analysis of two years of ascat and smos derived soil moisture estimates over europe and north africa

More than two years of soil moisture data derived from the Advanced SCATterometer (ASCAT) and from the Soil Moisture and Ocean Salinity (SMOS) radiometer are analysed and compared. The comparison has been performed within the framework of an activity aiming at validating the EUMETSAT Hydrology Satellite Application Facility (H-SAF) soil moisture product derived from ASCAT. The available database covers a large part of the SMOS mission lifetime (2010, 2011 and partially 2012) and both Europe and North Africa are considered. A specific strategy has been set up in order to enable the comparison between products representing a volumetric soil moisture content, as those derived from SMOS, and a relative saturation index, as those derived from ASCAT. Results demonstrate that the two products show a fairly good degree of correlation. Their consistency has some dependence on season, geographical zone and surface land cover. Additional factors, such as spatial property features, are also preliminary investigated

SMOS sea ice thickness - a review and way forward

The sea ice on the oceans in the Arctic and Antarctic is a relatively thin blanket that significantly influences the exchange between the ocean and the atmosphere. The sea ice thickness is a major parameter, which is of great importance for diagnosis and prediction. Determining seasonal and interannual variations in sea ice thickness was the primary objective of ESA's CryoSat Earth Explorer mission. ESA's second Earth Explorer mission, SMOS, provides L-band brightness temperature data that can also be used to infer the thickness of the sea ice, although that was not its primary objective. Both missions complement each other strongly in terms of spatiotemporal sampling and their sensitivity to different ice thickness regimes. In order to further improve the synergistic use of low-frequency radiometric data for sea ice applications, it is imperative to better characterize the uncertainties and covariances associated with the retrieval. A key factor is a thorough understanding of the physical processes that determine the emissivity of sea ice in order to improve the forward model used for retrieval. A thermodynamic model is used to estimate the vertical temperature profile through the snow and sea ice. Therefore, additional meteorological data such as from atmospheric reanalyses and parameterizations of snow and sea ice properties must be taken into account. Natural sea ice is not a homogeneous medium of uniform sea ice and snow thickness, but can only be described by statistical distribution functions on different spatial scales. Thin ice and open water in leads within the compact pack ice also have a significant influence on the brightness temperature measured by SMOS. In order to take all these effects into account, the forward model or the observation operator must be of the appropriate complexity. The inversion to determine the geophysical sea ice parameters can be optimized with a-priori information and parameterizations as well as with information from other satellite sensors. The presentation will focus on a review of the current retrieval method used to generate the AWI-ESA level 3 and level 4 Sea Ice Thickness products and the way forward to improve the emissivity model and to define a common basis metrics validation to assess algorithms evolution considering that in-situ validation data is only sparsely available

ESA’s Soil Moisture and Ocean Salinity Mission - An overview on the mission’s performance and scientific results

European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 1 pageThe Soil Moisture and Ocean Salinity (SMOS) mission, launched on 2 November 2009, is the European Space Agency’s (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth’s climate system. This paper will provide an overview on the various aspects of the SMOS mission, such as 1. The performance of the mission after more than 5 years in orbit: The SMOS mission has been in routine operations since May 2010, following the successful completion of the 6-months commissioning phase. The paper will summarise the technical and scientific status of the mission, including the status of the RFI detection and mitigation and its effect on the data products. SMOS has so far provided very reliable instrument operations, data processing and dissemination to users. The paper will also provide an overview on the MIRAS instrument performance, including the instrument calibration and level 1 brightness temperature data processing. 2. An overview on the SMOS data products: SMOS provides continuously level 1 (brightness temperature) and level 2 (soil moisture and ocean salinity) to its scientific user community since summer 2010. SMOS also provides brightness temperature data (level 1 data) to ECMWF in near-real time (NRT), who assimilates the data into their forecasting system. New services have been established to deliver a tailored NRT data product via the WMO’s GTS and EUMETSAT’s EUMETCast data dissemination systems to other operational agencies. This will open up new operational applications for SMOS data. Other data products are under development, responding to the requirements of the science community in particular in the area of hydrology, climate, land use and ship routing, namely a frozen soil indicator, data products for freeze/thaw periods, sea ice thickness and vegetation water content. 3. Provide an update on the overall validation approach and recent activities: SMOS data products are continuously improved and approach the scientific mission objectives. Validation activities are essential to ensure high data quality. ESA in collaboration with national agencies and institutions maintains a frame for validation activities such as reference sites, ground based observations as well as campaigns. The paper will provide an update on recent activities, such as the activities at DOME-C. 4. Summarise the collaboration with other space-borne L-band sensors, such as NASA’s Aquarius and SMAP missionsPeer Reviewe

ESA's Soil Moisture and Ocean Salinity Mission: Mission Performance and Operations

Mecklenburg, S. ... et. al.The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission was launched on the 2nd of November 2009. The first six months after launch, the so-called commissioning phase, were dedicated to test the functionalities of the spacecraft, the instrument, and the ground segment including the data processors. This phase was successfully completed in May 2010, and SMOS has since been in the routine operations phase and providing data products to the science community for over a year. The performance of the instrument has been within specifications. A parallel processing chain has been providing brightness temperatures in near-real time to operational centers, e.g., the European Centre for Medium-Range Weather Forecasts. Data quality has been within specifications; however, radio-frequency interference (RFI) has been detected over large parts of Europe, China, Southern Asia, and the Middle East. Detecting and flagging contaminated observations remains a challenge as well as contacting national authorities to localize and eliminate RFI sources emitting in the protected band. The generation of Level 2 soil moisture and ocean salinity data is an ongoing activity with continuously improved processors. This article will summarize the mission status after one year of operations and present selected first results. © 2012 IEEEPeer Reviewe

Observing Cyclones: Towards a Joint Active and Passive Approach

12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 5-9 March 2012, Villa MondragonePeer Reviewe

Error characterization of soil moisture satellite products: retrieving error cross-correlation through extended quadruple collocation

The triple collocation (TC) technique is being increasingly used to validate soil moisture retrievals derived from different systems, like satellites, hydrological models, or in situ probes. In recent years, several extensions of this method were proposed in order to evaluate the error standard deviations of more than three systems and to soften the TC hypothesis. In this paper, a novel extended quadruple collocation (E-QC) method is proposed, in order to consider the possibility of a cross correlation between product errors, identifying automatically the couple of error cross-correlated systems. The method is applicable even to a larger number of collocated datasets, although it may be unfeasible to collect them in practice. A synthetic experiment showed promising results, concluding that the E-QC is able to individuate (if any) the pair of systems with cross-correlated errors. It correctly compensates for the latter contribution and accurately retrieves error standard deviations of each system, otherwise biased if cross correlation is not taken into account. The E-QC was applied to soil moisture retrievals provided by satellite (SMOS, ASCAT, and SMAP), model (ERA Interim), and in situ probes (ISMN). The E-QC method identified the presence of error cross-correlation between the satellite products. This was also confirmed by analyzing the five datasets all together. E-QC showed fair performances of satellite products, especially of SMAP, although not as good as in case the presence of error correlation is not correctly taken into account

Quadruple collocation analysis for soil moisture product assessment

For validating remotely sensed products, the triple collocation (TC) is often adopted, which is able to retrieve the independent error variances of three systems observing the same target parameter. In this letter, three years of soil moisture data derived from the Advanced SCATterometer (ASCAT) aboard the MetOp satellite and the Soil Moisture and Ocean Salinity (SMOS) radiometer are analyzed and compared with the ERA Interim/Land model outputs and the ground measurements available from the International Soil Moisture Network. As we have four sources, a novel quadruple collocation (QC) approach is developed, which is more precise than TC since it uses the sources jointly. The results of QC show that the ERA model has the lowest error variance, while ground measurements are likely to be affected by the difficulty to represent a mean soil moisture within the satellite field of view by a limited number of stations. Moreover, the ASCAT retrievals outperform the SMOS ones if only anomalies with respect to the seasonal trend are considered, while the opposite occurs when the whole dynamic of soil moisture variation is considered

Analysis of ASCAT, SMOS, in-situ and land model soil moisture as a regionalized variable over Europe and North Africa

A comparison of soil moisture products derived from satellite data, in-situ measurements and land models was performed in the frame of the EUMETSAT H-SAF project. In particular, soil moisture retrievals of ASCAT/H-SAF and SMOS were compared with two other independent data sets, that are the NCEP/NCAR volumetric soil moisture content reanalysis developed by NOAA, and the ERA-Interim/Land soil moisture produced by ECMWF. In situ data available through the International Soil Moisture Network and distributed in regions comprising Denmark, France, Germany, Italy, Poland and Spain, were also included in the comparison. The whole H-SAF region of interest, including Europe and North Africa, was considered and the period between January 2010 and December 2012 was analysed.The Triple Collocation (TC) approach was adopted to perform the comparison exercise. TC was critically reviewed to compare different solutions proposed in the literature and to discuss the possibility of performing a pointwise TC, or a global TC, which considers each system as a whole, with unique gains and error standard deviations in the whole area. The TC results showed a very good behaviour of the ERA land model, while SMOS satellite slightly outperformed ASCAT or vice versa, depending on factors like the geographical area or the consideration of the whole dynamic range of soil moisture or only the anomalies with respect to the seasonal variability