CAROLS: A New Airborne L-Band Radiometer for Ocean Surface and Land Observations

The “Cooperative Airborne Radiometer for Ocean and Land Studies” (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer—STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity

SMOS instrument performance and calibration after six years in orbit

ESA's Soil Moisture and Ocean Salinity (SMOS) mission, launched 2-Nov-2009, has been in orbit for over 6 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps working well. The calibration strategy remains overall as established after the commissioning phase, with a few improvements. The data for this whole period has been reprocessed with a new fully polarimetric version of the Level-1 processor which includes a refined calibration schema for the antenna losses. This reprocessing has allowed the assessment of an improved performance benchmark. An overview of the results and the progress achieved in both calibration and image reconstruction is presented in this contribution.Peer ReviewedPostprint (author's final draft

Towards an Improved Characterization of Instrumental Biases and Forward Model Errors in SMOS Observations over the Ocean

SMOS & Aquarius Science Workshop, 15-17 April 2013, Brest, FranceThe Soil Moisture and Ocean Salinity (SMOS) satellite was launched on November 2, 2009 in the framework of the European Space Agency's (ESA's) Earth Explorer opportunity missions. Over the oceans, Sea Surface Salinity (SSS) is retrieved on a global basis with a spatio-temporal sampling appropriate for Ocean dynamics and Earth water cycle studies (Font 2010). The single payload onboard SMOS is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), a novel fully-polarimetric L-band radiometer which estimates the brightness temperature by means of two-dimensional aperture synthesis interferometry. It consists of a Y-shaped set of 72 receivers (McMullan, 2008). More than 3 years after launch, the salinity product accuracy has still not reached the mission objective, even in the RFI-free open ocean domain. Main reasons are: 1) the challenging but intrinsically low sensitivity of L-band brightness temperature to sea surface, 2) the imperfection of the forward model used in the inversion procedure, 3) the spatio-temporal biases still present in the reconstructed brightness temperature. The present work is a contribution to adressing above-mentioned points 2 and 3. Several forward model deficiencies have been identified which propagate down to the retrieved salinity. If different studies have recently pointed out roughness dependent SSS errors and proposed updated formulations for the increment of emissivity due to surface roughness (Guimbard et al., 2012; Yin et al., 2012), the agreement in their results suggests that a robust improvement has been achieved. Nevertheless, another critical component of the forward model is the celestial signal scattered by the rough sea surface (Tenerelli 2008). The complexity of the biscattering problem and the large number of parameters involved makes highly difficult the procedure to improve its description empirically from real data. In spite of this, a recent work by J.Tenerelli has produced very promising results. The amplitude of the modeled signal near the specular direction is improved and better mimics the changes due to surface roughness variations. Nevertheless, there is still some discrepancy between parameters obtained when using different datasets, especially when using ascending or descending passes, and between different geometrical observation conditions i.e. incidence angle. Such inconsistency in the model parameters suggest an imperfection of the model physics. As mentioned in the introduction, latitudinal and seasonal biases are also affecting SMOS reconstructed TB ocean images (Tenerelli et al. 2010, Oliva et al. 2012) and retrieved salinity fields (Reul et al. 2012). Results suggest a correlation of the error with the sun illumination of the instrument through thermal effects, but attempts to cancel the corresponding biases at the calibration level are still not conclusive. In this work, it is assumed that such biases are essentially uniform across the field of view.A key point in this discussion is that celestial reflection model errors and thermal instrumental biases both vary at latitudinal and seasonal scales. In the current approach, forward model updates are contaminated by the imperfect instrumental biases estimates and vice versa. The present work is an attempt to uncouple these two important steps. First, for a specific data subset where the celestial reflection signal is expected to be time-invariant, the temporal biases are estimated, an empirical correction applicable to the brightness temperatures is derived and a corrected data subset obtained. Second, the corrected dataset is used to obtain celestial reflection residuals. Their inconsistency with the current galactic model, primarily in terms of incidence angle dependence is analyzed to derive a modification of the model. Finally, after evaluating its performance, the updated model is evaluated for a much larger dataset and the instrumental biases are now evaluated both at the temporal and orbital scales. For a given latitudinal band, i.e. orbital position, and a limited set of locations in the FOV, a specific geometrical configuration is identified for which the celestial contamination does not significantly vary along the year. A data selection strategy developed for the antenna frame systematic errors study (Gourrion et al., 2012) is refined to characterize the instrumental temporal biases in that particular latitudinal range. Assuming that the thermally-induced instrumental biases are homogenous across the FOV, celestial reflection residuals are derived from a wide range of FOV locations but the same orbital location. Their analysis points out an imperfection in the shape of the bistatic scattering coefficients used in the computation of the celestial signal as scattered by the rough sea surface. Both theoretically-based and empirical ad-hoc modifications are tested to propose a modification of the bistatic scattering functionPeer Reviewe

Continuing Challenges in Salinity Retrieval for the SMOS Mission

SMOS & Aquarius Science Workshop, 15-17 April 2013, Brest, FranceThe European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission has provided nearly continuous global record of fully polarimetric brightness temperatures at L-band (1.4135 GHz) since November 2009. The single payload of the SMOS satellite, MIRAS, is a two-dimensional aperture synthesis radiometer that measures the cross-correlations between the signals from many L-band antennas distributed in a Y-shape array. These cross-correlations are transformed by ground processing into brightness temperature images that extend over a swath several hundred kilometers across. Over the ocean, these brightness temperature images are used, together with a forward model of the L-band scene brightness, to derive maps of surface salinity over the global oceans, with full earth coverage approximately every five days. Over the global oceans the surface salinity varies between about 32 and 38 on the practical salinity scale, with the strongest variations in the vicinity of river outflows and heavy rainfall. The sensitivity of the brightness temperature at L-band to a change in salinity depends somewhat upon polarization and sea surface temperature but, in tropical latitudes, is about +1 K in the first Stokes parameter per unit decrease of salinity on the pratical salinity scale. Thus, the dynamic range of L-band brightness temperatures over the open ocean is only several kelvin. As one goal of the mission is to produce global maps of salinity with an accuracy of 0.1 after averaging over 10-30 days, strict requirements must be placed upon the accuracy and stability of the brightness temperatures. Efforts to reach this goal continue, but challenges related to interannual, seasonal, and orbital stability of the retrieved salinity remain. These challenges stem from difficulties in the instrument calibration, image reconstruction, and modeling of the scene brightness over the ocean. On the one hand, the instrument calibration and image reconstruction are plagued by the sun which impacts the accuracy of the brightness temperatures indirectly, through variations in the thermal characteristics of the instrument, and directly, through its impact on the visibilities. On the other hand, the scene modeling is plagued by emission from the rough ocean surface, emission from foam, and galactic radiation scattered towards the instrument by the wind-roughened ocean surface. Moreover, the sun-synchronous orbit of the SMOS satellite is such that both the solar (direct and indirect) and galactic impacts exhibit orbital and seasonal cycles that, if not properly accounted for, will contribute to bias in the salinity. A key factor complicating progress is the fact that the aforementioned problems can produce similar bias evolutions, and so disentangling the various sources of bias is difficult. Using open-ocean model solutions for the brightness temperature images as well as the antenna temperatures (which provide the mean brightness temperature level for the images), this paper will examine the spatial and temporal structures observed in the biases over the nearly four years of continuous data. An attempt will be made to exploit the recent oscillatory character of the sun L-band brightness in order to separate the impacts of the sun and scattered galactic radiation. In parallel, improvements in the modeling of the scattering of galactic radiation will be presented, and a comparison will be made with the impact on the brightness temperatures and salinity maps from the Aquarius mission. Finally, recognizing that adequate calibration and forward scene modeling may not be achieved in the near future, the paper will examine practical alternatives to bias correction, with an emphasis on finding an approach that minimizes impact on the range of applications of the SMOS salinity mapsPeer Reviewe

Towards an Improved Diagnostic of Instrumental Biases and Forward Model Errors in SMOS Observations over the Ocean

European Space Agency (ESA) Living Planet Symposium, 9-13 September 2013, EdinburghPeer Reviewe

Continuing Challenges in Salinity Retrieval for the SMOS Mission

European Space Agency (ESA) Living Planet Symposium, 9-13 September 2013, EdinburghPeer Reviewe

SMOS brightness temperature and salinity over the ocean: systematic errors

1st SMOS Science Workshop, 27-29 September 2011, Arles, FrancePeer Reviewe

Characterization of the SMOS instrumental error pattern correction over the ocean

5 pages, 4 figures.-- © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2nd, 2009 aiming at providing sea surface salinity (SSS) estimates over the oceans with frequent temporal coverage. The detection and mitigation of residual instrumental systematic errors in the measured brightness temperatures is a key step prior to the SSS retrieval. For such purpose, the so-called Ocean Target Transformation (OTT) technique is currently used in the SMOS operational SSS processor. In this study, an assessment of the OTT is performed. It is found that, to compute a consistent and robust OTT, a large ensemble of measurements is required. Moreover, several effects are reported to significantly impact the OTT computation, namely, the apparent instrument (temporal) drift, forward model imperfections, auxiliary data (used by forward model) uncertainty and external error sources, such as galactic noise and Sun effects (among others). These effects have to be properly mitigated or filtered during the OTT computation, so as to successfully retrieve SSS from SMOS measurementsPeer Reviewe

Overview of the First SMOS Sea Surface Salinity Products. Part I: Quality Assessment for the Second Half of 2010

International audienceMulti-angular images of the brightness temperature (TB) of the Earth at 1.4 GHz are reconstructed from the Soil Moisture and Ocean Salinity (SMOS) satellite sensor data since end 2009. Sea surface salinity (SSS) products remote sensing from space is being attempted using these data over the world oceans. The quality of the first version of the European Space Agency operational Level 2 (L2) SSS swath products is assessed in this paper, using satellite/in situ SSS data match-ups that were collected over the second half of 2010. This database reveals that 95% of the SMOS L2 products show a global error standard deviation on the order of ~ 1.3 practical salinity scale. Simple spatiotemporal aggregation of the L2 products to generate monthly SSS maps at 1° ×1° spatial resolution reduces the error down to about 0.6 globally and 0.4 in the tropics for 90% of the data. Several major problems are, however, detected in the products. Systematically, SMOS SSS data are biased within a ~ 1500 km wide belt along the world coasts and sea ice edges, with a contamination intensity and spread varying from ascending to descending passes. Numerous world ocean areas are permanently or intermittently contaminated by radio-frequency interferences, particularly in the northern high latitudes and following Asia coastlines. Moreover, temporal drifts in the retrieved SSS fields are found with varying signatures in ascending and descending passes. In descending passes, a time-dependent strong latitudinal bias is found, with maximum amplitude reached at the end of the year. Errors in the forward modeling of the wind-induced emissivity and of the sea surface scattered galactic sources are as well identified, biasing the sss retrievals at high and low winds and when the galactic equator sources are reflected toward the sensor

Sea Surface Salinity Retrieval from CAROLS L-Band Measurements

International audienc