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Open AccessArticle

Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data

Institute of Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Campus Alpin, Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen, Germany
Forschungszentrum Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Wilhelm-Johnen-Straße, 52428 Jülich, Germany
Microwaves and Radar Institute, German Aerospace Center, Münchener Straße 20, 82234 Weßling, Germany
Institute of Geography, University of Augsburg, Alter Postweg 118, 86159 Augsburg, Germany
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(11), 1842;
Received: 14 September 2018 / Revised: 6 November 2018 / Accepted: 6 November 2018 / Published: 20 November 2018
(This article belongs to the Special Issue Soil Moisture Remote Sensing Across Scales)
Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture satellite missions SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) are able to provide soil moisture estimates on global scales and in kilometer accuracy. However, the SMOS data record has an appropriate length of 7.5 years since late 2009, but with a coarse resolution of ∼25 km only. In contrast, a spatially-enhanced SMAP product is available at a higher resolution of 9 km, but for a shorter time period (since March 2015 only). Being the fundamental observable from passive microwave sensors, reliable brightness temperatures (Tbs) are a mandatory precondition for satellite-based soil moisture products. We therefore develop, evaluate and apply a copula-based data fusion approach for combining SMAP Enhanced (SMAP_E) and SMOS brightness Temperature (Tb) data. The approach exploits both linear and non-linear dependencies between the two satellite-based Tb products and allows one to generate conditional SMAP_E-like random samples during the pre-SMAP period. Our resulting global Copula-combined SMOS-SMAP_E (CoSMOP) Tbs are statistically consistent with SMAP_E brightness temperatures, have a spatial resolution of 9 km and cover the period from 2010 to 2018. A comparison with Service Soil Climate Analysis Network (SCAN)-sites over the Contiguous United States (CONUS) domain shows that the approach successfully reduces the average RMSE of the original SMOS data by 15%. At certain locations, improvements of 40% and more can be observed. Moreover, the median NSE can be enhanced from zero to almost 0.5. Hence, CoSMOP, which will be made freely available to the public, provides a first step towards a global, long-term, high-resolution and multi-sensor brightness temperature product, and thereby, also soil moisture. View Full-Text
Keywords: brightness temperature; soil moisture; copula; data fusion; SMAP; SMOS brightness temperature; soil moisture; copula; data fusion; SMAP; SMOS
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Lorenz, C.; Montzka, C.; Jagdhuber, T.; Laux, P.; Kunstmann, H. Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data. Remote Sens. 2018, 10, 1842.

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