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Challenges and solutions to increasing quantity and diurnal coverage of scatterometer ocean vector wind measurements
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DopperScatt: A Ka-band Doppler Scatterometer for Simulataneous Wide-Swath Measurements of Ocean Surface Vector Winds and Currents and Spaceborned Mission Prototype
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Systematic Scatterometer Wind Errors Near Coastal Mountains
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Evaluating the Detection of Mesoscale Outflow Boundaries Using Scatterometer Winds at Different Spatial Resolutions
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Investigation of microwave backscatter from the air-sea interface
Monitoring the ocean surface winds and mean ocean surface level is essential for improving our knowledge of the climate. Two instruments that may provide us with this information are satellite-based scatterometers and altimeters. However, these instruments measure the backscatter characteristics of the ocean surface from which other physical parameters, such as the wind speed or ocean surface height, are derived. To improve the algorithms or models that relate the electromagnetic backscatter to the desired physical parameters, the University of Massachusetts (UMass) Microwave Remote Sensing Laboratory (MIRSL) designed and fabricated three airborne scatterometers: a C-band scatterometer (CSCAT), Ku-band scatterometer (KUSCAT) and C/Ku-band scatterometer (EMBR). One or more of these instruments participated in the Electromagnetic Bias experiment (EM Bias), Shelf Edge Exchange Processes experiment (SEEP), Surface Wave Dynamics Experiment (SWADE), Southern Ocean Wave Experiment (SOWEX), Hurricane Tina research flights, Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE), and Ladir In-space Technology Experiment (LITE). This document describes the three scatterometers, summarizes our measurement campaigns and major contributions to the scientific and engineering communities, lists the publications that resulted, and presents the degrees earned under the support of this NASA grant.
Radiometric correction of scatterometric wind measurements
Use of a spaceborne scatterometer to determine the ocean-surface wind vector requires accurate measurement of radar backscatter from ocean. Such measurements are hindered by the effect of attenuation in the precipitating regions over sea. The attenuation can be estimated reasonably well with the knowledge of brightness temperatures observed by a microwave radiometer. The NASA SeaWinds scatterometer is to be flown on the Japanese ADEOS2. The AMSR multi-frequency radiometer on ADEOS2 will be used to correct errors due to attenuation in the SeaWinds scatterometer measurements. Here we investigate the errors in the attenuation corrections. Errors would be quite small if the radiometer and scatterometer footprints were identical and filled with uniform rain. However, the footprints are not identical, and because of their size one cannot expect uniform rain across each cell. Simulations were performed with the SeaWinds scatterometer (13.4 GHz) and AMSR (18.7 GHz) footprints with gradients of attenuation. The study shows that the resulting wind speed errors after correction (using the radiometer) are small for most cases. However, variations in the degree of overlap between the radiometer and scatterometer footprints affect the accuracy of the wind speed measurements.
An airborne study of microwave surface sensing and boundary layer heat and moisture fluxes for FIFE
The objectives of this work were to perform imaging radar and scatterometer measurements over the Konza Prairie as a part of the First International land surface climatology project Field Experiments (EIFE) and to develop an mm-wave radiometer and the data acquisition system for this radiometer. We collected imaging radar data with the University of Kansas Side-Looking Airborne Radar (SLAR) operating at 9.375 GHz and scatterometer data with a helicopter-mounted scatterometer at 5.3 and 9.6 GHz. We also developed a 35-GHz null-balancing radiometer and data acquisition system. Although radar images showed good delineation of various features of the FIFE site, the data were not useful for quantitative analysis for extracting soil moisture information because of day-to-day changes in the system transfer characteristics. Our scatterometer results show that both C and X bands are sensitive to soil moisture variations over grass-covered soils. Scattering coefficients near vertical are about 4 dB lower for unburned areas because of the presence of a thatch layer, in comparison with those for burned areas. The results of the research have been documented in reports, oral presentations, and published papers.
Impact of Quikscat Data on Numerical Weather Prediction
Scatterometer observations of the ocean surface wind speed and direction improve the depiction and prediction of storms at sea. These data are especially valuable where observations are otherwise sparse ---mostly in the Southern Hemisphere and tropics, but also on occasion in the North Atlantic and North Pacific. The SeaWinds scatterometer on the QuikScat satellite was launched in July 1999 and it represents a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). The NASA Data Assimilation Office (DAO) was the first data assimilation center to assimilate QuikScat SeaWinds data and evaluate their impact on numerical weather prediction. Several data impact experiments have been performed, using systems from both the DAO (GEOS-3) and from NCEP (GDAS). In general, these experiments have shown a modest impact of SeaWinds data on numerical weather prediction, the magnitude of which appears to be comparable to the magnitude of the impact of AMI scatterometer data from the ERS satellites. Some of the main results from these experiments will be presented at the meeting.
A Radar/Radiometer Instrument for Mapping Soil Moisture and Ocean Salinity
The RadSTAR instrument combines an L-band, digital beam-forming radar with an L-band synthetic aperture, thinned array (STAR) radiometer. The RadSTAR development will support NASA Earth science goals by developing a novel, L-band scatterometer/ radiometer that measures Earth surface bulk material properties (surface emissions and backscatter) as well as surface characteristics (backscatter). Present, real aperture airborne L-Band active/passive measurement systems such as the JPUPALS (Wilson, et al, 2000) provide excellent sampling characteristics, but have no scanning capabilities, and are extremely large; the huge JPUPALS horn requires a the C-130 airborne platform, operated with the aft loading door open during flight operation. The approach used for the upcoming Aquarius ocean salinity mission or the proposed Hydros soil mission use real apertures with multiple fixed beams or scanning beams. For real aperture instruments, there is no upgrade path to scanning over a broad swath, except rotation of the whole aperture, which is an approach with obvious difficulties as aperture size increases. RadSTAR will provide polarimetric scatterometer and radiometer measurements over a wide swath, in a highly space-efficient configuration. The electronic scanning approaches provided through STAR technology and digital beam forming will enable the large L-band aperture to scan efficiently over a very wide swath. RadSTAR technology development, which merges an interferometric radiometer with a digital beam forming scatterometer, is an important step in the path to space for an L-band scatterometer/radiometer. RadSTAR couples a patch array antenna with a 1.26 GHz digital beam forming radar scatterometer and a 1.4 GHz STAR radiometer to provide Earth surface backscatter and emission measurements in a compact, cross-track scanning instrument with no moving parts. This technology will provide the first L-band, emission and backscatter measurements in a compact aircraft instrument and will be ideally suited to large apertures, possibly at GEO, and could possibly be implemented on a swarm of micro-satellites. This instrument will have wide application for validation studies, and will have application for other microwave frequencies.
Ocean-Atmosphere Interaction Over Agulhas Extension Meanders
Many years of high-resolution measurements by a number of space-based sensors and from Lagrangian drifters became available recently and are used to examine the persistent atmospheric imprints of the semi-permanent meanders of the Agulhas Extension Current (AEC), where strong surface current and temperature gradients are found. The sea surface temperature (SST) measured by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and the chlorophyll concentration measured by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) support the identification of the meanders and related ocean circulation by the drifters. The collocation of high and low magnitudes of equivalent neutral wind (ENW) measured by Quick Scatterometer (QuikSCAT), which is uniquely related to surface stress by definition, illustrates not only the stability dependence of turbulent mixing but also the unique stress measuring capability of the scatterometer. The observed rotation of ENW in opposition to the rotation of the surface current clearly demonstrates that the scatterometer measures stress rather than winds. The clear differences between the distributions of wind and stress and the possible inadequacy of turbulent parameterization affirm the need of surface stress vector measurements, which were not available before the scatterometers. The opposite sign of the stress vorticity to current vorticity implies that the atmosphere spins down the current rotation through momentum transport. Coincident high SST and ENW over the southern extension of the meander enhance evaporation and latent heat flux, which cools the ocean. The atmosphere is found to provide negative feedback to ocean current and temperature gradients. Distribution of ENW convergence implies ascending motion on the downwind side of local SST maxima and descending air on the upwind side and acceleration of surface wind stress over warm water (deceleration over cool water); the convection may escalate the contrast of ENW over warm and cool water set up by the dependence of turbulent mixing on stability; this relation exerts a positive feedback to the ENW-SST relation. The temperature sounding measured by the Atmospheric Infrared Sounder(AIRS) is consistent with the spatial coherence between the cloud-top temperature provided by the International Satellite Cloud Climatology Project (ISCCP) and SST. Thus ocean mesoscale SST anomalies associated with the persistent meanders may have a long-term effect well above the midlatitude atmospheric boundary layer, an observation not addressed in the past.
Topographic Signatures in Aquarius Radiometer/Scatterometer Response: Initial Results
The effect of topography on remote sensing at L-band is examined using the co-located Aquarius radiometer and scatterometer observations over land. A correlation with slope standard deviation is demonstrated for both the radiometer and scatterometer at topographic scales. Although the goal of Aquarius is remote sensing of sea surface salinity, the radiometer and scatterometer are on continuously and collect data for remote sensing research over land. Research is reported here using the data over land to determine if topography could have impact on the passive remote sensing at L-band. In this study, we report observations from two study regions: North Africa between 15 deg and 30 deg Northern latitudes and Australia less the Tasmania Island. Common to these two regions are the semi-arid climate and low population density; both favorable conditions to isolate the effect of topography from other sources of scatter and emission such as vegetation and urban areas. Over these study regions, topographic scale slopes within each Aquarius pixel are computed and their standard deviations are compared with Aquarius scatterometer and radiometer observations over a 36 day period between days 275 and 311 of 2011.
The Aquarius Salinity Retrieval Algorithm: Early Results
The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to O2, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind. This is based on the radar backscatter measurements by the scatterometer. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation (cal/val) activity needs to be completed. This is necessary in order to tune the inputs to the algorithm and remove biases that arise due to the instrument calibration, foremost the values of the noise diode injection temperatures and the losses that occur in the feedhorns. This is the subject of the second part of our presentation. The basic tool is to analyze the observed difference between the Aquarius measured TA and an expected TA that is computed from a reference salinity field. It is also necessary to derive a relation between the scatterometer backscatter measurements and the radiometer emissivity that is induced by surface winds. In order to do this we collocate Aquarius radiometer and scatterometer measurements with wind speed retrievals from the WindSat and SSMIS F17 microwave radiometers. Both of these satellites fly in orbits that have the same equatorial ascending crossing time (6 pm) as the Aquarius/SAC-D observatory. Rain retrievals from WindSat and SSMIS F 17 can be used to remove Aquarius observations that are rain contaminated. A byproduct of this analysis is a prediction for the wind-induced sea surface emissivity at L-band.
Towards an Optimal Noise Versus Resolution Trade-Off in Wind Scatterometry
A scatterometer is a radar that measures the normalized radar cross section sigma(sup 0) of the Earth's surface. Over the ocean this signal is related to the wind via the geophysical model function (GMF). The objective of wind scatterometry is to estimate the wind vector field from sigma(sup 0) measurements; however, there are many subtleties that complicate this problem-making it difficult to obtain a unique wind field estimate. Conventionally, wind estimation is split into two stages: a wind retrieval stage in which several ambiguous solutions are obtained, and an ambiguity removal stage in which ambiguities are chosen to produce an appropriate wind vector field estimate. The most common approach to wind field estimation is to grid the scatterometer swath into wind vector cells and estimate wind vector ambiguities independently for each cell. Then, field wise structure is imposed on the solution by an ambiguity selection routine. Although this approach is simple and practical, it neglects field wise structure in the retrieval step and does not account for the spatial correlation imposed by the sampling. This makes it difficult to develop a theoretically appropriate noise versus resolution trade-off using pointwise retrieval. Fieldwise structure may be imposed in the retrieval step using a model-based approach. However, this approach is generally only practical if a low order wind field model is applied, which may discard more information than is desired. Furthermore, model-based approaches do not account for the structure imposed by the sampling. A more general fieldwise approach is to estimate all the wind vectors for all the WVCs simultaneously from all the measurements. This approach can account for structure of the wind field as well as structure imposed by the sampling in the wind retrieval step. Williams and Long in 2010 developed a fieldwise retrieval method based on maximum a posteriori estimation (MAP). This MAP approach can be extended to perform a noise versus resolution trade-off, and deal with ambiguity selection. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed.
Ku-Band Ocean Backscatter Functions for Surface Wind Retrieval
For remote sensing of ocean surface wind, Ku-band scatterometer technology has been demonstrated and will be used to monitor global ocean wind fields from spaceborne sensors such as the NASA Scatterometer (NSCAT). Algorithms for wind velocity retrieval from scatterometer data utilize absolute radar returns and relative azimuth modulations of backscatter. The NUSCAT-SWADE data base is used.
Measuring scatter angle from mirrors
Two instrumentation systems are used to measure scatter angle: intensity scatterometer makes small angle measurements on order of 10 arc-minutes; amplitude scatterometer, which uses interferometric principle, measures smaller angles on order of 10 arc-seconds. Both scatterometers use laser sources and can measure into ultraviolet (0.325 micron) wavelengths.
Correlation between microwave scattering and emission from land and sea at 13.9 GHz
Correlations have been calculated between active and passive microwave responses received by the S-193 radiometer-scatterometer on Skylab. Over both land and sea, the correlations between polarizations are high, but the correlation between radiometer and scatterometer response at 30-deg incidence is negligible. This suggests that multipolarization instruments with this crude resolution (greater than 10 km in all cases) are redundant, but a combination of radiometer and scatterometer is useful. Correlations among the responses at different angles suggest that the five angles used in Skylab are more than would be useful between zero and 48 deg in future instruments, but that instruments with three angles of measurement would be useful. In small areas, conclusions based on these large-data-set averages may need to be modified.
Aircraft measurements of the microwave scattering signature of the ocean
Microwave scattering signatures of the ocean have been measured over a range of surface wind speeds from 3 m/s to 23.6 m/s using the AAFE RADSCAT scatterometer in an aircraft. Normalized scattering coefficients are presented for vertical and horizontal polarizations as a function of incidence angle (nadir to 55 deg) and radar azimuth angle (0 to 360 deg) relative to surface wind direction. For a given radar polarization, incidence angle, and azimuth angle relative to the wind direction, these scattering data exhibit a power law dependence on surface wind speed. The relation of the scattering coefficient to azimuth angle obtained during aircraft circles (antenna conical scans) is anisotropic and suggests that microwave scatterometers can be used to infer both wind speed and direction. These results have been used for the design of the Seasat-A Satellite Scatterometer (SASS) to be flown in 1978 on this first NASA oceanographic satellite.