年际变化）的原始卫星派生检索。更重要的是，原始土壤水分产品的长期变化也得到了保留。本文提出的方法允许从其他当前和未来的业务卫星的数据扩展的长期产品。多年代际混合数据集有望增强我们对水、能源和碳循环中土壤水分的基本理解。(C)2012 Elsevier Inc. All rights reserved.
A series of satellite-based passive and active microwave instruments provide soil moisture retrievals spanning altogether more than three decades. This offers the opportunity to generate a combined product that incorporates the advantages of both microwave techniques and spans the observation period starting 1979. However, there are several challenges in developing such a dataset, e.g., differences in instrument specifications result in different absolute soil moisture values, the global passive and active microwave retrieval methods produce conceptually different quantities, and products vary in their relative performances depending on vegetation density. This paper presents an approach for combining four passive microwave products from the VU University Amsterdam/National Aeronautics and Space Administration and two active microwave products from the Vienna University of Technology. First, passive microwave soil moisture retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), the Special Sensor Microwave Imager (SSM/I), and the Tropical Rainfall Measuring Mission microwave imager (TMI) instruments were scaled to the climatology of the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) derived product and then all four were combined into a single merged passive microwave product. Second, active microwave soil moisture estimates from the European Remote Sensing (ERS) Scatterometer instrument were scaled to the climatology of the Advanced Scatterometer (ASCAT) derived estimates. Both were combined into a merged active microwave product. Finally, the two merged products were rescaled to a common globally available reference soil moisture dataset provided by a land surface model (GLDAS-1-Noah) and then blended into a single passive/active product. Blending of the active and passive data sets was based on their respective sensitivity to vegetation density. While this three step approach imposes the absolute values of the land surface model dataset to the final product, it preserves the relative dynamics (e.g., seasonality and inter-annual variations) of the original satellite derived retrievals. More importantly, the long term changes evident in the original soil moisture products were also preserved. The method presented in this paper allows the long term product to be extended with data from other current and future operational satellites. The multi-decadal blended dataset is expected to enhance our basic understanding of soil moisture in the water, energy and carbon cycles. (C) 2012 Elsevier Inc. All rights reserved.