Preparing levels 3 and 4 for the SMOS mission

Peer Reviewe

The GNSS-R Eddy Experiment II: L-band and Optical Speculometry for Directional Sea-Roughness Retrieval from Low Altitude Aircraft

We report on the retrieval of directional sea-roughness (the full directional mean square slope, including MSS, direction and isotropy) through inversion of Global Navigation Satellite System Reflections (GNSS-R) and SOlar REflectance Speculometry (SORES)data collected during an experimental flight at 1000 m. The emphasis is on the utilization of the entire Delay-Doppler Map (for GNSS-R) or Tilt Azimuth Map (for SORES) in order to infer these directional parameters. Obtained estimations are analyzed and compared to Jason-1 measurements and the ECMWF numerical weather model.Comment: Proceedings from the 2003 Workshop on Oceanography with GNSS Reflections, Barcelona, Spain, 200

Issues in the balancing of the SMOS ocean salinity trieval cost function

Peer Reviewe

Review of the CALIMAS Team Contributions to European Space Agency's Soil Moisture and Ocean Salinity Mission Calibration and Validation

Camps, Adriano ... et al.-- 38 pages, 22 figuresThis work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoringThis work has been performed under research grants TEC2005-06863-C02-01/TCM, ESP2005-06823-C05, ESP2007-65667-C04, AYA2008-05906-C02-01/ESP and AYA2010-22062-C05 from the Spanish Ministry of Science and Innovation, and a EURYI 2004 award from the European Science FoundationPeer Reviewe

Semi-empirical dissipation source functions for ocean waves: Part I, definition, calibration and validation

New parameterizations for the spectra dissipation of wind-generated waves are proposed. The rates of dissipation have no predetermined spectral shapes and are functions of the wave spectrum and wind speed and direction, in a way consistent with observation of wave breaking and swell dissipation properties. Namely, the swell dissipation is nonlinear and proportional to the swell steepness, and dissipation due to wave breaking is non-zero only when a non-dimensional spectrum exceeds the threshold at which waves are observed to start breaking. An additional source of short wave dissipation due to long wave breaking is introduced to represent the dissipation of short waves due to longer breaking waves. Several degrees of freedom are introduced in the wave breaking and the wind-wave generation term of Janssen (J. Phys. Oceanogr. 1991). These parameterizations are combined and calibrated with the Discrete Interaction Approximation of Hasselmann et al. (J. Phys. Oceangr. 1985) for the nonlinear interactions. Parameters are adjusted to reproduce observed shapes of directional wave spectra, and the variability of spectral moments with wind speed and wave height. The wave energy balance is verified in a wide range of conditions and scales, from gentle swells to major hurricanes, from the global ocean to coastal settings. Wave height, peak and mean periods, and spectral data are validated using in situ and remote sensing data. Some systematic defects are still present, but the parameterizations yield the best overall results to date. Perspectives for further improvement are also given.Comment: revised version for Journal of Physical Oceanograph

SMOS Measurements Preliminary Validation: Objectives and Approach

European Geosciences Union General Assembly, 2-7 May 2010, Vienna, Austria.-- 2 pagesThe Earth Explorer Soil Moisture and Ocean Salinity (SMOS) mission was successfully launched on November 2nd, 2009, in the framework of the European Space Agency Living Planet programme. It will provide long-awaited remotely-sensed Sea Surface Salinity (SSS) maps over the oceans with a 3-day revisiting time [1]. The SMOS Barcelona Expert Centre (SMOS-BEC) in Barcelona, Spain, will be involved in several activities at different levels of the salinity retrieval processing chain, which are classified according to the objectives/issues being addressed. In particular, those described hereafter refer to the validation of the products and the consolidation/improvement of the salinity retrieval procedure itself [2]. This will be carried out by performing specific comparisons against modelled brightness temperatures (TB) or external salinity data sources. Due to start at the beginning of the Commissioning Phase, the post-launch 6-month checkout and calibration period, these studies will continue through the nominal satellite operation phase. They will support the choice of an optimal data selection strategy in regard to the existing trade-off, for instance the Ascending/Descending tracks selection, the AF-FOV/EAF-FOV (Alias-Free Field Of View/Extended Alias-Free Field Of View) selection, and some possible across-track data filtering. Moreover, they will help in the definition of an optimal processing configuration (separated polarization retrieval versus first Stokes parameter retrieval). Concerning the TB, the approach is to perform inter-comparisons of the TB departures (SMOS TB minus modelled TB, assuming knowledge of auxiliary information and proper TB direct modelling). [...]Peer reviewe

Observation and estimation of Lagrangian, Stokes and Eulerian currents induced by wind and waves at the sea surface

The surface current response to winds is analyzed in a two-year time series of a 12 MHz (HF) Wellen Radar (WERA) off the West coast of France. The measured currents, with tides filtered out, are of the order of 1.0 to 1.8% of the wind speed, in a direction 10 to 40 degrees to the right of the wind. This Lagrangian current can be decomposed as the vector sum of a quasi-Eulerian current U_E, representative of the top 1 m of the water column, and a part of the wave-induced Stokes drift Uss at the sea surface. Here Uss is estimated with an accurate numerical wave model, thanks to a novel parameterization of wave dissipation processes. Using both observed and modelled wave spectra, Uss is found to be very well approximated by a simple function of the wind speed and significant wave height, generally increasing quadratically with the wind speed. Focusing on a site located 100 km from the mainland, the estimated contribution of Uss to the radar measurement has a magnitude of 0.6 to 1.3% of the wind speed, in the wind direction, a fraction that increases with wind speed. The difference U_E of Lagrangian and Stokes contributions is found to be of the order of 0.4 to 0.8% of the wind speed, and 45 to 70 degrees to the right of the wind. This elatively weak quasi-Eulerian current with a large deflection angle is interpreted as evidence of strong near-surface mixing, likely related to breaking waves.Comment: Submitted to J. Phys. Oceanogr. le 16/10/2008. Revised 18/02/2009, Accepted 03/04/201

A new approach to estimation of global air-sea gas transfer velocity fields using dual-frequency altimeter backscatter

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C11003, doi:10.1029/2006JC003819.A new approach to estimating air-sea gas transfer velocities based on normalized backscatter from the dual-frequency TOPEX and Jason-1 altimeters is described. The differential scattering of Ku-band (13.6 GHz) and C-band (5.3 GHz) microwave pulses is used to isolate the contribution of small-scale waves to mean square slope and gas transfer. Mean square slope is derived for the nominal wave number range 40–100 rad m−1 by differencing mean square slope estimates computed from the normalized backscatter in each band, using a simple geometric optics model. Model parameters for calculating the differenced mean square slope over this wave number range are optimized using in situ optical slope measurements. An empirical relation between gas transfer velocity and mean square slope, also based on field measurements, is then used to derive gas transfer velocities. Initial results demonstrate that the calculated transfer velocities exhibit magnitudes and a dynamic range which are generally consistent with existing field measurements. The new algorithm is used to construct monthly global maps of gas transfer velocity and to illustrate seasonal transfer velocity variations over a 1-year period. The measurement precision estimated from >106 duplicate observations of the sea surface by TOPEX and Jason-1 altimeters orbiting in tandem is better than 10%. The estimated overall uncertainty of the method is ±30%. The long-term global, area-weighted, Schmidt number corrected, mean gas transfer velocity is 13.7 ± 4.1 cm h−1. The new approach, based on surface roughness, represents a potential alternative to commonly used parameterizations based on wind speed.Financial support for this research from the National Aeronautics and Space Administration through Jet Propulsion Laboratory contract 961425 and the NOAA Global Carbon Cycle Program under grant NA16GP2918, Office of Global Programs is gratefully acknowledged