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DOE OSTI2020

A Satellite-Derived Upper-Ocean Stratification Data Set for the Tropical North Atlantic With Potential Applications for Hurricane Intensity Prediction

Upper-ocean stratification strongly impacts vertical mixing and the heat flux between the ocean and atmosphere, especially under extreme conditions of tropical cyclones (TCs). Knowledge of prestorm stratification is important for accurate TC intensity prediction. In situ observations of the tropical ocean have significantly increased in the past decade. However, they are still too sparse to resolve ocean stratification variability in near-real time and on small spatial scales. Here, in this study, based on long-term observations and an ocean reanalysis data set from 2004–2017, we investigate the possibility of retrieving upper-ocean stratification from sea surface temperature (SST), sea surface salinity (SSS), and sea surface height (SSH) using a simple regression method. It is found that more than 90% of the mean seasonal cycle and about 30% to 80% of temperature and salinity stratification anomalies can be reconstructed using surface data from either observations or an ocean reanalysis. Simple regression can be used with satellite observations to create a high-resolution, near-real-time-gridded ocean stratification data set that successfully reproduces both the large and mesoscale variability of ocean stratification. When used in a simple expression for TC-induced SST cooling, the satellite-derived stratification shows improvements over an ocean analysis in terms of variance explained of SST cooling, offering promise as a near-real-time indicator of the ocean's impact on TC intensification.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

Analysis of RFI Statistics for Aquarius RFI Detection and Mitigation Improvements

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI) which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Microwave remote sensing↗

NASA NTRS2017

RFI Statistical Distribution and Missed Detection in Aquarius Radiometer Measurements

Aquarius is an microwave active/passive sensor whose main goal is to globally estimate sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, operate at L-band observing the same surface footprint almost simultaneously. The sensitivity to sea surface salinity (SSS) is given by the radiometer, while the scatterometer measurements provide a correction for sea surface roughness. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. Radio Frequency Interference (RFI) can occur in both the radiometer and the scatterometer bands of operation, and for this reason detection and mitigation of RFI was included in the data processing of both active and passive instruments. This paper will focus on the RFI processing for the Aquarius radiometer only and provide an update on the efforts to reduce the amount of missed RFI detection.

RFI↗

NASA NTRS1981

Remote sensing of the Chesapeake Bay plume salinity via microwave radiometry

The NASA-Langley-developed L-Band microwave radiometer was used to remotely measure sea surface salinity during the Chesapeake Bay plume studies. Obtained measurements of microwave brightness temperatures of the sea surface were combined with measurements of sea surface temperature obtained with an infrared radiometer and inverted to produce corresponding values of sea surface salinity. Results from the plume measurements, which indicate the southward extent of the plume along the Virginia-North Carolina coast, are presented and discussed. Additional measurements obtained for the Delaware Bay Mouth flight, and the James River-Shelf flight, are also discussed.

Kendall, B. M.↗

NASA NTRS2021

Sensitivity of Wide Bandwidth Radiometer for Remote Sensing of Ocean Salinity

Passive microwave remote sensing of sea surface salinity from space is currently being done with measurements in the 27 MHz wide spectral window at 1.413 GHz (L-band) protected for passive use. Modern L-band instruments, such as the radiometers on SMOS and Aquarius, have demonstrated the feasibility of monitoring surface salinity from space, and they have also demonstrated the need for better accuracy, especially in cold water. Proposals to improve accuracy have largely involved adding measurement at more frequencies. For example, adding lower frequencies to improve the sensitivity to salinity in cold water and adding higher frequencies to enable simultaneous retrieval of sea surface temperature which is needed in the retrieval of salinity. These strategies involve trade-offs, some obvious such as the effects of interference from anthropogenic sources of radio frequency radiation (RFI) when operating outside the protected band and the loss of spatial resolution at lower frequencies. But, some are more subtle and arise because of the dependence of the retrieval of salinity on other parameters of the ocean surface, in particular, water temperature and roughness (wind speed). The effect of these interdependencies on the potential accuracy of salinity remote sensing in the frequency range 0.3 – 3.0 GHz is examined here to gain insight into the potential for future wide bandwidth instruments for remote sensing of salinity and the optimization of their design. There is benefit including the low frequencies, especially for cold water, but a danger of increased error including frequencies above 1.5 - 2.0 GHz depending on temperature.

Microwave Remote Sensing↗

NASA NTRS2023

New Seawater Dielectric Constant Parametrization and Application to SMOS Retrieved Salinity

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the reliability of the dielectric constant model. Two new parametrizations were recently developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements by Boutin et al. (2021) (BV), and on the other hand, on new George Washington University laboratory measurements by Zhou et al. (2021) (GW2020). These two approaches are fully independent. For most SSS and Sea Surface Temperature (SST) conditions commonly observed over the open ocean, the relative variations of brightness temperatures Tb simulated through the BV and GW2020 parametrizations agree particularly well, and better than with earlier parametrizations previously used in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Nevertheless, uncertainty remains, especially below 10 °C where a ∼ 0.1 K relative difference between the two models is observed. This motivates the development of a revised parameterization, BVZ, based on a methodology similar to that used to derive BV but using GW2020 instead of SMOS measurements. Compared to the GW2020 parameterization, BVZ is derived with a reduced number of degrees of freedom, it relies on the TEOS10 PSS78 conductivity-salinity relationship, and on the previously derived static permittivity of fresh water. One month per season of SMOS data have been reprocessed in 2018 using BV, GW2020, and BVZ. We find the best overall agreement between SMOS SSS and Argo SSS with BVZ parametrization, with noticeable improvement in the 5 °C–15 °C SST range.

sea measurements↗

NASA NTRS2001

Surface Salinity Variability in the North Atlantic During Recent Decades

The sea surface salinity (SSS) variability in the North Atlantic is investigated using numerical model simulations for the last 50 years based on atmospheric forcing variability from Comprehensive Atmosphere Ocean Data Set (COADS) and National Center for Environmental Prediction / National Center for Atmospheric Research (NCEP/NCAR) Reanalysis. The largest interannual and longer term variability occurs in two regions: the Labrador Sea and the North Equatorial Countercurrent (NECC) region. In both regions the seasonality of the surface salinity variability is prominent with the maximum standard deviation occurring in the summer/fall period. In the Labrador Sea the summer SSS anomalies far exceed those of wintertime in amplitude. The interannual SSS variability in the subpolar gyre can be attributed to two factors: excess ice melt and heat flux (i.e. deep mixing) variations. On the other hand, heat flux variability can also lead to meridional overturning changes on decadal time scales such that weak overturning is manifested in fresh surface conditions in the subpolar gyre. The overturning changes also influence the NECC region SSS variability. Moreover, the subpolar freshening events are expected to occur during the negative phase of North Atlantic Oscillation which is associated with a weak wintertime surface heat loss in the subpolar gyre. No excess sea ice melt or precipitation is necessary for the formation of the fresh anomalies, because with the lack of wide-spread deep mixing, the fresh water that would be expected based on climatology, would accumulate at the surface. Thus, the fresh water 'conveyor' in the Atlantic operates via the overturning circulation such that deep mixing inserts fresh water while removing heat from the water column.

Haekkinen, Sirpa↗

NASA NTRS2011

Remote Sensing of Salinity: The Dielectric Constant of Sea Water

Global monitoring of sea surface salinity from space requires an accurate model for the dielectric constant of sea water as a function of salinity and temperature to characterize the emissivity of the surface. Measurements are being made at 1.413 GHz, the center frequency of the Aquarius radiometers, using a resonant cavity and the perturbation method. The cavity is operated in a transmission mode and immersed in a liquid bath to control temperature. Multiple measurements are made at each temperature and salinity. Error budgets indicate a relative accuracy for both real and imaginary parts of the dielectric constant of about 1%.

LeVine, David M.↗

NASA NTRS2005

The Impact of the Sun on Passive Remote Sensing at L-band

The sun is a strong source of radiation at L-band behaving roughly like a thermal source with a temperature ranging between 10(exp 5) - 10(exp 7) K, depending on solar activity. This is an important consideration at 1.4 GHz (the window set aside for passive use only) where future satellite sensors will operate to monitor soil moisture and sea surface salinity (e.g. SMOS, Aquarius, and Hydros). Straight forward calculations show that such a source of radiation can be a significant issue for these remote sensing applications, especially in the case of remote sensing of sea surface salinity. Radiation from the sun impacts passive remote sensing systems in several ways. First, is the solar radiation that comes directly from the sun (line-of-sight from sun to spacecraft that enters the radiometer through antenna side lobes). This is a particular problem for sensors in sunsynchronous orbits near the terminator (e.g. orbits with equatorial crossing times near 6am/6pm) because the spacecraft is in the sun most of the time. Second, is solar radiation that is reflected (specularly) from the mean surface to the radiometer. This contribution can be nearly as large as the direct ray, especially when the reflection is from the ocean surface which has a high reflection coefficient. Finally, there is "incoherent" signal reflected from the surface structure (roughness) to the radiometer antenna. Examples illustrating the significance of these terms is presented for the case of a pushbroom radiometer such as Aquarius and a conically scanning radiometer such as proposed for Hydros. Calculations are made using a set of theoretical patterns for these beams together with data on solar radiation obtained from by a worldwide network of observing stations known as Radio Solar Telescope Network (RSTN). Near solar minimum, solar contamination is not a problem unless the sun enters near the main beam. But near solar maximum, account must be made for radiation from the sun even when the signal enters in sidelobes far from the main beam.

LeVine, David M.↗

NASA NTRS2000

Galactic Noise and Passive Microwave Remote Sensing from Space at L-Band

The spectral window at L-band (1.4 GHz) is important for passive remote sensing of parameters such as soil moisture and ocean salinity best measured at long wavelengths. At L-band, radiation from extraterrestrial (galactic) sources is strong enough to warrant inclusion in calibration and retrieval algorithms and unlike the constant cosmic background is spatially variable. Previous estimates of the magnitude and distribution of this background radiation have been rather coarse, However, recent surveys of the radio sky at 1.4 GHz have made it possible to produce maps with sufficient spatial and radiometric accuracy to be relevant to remote sensing applications. This is of particular concern for remote sensing of sea surface salinity because the surface (water) is a good reflector and the salinity signal is relatively small. This paper presents a modem map of the radiometric sky at L-band and a solution to the problem of determining the portion of the sky seen by a radiometer in orbit. The data is derived from recent radio astronomy surveys and is presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Radiation near the galactic plane can exceed several kelvin.

LeVine, D. M.↗

NASA NTRS1984

Errors in radiometric remote sensing of sea-surface temperature and salinity

Techniques for remote measurement of sea-surface physical temperature and salinity using radiometric measurements from aircraft or satellite are reviewed. Studies have been conducted to determine the sensitivity of the errors in surface temperature and salinity to errors in the measured brightness temperatures using combinations of UHF, L, S, and C-band measurements. These investigations were made using values of conductivity, static dielectric constant, and relaxation time derived from the regression equations of Klein and Swift (1977). Results of the error sensitivity study are presented in the form of error contour plots which permit the calculation of errors in the estimation of the physical parameters for given errors in the raw radiometric measurements.

Britt, C. L., Jr.↗

NASA NTRS2012

Ocean Surface Emissivity at L-band (1.4 GHz): The Dependence on Salinity and Roughness

A characterization of the emissivity of sea water at L-band is important for the remote sensing of sea surface salinity. Measurements of salinity are currently being made in the radio astronomy band at 1.413 GHz by ESA's Soil Moisture and Ocean Salinity (SMOS) mission and NASA's Aquarius instrument aboard the Aquarius/SAC-D observatory. The goal of both missions is accuracy on the order of 0.1 psu. This requires accurate knowledge of the dielectric constant of sea water as a function of salinity and temperature and also the effect of waves (roughness). The former determines the emissivity of an ideal (i.e. flat) surface and the later is the major source of error from predictions based on a flat surface. These two aspects of the problem of characterizing the emissivity are being addressed in the context of the Aquarius mission. First, laboratory measurements are being made of the dielectric constant of sea water. This is being done at the George Washington University using a resonant cavity. In this technique, sea water of known salinity and temperature is fed into the cavity along its axis through a narrow tube. The sea water changes the resonant frequency and Q of the cavity which, if the sample is small enough, can be related to the dielectric constant of the sample. An extensive set of measurements have been conducted at 1.413 GHz to develop a model for the real and imaginary part of the dielectric constant as a function of salinity and temperature. The results are compared to the predictions of models based on parameterization of the Debye resonance of the water molecule. The models and measurements are close; however, the differences are significant for remote sensing of salinity. This is especially true at low temperatures where the sensitivity to salinity is lowest.

LeVine, D. M.↗

NASA NTRS2021

Seawater Debye Model Function at L-Band and Its Impact on Salinity Retrieval From Aquarius Satellite Data

A model function of seawater, which specifies the dielectric constant of seawater as a function of salinity, temperature, and frequency, is important for the retrieval of sea surface salinity using satellite data. In 2017, a model function has been developed based on measurement data at 1.4134 GHz using a third-order polynomial expression in salinity ( S ) and temperature ( T ). Although the model showed improvements in salinity retrieval, it had an inconsistent behavior between partitioned salinities. To improve the stability of the model, new dielectric measurements of seawater have been made recently over a broad range of salinities and temperatures to expand the data set used for developing the model function. The structure of the model function has been changed from a polynomial expansion in S and T to a physics-based model consisting of a Debye molecular resonance term plus a conductivity term. Each unknown parameter is expressed in S and T based on the expanded measurement data set. Physical arguments have been used to limit the number of unknown coefficients in these expressions to improve the stability of the model function. The new model function has been employed in the retrieval algorithm of the Aquarius satellite mission to obtain a global salinity map. The retrieved salinity using a different model function is compared with in situ data collected by Argo floats to evaluate the impact and the performance of model functions. The results indicate that the new model function has significant improvements in salinity retrieval compared with other existing models.

Seawater↗

NASA NTRS2002

Sensitivity of Global Sea-Air CO2 Flux to Gas Transfer Algorithms, Climatological Wind Speeds, and Variability of Sea Surface Temperature and Salinity

Sensitivity analyses of sea-air CO2 flux to gas transfer algorithms, climatological wind speeds, sea surface temperatures (SST) and salinity (SSS) were conducted for the global oceans and selected regional domains. Large uncertainties in the global sea-air flux estimates are identified due to different gas transfer algorithms, global climatological wind speeds, and seasonal SST and SSS data. The global sea-air flux ranges from -0.57 to -2.27 Gt/yr, depending on the combination of gas transfer algorithms and global climatological wind speeds used. Different combinations of SST and SSS global fields resulted in changes as large as 35% on the oceans global sea-air flux. An error as small as plus or minus 0.2 in SSS translates into a plus or minus 43% deviation on the mean global CO2 flux. This result emphasizes the need for highly accurate satellite SSS observations for the development of remote sensing sea-air flux algorithms.

McClain, Charles R.↗

NASA NTRS1991

A model of the formation of high-salinity shelf water on polar continental shelves

This study presents a model of the flow and salinity fields forced by sea-surface salinity flux and wind stress curl and examines the processes that create High-Salinity Shelf Water (HSSW). To investigate the relative effects of wind stress and buoyancy forcing in HSSW production, the polynya freezing rate in the model is varied from 0.0 to 0.30 m/d, and the Ekman pumping derived from the wind stress curl is varied independently from 0.0 to 1.8 x 10 exp 6 m/s. The Ekman pumping was found to control the magnitude of the circulation, while the polynya freezing rate controlled the extent of salinization in the shelf water. The flux of HSSW increases linearly with increasing Ekman pumping above 0.3 x 10 exp -6 m/s. The modeled flux of HSSW and the flux of derived Botttom Water for the present estimates of the forcings (a peak freezing rate of 0.10 m/d and Ekman pumping of 0.2 x 10 exp -6 m/s) agree with the fluxes inferred from physical and chemical observations in the deep Weddel Sea by oceanographic field programs.

Grumbine, Robert W.↗

NASA NTRS2008

The Detection and Mitigation of RFI with the Aquarius L-Band Scatterometer

The Aquarius sea-surface salinity mission includes an L-band scatterometer to sense sea-surface roughness. This radar is subject to radio-frequency interference (RFI) in its passband from 1258 to 1262 MHz, a region also allocated for terrestrial radio location. Due to its received power sensitivity requirements, the expected RFI environment poses significant challenges. We present the results of a study evaluating the severity of terrestrial RFI sources on the operation of the Aquarius scatterometer, and propose a scheme to both detect and remove problematic RFI signals in the ocean backscatter measurements. The detection scheme utilizes the digital sampling of the ambient input power to detect outliers from the receiver noise floor which are statistically significant, and flags nearby radar echoes as potentially contaminated by RFI. This detection strategy, developed to meet tight budget and data downlink requirements, has been implemented and tested in hardware, and shows great promise for the detection and global mapping of L-band RFI sources.

Electromagnetic radiative interference↗

NASA NTRS2022

Measurement of SST and SSS Using Frequencies in the Range 0.3–2.0 GHz

Wide bandwidth radiometer systems that make measurements at multiple frequencies in the range from 300 MHz to 2 GHz have been proposed to address parameters important for understanding issues in the cryosphere associated with climate change such as ice sheet thickness and temperature. It is also possible with such a system to retrieve sea surface salinity (SSS), which is important for understanding the impact of climate change on ocean circulation at high latitude. In contemporary sensors for retrieving SSS, such as on Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), sea surface temperature (SST), another parameter important for understanding ocean circulation and necessary in the retrieval of salinity, is treated as an ancillary parameter obtained from an independent source. However, both SSS and SST have peaks in sensitivity below 1 GHz; and it has been shown that measurements at multiple frequencies in this portion of the spectrum can take advantage of this peak in sensitivity to improve the accuracy of the retrieval of SSS. In this manuscript, it will be shown that there is also the potential to retrieve SST and, in cold water, the possibility for improved accuracy over existing retrievals.

Microwave remote sensing↗

NASA NTRS1977

Sea-surface temperature and salinity mapping from remote microwave radiometric measurements of brightness temperature

A technique to measure remotely sea surface temperature and salinity was demonstrated with a dual frequency microwave radiometer system. Accuracies in temperature of 1 C and in salinity of part thousand for salinity greater than 5 parts per thousand were attained after correcting for the influence of extraterrestrial background radiation, atmospheric radiation and attenuation, sea-surface roughness, and antenna beamwidth. The radiometers, operating at 1.43 and 2.65 GHz, comprise a third-generation system using null balancing and feedback noise injection. Flight measurements from an aircraft at an altitude of 1.4 km over the lower Chesapeake Bay and coastal areas of the Atlantic Ocean resulted in contour maps of sea-surface temperature and salinity with a spatial resolution of 0.5 km.

Hans-Juergen, C. B.↗