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NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

Sea surface salinity (SSS) observations from space allow us to investigate if improved estimates of near-surface density stratification and associated mixing can positively impact seasonal to interannual variability of tropical Pacific Ocean dynamics as well as dynamical ENSO forecasts. For the first part of the presentation, we utilize our intermediate-complexity coupled model. Baseline experiments assimilate satellite sea level (multi-satellite gridded AVISO, 2013), SST (Reynolds et al., 2004), and in situ subsurface temperature and salinity observations (GTSPP NODC, 2006). These baseline experiments are then compared with experiments that additionally assimilate Aquarius (V5.0 Lilly and Lagerloef, 2008) and SMAP (V4.0 Fore et al., 2016) SSS. Twelve-month forecasts are initialized for each month from September 2011 to September 2017. For initialization of the coupled forecast, the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. This pattern enhances air/sea interaction and amplifies the equatorial Kelvin wave signal. We find that including satellite SSS significantly improves NINO3.4 sea surface temperature anomaly validation over most forecast lead times. We next assess how different satellite SSS products impact the validation of ENSO forecasts. SMAP V4 reduces the salty bias in the western Pacific and so is an improvement upon SMAP V2 and SMOS V2 (Boutin et al., 2017) has similar validation characteristics as a combination of Aquarius and SMAP V4. Next we shift to present results from the NASA GMAO Sub-seasonal to seasonal (S2S_v2.1) production coupled model (i.e. the same model that contributes ENSO forecasts to the North American Multi-Model Ensemble Experiment). From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts for the big 2015 El Nino event. We will present distinct experiments for the overlap period that include 1) freely evolving SSS (i.e. no satellite SSS as the production system), 2) Aquarius, and 3) SMAP initialization. Our results show that using Aquarius slightly improves validation of the reanalysis (including sea level and temperature statistics). Our production system without SSS assimilation generated too warm forecasts for the 2015 El Nino from March initial conditions. Incorporating Aquarius into initialization of the coupled system leads to a deeper, more realistic MLD that acts to damp the downwelling Kelvin signal and slightly cool NINO3.4 SST. With Aquarius the forecasts better match the observed amplitude of the 2015 event. On the other hand, SMAP V2 relaxation generally degrades validation statistics. At forecast initialization, SMAP is much too salty within 10o of the equator, leading to deeper MLD east of 165W. This deeper MLD leads to over-damping of the downwelling signal (i.e. relative upwelling), in turn leading to relatively too cool ENSO forecasts.

Hackert, E.↗
NASA NTRS2019

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large-scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 psu in October and low values of 33.40 psu in May, theSMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root mean square difference from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias adjustment done on the data set. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season. Salinity together with temperature is the key parameters that control the state and circulation of the World's oceans. The large‐scale distribution of the sea surface salinity of the Southern Ocean is quantified for the first time using Aquarius, Soil Moisture and Ocean Salinity, and Soil Moisture Active and Passive satellite microwave data. Seasonal and interannual changes in the distribution as affected by the sea ice cover, surface temperature, and precipitation are evaluated. Comparative studies were done, using four different products that are publicly available, in conjunction with in situ observations to gain insights into the true nature of the distribution and how consistently the sea surface salinity is depicted by the different products. There are general consistencies in the products, and discrepancies are attributed to different algorithms, smoothing techniques, and sea ice masking. Aquarius data are shown to have higher accuracy than Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive products in part because of having concurrent scatterometer that provides accurate correction to roughness effects.

Garcia-Eidell, Cynthia↗
NASA NTRS2006

Miniature Wireless Sensors Size Up to Big Applications

Like the environment of space, the undersea world is a hostile, alien place for humans to live. But far beneath the waves near Key Largo, Florida, an underwater laboratory called Aquarius provides a safe harbor for scientists to live and work for weeks at a time. Aquarius is the only undersea laboratory in the world. It is owned by the National Oceanic and Atmospheric Administration (NOAA), administered by NOAA s National Undersea Research Program, and operated by the National Undersea Research Center at the University of North Carolina at Wilmington. Aquarius was first deployed in underwater operations in 1988 and has since hosted more than 200 scientists representing more than 90 organizations from around the world. For NASA, Aquarius provides an environment that is analogous to the International Space Station (ISS) and the space shuttle. As part of its NASA Extreme Environment Mission Operations (NEEMO) program, the Agency sends personnel to live in the underwater laboratory for up to 2 weeks at a time, some of whom are crew members or "aquanauts" who are subjected to the same tasks and challenges underwater that they would face in space. In fact, many participants have found the deep-sea diving experience to be much akin to spacewalking. To maintain Aquarius, the ISS, and the space shuttle as safe, healthy living/research habitats for its personnel, while keeping costs in mind, NASA, in 1997, recruited the help of Conroe, Texas-based Invocon, Inc., to develop wireless sensor technology that monitors and measures various environmental and structural parameters inside these facilities.

Source record↗
NASA NTRS2015

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = −0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil MOisture↗
NASA NTRS2019

Remote Sensing of Sea Surface Salinity: Comparison of Satellite and In Situ Observations and Impact of Retrieval Parameters

Since 2009, three low frequency microwave sensors have been launched into space with the capability of global monitoring of sea surface salinity (SSS). The European Space Agency's (ESA's) Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), onboard the Soil Moisture and Ocean Salinity mission (SMOS), and National Aeronautics and Space Administration's (NASA's) Aquarius and Soil Moisture Active Passive mission (SMAP) use L-band radiometry to measure SSS. There are notable differences in the instrumental approaches, as well as in the retrieval algorithms. We compare the salinity retrieved from these three spaceborne sensors to in situ observations from theArgo network of drifting floats, and we analyze some possible causes for the differences. We present comparisons of the long-term global spatial distribution, the temporal variability for a set of regions of interest and statistical distributions. We analyze some of the possible causes for the differences between the various satellite SSS products by reprocessing the retrievals from Aquarius brightness temperatures changing the model for the sea water dielectric constant and the ancillary product for the sea surface temperature. We quantify the impact of these changes on the differences in SSS between Aquarius and SMOS.We also identify the impact of the corrections for atmospheric effectsrecently modified in the Aquarius SSS retrievals. All three satellites exhibit SSS errors with a strong dependence on sea surface temperature, but this dependence varies significantly with the sensor. We show that these differences are first and foremost due to the dielectric constant model, then to atmospheric corrections and to a lesser extent to the ancillary product of the sea surface temperature.

SSS↗
NASA NTRS2006

Effects of the Antenna Aperture on Remote Sensing of Sea Surface Salinity at L-Band

Remote sensing of sea surface salinity with sufficient accuracy to meet the needs of global oceanography is a challenging task. The global variability of the salinity signal in the open ocean is only a few Kelvin even at L-band and an accuracy on the order of 0.1K is desired to study the influence of salinity on ocean circulation and energy exchange with the atmosphere. On the other hand, resolution is not an issue for understanding the dynamics of the open ocean where scales of hundreds of km are not uncommon. This permits remote sensing with large antenna footprints and spatial averaging to reduce noise. However, antennas with large footprints introduce other problems. For example, the angle of incidence and hence the brightness temperature varies over the footprint. Similarly, the polarization of brightness temperature relative to the antenna ports changes. Studies have been conducted using antenna patterns representative of the antenna that will be flown on the Aquarius mission to examine these effects. Aquarius is a pushbroom style radiometer with three beams looking across track away from the sun. The beams are at incidences angles (at the spacecraft) of about 26.5, 34 and 40 degrees each with a half-power beam width of about 5.8 degrees. It is shown that the measured brightness temperature is biased relative to the value at boresight because of changes across the field of view. The bias can be as much as 4K and positive or negative depending on polarization. Polarization mixing because of the variations of the local plane of incidence across the footprint also occur and can result in biased polarimetric measurements. A bias in the third Stokes parameter of as much as 0.4K is possible. Such effects may affect algorithms that use the third Stokes parameter to correct for Faraday rotation. Another issue associated with the antenna is sun glint. This is an issue determined by surface roughness and antenna sidelobes. Examples will be given for the random component (glint) for the case of the Aquarius antenna beams. Fortunately, the Aquarius beams mostly look to the dark side of the day-night termination, but during some portions of the year they will see sun-lighted ocean. In this case, glint could be an issue for the inner-most beam.

Dinnat, Emmanuel P.↗
NASA NTRS2012

Increased Accuracy in the Measurement of the Dielectric Constant of Seawater at 1.413 GHz

This paper describes the latest results for the measurements of the dielectric constant at 1.413 GHz by using a resonant cavity technique. The purpose of these measurements is to develop an accurate relationship for the dependence of the dielectric constant of sea water on temperature and salinity which is needed by the Aquarius inversion algorithm to retrieve salinity. Aquarius is the major instrument on the Aquarius/SAC-D observatory, a NASA/CONAE satellite mission launched in June of20ll with the primary mission of measuring global sea surface salinity to an accuracy of 0.2 psu. Aquarius measures salinity with a 1.413 GHz radiometer and uses a scatterometer to compensate for the effects of surface roughness. The core part of the seawater dielectric constant measurement system is a brass microwave cavity that is resonant at 1.413 GHz. The seawater is introduced into the cavity through a capillary glass tube having an inner diameter of 0.1 mm. The change of resonance frequency and the cavity Q value are used to determine the real and imaginary parts of the dielectric constant of seawater introduced into the thin tube. Measurements are automated with the help of software developed at the George Washington University. In this talk, new results from measurements made since September 2010 will be presented for salinities 30, 35 and 38 psu with a temperature range of O C to 350 C in intervals of 5 C. These measurements are more accurate than earlier measurements made in 2008 because of a new method for measuring the calibration constant using methanol. In addition, the variance of repeated seawater measurements has been reduced by letting the system stabilize overnight between temperature changes. The new results are compared to the Kline Swift and Meissner Wentz model functions. The importance of an accurate model function will be illustrated by using these model functions to invert the Aquarius brightness temperature to get the salinity values. The salinity values will be compared to co-located in situ data collected by Argo buoys.

Zhou, Y.↗
NASA NTRS2005

Ultra Stable Microwave Radiometers for Future Sea Surface Salinity Missions

The NASA Earth Science System Pathfinder (ESSP) mission Aquarius will measure global sea surface salinity with 100-km spatial resolution every 8 days with an average monthly salinity accuracy of 0.2 psu (parts per thousand). This requires an L-band low-noise radiometer with the long-term calibration stability of less than 0.1 K over 8 days. This three-year research program on ultra stable radiometers has addressed the radiometer requirements and configuration necessary to achieve this objective for Aquarius and future ocean salinity missions. The system configuration and component performance have been evaluated with radiometer testbeds at both JPL and GSFC. The research has addressed several areas including component characterization as a function of temperature, a procedure for the measurement and correction for radiometer system non-linearity, noise diode calibration versus temperature, low noise amplifier performance over voltage, and temperature control requirements to achieve the required stability. A breadboard radiometer, utilizing microstrip-based technologies, has been built to demonstrate this long-term stability. This report also presents the results of the radiometer test program, a detailed radiometer noise model, and details of the operational switching sequence optimization that can be used to achieve the low noise and stability requirements. Many of the results of this research have been incorporated into the Aquarius radiometer design and will allow this instrument to achieve its goals.

sea surface salinity↗
NASA NTRS2012

New Dielectric Measurement Data to Determine the Permittivity of Seawater at 1.4313 Hz

This paper describes the new measurements - made in 2010-2011 - of the dielectric constant of seawater at 1.413 GHz using a resonant cavity technique. The purpose of these measurements is to develop an accurate relationship concerning the dependence of the dielectric constant of seawater on temperature and salinity for use by the Aquarius inversion algorithm. Aquarius is a NASA/CONAE satellite mission launched in June of 2011 with the primary mission of measuring global sea surface salinity with a 1.413 GHz radiometer to an accuracy of 0.2 psu. A brass microwave cavity resonant at 1.413 GHz has been used to measure the dielectric constant of seawater. The seawater is introduced into the cavity through a capillary glass tube having an inner diameter of 0.1 mm. The change of resonant frequency and the cavity Q value are used to determine the real and imaginary parts of the dielectric constant of seawater. Measurements are automated with Visual Basic software developed at the George Washington University. In this paper, new results from measurements made since September 2010 will be presented for salinities of 30, 35 and 38 psu with a temperature range of 0 C to 35 C in intervals of 5 C. These measurements are more accurate than earlier measurements made in 2008. The new results will be compared to the Klein-Swift (KS) and Meissner-Wentz (MW) model functions. The importance of an accurate model function will be illustrated by using these model functions to invert the Aquarius brightness temperature to retrieve the salinity values. The salinity values will be compared to co-located in situ data collected by Argo buoys.

Lang, R.↗
NASA NTRS2012

Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/ active L-band instruments. Aquarius s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research. In this innovation, an algorithm has been developed to retrieve simultaneously ocean surface salinity and wind from combined passive/active L-band microwave observations of sea surfaces. The algorithm takes advantage of the differing response of brightness temperatures and radar backscatter to salinity, wind speed, and direction, thus minimizing the least squares error (LSE) measure, which signifies the difference between measurements and model functions of brightness temperatures and radar backscatter. The algorithm uses the conjugate gradient method to search for the local minima of the LSE. Three LSE measures with different measurement combinations have been tested. The first LSE measure uses passive microwave data only with retrieval errors reaching 1 to 2 psu (practical salinity units) for salinity, and 1 to 2 m/s for wind speed. The second LSE measure uses both passive and active microwave data for vertical and horizontal polarizations. The addition of active microwave data significantly improves the retrieval accuracy by about a factor of five. To mitigate the impact of Faraday rotation on satellite observations, the third LSE measure uses measurement combinations invariant under the Faraday rotation. For Aquarius, the expected RMS SSS (sea surface salinity) error will be less than about 0.2 psu for low winds, and increases to 0.3 psu at 25 m/s wind speed for warm waters (25 C). To achieve the required 0.2 psu accuracy, the impact of sea surface roughness (e.g. wind-generated ripples) on the observed brightness temperature has to be corrected to better than one tenth of a degree Kelvin. With this algorithm, the accuracy of retrieved wind speed will be high, varying from a few tenths to 0.6 m/s. The expected direction accuracy is also excellent (less than 10 ) for mid to high winds, but degrades for lower speeds (less than 7 m/s).

Yueh, Simon H.↗
NASA NTRS2015

Evaluation of Spaceborne L-band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada

The landscape freeze/thaw (FT) state has an important impact on the surface energy balance, carbon fluxes, and hydrologic processes; the timing of spring melt is linked to active layer dynamics in permafrost areas. L-band (1.4 GHz) microwave emission could allow the monitoring of surface state dynamics due to its sensitivity to the pronounced permittivity difference between frozen and thawed soil. The aim of this paper is to evaluate the performance of both Aquarius and Soil Moisture and Ocean Salinity (SMOS) L-band passive microwave measurements using a polarization ratio-based algorithm for landscape FT monitoring. Weekly L-band satellite observations are compared with a large set of reference data at 48 sites across Canada spanning three environments: tundra, boreal forest, and prairies. The reference data include in situ measurements of soil temperature (Tsoil) and air temperature (Tair), and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover area (SCA) products. Results show generally good agreement between Lband FT detection and the surface state estimated from four reference datasets. The best apparent accuracies for all seasons are obtained using Tair as the reference. Aquarius radiometer 2 (incidence angle of 39.6) data gives the best accuracies (90.8), while for SMOS the best results (87.8 of accuracy) are obtained at higher incidence angles (55- 60). The FT algorithm identifies both freeze onset and end with a delay of about one week in tundra and two weeks in forest and prairies, when compared to Tair. The analysis shows a stronger FT signal at tundra sites due to the typically clean transitions between consistently frozen and thawed conditions (and vice versa) and the absence of surface vegetation. Results in the prairies were poorer because of the influence of vegetation growth in summer (which decreases the polarization ratio) and the high frequency of ephemeral thaw events during winter. Freeze onset and end maps created from the same algorithm applied to SMOS and Aquarius measurements characterize similar FT patterns over Canada. This study shows the potential of using L-band spaceborne observations for FT monitoring, but underlines some limitations due to ice crusts in the snowpack, liquid water content in snow cover during the spring freeze to thaw transition, and vegetation growth.

soil freeze/thaw↗
NASA NTRS2018

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius/SAC-D, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 in October and low values of 33.40 in May, the SMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root-mean-square-errors from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias-adjustment done on the dataset. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season.

SSS↗
NASA NTRSDate not supplied

NASA Extreme Environment Mission Operations (NEEMO)

Introduction: NASA is preparing to land the first woman and first person of color on the Moon within the next decade, and ensuring the success of these missions will depend on our preparation on the ground in multiple ground-based lunar environment analogs. To achieve this, NASA has used full mission class analogs, of which NASA Extreme Environment Mission Operations (NEEMO) is the longest continuously running example. Discussion: NEEMO is NASA’s long-standing undersea high-fidelity spaceflight mission analog. It focuses on exploration science, EVA techniques and tools, and maturing ISS IVA flight hardware and operations concepts. NEEMO crews are composed of groups of US and International Partner (IP) astronauts, engineers and scientists who live, work and explore in a challenging environment analogous to the environment experienced currently on ISS and what is expected for future deep space exploration destinations. NEEMO missions are conducted at Aquarius Reef Base (ARB), which includes a shore base in Tavernier, FL, and the world's only undersea research station, the Aquarius habitat, which is located 5.4 miles (9 kilometers) off Key Largo in the Florida Keys National Marine Sanctuary. ARB is owned and operated by Florida International University (FIU). Aquarius was selected due to its remote and extreme location and its ability to provide the unique isolation and risk factors that spaceflight presents. NEEMO missions allow for evaluations of end-to-end EVA and Science exploration concepts of operations with a crew that is in situ in a true extreme environment. They also allow for evaluations of flight hardware and ops tools that are either pondered or destined for ISS or Gateway in the near future. NEEMO missions feature flight-like interactions between the crew and a Mission Control Center (MCC )and Science Team, which in turn allows evaluation of mission and science operations decision making and communications techniques. One reason NEEMO missions are of such high fidelity is that so many of the participants are experienced human space flight end operators. The majority of crewmembers are trained astronauts, and many of the MCC operators have credentials as current or former certified ISS MCC operators (e.g., CapCom, EVA Officer, etc.). Mission products are generated daily by the ground team and are modeled on ISS products (but modified as needed). A planning team manages the constantly evolving mission timelines in response to the ever-changing constraints and opportunities. During NEEMO missions, suited EVA crewmembers (using diving helmets) have clear voice communications with each other, the habitat, and the MCC and Science Team back on shore. Each EVA crewmember also sends helmet cam video to the habitat and MCC and Science Teams. Appropriate communications latencies are inserted for the destination being simulated as well. NEEMO missions are made possible by a broad collaboration of participants. Astronauts from all of the ISS partner agencies are eligible for crew assignment. Often the crew includes a NASA scientist, doctor or engineer with a particular skill to contribute. Sometimes crewmembers come from external entities–generally institutes or universities. Objectives come from a wide variety of sources as well, from within NASA, IPs, government agencies, academia, commercial companies and research institutes. A typical NEEMO mission is a collaboration between at least 5 NASA centers. To date, 23 NEEMO missions have been conducted since 2001, and NEEMO 24 is planned for 2022. Conclusion: NEEMO is a high-fidelity mission analog conducted in an extreme subsea environment. It features experienced end-operators in human spaceflight, from the astronaut crewmembers to key personnel staffing Mission Control. Acknowledgments: The authors wish to thank FIU and NASA’s HEO SEI/Strategic Analysis and Exploration Integration and Science Directorate organizations for the continued support that makes the NEEMO Project possible.

M L Reagan↗
NASA NTRS2012

Sea Surface Salinity : Research Challenges and Opportunities

Sea surface salinity (SSS) can be important in regulating sea surface temperature (SST). Two technological breakthrough satellite SSS missions, Aquarius and Soil Moisture and Ocean Salinity (SMOS), are currently producing high-quality SSS data. This paper provides an overview of the importance of SSS for weather and climate applications and describes the Aquarius and SMOS missions. The newness of adequately sampled SSS data prompted a first-time at-sea field campaign devoted to improved understanding of SSS variations.

Aquarius↗
NASA NTRS2016

L-Band RFI in Japan

In recent years, three instruments have been launched into orbit with the aim of producing global maps of sea surface salinity and soil moisture using the 1400-1427 MHz band: SMOS, Aquarius and SMAP. Although this frequency band is allocated to passive measurements only, RFI (Radio-Frequency Interference) is present in the data of all three missions. On a global scale, the three sensors have observed approximately the same distribution of RFI. Japan is an important exception that has implications for the design of RFI detection algorithms. RFI in Japan is caused by a large number of emitters belonging to the same system (TV receivers) and for this reason some traditional RFI detection strategies detect little to no RFI over Japan. The study of this case has led to an improvement of the approach to detect RFI in Aquarius data.

Aquarius↗
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 NTRS2005

Impact of the Sun on Remote Sensing of Sea Surface Salinity from Space

The sun is a sufficiently strong source of radiation at L-band to be an important source of interference for radiometers on future satellite missions such as SMOS, Aquarius, and Hydros designed to monitor soil moisture and sea surface salinity. Radiation from the sun can impact passive remote sensing systems in several ways, including line-of-sight radiation that comes directly from the sun and enters through antenna side lobes and radiation that is reflected from the surface to the radiometer. Examples are presented in the case of Aquarius, a pushbroom radiometer with three beams designed to monitor sea surface salinity. Near solar minimum, solar contamination is not a problem unless the sun enters near the main beam. But near solar maximum, contamination from the sun equivalent to a change of salinity on the order of 0.1 psu can occur even when the signal enters in sidelobes far from the main beam.

COMPONENT REPORTS↗
NASA NTRS2007

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.

LeVine, David M.↗