First Assessment of SMOS Data Over Open Ocean: Part I—Pacific Ocean

The Soil Moisture and Ocean Salinity (SMOS) mission carries the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument. It is the first time that an interferometric radiometer is in orbit. The objective of this paper is to assess the quality of the brightness temperatures (TBs) derived from this novel instrument, as processed with the SMOS operational chain at the end of the SMOS commissioning phase. Extensive comparisons have been conducted between reconstructed TBs derived from MIRAS measurements (MIRAS TB) and TBs simulated using the default radiative transfer model implemented in the European Space Agency SMOS ocean salinity processor and the European Centre for Medium-Range Weather Forecast forcings. At first order, the North-South variability of MIRAS TB due to geophysical variations of temperature, salinity, and wind speed over the ocean is consistent with the simulated L-band signal, and the standard deviation of the MIRAS TB minus the model simulations is close to the theoretical radiometric resolution. On the other hand, biases of several Kelvins, that depend on the location in the field of view, are observed between averaged MIRAS TB and simulations. After these biases are removed, the North-South gradient of sea surface salinity is well sensed by MIRAS except at high wind speed.

[1]  Philippe Waldteufel,et al.  Ionospheric effects for L-band 2-D interferometric radiometry , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Yann Kerr,et al.  The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle , 2010, Proceedings of the IEEE.

[3]  Adriano Camps,et al.  Improved Image Reconstruction Algorithms for Aperture Synthesis Radiometers , 2008, IEEE Trans. Geosci. Remote. Sens..

[4]  Jacqueline Boutin,et al.  First Assessment of SMOS Data Over Open Ocean: Part II—Sea Surface Salinity , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[5]  David M. Le Vine,et al.  The effect of the ionosphere on remote sensing of sea surface salinity from space: absorption and emission at L band , 2002, IEEE Trans. Geosci. Remote. Sens..

[6]  Philippe Waldteufel,et al.  Apodization functions for 2-D hexagonally sampled synthetic aperture imaging radiometers , 2002, IEEE Trans. Geosci. Remote. Sens..

[7]  Jacqueline Boutin,et al.  Surface Salinity Retrieved from SMOS Measurements over the Global Ocean: Imprecisions Due to Sea Surface Roughness and Temperature Uncertainties , 2004 .

[8]  M. Vall-llossera,et al.  Retrieving sea surface salinity with multiangular L‐band brightness temperatures: Improvement by spatiotemporal averaging , 2005 .

[9]  N. Skou.  Faraday rotation and L band oceanographic measurements , 2003 .

[10]  Jacqueline Boutin,et al.  Influence of sea surface emissivity model parameters at L-band for the estimation of salinity , 2002 .

[11]  Jacqueline Boutin,et al.  Overview of the SMOS Sea Surface Salinity Prototype Processor , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[12]  Jacqueline Boutin,et al.  Resolving the global surface salinity field and variations by blending satellite and in situ observations , 2010 .

[13]  J. Snyder.  An Equal-Area Map Projection For Polyhedral Globes , 1992 .

[14]  Y. Kerr,et al.  Selecting an optimal configuration for the Soil Moisture and Ocean Salinity mission , 2003 .

[15]  Adriano Camps,et al.  Simulated SMOS Levels 2 and 3 Products: The Effect of Introducing ARGO Data in the Processing Chain and Its Impact on the Error Induced by the Vicinity of the Coast , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Adriano Camps,et al.  Performance of sea surface salinity and soil moisture retrieval algorithms with different auxiliary datasets in 2-D L-band aperture synthesis interferometric radiometers , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Bertrand Chapron,et al.  Earth-Viewing L-Band Radiometer Sensing of Sea Surface Scattered Celestial Sky Radiation—Part I: General Characteristics , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[18]  David M. Le Vine,et al.  The sensitivity of synthetic aperture radiometers for remote sensing applications from space , 1990 .

[19]  Adriano Camps,et al.  Improved Image Reconstruction Algorithms for Aperture Synthesis Radiometers , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Philippe Waldteufel,et al.  About off-axis radiometric polarimetric measurements , 2002, IEEE Trans. Geosci. Remote. Sens..

[21]  Adriano Camps,et al.  Radiometric sensitivity computation in aperture synthesis interferometric radiometry , 1998, IEEE Trans. Geosci. Remote. Sens..

[22]  Eric Anterrieu.  On the Reduction of the Reconstruction Bias in Synthetic Aperture Imaging Radiometry , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[23]  Joaquim Ballabrera-Poy,et al.  SMOS: objectives and approach for ocean salinity observations , 2010 .

[24]  Eric Anterrieu.  On the Reduction of the Reconstruction Bias in Synthetic Aperture Imaging Radiometry (Corrected)$^{\ast}$ , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[25]  Adriano Camps,et al.  Considerations about antenna pattern measurements of 2-D aperture synthesis radiometers , 2006, IEEE Geoscience and Remote Sensing Letters.

[26]  Y. Kerr,et al.  Observing the Ocean from Space: Emerging Capabilities in Europe , 2001 .

[27]  Manuel Martín-Neira,et al.  The Flat Target Transformation , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[28]  Yann Kerr,et al.  SMOS: The Challenging Sea Surface Salinity Measurement From Space , 2010, Proceedings of the IEEE.

[29]  Bertrand Chapron,et al.  Modeling Sun Glitter at L-Band for Sea Surface Salinity Remote Sensing With SMOS , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[30]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[31]  Yann Kerr,et al.  Comparison of model prediction with measurements of galactic background noise at L-band , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Adriano Camps,et al.  Sun effects in 2-D aperture synthesis radiometry imaging and their cancelation , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[33]  S. Philipps,et al.  Impact of SMOS space-time averaging on sea surface salinity retrieval , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[34]  C. Ruf,et al.  Interferometric synthetic aperture microwave radiometry for the remote sensing of the Earth , 1988 .

[35]  Simon Yueh,et al.  Error sources and feasibility for microwave remote sensing of ocean surface salinity , 2001, IEEE Trans. Geosci. Remote. Sens..

[36]  Jacqueline Boutin,et al.  Issues About Retrieving Sea Surface Salinity in Coastal Areas From SMOS Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[37]  Bertrand Chapron,et al.  Earth-Viewing L-Band Radiometer Sensing of Sea Surface Scattered Celestial Sky Radiation—Part II: Application to SMOS , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Eric Anterrieu,et al.  A resolving matrix approach for synthetic aperture imaging radiometers , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[39]  S. Gorshkov,et al.  World ocean atlas , 1976 .

[40]  David M. Le Vine,et al.  Aquarius and Remote Sensing of Sea Surface Salinity from Space , 2010, Proceedings of the IEEE.

[41]  Jacqueline Boutin,et al.  SMOS first data analysis for sea surface salinity determination , 2013 .

[42]  Jacqueline Boutin,et al.  Issues concerning the sea emissivity modeling at L band for retrieving surface salinity , 2003 .

[43]  Manuel Martín-Neira,et al.  Minimization of Image Distortion in SMOS Brightness Temperature Maps Over the Ocean , 2012, IEEE Geoscience and Remote Sensing Letters.

[44]  Hervé Carfantan,et al.  On the Reduction of the Systematic Error in Imaging Radiometry by Aperture Synthesis: A New Approach for the SMOS Space Mission , 2009, IEEE Geoscience and Remote Sensing Letters.