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At least 73 records · Page 4
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NASA NTRS1988

Salinity stress inhibits bean leaf expansion by reducing turgor, not wall extensibility

Treatment of bean (Phaseolus vulgaris L.) seedlings with low levels of salinity (50 or 100 millimolar NaCl) decreased the rate of light-induced leaf cell expansion in the primary leaves over a 3 day period. This decrease could be due to a reduction in one or both of the primary cellular growth parameters: wall extensibility and cell turgor. Wall extensibility was assessed by the Instron technique. Salinity did not decrease extensibility and caused small increases relative to the controls after 72 hours. On the other hand, 50 millimolar NaCl caused a significant reduction in leaf bulk turgor at 24 hours; adaptive decreases in leaf osmotic potential (osmotic adjustment) were more than compensated by parallel decreases in xylem tension potential and the leaf apoplastic solute potential, resulting in a decreased leaf water potential. It is concluded that in bean seedlings, mild salinity initially affects leaf growth rate by a decrease in turgor rather than by a reduction in wall extensibility. Moreover, long-term salinization (10 days) resulted in an apparent mechanical adjustment, i.e. an increase in wall extensibility, which may help counteract reductions in turgor and maintain leaf growth rates.

NASA Discipline Number 40-10↗
NASA NTRS2011

Aquarius Instrument and Salinity Retrieval

Aquarius has been designed to map the surface salinity field of the global ocean from space a parameter important for understanding ocean circulation and its relationship to climate and the global water cycle. Salinity is measured remotely from space by measuring the thermal emission from the ocean surface. This is done at the low frequency end of the microwave spectrum (e.g. 1.4 GHz) where the emission is sufficiently sensitive to changes in salinity to be detected with sophisticated radiometers. The goal is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean by providing maps on a monthly basis with a spatial resolution of 150 km and an accuracy of 0.2 psu. These are challenging requirements that have led to some unique features of the instrument. These include: a) The addition of a co-located scatterometer to help provide a correction for roughness; b) The addition of a polarimetric channel (third Stokes parameter) to the radiometer to help correct for Faraday rotation; c) Asun-synchronous orbit with a 6 pm ascending equatorial crossing to minimize Faraday rotation and with the antennas looking away from the sun toward the nighttime side to minimize contamination by radiation from the sun; and d) An antenna designed to limit side lobes in the direction of rays from the sun. In addition, achieving the accuracy goal of 0.2 psu requires averaging over one month and to do this requires a highly stable radiometer. Aquarius has three separate radiometers that image in pushbroom fashion with the three antenna beams looking across track. The antenna is a 2.5-m diameter, offset parabolic reflector with three feed horns and the three beams are arranged to image with the boresight aligned to look across track, roughly perpendicular to the spacecraft heading and pointing away from the Sun. The three beams point at angles of theta = 25.8 deg., 33.8 deg. and 40.3 deg. with respect to the spacecraft nadir which correspond to local incidence angles at the surface of 28.7 deg., 37.8 deg. and 45.6 deg., respectively. The resolution of the three radiometer beams (axes of the 3dB ellipse) is: 76 x 94 km for the inner beam, 84 x 120 km for the middle beam to 96 x 156 km for the outer beam. Together they cover a swath of about 390 km. Aquarius will map the global ice-free ocean every 7-days from which monthly average composites will be derived. This will provide a snapshot of the mean field, as well as resolving the seasonal to interannual variations over the three-year baseline of the mission.

Le Vine, D. M.↗
NASA NTRS2012

Highlights of the First 15 Months of Aquarius Salinity Measurements

Aquarius satellite salinity measurements are resolving the major global and regional spatial patterns, and temporal variations, since the start of routine data collection on 25 August 2011. This description includes the principal seasonal variations over the first annual cycle as observed by the mission. In particular, we identify the evolution of low salinity anomalies associated with the Atlantic and Pacific intertropical convergence zones (ITCZ), major river outflows such as the Amazon, a seasonal low salinity anomaly in the Panama bight, and other features. We also explore the links that the salinity variations have with precipitation and surface currents. We then will describe the variations related to the presently evolving 2012 El Nino, now evident, as it progresses through the summer and fall 2012. We conclude with a brief summary of the Aquarius data products and validation

Lagerloef, Gary S. E.↗
NASA NTRS2011

Warm and Saline Events Embedded in the Meridional Circulation of the Northern North Atlantic

Ocean state estimates from 1958 to 2005 from the Simple Ocean Assimilation System (SODA) system are analyzed to understand circulation between subtropical and subpolar Atlantic and their connection with atmospheric forcing. This analysis shows three periods (1960s, around 1980, and 2000s) with enhanced warm, saline waters reaching high latitudes, alternating with freshwater events originating at high latitudes. It complements surface drifter and altimetry data showing the subtropical -subpolar exchange leading to a significant temperature and salinity increase in the northeast Atlantic after 2001. The warm water limb of the Atlantic meridional overturning cell represented by SODA expanded in density/salinity space during these warm events. Tracer simulations using SODA velocities also show decadal variation of the Gulf Stream waters reaching the subpolar gyre and Nordic seas. The negative phase of the North Atlantic Oscillation index, usually invoked in such variability, fails to predict the warming and salinization in the early 2000s, with salinities not seen since the 1960s. Wind stress curl variability provided a linkage to this subtropical/subpolar gyre exchange as illustrated using an idealized two ]layer circulation model. The ocean response to the modulation of the climatological wind stress curl pattern was found to be such that the northward penetration of subtropical tracers is enhanced when amplitude of the wind stress curl is weaker than normal. In this case both the subtropical and subpolar gyres weaken and the subpolar density surfaces relax; hence, the polar front moves westward, opening an enhanced northward access of the subtropical waters in the eastern boundary current.

Hakkinen, Sirpa↗
NASA NTRS2014

The Effect of Growth Environment and Salinity on Lipid Production and Composition of Salicornia virginica

Finding a viable and sustainable source of renewable energy is a global task. Biofuels as a renewable energy source can potentially be a viable option for sustaining long-term energy needs. Biodiesel from halophytes shows great promise due to their ability to serve not only as a fuel source, but a food source as well. Halophytes are one of the few biomass plant species that can tolerate a wide range of saline conditions. We investigate the feasibility of using the halophyte, Salicornia virginica as a biofuel source by conducting a series of experiments utilizing various growth and salinity conditions. The goal is to determine if the saline content of Salicornia virginica in our indoor growth vs outdoor growth conditions has an influence on lipid recovery and total biomass composition. We focused on using standard lipid extraction protocols and characterization methods to evaluate twelve Salicornia virginica samples under six saline values ranging from freshwater to seawater and two growth conditions. The overall goal is to develop an optimal lipid extraction protocol for Salicornia virginica and potentially apply this protocol to halophytes in general.

Bomani, Bilal Mark McDowell↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain Corrected Satellite Sea Surface Salinity Using the GMAO S2S Forecast System

During the past years, we have seen that the La Nina to El Nino transition has had a significant global socio-economic impact and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help to improve the initialization of the thermocline, while satellite Sea Surface Temperature (SST) aids in constraining surface heat-fluxes, leading to improved subseasonal to seasonal forecasts of the coupled system. However, few studies have focused on improving the fresh-water flux and near-surface density and mixing through assimilation of satellite sea surface salinity (SSS). For expediency, the few ocean models that do assimilate SSS bias-correct the satellite SSS data to normalize towards the near-surface Argo data. However, in rainy regions, where buoyant water sits as a fresh lens at the surface, this assumption is likely inadequate. In previous work, we have shown that adjusting SSS data to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 has improved the near-surface density and mixed layer depth, leading to deeper thermocline and improved the NINO3.4 SST forecasts. Now we utilize the Soil Moisture/Ocean Salinity, Rain Corrected (SMOS_RC) SSS product provided by the Centre Aval de Traitement des données SMOS (CATDS CPDC) to represent the Sb more accurately at first model layer (in our case 5 m). Rather than using a diffusivity model as with RIM, SMOS_RC relies on an observed relationship between the spatial heterogeneity of SMOS SSS and instantaneous rain rate (RR) (Supply et al., 2020). In order to test the impact of SMOS_RC versus SMOS, we compare two reanalyses over the period 2014 to 2021. For both reanalysis experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is (i.e., with the fresh bias), and a separate reanalysis is performed assimilating the SMOS_RC data. We assess the impact for near-surface and subsurface dynamics within ocean reanalyses by validating against observations and explore how SSS assimilation (SMOS versus SMOS_RC) impacts dynamical ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (GEOS S2S-3, Molod et al., 2020, Hackert et al., 2023). We will show that improved SSS estimates and near-surface density and mixing led to more accurate coupled air/sea interaction and better ENSO forecasts.

Eric Hackert↗
NASA NTRS2023

Soil Moisture and Sea Surface Salinity Derived from Satellite-Borne Sensors

The monitoring of soil moisture and sea surface salinity over the Earth has been profoundly enhanced during the last thirteen years owing to new generation of satellite sensors. L-band radiometry is currently the only technology providing direct measurements of soil moisture, insensitive to surface roughness and distribution of elements in the soil, and the only technology that allows to measure sea surface salinity from space. The SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active Passive) satellite missions resolve global and local variability with a spatial resolution of approximately 43 km, a swath width close to 1000 km, and a sampling time, for each mission, of at least twice every 3 days. These resolutions and samplings can be increased by either merging data from the two sensors, and with complementary informations gathered with other passive or active sensors, or with in situ information at higher spatial resolution. Numerous scientific studies based on the use of this new type of measurement have led to a better understanding and constraint of the processes governing the variability of the water cycle, ocean circulation and the Earth's climate. The continuity of measurements, and the increased spatial and radiometric resolution is critical for fulfilling scientific needs. Future L-band radiometry missions currently being planned in Europe (the Copernicus Imaging Microwave Radiometer), and in China (the Ocean Salinity Mission) should provide better constraint on auxiliary parameters by combining multiple frequencies, but they will not have improved spatial resolution beyond SMOS and SMAP. The temporal continuity with SMOS and SMAP will most likely not be ensured. In parallel, new concepts are being developed to increase spatial resolution of both land and ocean parameters.

J. Boutin↗
NASA NTRS2022

Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC

The 2020 ‘Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere’ (EUREC4A-OA) and the ‘Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign’ (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Kashawn Hall↗
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 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 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 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 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 NTRS1972

Estuarine turbidity, flushing, salinity, and circulation

The effects of estuarine turbidity, flushing, salinity, and circulation on the ecology of the Chesapeake Bay are discussed. The sources of fresh water, the variations in salinity, and the circulation patterns created by temperature and salinity changes are analyzed. The application of remote sensors for long term observation of water temperatures is described. The sources of sediment and the biological effects resulting from increased sediments and siltation are identified.

Pritchard, D. W.↗
NASA NTRS1979

Investigation of effects of temperature, salinity, and electrode design on the performance of an electrochemical coliform detector

The results of two research programs to determine the optimum detector design for measuring fecal coliforms in saline waters for operational systems are presented. One program was concerned with the effects of temperature and salinity on endpoint response time, and the other, the interaction between electrode configurations and the test organisms. Test results show that the endpoint response time is related to salinity and seawater temperature; however, these results can be minimized by the correct choice of growth media. Electrode configurations were developed from stainless steel, Parlodion-coated stainless steel, and platinum that circumvented problems associated with the commercial redox electrodes.

Grana, D. C.↗
NASA NTRS1982

Remote sensing of salinity in the San Francisco Bay Delta

Landsat multispectral scanner data and color and color infrared photographs acquired from a U-2 aircraft are combined with surface measurements for salinity mapping of the San Fransisco Bay Delta. A regression model is developed between the surface truth data and Landsat digital data for 29 sample sites, and is then extended over the entire study area. Results are in general agreement with reported salinity distribution values. It appears to be impossible to establish any quantitative judgement regarding the salinity values by visual interpretation of the imagery within the test site.

Khorram, S.↗
NASA NTRS1984

Recent progress in the measurement of temperature and salinity by optical scattering

Recent progress is described in the use of Brillouin and Raman scattering for the measurement of temperature and salinity in the ocean. The use of Brillouin scattering is described for the measurement of the sound velocity, and the use of Raman scattering is described for the independent measurement of the temperature and salinity. Coupling these techniques permits the assessment of both temperature and salinity. The experimental techniques are described together with the results of recent experiments and an assessment of the errors to be expected.

Collins, D. J.↗