A Roughness Correction for Aquarius Ocean Brightness Temperature Using the CONAE MicroWave Radiometer

Aquarius/SAC-D is a joint NASA/CONAE (Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using an L-band radiometer that measures ocean brightness temperature (Tb). The application of L-band radiometry to retrieve SSS is a difficult task, and therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that warms the ocean Tb. The Aquarius (AQ) instrument (L-band radiometer/scatterometer) baseline approach uses the radar scatterometer to provide this ocean roughness correction, through the correlation of radar backscatter with the excess ocean emissivity. In contrast, this dissertation develops an ocean roughness correction for AQ measurements using the MicroWave Radiometer (MWR) instrument Tb measurements at Ka-band to remove the errors that are caused by ocean wind speed and direction. The new ocean emissivity radiative transfer model was tuned using one year (2012) of on-orbit combined data from the MWR and the AQ instruments that are collocated in space and time. The roughness correction in this paper is a theoretical Radiative Transfer Model (RTM) driven by numerical weather forecast model surface winds, combined with ancillary satellite data from WindSat and SSMIS, and environmental parameters from NCEP. This RTM provides an alternative approach for estimating the scatterometer-derived roughness correction, which is independent. The theoretical basis of the algorithm is described and results are compared with the AQ baseline scatterometer method. Also results are presented for a comparison of AQ SSS retrievals using both roughness corrections

L-Band Vegetation optical depth and effective scattering albedo estimation from SMAP

Over land the vegetation canopy affects the microwave brightness temperature by emission, scattering and attenuation of surface soil emission. Attenuation, as represented by vegetation optical depth (VOD), is a potentially useful ecological indicator. The NASA Soil Moisture Active Passive (SMAP) mission carries significant potential for VOD estimates because of its radio frequency interference mitigation efforts and because the L-band signal penetrates deeper into the vegetation canopy than the higher frequency bands used for many previous VOD retrievals. In this study, we apply the multi-temporal dual-channel retrieval algorithm (MT-DCA) to derive global VOD, soil moisture, and effective scattering albedo estimates from SMAP Backus-Gilbert enhanced brightness temperatures posted on a 9 km grid and with three day revisit time. SMAP VOD values from the MT-DCA follow expected global distributions and are shown to be highly correlated with canopy height. They are also broadly similar in magnitude (though not always in seasonal amplitude) to European Space Agency Soil Moisture and Ocean Salinity (SMOS) VOD. The SMOS VOD values are based on angular brightness temperature information while the SMAP measurements are at a constant incidence angle, requiring an alternate approach to VOD retrieval presented in this study. Globally, albedo values tend to be high over regions with heterogeneous land cover types. The estimated effective scattering albedo values are generally higher than those used in previous soil moisture estimation algorithms and linked to biome classifications. MT-DCA retrievals of soil moisture show only small random differences with soil moisture retrievals from the Baseline SMAP algorithm, which uses a prior estimate of VOD based on land cover and optical data. However, significant biases exist between the two datasets. The soil moisture biases follow the pattern of differences between the MT-DCA retrieved and Baseline-assigned VOD values

Faraday Rotation Correction for Passive Microwave Remote Sensing from Space

Faraday rotation (FR) is one of the main error sources for passive microwave remote sensing from space especially in frequencies less than or equal to 10.7 GHz. In this paper, Faraday rotation correction for the vertical brightness temperature at L band and the third Stokes parameter brightness temperature at 10.7 GHz are discussed. Two approaches are studied to remove the influence of FR: correction by auxiliary data and correction by polarimetric mode. At 1.4 GHz, correction by polarimetric mode performs better than correction by auxiliary data. At 10.7 GHz, correction by auxiliary data is feasible while polarimetric mode correction becomes invalid. We propose a new method of using TEC data released by international GNSS service (IGS) for correction. It has been proved that the residual correction errors are reduced. IGS data method greatly improves the correction accuracy

Sun Glint and Sea Surface Salinity Remote Sensing

A new mission in space, called Aquarius/SAC-D, is being built to measure the salinity of the world's oceans. Salinity is an important parameter for understanding movement of the ocean water. This circulation results in the transportation of heat and is important for understanding climate and climate change. Measuring salinity from space requires precise instruments and a careful accounting for potential sources of error. One of these sources of error is radiation from the sun that is reflected from the ocean surface to the sensor in space. This paper examines this reflected radiation and presents an advanced model for describing this effect that includes the effects of ocean waves on the reflection

2000 days of SMOS at the Barcelona Expert Centre: a tribute to the work of Jordi Font

Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission capable of measuring sea surface salinity and soil moisture from space. Its novel instrument (the L-band radiometer MIRAS) has required the development of new algorithms to process SMOS data, a challenging task due to many processing issues and the difficulties inherent in a new technology. In the wake of SMOS, a new community of users has grown, requesting new products and applications, and extending the interest in this novel brand of satellite services. This paper reviews the role played by the Barcelona Expert Centre under the direction of Jordi Font, SMOS co-principal investigator. The main scientific activities and achievements and the future directions are discussed, highlighting the importance of the oceanographic applications of the mission.Peer ReviewedPostprint (published version

SMAP L-Band Microwave Radiometer: Instrument Design and First Year on Orbit

The Soil Moisture Active Passive (SMAP) L-band microwave radiometer is a conical scanning instrument designed to measure soil moisture with 4 percent volumetric accuracy at 40-kilometer spatial resolution. SMAP is NASA's first Earth Systematic Mission developed in response to its first Earth science decadal survey. Here, the design is reviewed and the results of its first year on orbit are presented. Unique features of radiometer include a large 6-meter rotating reflector, fully polarimetric radiometer receiver with internal calibration, and radio-frequency interference detection and filtering hardware. The radiometer electronics are thermally controlled to achieve good radiometric stability. Analyses of on-orbit results indicate the electrical and thermal characteristics of the electronics and internal calibration sources are very stable and promote excellent gain stability. Radiometer NEdT (Noise Equivalent differential Temperature) less than 1 degree Kelvin for 17-millisecond samples. The gain spectrum exhibits low noise at frequencies greater than 1 megahertz and 1 divided by f (pink) noise rising at longer time scales fully captured by the internal calibration scheme. Results from sky observations and global swath imagery of all four Stokes antenna temperatures indicate the instrument is operating as expected

The Influence of Antenna Pattern on Faraday Rotation in Remote Sensing at L-band

Faraday rotation is a change in the polarization vector of electromagnetic radiation that occurs as the waves propagate from the Earth surface through the ionosphere to a spaceborne sensor. This change can cause errors in monitoring parameters at the surface such as soil moisture and sea surface salinity and it is an important consideration for radiometers on future missions in space such as NASA's Aquarius mission and ESA's SMOS mission. Two prominent strategies for compensating for Faraday rotation are using a sum of the signal at two polarizations and using the correlation between the signals at the two polarizations. These strategies work for an idealized antenna. This paper evaluates the strategies in the context of realistic antennas such as will be built for the Aquarius radiometer. Realistic antennas will make small differences that need to be included in planning for retrieval algorithms in future missions

Development Of An Oceanic Rain Accumulation Product In Support Of Sea Surface Salinity Measurements From Aquarius/sac-d

Aquarius/SAC-D is a joint mission by National Aeronautics and Space Administration (NASA) and the Comision Nacional de Actividades Espaciales (CONAE), Argentine Space Agency. The satellite was launched in June 2011 and the prime remote sensing instrument is also named Aquarius (AQ). The main objective of this science program is to provide Sea Surface Salinity (SSS) maps of the global oceans every 7 days for understanding the Earth’s hydrologic cycle and for assessing long-term global climate change. The Aquarius instrument was built jointly by NASA’s Goddard Space Flight Center and the Jet Propulsion Laboratory. It is an active/passive L-band remote sensor that measures ocean brightness temperature (Tb) and radar backscatter, and these quantities are used to infer sea surface salinity. Other environmental parameters (e.g., sea surface temperature, wind speed and rain) also affect the microwave emitted radiance or brightness temperature. The SSS geophysical retrieval algorithm considers all these environmental parameters and makes the Tb corrections before retrieving SSS. Instantaneous rainfall can cause increase roughness that raises the ocean surface Tb. Further short term rain accumulation can produce a fresh water lens that floats on the ocean surface and dilutes the surface salinity. iv This thesis presents results of a study to develop an oceanic rain accumulation (RA) product that may be valuable to remote sensing engineers and algorithm developers and Aquarius scientists. The use of this RA product, along with in situ ocean salinity measurements from buoys, may be used to mitigate the effects of rain on the SSS retrieva

Aquarius Final Release Product and Full Range Calibration of L-band Radiometers

Aquarius final product V5.0 has been released. The dataset includes close to four years of global radiometric measurements at L-band. The mission's objective was to monitor sea surface salinity, but other applications of its data over land and the cryosphere have been developed. For this reason, it is important to have accurate calibration over the full range of antenna temperatures from natural targets. It is also needed in order to combine Aquarius measurements with other L-band sensors. Aquarius calibration is strongly focused on the ocean. We present a research product which is part of the final release and aims at producing an accurate calibration from the low end (celestial sky) to the high end (land and ice) of the brightness temperature scale. We calibrate the Aquarius radiometers using measurements over the Sky and oceans and assess the new calibration using measurements over land

Comparisons of Aquarius Measurements over Oceans with Radiative Transfer Models at L-Band

The Aquarius/SAC-D spacecraft includes three L-band (1.4 GHz) radiometers dedicated to measuring sea surface salinity. It was launched in June 2011 by NASA and CONAE (Argentine space agency). We report detailed comparisons of Aquarius measurements with radiative transfer model predictions. These comparisons are used as part of the initial assessment of Aquarius data and to estimate the radiometer calibration bias and stability. Comparisons are also being performed to assess the performance of models used in the retrieval algorithm for correcting the effect of various sources of geophysical "noise" (e.g. Faraday rotation, surface roughness). Such corrections are critical in bringing the error in retrieved salinity down to the required 0.2 practical salinity unit on monthly global maps at 150 km by 150 km resolution