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 ~0.1K 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 TEOS10 PSS78 conductivity-salinity relationship and on 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.
Earlier studies have pointed out systematic differences between sea surface salinity retrieved from L-band radiometric measurements and measured in situ , which depend on sea surface temperature ...(SST). We investigate how to cope with these differences given existing physically based radiative transfer models. In order to study differences coming from seawater dielectric constant parametrization, we consider the model of Somaraju and Trumpf (2006) (ST) which is built on sound physical bases and close to a single relaxation term Debye equation. While ST model uses fewer empirically adjusted parameters than other dielectric constant models currently used in salinity retrievals, ST dielectric constants are found close to those obtained using the Meissner and Wentz (2012) (MW) model. The ST parametrization is then slightly modified in order to achieve a better fit with seawater dielectric constant inferred from SMOS data. Upgraded dielectric constant model is intermediate between KS and MW models. Systematic differences between SMOS and in situ salinity are reduced to less than +/−0.2 above 0 °C and within +/−0.05 between 7 °C and 28 °C. Aquarius salinity becomes closer to in situ salinity, and within +/−0.1. The order of magnitude of remaining differences is very similar to the one achieved with the Aquarius version 5 empirical adjustment of wind model SST dependence. The upgraded parametrization is recommended for use in processing the SMOS data. Further assessment or improvement using new laboratory measurements should consider keeping the physics-based formulation by ST that has been shown here to be very efficient.
Active removal of Na⁺ from the cytosol into the vacuole plays a critical role in salinity tissue tolerance, but another, often neglected component of this trait is Na⁺ retention in vacuoles. This ...retention is based on an efficient control of Na⁺-permeable slow- and fast-vacuolar channels that mediate the back-leak of Na⁺ into cytosol and, if not regulated tightly, could result in a futile cycle. This Tansley insight summarizes our current knowledge of regulation of tonoplast Na⁺-permeable channels and discusses the energy cost of vacuolar Na⁺ sequestration, under different scenarios. We also report on a phylogenetic and bioinformatic analysis of the plant two-pore channel family and the difference in its structure and regulation between halophytes and glycophytes, in the context of salinity tolerance.
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 (<inline-formula> <tex-math notation="LaTeX">S </tex-math></inline-formula>) and temperature (<inline-formula> <tex-math notation="LaTeX">T </tex-math></inline-formula>). 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 <inline-formula> <tex-math notation="LaTeX">S </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">T </tex-math></inline-formula> to a physics-based model consisting of a Debye molecular resonance term plus a conductivity term. Each unknown parameter is expressed in <inline-formula> <tex-math notation="LaTeX">S </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">T </tex-math></inline-formula> 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.
Soil salinization is one of the most common land desertification processes that can be found worldwide. It is a certainly severe environment hazard and threatens the stability of ecosystems. As a ...rapid and inexpensive tool, remote sensing technology combining with the measurements of soil spectra has been widely concerned on identifying and mapping salt effect on lands. However, as effects of the soil moisture often immerge the effects of salt to soil reflectance spectra, soil moisture became a major factor to restrict soil salinity monitoring from soil reflectance. High soil moisture content will lead to failure on soil salinity estimation from soil reflectance data. In this paper, a semianalytical model using an exponent function was developed to estimate soil salt content (SSC) under different moisture levels based on a control laboratory experiment. And the root-mean-square error and mean relative error were 0.799 g/kg and 31.294%, respectively, when the model was applied to estimate SSCs by wet soil reflectance. To sum up, considering both effects of soil moisture and soil salt on soil reflectance, the semianalytical model reduced SSC estimated error. The approach presented in this paper provides a new way of estimating soil salinity from soil spectra under various soil moisture conditions, and it will be a potential application for large-scale SSC mapping.
The injection of carbon dioxide (COsub.2) is an essential technology for maximizing the potential of hydrocarbon reservoirs while reducing the impact of greenhouse gases. However, because of the ...complexity of this injection, there will be many different chemical reactions between the formation fluids and the rock minerals. This is related to the clay content of sandstone reservoirs, which are key storage targets. Clay content and clay types in sandstone can vary substantially, and the influence of these factors on reservoir-scale COsub.2-water-sandstone interactions has not been managed appropriately. Consequently, by simulating the process of COsub.2 injection in two different clay-content sandstones (i.e., high- and low-clay content), we investigated the effect of the sandstone clay concentration on COsub.2-water-sandstone interactions in this article. High clay content (Bandera Grey sandstone) and low clay content (Bandera Brown sandstone) were considered as potential storage reservoirs and their responses to COsub.2 injection were computationally assessed. Our results indicate that the mineralogical composition of the sandstone reservoir significantly varies as a result of COsub.2-water-sandstone interactions. Clearly, the high clay-content sandstone (Bandera Grey) had a higher maximum COsub.2 mineral-trapping capacity (6 kg COsub.2/msup.3 sandstone) than Bandera Brown Sandstone (low clay content), which had only 3.3 kg COsub.2/msup.3 sandstone mineral-storage capacity after 400 years of storage. Interestingly, pH was decreased by ~3 in Bandera Grey sandstone and by ~2.5 in Bandera Brown sandstone. Furthermore, porosity increased in Bandera Grey sandstone (by +5.6%), more than in Bandera Brown Sandstone (+4.4%) after a 400-year storage period. Overall, we concluded that high clay-content sandstone shows more potential for COsub.2 mineral-trapping.
The Soil Moisture and Ocean Salinity (SMOS) mission has provided a unique remote sensing capability for observing key variables of the hydrological cycle, such as the Sea Surface Salinity (SSS). ...However, due to some limitations related to the instrument interferometric concept and its challenging data processing, SMOS SSS maps still display significant artifacts and biases, especially close to the coast, mainly due to the presence of Radio Frequency Interferences (RFI) and Land-sea contamination (LSC). In this paper, a new methodology for filtering salinity retrievals and correcting for spatial biases is introduced and validated.
•Presentation of a new methodology for SMOS SSS retrieval•Mitigation of the Land-Sea Contamination•Computation of SMOS SSS in regions affected by Radio Frequencies Interference (RFI)•SMOS SSS retrieval in the Mediterranean Sea, Arctic Ocean and Antarctic Ocean
Plant growth promoting rhizobacteria (PGPR) hold promising future for sustainable agriculture. Here, we demonstrate a carotenoid producing halotolerant PGPR Dietzia natronolimnaea STR1 protecting ...wheat plants from salt stress by modulating the transcriptional machinery responsible for salinity tolerance in plants. The expression studies confirmed the involvement of ABA-signalling cascade, as TaABARE and TaOPR1 were upregulated in PGPR inoculated plants leading to induction of TaMYB and TaWRKY expression followed by stimulation of expression of a plethora of stress related genes. Enhanced expression of TaST, a salt stress-induced gene, associated with promoting salinity tolerance was observed in PGPR inoculated plants in comparison to uninoculated control plants. Expression of SOS pathway related genes (SOS1 and SOS4) was modulated in PGPR-applied wheat shoots and root systems. Tissue-specific responses of ion transporters TaNHX1, TaHAK, and TaHKT1, were observed in PGPR-inoculated plants. The enhanced gene expression of various antioxidant enzymes such as APX, MnSOD, CAT, POD, GPX and GR and higher proline content in PGPR-inoculated wheat plants contributed to increased tolerance to salinity stress. Overall, these results indicate that halotolerant PGPR-mediated salinity tolerance is a complex phenomenon that involves modulation of ABA-signalling, SOS pathway, ion transporters and antioxidant machinery.
Sea surface salinity (SSS) can be measured by L-band (1.4 GHz) radiometry. However, the L-band brightness temperature is sensitive to ocean surface roughness, so that the precise knowledge of sea ...state can help to improve the accuracy of SSS retrievals. Cyclone Global Navigation Satellite System (CyGNSS) mission measures tropical ocean wind speeds, which can provide further knowledge about sea state. This letter, by investigating the sensitivity of brightness temperature derived from two L-band radiometry satellite missions i.e., Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) to CyGNSS data, first explores the potential of using spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) to improve the accuracy of SSS measurements. The statistical results from two-year CyGNSS data show that the systematic uncertainties of the brightness temperature up to 0.5 K in the SMOS/SMAP can be minimized at low wind speed, which proves the concept that CyGNSS wind speed data can be used to improve the accuracy of SSS retrievals across the oceans. The findings strongly suggest that the spaceborne GNSS-R instruments could be utilized as cost-effective hosted payloads in designing future ocean remote sensing missions.
Producing sufficient food for nine billion people by 2050 will be constrained by soil salinity, especially in irrigated systems. To improve crop yield, greater understanding of the genetic control of ...traits contributing to salinity tolerance in the field is needed. Here, we exploit natural variation in exotic germplasm by taking a genome-wide association approach to a new nested association mapping population of barley called HEB-25. The large population (1,336 genotypes) allowed cross-validation of loci, which, along with two years of phenotypic data collected from plants irrigated with fresh and saline water, improved statistical power. We dissect the genetic architecture of flowering time under high salinity and we present genes putatively affecting this trait and salinity tolerance. In addition, we identify a locus on chromosome 2H where, under saline conditions, lines homozygous for the wild allele yielded 30% more than did lines homozygous for the Barke allele. Introgressing this wild allele into elite cultivars could markedly improve yield under saline conditions.
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