Details

Autor(en) / Beteiligte

• Olmedo, Estrella
• Martínez, Justino
• Turiel, Antonio
• Ballabrera-Poy, Joaquim
• Portabella, Marcos

Titel

Debiased non-Bayesian retrieval: A novel approach to SMOS Sea Surface Salinity

Ist Teil von

• Remote sensing of environment, 2017-05, Vol.193, p.103-126

Ort / Verlag

New York: Elsevier Inc

Erscheinungsjahr

2017

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The Soil Moisture and Ocean Salinity (SMOS) mission has provided a unique remote sensing capability for observing key variables of the hydrological cycle, such as the Sea Surface Salinity (SSS). However, due to some limitations related to the instrument interferometric concept and its challenging data processing, SMOS SSS maps still display significant artifacts and biases, especially close to the coast, mainly due to the presence of Radio Frequency Interferences (RFI) and Land-sea contamination (LSC). In this paper, a new methodology for filtering salinity retrievals and correcting for spatial biases is introduced and validated. •Presentation of a new methodology for SMOS SSS retrieval•Mitigation of the Land-Sea Contamination•Computation of SMOS SSS in regions affected by Radio Frequencies Interference (RFI)•SMOS SSS retrieval in the Mediterranean Sea, Arctic Ocean and Antarctic Ocean