Evolution of the 2011 Mississippi River Peak Flood Plume from Coincident Satellite and Airborne L-band Radiometer Surface Salinity Observations.

NASA Astrophysics Data System (ADS)

Burrage, D. M.; Wesson, J. C.; Hwang, P. A.; Wang, D. W.; Wijesekera, H. W.

2016-02-01

Airborne mapping of Sea Surface Salinity (SSS) with L-band radiometers has been practiced for 20 yrs., while global satellite observations began with the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) Satellite launch in 2009. Airborne data with high ( 1km) resolution, but limited coverage, complement the lower resolution ( 35 km at nadir) but global coverage and 3-5 day revisit of SMOS. The record June, 2011 Mississippi R. peak flood, with flows exceeding 42,500 m^3/s, required diversions into Lake Pontchartrain and the Atchafalaya R. to avoid flooding New Orleans and Baton Rouge. The resulting merged outflows formed a single freshwater plume that spanned the Mississippi, Louisiana and Texas `Gulf Coast', and reached up to 300 km across the shelf. SSS was mapped by the NRL airborne Salinity Temperature and Roughness Remote Scanner (STARRS) and SMOS radiometers during a two week (2-13 June 2011) campaign immediately following the flood crest. STARRS obtained oblique across-shelf transects spanning the Northern Gulf of Mexico, under-flying SMOS, and shorter zig-zag coastal transects. SSS samples from a ship near the shelf edge agreed well with STARRS and SMOS after applying standard geophysical correction models and roughness corrections from an SSA/SPM E-M model and an advanced wave spectrum. The minimum SMOS footprint size (35 km at nadir), produced a coastal data gap filled by STARRS transects that reached the coast. The 200 km overlap between the two sensors along coincident ground tracks agreed closely near the frontal boundary, with salinity contrasts of 7-15 psu over a 10 km span at the plume edge evident in both data sets. Successive SMOS Level 2 (L2) SSS data swaths obtained at 2-5 day intervals showed the evolution of the plume in three well-separated seaward extensions located near the Mississippi Delta, and well east and west of the Delta. The dispersal of the plume was also detected by SMOS following the airborne campaign.

The Impact of Dielectric Constant Model and Surface Reference on Differences Between SMOS and Aquarius Sea Surface Salinity

NASA Technical Reports Server (NTRS)

Dinnat, E. P.; Boutin, J.; Yin, X.; LeVine, D. M.

2014-01-01

Two ongoing space missions share the scientific objective of mapping the global Sea Surface Salinity (SSS), yet their observations show significant discrepancies. ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Figure 1 is an example of the difference between the SSS retrieved by SMOS and Aquarius averaged over one month and 1 degree in longitude and latitude. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and retrieval algorithm used by both mission on these differences.

Tropical Pacific sea surface salinity variability derived from SMOS data: Comparison with in-situ observations.

NASA Astrophysics Data System (ADS)

Ballabrera, Joaquim; Hoareau, Nina; Umbert, Marta; Martínez, Justino; Turiel, Antonio

2013-04-01

Prediction of El Niño/Southern Oscillation (ENSO), and its relation with global climate anomalies, continues to be an important research effort in short-term climate forecasting. This task has become even more challenging as researchers are becoming more and more convinced that there is not a single archetypical El Niño (or La Niña) pattern, but several. During some events (called now Standard or East Pacific), the largest temperature anomalies are located at the eastern part of the Pacific. However, during some of the most recent events, the largest anomalies are restricted to the central part of the Pacific Ocean, and are now called Central Pacific or Modoki (a Japanese word for "almost") events. Although the role of salinity in operational ENSO forecasting was initially neglected (in contrast with temperature, sea level, or surface winds), recent studies have shown that salinity does play a role in the preconditioning of ENSO. Moreover, some researchers suggest that sea surface salinity might play a role (through the modulation of the western Pacific barrier layer) to favor the Standard or the Modoki nature of each event. Sea Surface Salinity maps are being operationally generated from microwave (L-band, 1.4 Ghz) brightness temperature maps. The L-band frequency was chosen because is the optimal one for ocean salinity measurements. However, after three years of satellite data, it has been found that noise in brightness temperatures (due to natural and artificial sources) is larger than expected. Moreover, the retrieval of SSS information requires special care because of the low sensitivity of the brightness temperature to SSS: from 0.2-0.8 K per salinity unit. Despite of all these facts, current accuracy of SS maps ranges from 0.2-0.4, depending on the processing level and the region being considered. We present here our study about the salinity variability in the tropical Pacific Ocean from the 9-day, 0.25 bins salinity maps derived from the SMOS

Understanding the Dynamics of the South Indian Ocean Sea Surface Salinity Maximum Pool From Argo, Rama, Aquarius, SMOS & Other Satellites

NASA Astrophysics Data System (ADS)

Menezes, V. V.; Phillips, H. E.

2016-02-01

Subtropical salinity maximum regions are particularly important because the salty subtropical underwater (STW) is formed by subduction of surface waters in these areas. In all oceans, the STW is transported equatorward from the formation region and are tightly related to the Subtropical-Tropical Cell. In the South Indian Ocean (SIO), the salinity maximum pool is further poleward (25S-38S) and eastward (60E-120E). It significantly impacts the circulation of the eastern basin, because the STW forms a strong haline front with the fresh Indonesian Throughflow waters. This haline front overwhelms the temperature contribution establishing the eastward Eastern Gyral Current, an important upstream source for the Leeuwin Current. In the present work, we analyze the variability of the SSS maximum pool using Aquarius and SMOS satellites, an Argo gridded product and the RAMA mooring located at 25S-100E. OAFLUX, 3B42 TRMM, Ascat/Quikscat winds and OSCAR products complement this study. The salinity maximum pool has a strong seasonal cycle of contraction (min in Oct) and expansion (max in April), and most of this variation occurs in the pool poleward side. Advection and entrainment control the contraction, while expansion is due to atmospheric forcing (E-P). From 2004 to 2014, a clear reduction in the pool area is identified, which might be related to a decadal variability. In this case, the variation is in the equatorward side of the pool. Processes controlling this long-term variability are being investigated.

Statistical characterization of global Sea Surface Salinity for SMOS level 3 and 4 products

NASA Astrophysics Data System (ADS)

Gourrion, J.; Aretxabaleta, A. L.; Ballabrera, J.; Mourre, B.

2009-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency will soon provide sea surface salinity (SSS) estimates to the scientific community. Because of the numerous geophysical contamination sources and the instrument complexity, the salinity products will have a low signal to noise ratio at level 2 (individual estimates??) that is expected to increase up to mission requirements (0.1 psu) at level 3 (global maps with regular distribution) after spatio-temporal accumulation of the observations. Geostatistical methods such as Optimal Interpolation are being implemented at the level 3/4 production centers to operate this noise reduction step. The methodologies require auxiliary information about SSS statistics that, under Gaussian assumption, consist in the mean field and the covariance of the departures from it. The present study is a contribution to the definition of the best estimates for mean field and covariances to be used in the near-future SMOS level 3 and 4 products. We use complementary information from sparse in-situ observations and imperfect outputs from state-of-art model simulations. Various estimates of the mean field are compared. An alternative is the use of a SSS climatology such as the one provided by the World Ocean Atlas 2005. An historical SSS dataset from the World Ocean Database 2005 is reanalyzed and combined with the recent global observations obtained by the Array for Real-Time Geostrophic Oceanography (ARGO). Regional tendencies in the long-term temporal evolution of the near-surface ocean salinity are evident, suggesting that the use of a SSS climatology to describe the current mean field may introduce biases of magnitude similar to the precision goal. Consequently, a recent SSS dataset may be preferred to define the mean field needed for SMOS level 3 and 4 production. The in-situ observation network allows a global mapping of the low frequency component of the variability, i.e. decadal, interannual and seasonal

SSS variability inferred from recent SMOS reprocessing at CATDS

NASA Astrophysics Data System (ADS)

Boutin, Jacqueline; Vergely, Jean-Luc; Marchand, Stéphane; Tarot, Stéphane; Hasson, Audrey; Reverdin, Gilles

2017-04-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission has monitored sea surface salinity (SSS) over the global ocean for over 7 years. In this poster, we present results obtained at the LOCEAN/ACRI-st expertise center using recent CATDS (Centre Aval de Traitement des Données) SMOS RE05 reprocessing., We find that correction for systematic errors and removal of data contaminated by ice and radio frequency interferences in fresh regions (river mouths, high latitudes) has been improved with respect to SMOS CATDS RE04 reprocessing. We analyze SSS variability as observed by SMOS on a wide range of spatial and temporal scales using various statistical indicators such as mean, median, standard deviation, minimum, maximum values and spectral analysis. We compare them with ARGO interpolated fields (In Situ Analysis System fields) at global scale and with ship SSS transects from the GOSUD and ORE SSS data base. This allows us 1) to demonstrate and quantify the improvement of SMOS SSS fields with respect to earlier versions and 2) to study SSS variability, especially at spatial scales between 50km and 600km not well covered globally by in situ network. The complementarity of this information with respect to SMAP (Soil Moisture Active Passive) SSS fields will be discussed.

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets

USDA-ARS?s Scientific Manuscript database

Two satellites are currently monitoring surface soil moisture (SM) from L-band observations: SMOS (Soil Moisture and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration...

Aquarius and SMOS detect effects of an extreme Mississippi River flooding event in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Gierach, Michelle M.; Vazquez-Cuervo, Jorge; Lee, Tong; Tsontos, Vardis M.

2013-10-01

surface salinity (SSS) measurements from the Aquarius/Satélite de Aplicaciones Científicas (SAC)-D satellite and Soil Moisture and Ocean Salinity (SMOS) mission were used to document the freshening associated with the record 2011 Mississippi River flooding event in the Gulf of Mexico (GoM). Assessment of the salinity response was aided by additional satellite observations, including chlorophyll-a (chl-a) and ocean surface currents, and a passive tracer simulation. Low SSS values associated with the spreading of the river plume were observed 1-3 months after peak river discharge which then receded and became unidentifiable from satellite observations 5 months after maximum discharge. The seasonal wind pattern and general circulation of the GoM dramatically impacted the observed salinity response, transporting freshwater eastward along the Gulf coast and entraining low salinity waters into the open GoM. The observed salinity response from Aquarius was consistent with SMOS SSS, chl-a concentrations, and the passive tracer simulation in terms of the pathway and transit time of the river plume spreading. This study is the first successful application of satellite SSS to study salinity variation in marginal seas.

ESAC RFI Survey in the SMOS 1400-1427MHz Passive Band

NASA Astrophysics Data System (ADS)

Castillo-Fraile, Manuel; Uranga, Ekhi

2016-08-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was launched on 2 November 2009, and it is the ESA second Earth Explorer Opportunity mission. After 6 years of successful Operations, the status of the SMOS mission is excellent, and it is providing very reliable acquisition, nominal and NRT data processing, archiving, and dissemination services of Level 1 and Level 2 processed data around the entire Planet. However, SMOS observations are significantly affected by RF interferences in several World areas. In this context, a new RFI detection and monitoring tool has been implemented at ESAC to provide to the national radiofrequency authorities with a proper detection and localization method of the illegal ground emitters in order to ensure the protection of the SMOS 1400- 1427MHz Passive Band for scientific applications.

SMOS soil moisture validation with U.S. in situ newworks

USDA-ARS?s Scientific Manuscript database

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor u...

Inter-Comparison of SMOS and Aquarius Sea Surface Salinity: Effects of the Dielectric Constant and Vicarious Calibration

NASA Technical Reports Server (NTRS)

Dinnat, Emmanuel P.; Boutin, Jacqueline; Yin, Xiaobin; Le Vine, David M.

2014-01-01

Two spaceborne instruments share the scientific objective of mapping the global Sea Surface Salinity (SSS). ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometry to retrieve SSS. We find that SSS retrieved by SMOS is generally lower than SSS retrieved by Aquarius, except for very cold waters where SMOS SSS is higher overall. The spatial distribution of the differences in SSS is similar to the distribution of sea surface temperature. There are several differences in the retrieval algorithm that could explain the observed SSS differences. We assess the impact of the dielectric constant model and the ancillary sea surface salinity used by both missions for calibrating the radiometers and retrieving SSS. The differences in dielectric constant model produce differences in SSS of the order of 0.3 psu and exhibit a dependence on latitude and temperature. We use comparisons with the Argo in situ data to assess the performances of the model in various regions of the globe. Finally, the differences in the ancillary sea surface salinity products used to perform the vicarious calibration of both instruments are relatively small (0.1 psu), but not negligible considering the requirements for spaceborne remote sensing of SSS.

Sea Surface Salinity : Research Challenges and Opportunities

NASA Technical Reports Server (NTRS)

Halpern, David; Lagerloef, Gary; Font, Jordi

2012-01-01

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.

An approach to constructing a homogeneous time series of soil mositure using SMOS

USDA-ARS?s Scientific Manuscript database

Overlapping soil moisture time series derived from two satellite microwave radiometers (SMOS, Soil Moisture and Ocean Salinity; AMSR-E, Advanced Microwave Scanning Radiometer - Earth Observing System) are used to generate a soil moisture time series from 2003 to 2010. Two statistical methodologies f...

Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. The commissioning phase ended in May 2010. Subsequently, the satellite has been in operation for over 5 years while the retrieval algorithms from Level 1 to Level 2 underw...

SMOS L1C and L2 Validation in Australia

NASA Technical Reports Server (NTRS)

Rudiger, Christoph; Walker, Jeffrey P.; Kerr, Yann H.; Mialon, Arnaud; Merlin, Olivier; Kim, Edward J.

2012-01-01

Extensive airborne field campaigns (Australian Airborne Cal/val Experiments for SMOS - AACES) were undertaken during the 2010 summer and winter seasons of the southern hemisphere. The purpose of those campaigns was the validation of the Level 1c (brightness temperature) and Level 2 (soil moisture) products of the ESA-led Soil Moisture and Ocean Salinity (SMOS) mission. As SMOS is the first satellite to globally map L-band (1.4GHz) emissions from the Earth?s surface, and the first 2-dimensional interferometric microwave radiometer used for Earth observation, large scale and long-term validation campaigns have been conducted world-wide, of which AACES is the most extensive. AACES combined large scale medium-resolution airborne L-band and spectral observations, along with high-resolution in-situ measurements of soil moisture across a 50,000km2 area of the Murrumbidgee River catchment, located in south-eastern Australia. This paper presents a qualitative assessment of the SMOS brightness temperature and soil moisture products.

Fibre optics in the SMOS mission

NASA Astrophysics Data System (ADS)

Kudielka, K.; Benito-Hernández, F. J.; Rits, W.; Martin-Neira, M.

2017-11-01

Launched on November 2nd, 2009, SMOS (Soil Moisture, Ocean Salinity) is the second Earth Explorer Opportunity mission developed as part of ESA's Living Planet Programme. It demonstrates a completely new type of instrument - a large, deployable synthetic-aperture microwave radiometer [1]. RUAG Space, Switzerland, as a subcontractor of EADS Astrium, Spain, has provided the instrument's fibreoptic harness, which interconnects the central data processor with all 69 microwave receivers, as well as 12 auxiliary units on board. For reasons explained in Section 3, SMOS is the first European mission extensively using both fibre-optic clock distribution and data transmission in space. In Section 2, we present an overview of the scientific goals of SMOS, and describe the payload's basic function. There from we derive the rationale and the design of the fibre-optic harness (Section 3). In Section 4 all development, manufacturing, and test activities are summarised, which culminated in the successful delivery of all flight units to EADS Astrium by October 2006. We present the major test results obtained with the flight harness (Section 5), and conclude with a short summary of the higher-level activities, which lead to successful launch and commissioning of the SMOS satellite (Section 6).

Satellite surface salinity maps to determine fresh water fluxes in the Arctic Ocean

NASA Astrophysics Data System (ADS)

Gabarro, Carolina; Estrella, Olmedo; Emelianov, Mikhail; Ballabrera, Joaquim; Turiel, Antonio

2017-04-01

Salinity and temperature gradients drive the thermohaline circulation of the oceans, and play a key role in the ocean-atmosphere coupling. The strong and direct interactions between the ocean and the cryosphere (primarily through sea ice and ice shelves) are also a key ingredient of the thermohaline circulation. Recent observational studies have documented changes in upper Arctic Ocean hydrography [1, 2]. The ESA's Soil Moisture and Ocean Salinity (SMOS) mission, launched in 2009, have the objective to measure soil moisture over the continents and sea surface salinity over the oceans [3]. However, SMOS is also making inroads in Cryospheric science, as the measurements of thin ice thickness and sea ice concentration. SMOS carries an innovative L-band (1.4 GHz, or 21-cm wavelength), passive interferometric radiometer (the so-called MIRAS) that measures the electromagnetic radiation emitted by the Earth's surface, at about 50 km spatial resolution wide swath (1200-km), and with a 3-day revisit time at the equator, but more frequently at the poles. Although the SMOS radiometer operating frequency offers almost the maximum sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) variations, such sensitivity is rather low, even lower at cold waters [4]: 90% of ocean SSS values span a range of brightness temperatures of just 5K. This implies that the SMOS SSS retrieval requires a high performance of the MIRAS interferometric radiometer [5]. New algorithms, recently developed at the Barcelona Expert Center (BEC) to improve the quality of SMOS measurements [6], allow for the first time to derive cold-water SSS maps from SMOS data, and to observe the variability of the SSS in the higher north Atlantic and the Arctic Ocean. In this work, we will provide an assessment of the quality of these new SSS Arctic maps, and we will illustrate their potential to monitor the impact on ocean state of the discharges from the main rivers to the Arctic Ocean. Moreover

Implementation of SMOS data monitoring in the Integrated Forecast System. Preliminary results.

NASA Astrophysics Data System (ADS)

Muñoz Sabater, Joaquin; de Rosnay, Patricia; Drusch, Mathias; Dahoui, Mohamed; Delwart, Steven; Wright, Norrie

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA) was successfully launched on November 2nd 2009. Using a novel concept based on the Synthetic Aperture Radar technique, it is expected that SMOS observations will provide global accurate maps of brightness temperatures (TB) and soil moisture at L-band every 3 days and at 50 km ground-spatial resolution. Thus, SMOS data will soon provide a valuable input for numerical weather prediction (NWP), hydrological and land surface systems, among others. Operational numerical weather forecast systems are widely used to evaluate and analyse new types of satellite observations. NWP centres use these observations in their analyses to derive level 2 retrieved geophysical parameters (e.g. soil moisture and ocean salinity for SMOS) from the observed radiances. The European Centre for Medium Range Weather Forecasts is monitoring the first flow of SMOS level 1C TB over sea and land. Monitoring, i.e. the systematic comparison between observations and the corresponding model parameters, is a mandatory step prior to data assimilation. Consequently, monitoring provides an overall quality assessment of SMOS data based on departures values between SMOS observations and the modelled equivalent in the observation space. This is a significant contribution to the calibration / validation activities during the SMOS commissioning phase. Any systematic error or spikes in the data become visible and can be reported to ESA and the other calibration and validation teams without significant delays. Furthermore, the monitored data at global scale will help to calibrate the SMOS instrument at key decision points during the commissioning phase. In this paper the first SMOS data over land is monitored. Special emphasis is given to the effect of different parametrisations and auxiliary data sets on the simulated TB. This is a first step towards the assimilation of SMOS TB to improve the initialization of soil moisture

The SWEX at the area of Eastern Poland: Comparison of soil moisture obtained from ground measurements and SMOS satellite data*

NASA Astrophysics Data System (ADS)

Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.

2012-04-01

Soil moisture, together with soil and vegetation characteristics, plays an important role in exchange of water and energy between the land surface and the atmospheric boundary layer. Accurate knowledge of current and future spatial and temporal variation in soil moisture is not well known, nor easy to measure or predict. Knowledge of soil moisture in surface and root zone soil moisture is critical for achieving sustainable land and water management. The importance of SM is so high that this ECV is recommended by GCOS (Global Climate Observing System) to any attempts of evaluating of effects the climate change, and therefore it is one of the goals for observing the Earth by the ESA SMOS Mission (Soil Moisture and Ocean Salinity), globally. SMOS provides its observations by means of the interferometric radiometry method (1.4 GHz) from the orbit. In parallel, ten ground based stations are kept by IA PAN, in area of the Eastern Wall in Poland, in order to validate SMOS data and for other ground based agrophysical purposes. Soil moisture measurements obtained from ground and satellite measurements from SMOS were compared using Bland-Altman method of agreement, concordance correlation coefficient (CCC) and total deviation index (TDI). Observed similar changes in soil moisture, but the values obtained from satellite measurements were lower. Minor differences between the compared data are at higher moisture contents of soil and they grow with decreasing soil moisture. Soil moisture trends are maintained in the individual stations. Such distributions of soil moisture were mainly related to soil type. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

The Ups and Downs of Measuring Sea Surface Salinity from Space

NASA Astrophysics Data System (ADS)

Banks, C. J.; Gommenginger, C. P.; Srokosz, M. A.; Snaith, H. M.

2012-12-01

In November 2009, the European Space Agency (ESA) launched the Soil Moisture and Ocean Salinity (SMOS) satellite and a new era of satellite oceanography began vastly improving our ability to synoptically measure sea surface salinity (SSS). SMOS was joined in June 2011 by the NASA/Argentine Aquarius/SAC-D mission designed specifically to measure SSS. Although there are significant differences in how both satellites retrieve SSS, both utilise passive systems to measure the response of the brightness temperature (Tb) at L-band (1.4 GHz). We report on-going investigations into the validation of SMOS and Aquarius 'Level 3' measurements of SSS using monthly data on a 1° by 1° global grid between 60°S and 60°N. Previous studies have indicated significant temporally varying differences between SSS from SMOS ascending passes and from SMOS descending passes: therefore, for both SMOS and Aquarius, data from ascending and descending passes will be studied separately. Both satellites have sun-synchronous orbits but the direction of travel for the two satellites are twelve hours out of phase (i.e. at approximately 6 a.m. local time SMOS is travelling south-to-north (ascending) and Aquarius is travelling north-to-south (descending) whereas at 6 p.m. the directions of travel are switched). For validation purposes two separate monthly, 1° by 1° datasets are used over the same locations as the satellite data. The first is based on averaged near-surface salinity (depth less than 10 m) as derived from the drifting Argo float programme. The second validation data source is output from the UK Met Office Forecasting Ocean Assimilation Model (FOAM) based on NEMO (Nucleus for European Modelling of the Ocean). The SMOS Level 3 products are developed from ESA Level 2 products after quality control (QC) based on flags and SSS error provided in the ESA Level 2 products. Aquarius data (QC) is based only on data flags and a simple selection of in-range SSS values ([30, 40]). The study is

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.

2011-01-01

The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

SMOS Measurements Preliminary Validation: Objectives and Approach

NASA Astrophysics Data System (ADS)

Sabia, Roberto; Gourrion, Jerome; Gabarró, Carolina; Talone, Marco; Portabella, Marcos; Ballabrera, Joaquim; Lopez de Aretxabaleta, Alfredo; Camps, Adriano; Monerris, Alessandra; Font, Jordi

2010-05-01

The Earth Explorer Soil Moisture and Ocean Salinity (SMOS) mission was successfully launched on November 2nd, 2009, in the framework of the European Space Agency Living Planet programme. It will provide long-awaited remotely-sensed Sea Surface Salinity (SSS) maps over the oceans with a 3-day revisiting time [1]. The SMOS Barcelona Expert Centre (SMOS-BEC) in Barcelona, Spain, will be involved in several activities at different levels of the salinity retrieval processing chain, which are classified according to the objectives/issues being addressed. In particular, those described hereafter refer to the validation of the products and the consolidation/improvement of the salinity retrieval procedure itself [2]. This will be carried out by performing specific comparisons against modelled brightness temperatures (TB) or external salinity data sources. Due to start at the beginning of the Commissioning Phase, the post-launch 6-month checkout and calibration period, these studies will continue through the nominal satellite operation phase. They will support the choice of an optimal data selection strategy in regard to the existing trade-off, for instance the Ascending/Descending tracks selection, the AF-FOV/EAF-FOV (Alias-Free Field Of View/Extended Alias-Free Field Of View) selection, and some possible across-track data filtering. Moreover, they will help in the definition of an optimal processing configuration (separated polarization retrieval versus first Stokes parameter retrieval). Concerning the TB, the approach is to perform inter-comparisons of the TB departures (SMOS TB minus modelled TB, assuming knowledge of auxiliary information and proper TB direct modelling). The TB departures statistics analysis will be performed at both Antenna and Earth-surface levels. In order to obtain the latter product, a surface TB module is being derived taking into account the various TB perturbing sources. The comparison with forward-modelled TB will help to devise an optimum

SMOS data and extreme events

NASA Astrophysics Data System (ADS)

Kerr, Yann; Wigneron, Jean-Pierre; Ferrazzoli, Paolo; Mahmoodi, Ali; Al-Yaari, Amen; Parrens, Marie; Bitar, Ahmad Al; Rodriguez-Fernandez, Nemesio; Bircher, Simone; Molero-rodenas, Beatriz; Drusch, Matthias; Mecklenburg, Susanne

2017-04-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3), vegetation water content over land, and ocean salinity. These geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches, and in particular in improving model forecasts. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. The whole data set has been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets

The salinity signature of the cross-shelf exchanges in the Southwestern Atlantic Ocean: Satellite observations.

PubMed

Guerrero, Raul A; Piola, Alberto R; Fenco, Harold; Matano, Ricardo P; Combes, Vincent; Chao, Yi; James, Corinne; Palma, Elbio D; Saraceno, Martin; Strub, P Ted

2014-11-01

Satellite-derived sea surface salinity (SSS) data from Aquarius and SMOS are used to study the shelf-open ocean exchanges in the western South Atlantic near 35°S. Away from the tropics, these exchanges cause the largest SSS variability throughout the South Atlantic. The data reveal a well-defined seasonal pattern of SSS during the analyzed period and of the location of the export of low-salinity shelf waters. In spring and summer, low-salinity waters over the shelf expand offshore and are transferred to the open ocean primarily southeast of the river mouth (from 36°S to 37°30'S). In contrast, in fall and winter, low-salinity waters extend along a coastal plume and the export path to the open ocean distributes along the offshore edge of the plume. The strong seasonal SSS pattern is modulated by the seasonality of the along-shelf component of the wind stress over the shelf. However, the combined analysis of SSS, satellite-derived sea surface elevation and surface velocity data suggest that the precise location of the export of shelf waters depends on offshore circulation patterns, such as the location of the Brazil Malvinas Confluence and mesoscale eddies and meanders of the Brazil Current. The satellite data indicate that in summer, mixtures of low-salinity shelf waters are swiftly driven toward the ocean interior along the axis of the Brazil/Malvinas Confluence. In winter, episodic wind reversals force the low-salinity coastal plume offshore where they mix with tropical waters within the Brazil Current and create a warmer variety of low-salinity waters in the open ocean. Satellite salinity sensors capture low-salinity detrainment events from shelves SW Atlantic low-salinity detrainments cause highest basin-scale variability In summer low-salinity detrainments cause extended low-salinity anomalies.

The salinity signature of the cross-shelf exchanges in the Southwestern Atlantic Ocean: Satellite observations

PubMed Central

Guerrero, Raul A; Piola, Alberto R; Fenco, Harold; Matano, Ricardo P; Combes, Vincent; Chao, Yi; James, Corinne; Palma, Elbio D; Saraceno, Martin; Strub, P Ted

2014-01-01

Satellite-derived sea surface salinity (SSS) data from Aquarius and SMOS are used to study the shelf-open ocean exchanges in the western South Atlantic near 35°S. Away from the tropics, these exchanges cause the largest SSS variability throughout the South Atlantic. The data reveal a well-defined seasonal pattern of SSS during the analyzed period and of the location of the export of low-salinity shelf waters. In spring and summer, low-salinity waters over the shelf expand offshore and are transferred to the open ocean primarily southeast of the river mouth (from 36°S to 37°30′S). In contrast, in fall and winter, low-salinity waters extend along a coastal plume and the export path to the open ocean distributes along the offshore edge of the plume. The strong seasonal SSS pattern is modulated by the seasonality of the along-shelf component of the wind stress over the shelf. However, the combined analysis of SSS, satellite-derived sea surface elevation and surface velocity data suggest that the precise location of the export of shelf waters depends on offshore circulation patterns, such as the location of the Brazil Malvinas Confluence and mesoscale eddies and meanders of the Brazil Current. The satellite data indicate that in summer, mixtures of low-salinity shelf waters are swiftly driven toward the ocean interior along the axis of the Brazil/Malvinas Confluence. In winter, episodic wind reversals force the low-salinity coastal plume offshore where they mix with tropical waters within the Brazil Current and create a warmer variety of low-salinity waters in the open ocean. Key Points Satellite salinity sensors capture low-salinity detrainment events from shelves SW Atlantic low-salinity detrainments cause highest basin-scale variability In summer low-salinity detrainments cause extended low-salinity anomalies PMID:26213672

Analyzing the 2010-2011 La Niña signature in the tropical Pacific sea surface salinity using in situ data, SMOS observations, and a numerical simulation

NASA Astrophysics Data System (ADS)

Hasson, Audrey; Delcroix, Thierry; Boutin, Jacqueline; Dussin, Raphael; Ballabrera-Poy, Joaquim

2014-06-01

The tropical Pacific Ocean remained in a La Niña phase from mid-2010 to mid-2012. In this study, the 2010-2011 near-surface salinity signature of ENSO (El Niño-Southern Oscillation) is described and analyzed using a combination of numerical model output, in situ data, and SMOS satellite salinity products. Comparisons of all salinity products show a good agreement between them, with a RMS error of 0.2-0.3 between the thermosalinograph (TSG) and SMOS data and between the TSG and model data. The last 6 months of 2010 are characterized by an unusually strong tripolar anomaly captured by the three salinity products in the western half of the tropical Pacific. A positive SSS anomaly sits north of 10°S (>0.5), a negative tilted anomaly lies between 10°S and 20°S and a positive one south of 20°S. In 2011, anomalies shift south and amplify up to 0.8, except for the one south of 20°S. Equatorial SSS changes are mainly the result of anomalous zonal advection, resulting in negative anomalies during El Niño (early 2010), and positive ones thereafter during La Niña. The mean seasonal and interannual poleward drift exports those anomalies toward the south in the southern hemisphere, resulting in the aforementioned tripolar anomaly. The vertical salinity flux at the bottom of the mixed layer tends to resist the surface salinity changes. The observed basin-scale La Niña SSS signal is then compared with the historical 1998-1999 La Niña event using both observations and modeling.

Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2018-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm3 cm−3. These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve. PMID:29367795

Validation/Calibration of SMOS L2 Soil Moisture in Crop Area, Eastern China

NASA Astrophysics Data System (ADS)

Cui, Huizhen; Jiang, Lingmei; Yang, Na; Lu, Zheng

2016-08-01

The Soil Moisture and Ocean Salinity (SMOS) is the worldwide satellite dedicated to retrieve soil moisture information at the global scale, with a high temporal resolution, and from space borne L-band 2-D interferometry radiometer. Product validation for the accuracy of data and utilization is a crucial step. At present, the validation work carried out in China was mainly concentrated in the Tibetan Plateau. The study of this paper mainly focused on the validation of SMOS L2 soil moisture data products in the north of Henan province plain region. This region is in front of Taihang Mountains. Results from the average-average and node- site comparison show that the correlation coefficients (R) between 0.20 and 0.40, also the existence of dry bias mainly concentrated in the 0.07 0.11m3m-3. Finally, this paper analysed the influence factors on the quality of SMOS soil moisture products.

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

NASA Astrophysics Data System (ADS)

Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

2014-05-01

Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These

Satellite observed salinity distributions at high latitudes in the Northern Hemisphere: A comparison of four products

NASA Astrophysics Data System (ADS)

Garcia-Eidell, Cynthia; Comiso, Josefino C.; Dinnat, Emmanuel; Brucker, Ludovic

2017-09-01

Global surface ocean salinity measurements have been available since the launch of SMOS in 2009 and coverage was further enhanced with the launch of Aquarius in 2011. In the polar regions where spatial and temporal changes in sea surface salinity (SSS) are deemed important, the data have not been as robustly validated because of the paucity of in situ measurements. This study presents a comparison of four SSS products in the ice-free Arctic region, three using Aquarius data and one using SMOS data. The accuracy of each product is assessed through comparative analysis with ship and other in situ measurements. Results indicate RMS errors ranging between 0.33 and 0.89 psu. Overall, the four products show generally good consistency in spatial distribution with the Atlantic side being more saline than the Pacific side. A good agreement between the ship and satellite measurements was also observed in the low salinity regions in the Arctic Ocean, where SSS in situ measurements are usually sparse, at the end of summer melt seasons. Some discrepancies including biases of about 1 psu between the products in spatial and temporal distribution are observed. These are due in part to differences in retrieval techniques, geophysical filtering, and sea ice and land masks. The monthly SSS retrievals in the Arctic from 2011 to 2015 showed variations (within ˜1 psu) consistent with effects of sea ice seasonal cycles. This study indicates that spaceborne observations capture the seasonality and interannual variability of SSS in the Arctic with reasonably good accuracy.

Arctic sea ice concentration observed with SMOS during summer

NASA Astrophysics Data System (ADS)

Gabarro, Carolina; Martinez, Justino; Turiel, Antonio

2017-04-01

The Arctic Ocean is under profound transformation. Observations and model predictions show dramatic decline in sea ice extent and volume [1]. A retreating Arctic ice cover has a marked impact on regional and global climate, and vice versa, through a large number of feedback mechanisms and interactions with the climate system [2]. The launch of the Soil Moisture and Ocean Salinity (SMOS) mission, in 2009, marked the dawn of a new type of space-based microwave observations. Although the mission was originally conceived for hydrological and oceanographic studies [3,4], SMOS is also making inroads in the cryospheric sciences by measuring the thin ice thickness [5,6]. SMOS carries an L-band (1.4 GHz), passive interferometric radiometer (the so-called MIRAS) that measures the electromagnetic radiation emitted by the Earth's surface, at about 50 km spatial resolution, continuous multi-angle viewing, large wide swath (1200-km), and with a 3-day revisit time at the equator, but more frequently at the poles. A novel radiometric method to determine sea ice concentration (SIC) from SMOS is presented. The method uses the Bayesian-based Maximum Likelihood Estimation (MLE) approach to retrieve SIC. The advantage of this approach with respect to the classical linear inversion is that the former takes into account the uncertainty of the tie-point measured data in addition to the mean value, while the latter only uses a mean value of the tie-point data. When thin ice is present, the SMOS algorithm underestimates the SIC due to the low opacity of the ice at this frequency. However, using a synergistic approach with data from other satellite sensors, it is possible to obtain accurate thin ice thickness estimations with the Bayesian-based method. Despite its lower spatial resolution relative to SSMI or AMSR-E, SMOS-derived SIC products are little affected by the atmosphere and the snow (almost transparent at L-band). Moreover L-band measurements are more robust in front of the

Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

2016-06-01

Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies

Towards an estimation of water masses formation areas from SMOS-based TS diagrams

NASA Astrophysics Data System (ADS)

Klockmann, Marlene; Sabia, Roberto; Fernandez-Prieto, Diego; Donlon, Craig; Font, Jordi

2014-05-01

Temperature-Salinity (TS) diagrams emphasize the mutual variability of ocean temperature and salinity values, relating them to the corresponding density. Canonically used in oceanography, they provide a means to characterize and trace ocean water masses. In [1], a first attempt to estimate surface-layer TS diagrams based on satellite measurements has been performed, profiting from the recent availability of spaceborne salinity data. In fact, the Soil Moisture and Ocean Salinity (SMOS, [2]) and the Aquarius/SAC-D [3] satellite missions allow to study the dynamical patterns of Sea Surface Salinity (SSS) for the first time on a global scale. In [4], given SMOS and Aquarius salinity estimates, and by also using Sea Surface Temperature (SST) from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA, [5]) effort, experimental satellite-based TS diagrams have been routinely derived for the year 2011. They have been compared with those computed from ARGO-buoys interpolated fields, referring to a customised partition of the global ocean into seven regions, according to the water masses classification of [6]. In [7], moreover, besides using TS diagrams as a diagnostic tool to evaluate the temporal variation of SST and SSS (and their corresponding density) as estimated by satellite measurements, the emphasis was on the interpretation of the geographical deviations with respect to the ARGO baseline (aiming at distinguishing between the SSS retrieval errors and the additional information contained in the satellite data with respect to ARGO). In order to relate these mismatches to identifiable oceanographic structures and processes, additional satellite datasets of ocean currents, evaporation/precipitation fluxes, and wind speed have been super-imposed. Currently, the main focus of the study deals with the exploitation of these TS diagrams as a prognostic tool to derive water masses formation areas. Firstly, following the approach described in [8], the surface

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

SMOS near-real-time soil moisture product: processor overview and first validation results

NASA Astrophysics Data System (ADS)

Rodríguez-Fernández, Nemesio J.; Muñoz Sabater, Joaquin; Richaume, Philippe; de Rosnay, Patricia; Kerr, Yann H.; Albergel, Clement; Drusch, Matthias; Mecklenburg, Susanne

2017-10-01

Measurements of the surface soil moisture (SM) content are important for a wide range of applications. Among them, operational hydrology and numerical weather prediction, for instance, need SM information in near-real-time (NRT), typically not later than 3 h after sensing. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure SM from space. The ESA Level 2 SM retrieval algorithm is based on a detailed geophysical modelling and cannot provide SM in NRT. This paper presents the new ESA SMOS NRT SM product. It uses a neural network (NN) to provide SM in NRT. The NN inputs are SMOS brightness temperatures for horizontal and vertical polarizations and incidence angles from 30 to 45°. In addition, the NN uses surface soil temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The NN was trained on SMOS Level 2 (L2) SM. The swath of the NRT SM retrieval is somewhat narrower (˜ 915 km) than that of the L2 SM dataset (˜ 1150 km), which implies a slightly lower revisit time. The new SMOS NRT SM product was compared to the SMOS Level 2 SM product. The NRT SM data show a standard deviation of the difference with respect to the L2 data of < 0.05 m3 m-3 in most of the Earth and a Pearson correlation coefficient higher than 0.7 in large regions of the globe. The NRT SM dataset does not show a global bias with respect to the L2 dataset but can show local biases of up to 0.05 m3 m-3 in absolute value. The two SMOS SM products were evaluated against in situ measurements of SM from more than 120 sites of the SCAN (Soil Climate Analysis Network) and the USCRN (US Climate Reference Network) networks in North America. The NRT dataset obtains similar but slightly better results than the L2 data. In summary, the NN SMOS NRT SM product exhibits performances similar to those of the Level 2 SM product but it has the advantage of

SMOS after 2 YEARS and a half in orbit

NASA Astrophysics Data System (ADS)

Kerr, Y.; Richaume, P.; Wigneron, J.-P.; Waldteufel, P.; Mecklenburg, S.; Cabot, F.; Boutin, J.; Font, J.; Reul, N.

2012-04-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3) and ocean salinity. These two geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches in particular in improving models forecasts. The purpose of this communication is to present the mission results after more than two years in orbit as well as some outstanding results already obtained. A special attention will be devoted to level 2 products. Modeling multi-angular brightness temperatures is not straightforward. The radiative model transfer model L-MEB (L-band Microwave Emission) is used over land while different models with different approaches as to the modeling of sea surface roughness are used over ocean surfaces. Over land the approach is based on semi-empirical relationships, adapted to different type of surface. The model computes a dielectric constant leading to surface emissivity. Surface features (roughness, vegetation) are also considered in the models. However, considering SMOS spatial resolution a wide area is seen by the instrument with strong heterogeneity. The L2 soil moisture retrieval scheme takes this into account. Brightness temperatures are computed for every classes composing a working area. A weighted function is applied for the incidence angle and the antenna beam. Once the brightness temperature is computed for the entire working area, the minimizing process starts. If no soil moisture is derived (not attempted or process failed) a dielectric constant is still derived from an simplified modeled (the cardioid model). SMOS data enabled very quickly to infer Sea surface salinity fields. As salinity retrieval is quite challenging, retrieving it enable to assess very

SMOS and SMAP: from Lessons Learned to Future Mission Requirements

NASA Astrophysics Data System (ADS)

Kerr, Y. H.; Wigneron, J. P.; Cabot, F.; Escorihuela, M. J.; Anterrieu, E.; Rouge, B.; Rodriguez Fernandez, N.; Bindlish, R.; Khazaal, A.; Al-Bitar, A.; Mialon, A.; Lesthievent, G.

2017-12-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface, vegetation water content over land, and ocean salinity. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. TheSoil Moisture Active and Passive for over 2 years.The two data set have been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) to be merged into one product, while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years of L-Band data acquisition, it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the two mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets of L-band microwave radiometry in two specific cases, namely droughts and water budget over a large basin. Several other analyses are under way currently. Obviously

The Aquarius Salinity Product: Intercomparison with SMOS and In-Situ Observations and Importance of the Ocean Surface Roughness Correction

NASA Astrophysics Data System (ADS)

Meissner, Thomas; Hilburn, Kyle; Wentz, Frank; Gentemann, Chelle

2013-04-01

The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to an accuracy of 0.2 psu. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. This first part of the presentation gives an overview over the major features of the Version 2.1 Aquarius Level 2 salinity retrieval algorithm: 1. Antenna pattern correction: spillover and cross polarization contamination. 2. Correction for the drift of the Aquarius internal calibration system. 3. Correction for intruding celestial radiation, foremost from the galaxy. 4. Correction for effects of the wind roughened ocean surface. We then present a thorough validation study for the salinity product, which consists in a 3-way intercomparison between Aquarius, SMOS and in-situ buoy salinity measurements. The Aquarius - buy comparison shows that that the Aquarius Version 2.1 salinity product is very close to meet the aforementioned mission requirement of 0.2 psu. We demonstrate that in order to meet this accuracy it is crucial to use the L-band scatterometer for correcting effects from the wind roughened ocean surface, which turns out to be the major driver in the salinity retrieval uncertainty budget. A surface roughness correction algorithm that is based solely on auxiliary input of wind fields from numerical weather prediction models (e.g. NCEP, ECMWF) is not sufficient to meet the stringent Aquarius mission requirement, especially at wind speeds above 10 m/s. We show that presence of the Aquarius L-band scatterometer together with the L-band radiometer allows the retrieval of an Aquarius wind speed product whose accuracy matches or exceeds that of other common ocean wind speeds (WindSat, SSMIS). By comparing SMOS and Aquarius salinity fields with the in-situ observations we assess the importance of the roughness correction

Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals

NASA Astrophysics Data System (ADS)

Tian, Siyuan; Tregoning, Paul; Renzullo, Luigi J.; van Dijk, Albert I. J. M.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.; Allgeyer, Sébastien

2017-03-01

The accuracy of global water balance estimates is limited by the lack of observations at large scale and the uncertainties of model simulations. Global retrievals of terrestrial water storage (TWS) change and soil moisture (SM) from satellites provide an opportunity to improve model estimates through data assimilation. However, combining these two data sets is challenging due to the disparity in temporal and spatial resolution at both vertical and horizontal scale. For the first time, TWS observations from the Gravity Recovery and Climate Experiment (GRACE) and near-surface SM observations from the Soil Moisture and Ocean Salinity (SMOS) were jointly assimilated into a water balance model using the Ensemble Kalman Smoother from January 2010 to December 2013 for the Australian continent. The performance of joint assimilation was assessed against open-loop model simulations and the assimilation of either GRACE TWS anomalies or SMOS SM alone. The SMOS-only assimilation improved SM estimates but reduced the accuracy of groundwater and TWS estimates. The GRACE-only assimilation improved groundwater estimates but did not always produce accurate estimates of SM. The joint assimilation typically led to more accurate water storage profile estimates with improved surface SM, root-zone SM, and groundwater estimates against in situ observations. The assimilation successfully downscaled GRACE-derived integrated water storage horizontally and vertically into individual water stores at the same spatial scale as the model and SMOS, and partitioned monthly averaged TWS into daily estimates. These results demonstrate that satellite TWS and SM measurements can be jointly assimilated to produce improved water balance component estimates.

Synthesizing SMOS Zero-Baselines with Aquarius Brightness Temperature Simulator

NASA Technical Reports Server (NTRS)

Colliander, A.; Dinnat, E.; Le Vine, D.; Kainulainen, J.

2012-01-01

SMOS [1] and Aquarius [2] are ESA and NASA missions, respectively, to make L-band measurements from the Low Earth Orbit. SMOS makes passive measurements whereas Aquarius measures both passive and active. SMOS was launched in November 2009 and Aquarius in June 2011.The scientific objectives of the missions are overlapping: both missions aim at mapping the global Sea Surface Salinity (SSS). Additionally, SMOS mission produces soil moisture product (however, Aquarius data will eventually be used for retrieving soil moisture too). The consistency of the brightness temperature observations made by the two instruments is essential for long-term studies of SSS and soil moisture. For resolving the consistency, the calibration of the instruments is the key. The basis of the SMOS brightness temperature level is the measurements performed with the so-called zero-baselines [3]; SMOS employs an interferometric measurement technique which forms a brightness temperature image from several baselines constructed by combination of multiple receivers in an array; zero-length baseline defines the overall brightness temperature level. The basis of the Aquarius brightness temperature level is resolved from the brightness temperature simulator combined with ancillary data such as antenna patterns and environmental models [4]. Consistency between the SMOS zero-baseline measurements and the simulator output would provide a robust basis for establishing the overall comparability of the missions.

SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann

2011-01-01

Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS

Estimation of the barrier layer thickness in the Indian Ocean using Aquarius Salinity

NASA Astrophysics Data System (ADS)

Felton, Clifford S.; Subrahmanyam, Bulusu; Murty, V. S. N.; Shriver, Jay F.

2014-07-01

Monthly barrier layer thickness (BLT) estimates are derived from satellite measurements using a multilinear regression model (MRM) within the Indian Ocean. Sea surface salinity (SSS) from the recently launched Soil Moisture and Ocean Salinity (SMOS) and Aquarius SAC-D salinity missions are utilized to estimate the BLT. The MRM relates BLT to sea surface salinity (SSS), sea surface temperature (SST), and sea surface height anomalies (SSHA). Three regions where the BLT variability is most rigorous are selected to evaluate the performance of the MRM for 2012; the Southeast Arabian Sea (SEAS), Bay of Bengal (BoB), and Eastern Equatorial Indian Ocean (EEIO). The MRM derived BLT estimates are compared to gridded Argo and Hybrid Coordinate Ocean Model (HYCOM) BLTs. It is shown that different mechanisms are important for sustaining the BLT variability in each of the selected regions. Sensitivity tests show that SSS is the primary driver of the BLT within the MRM. Results suggest that salinity measurements obtained from Aquarius and SMOS can be useful for tracking and predicting the BLT in the Indian Ocean. Largest MRM errors occur along coastlines and near islands where land contamination skews the satellite SSS retrievals. The BLT evolution during 2012, as well as the advantages and disadvantages of the current model are discussed. BLT estimations using HYCOM simulations display large errors that are related to model layer structure and the selected BLT methodology.

Different rates of soil drying after rainfall are observed by the SMOS satellite and the South Fork In Situ Soil Moisture Network

USDA-ARS?s Scientific Manuscript database

Soil moisture affects the spatial variation of land–atmosphere interactions through its in'uence on the balance of latent and sensible heat 'ux. Wetter soils are more prone to 'ooding because a smaller fraction of rainfall can in'ltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) sa...

Coincident Retrieval of Ocean Surface Roughness and Salinity Using Airborne and Satellite Microwave Radiometry and Reflectometry Measurements during the Carolina Offshore (Caro) Experiment.

NASA Astrophysics Data System (ADS)

Burrage, D. M.; Wesson, J. C.; Wang, D. W.; Garrison, J. L.; Zhang, H.

2017-12-01

The launch of the Cyclone Global Navigation Satellite System (CYGNSS) constellation of 8 microsats carrying GPS L-band reflectometers on 15 Dec., 2016, and continued operation of the L-band radiometer on the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite, allow these complementary technologies to coincidentally retrieve Ocean surface roughness (Mean Square Slope, MSS), Surface Wind speed (WSP), and Sea Surface Salinity (SSS). The Carolina Offshore (Caro) airborne experiment was conducted jointly by NRL SSC and Purdue University from 7-11 May, 2017 with the goal of under-flying CYGNSS and SMOS and overflying NOAA buoys, to obtain high-resolution reflectometer and radiometer data for combined retrieval of MSS, SSS and WSP on the continental shelf. Airborne instruments included NRL's Salinity Temperature and Roughness Remote Scanner (STARRS) L-, C- and IR-band radiometer system, and a 4-channel dual-pol L-band (GPS) and S-band (XM radio) reflectometer, built by Purdue University. Flights either crossed NOAA buoys on various headings, or intersected with specular point ground tracks at predicted CYGNSS overpass times. Prevailing winds during Caro were light to moderate (1-8 m/s), so specular returns dominated the reflectometer Delay Doppler Maps (DDMs), and MSS was generally low. In contrast, stronger winds (1-12 m/s) and rougher seas (wave heights 1-5 m) were experienced during the preceding Maine Offshore (Maineo) experiment in March, 2016. Several DDM observables were used to retrieve MSS and WSP, and radiometer brightness temperatures produced Sea Surface Temperature (SST), SSS and also WSP estimates. The complementary relationship of Kirchoff's formula e+r=1, between radiometric emissivity, e, and reflectivity, r, was exploited to seek consistent estimates of MSS, and use it to correct the SSS retrievals for sea surface roughness effects. The relative performance and utility of the various airborne and satellite retrieval algorithms

Assimilation of SMOS brightness temperatures in the ECMWF EKF for the analysis of soil moisture

NASA Astrophysics Data System (ADS)

Munoz-Sabater, Joaquin

2012-07-01

Since November 2nd 2009, the European Centre for Medium-Range Weather Forecasts (ECMWF) has being monitoring, in Near Real Time (NRT), L-band brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) satellite mission of the European Space Agency (ESA). The main objective of the monitoring suite for SMOS data is to systematically monitor the difference between SMOS observed brightness temperatures and the corresponding model equivalent simulated by the Community Microwave Emission Model (CMEM), the so-called first guess departures. This is a crucial step, as first guess departures is the quantity used in the analysis. The ultimate goal is to investigate how the assimilation of SMOS brightness temperatures over land improves the weather forecast skill, through a more accurate initialization of the global soil moisture state. In this presentation, some significant results from the activities preparing for the assimilation of SMOS data are shown. Among these activities, an effective data thinning strategy, a practical approach to reduce noise from the observed brightness temperatures and a bias correction scheme are of special interest. Firstly, SMOS data needs to be significantly thinned as the data volume delivered for a single orbit is too large for the current operational capabilities in any Numerical Weather Prediction system. Different thinning strategies have been analysed and tested. The most suitable one is the assimilation of SMOS brightness temperatures which match the ECMWF T511 (~40 km) reduced Gaussian Grid. Secondly, SMOS observational noise is reduced significantly by averaging the data in angular bins. In addition, this methodology contributes to further thinning of the SMOS data before the analysis. Finally, a bias correction scheme based on a CDF matching is applied to the observations to ensure an unbiased dataset ready for assimilation in the ECMWF surface analysis system. The current ECMWF operational soil moisture analysis

Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin, USA

NASA Technical Reports Server (NTRS)

Lievens, H.; Verhoest, N. E. C.; Martens, B.; VanDenBerg, M. J.; Bitar, A. Al; Tomer, S. Kumar; Merlin, O.; Cabot, F.; Kerr, Y.; DeLannoy, G. J. M.;

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Pauwels, Valentijn; Reichle, Rolf H.; Draper, Clara; Koster, Randy; Liu, Qing

2012-01-01

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

2016-01-01

Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

Measuring surface salinity in the N. Atlantic subtropical gyre. The SPURS-MIDAS cruise, spring 2013

NASA Astrophysics Data System (ADS)

Font, Jordi; Ward, Brian; Emelianov, Mikhail; Morisset, Simon; Salvador, Joaquin; Busecke, Julius

2014-05-01

SPURS-MIDAS (March-April 2013) on board the Spanish R/V Sarmiento de Gamboa was a contribution to SPURS (Salinity Processes in the Upper ocean Regional Study) focused on the processes responsible for the formation and maintenance of the salinity maximum associated to the North Atlantic subtropical gyre. Scientists from Spain, Ireland, France and US sampled the mesoscale and submesoscale structures in the surface layer (fixed points and towed undulating CTD, underway near surface TSG) and deployed operational and experimental drifters and vertical profilers, plus additional ocean and atmospheric data collection. Validation of salinity maps obtained from the SMOS satellite was one of the objectives of the cruise. The cruise included a joint workplan and coordinated sampling with the US R/V Endeavor, with contribution from SPURS teams on land in real time data and analysis exchange. We present here an overview of the different kinds of measurements made during the cruise, as well as a first comparison between SMOS-derived sea surface salinity products and salinity maps obtained from near-surface sampling in the SPURS-MIDAS area and from surface drifters released during the cruise.

The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record

NASA Astrophysics Data System (ADS)

de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne

2015-04-01

Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004.

SMOS Soil Moisture Data Assimilation in the NASA Land Information System: Impact on LSM Initialization and NWP Forecasts

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley

2015-01-01

Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.

Air-sea fluxes and satellite-based estimation of water masses formation

NASA Astrophysics Data System (ADS)

Sabia, Roberto; Klockmann, Marlene; Fernandez-Prieto, Diego; Donlon, Craig

2015-04-01

Recent work linking satellite-based measurements of sea surface salinity (SSS) and sea surface temperature (SST) with traditional physical oceanography has demonstrated the capability of generating routinely satellite-derived surface T-S diagrams [1] and analyze the distribution/dynamics of SSS and its relative surface density with respect to in-situ measurements. Even more recently [2,3], this framework has been extended by exploiting these T-S diagrams as a diagnostic tool to derive water masses formation rates and areas. A water mass describes a water body with physical properties distinct from the surrounding water, formed at the ocean surface under specific conditions which determine its temperature and salinity. The SST and SSS (and thus also density) at the ocean surface are largely determined by fluxes of heat and freshwater. The surface density flux is a function of the latter two and describes the change of the density of seawater at the surface. To obtain observations of water mass formation is of great interest, since they serve as indirect observations of the thermo-haline circulation. The SSS data which has become available through the SMOS [4] and Aquarius [5] satellite missions will provide the possibility of studying also the effect of temporally-varying SSS fields on water mass formation. In the present study, the formation of water masses as a function of SST and SSS is derived from the surface density flux by integrating the latter over a specific area and time period in bins of SST and SSS and then taking the derivative of the total density flux with respect to density. This study presents a test case using SMOS SSS, OSTIA SST, as well as Argo ISAS SST and SSS for comparison, heat fluxes from the NOCS Surface Flux Data Set v2.0, OAFlux evaporation and CMORPH precipitation. The study area, initially referred to the North Atlantic, is extended over two additional ocean basins and the study period covers the 2011-2012 timeframe. Yearly, seasonal

Comparison of remote sensing and in-situ soil moisture measurements: 6 years survey of SMOS data and agrometeorological stations in Eastern Poland

NASA Astrophysics Data System (ADS)

Szlazak, Radoslaw; Rojek, Edyta; Lukowski, Mateusz; Marczewski, Wojciech; Slominski, Jan; Sagan, Joanna; Gluba, Lukasz; Usowicz, Jerzy; Usowicz, Boguslaw

2017-04-01

Long term measurements of soil moisture on a large scale provide important information about not only periodical changes in water content, but also its contribute to better understanding of water cycle in environment. In addition, if in the studied area occurred extreme weather conditions or even anomalies, it is scientifically challenging to compare and validate data from two such different techniques like remote sensing and in-situ measurements. The aim of our research was to compare data of independent soil moisture measurements from SMOS (Soil Moisture and Ocean Salinity) satellite and 9 agrometeorological stations installed on Eastern Poland (Polesie and Podlasie regions). Those regions have similar climatic and topographic conditions, however, different vegetation covers and soil properties. Radiometric SMOS data contain surface water content values (approx. 45 km) for the area corresponding to the positions of chosen agrometeorological stations. For the purpose of those studies only morning satellite overpasses (ascending) were used. In-situ sensors in stations measure precisely soil moisture at 5-10 cm depth, but each only in one point. Both datasets were 7-days averaged in order to standardize. Analysis of a long term data is very interesting, especially because of occurrence of flood and drought events during the analyzed period of time. For example, the analyses revealed clear rainfall trend between ground and satellite data. Some shifts between SMOS and ground measurements were also observed, what may be explained by impact of different depths of SMOS measurements (<5 cm) and layer measured by sensors in the stations (0-10 cm). The influence of different sensing depths for both techniques is also reflected in bigger variability of SMOS data as they came from shallower layer of soil that have smaller "inertia" (in terms of soil moisture variability) than deeper in situ measurements. The results from SMOS and those obtained with the soil moisture sensor

Towards SMOS: The 2006 National Airborne Field Experiment Plan

NASA Astrophysics Data System (ADS)

Walker, J. P.; Merlin, O.; Panciera, R.; Kalma, J. D.

2006-05-01

The 2006 National Airborne Field Experiment (NAFE) is the second in a series of two intensive experiments to be conducted in different parts of Australia. The NAFE'05 experiment was undertaken in the Goulburn River catchment during November 2005, with the objective to provide high resolution data for process level understanding of soil moisture retrieval, scaling and data assimilation. The NAFE'06 experiment will be undertaken in the Murrumbidgee catchment during November 2006, with the objective to provide data for SMOS (Soil Moisture and Ocean Salinity) level soil moisture retrieval, downscaling and data assimilation. To meet this objective, PLMR (Polarimetric L-band Multibeam Radiometer) and supporting instruments (TIR and NDVI) will be flown at an altitude of 10,000 ft AGL to provide 1km resolution passive microwave data (and 20m TIR) across a 50km x 50km area every 2-3 days. This will both simulate a SMOS pixel and provide the 1km soil moisture data required for downscale verification, allowing downscaling and near-surface soil moisture assimilation techniques to be tested with remote sensing data which is consistent with that from current (MODIS) and planned (SMOS) satellite sensors.. Additionally, two transects will be flown across the area to provide both 1km multi-angular passive microwave data for SMOS algorithm development, and on the same day, 50m resolution passive microwave data for algorithm verification. The study area contains a total of 13 soil moisture profile and rainfall monitoring sites for assimilation verification, and the transect fight lines are planned to go through 5 of these. Ground monitoring of surface soil moisture and vegetation for algorithm verification will be targeted at these 5 focus farms, with soil moisture measurements made at 250m spacing for 1km resolution flights and 50m spacing for 50m resolution flights. While this experiment has a particular emphasis on the remote sensing of soil moisture, it is open for collaboration

Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio

2015-04-01

Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal

DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia

NASA Astrophysics Data System (ADS)

Malbéteau, Yoann; Merlin, Olivier; Molero, Beatriz; Rüdiger, Christoph; Bacon, Stephan

2016-03-01

Validating coarse-scale satellite soil moisture data still represents a big challenge, notably due to the large mismatch existing between the spatial resolution (> 10 km) of microwave radiometers and the representativeness scale (several m) of localized in situ measurements. This study aims to examine the potential of DisPATCh (Disaggregation based on Physical and Theoretical scale Change) for validating SMOS (Soil Moisture and Ocean Salinity) and AMSR-E (Advanced Microwave Scanning Radiometer-Earth observation system) level-3 soil moisture products. The ∽40-50 km resolution SMOS and AMSR-E data are disaggregated at 1 km resolution over the Murrumbidgee catchment in Southeastern Australia during a one year period in 2010-2011, and the satellite products are compared with the in situ measurements of 38 stations distributed within the study area. It is found that disaggregation improves the mean difference, correlation coefficient and slope of the linear regression between satellite and in situ data in 77%, 92% and 94% of cases, respectively. Nevertheless, the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. Consistently, better results are obtained in the semi-arid than in a temperate zone of the catchment. In the semi-arid Yanco region, disaggregation in summer increases the correlation coefficient from 0.63 to 0.78 and from 0.42 to 0.71 for SMOS and AMSR-E in morning overpasses and from 0.37 to 0.63 and from 0.47 to 0.73 for SMOS and AMSR-E in afternoon overpasses, respectively. DisPATCh has strong potential in low vegetated semi-arid areas where it can be used as a tool to evaluate coarse-scale remotely sensed soil moisture by explicitly representing the sub-pixel variability.

Droughts and floods monitoring in Poland with SMOS, SEVIRI and model data

NASA Astrophysics Data System (ADS)

Kotarba, A. Z.; Stankiewicz, K.; Słomiński, J.; Słomińska, E.; Marczewski, W.

2012-04-01

Droughts and floods represent the extreme cases of hydrological regime. Both significantly influence ecological processes in the environment as well as socio-economic situation of human activity. Measurements of soil moisture and rainfall is being recognized as fundamental for droughts and floods monitoring. We used Soil Moisture and Ocean Salinity (SMOS) L2 soil moisture data and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) rain rate approximation to evaluate the intensity and extend of droughts/floods events in Poland in 2010 and 2011. SEVIRI Multi-Sensor Precipitation Estimate rain rates were used for calculation of monthly rain accumulation (24 SEVIRI L2 datasets per day), then projected to match SMOS spatial reference. Based on SEVIRI data, monthly sum of precipitation was estimated for each SMOS DGG cell within area of interest (the ROI covers Poland and the closest neighborhood). At the DGG level, SMOS SM and SEVIRI precipitation data were compared for each month since May 2010. Nearly two year series provided a background for droughts and floods events. Final L3 products of SMOS SM and SEVIRI precipitation were compared with operational, traditionally-developed drought risk maps, in order to evaluate the degree of agreement between remotely sensed products and models calculated with surface-based measurements only.

Smos Land Product Validation Activities at the Valencia Anchor Station

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto

ABSTRACT Soil moisture is a key parameter controlling the exchanges between the land surface and the atmosphere. In spite of being important for weather and climate modeling, this parameter is not well observed at a global scale. The SMOS (Soil Moisture and Ocean Salinity) Mission was designed by the European Space Agency (ESA) to measure soil moisture over continental surfaces as well as surface salinity over the oceans. Since 2001, the Valencia Anchor Station is currently being prepared for the validation of SMOS land products, namely soil moisture content and vegetation water content. The site has recently been selected by the Mission as a core validation site, mainly due to the reasonable homogeneous characteristics of the area which make it appropriate to undertake the validation of SMOS Level 2 land products during the Mission Commissioning Phase, before attempting more complex areas. Close to SMOS launch, ESA has defined and designed a SMOS V alidation Rehearsal C ampaign P lan which purpose is to repeat the Commissioning Phase execution with all centers, all tools, all participants, all structures, all data available, assuming all tools and structures are ready and trying to produce as close as possible the post-launch conditions. The aim is to test the readiness, the ensemble coordination and the speed of operations, and to avoid as far as possible any unexpected deficiencies of the plan and procedure during the real C ommissioning P hase campaigns. For the rehearsal activity, a control area of 10 x 10 km2 has been chosen at the Valencia Anchor Station study area where a network of ground soil moisture measuring stations is being set up based on the definition of homogeneous physio-hydrological units, attending to climatic, soil type, lithology, geology, elevation, slope and vegetation cover conditions. These stations are linked via a wireless communication system to a master post accessible via internet. The ground soil moisture stations will also be used

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

ESA's Soil Moisture dnd Ocean Salinity Mission - Contributing to Water Resource Management

NASA Astrophysics Data System (ADS)

Mecklenburg, S.; Kerr, Y. H.

2015-12-01

The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface soil moisture provides the input to derive root-zone soil moisture, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface soil moisture, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for soil moisture data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 soil moisture product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the

Sea surface temperature and salinity from French research vessels, 2001–2013

PubMed Central

Gaillard, Fabienne; Diverres, Denis; Jacquin, Stéphane; Gouriou, Yves; Grelet, Jacques; Le Menn, Marc; Tassel, Joelle; Reverdin, Gilles

2015-01-01

French Research vessels have been collecting thermo-salinometer (TSG) data since 1999 to contribute to the Global Ocean Surface Underway Data (GOSUD) programme. The instruments are regularly calibrated and continuously monitored. Water samples are taken on a daily basis by the crew and later analysed in the laboratory. We present here the delayed mode processing of the 2001–2013 dataset and an overview of the resulting quality. Salinity measurement error was a few hundredths of a unit or less on the practical salinity scale (PSS), due to careful calibration and instrument maintenance, complemented with a rigorous adjustment on water samples. In a global comparison, these data show excellent agreement with an ARGO-based salinity gridded product. The Sea Surface Salinity and Temperature from French REsearch SHips (SSST-FRESH) dataset is very valuable for the ‘calibration and validation’ of the new satellite observations delivered by the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions. PMID:26504523

Evaluating Soil Moisture Retrievals from ESA's SMOS and NASA's SMAP Brightness Temperature Datasets

NASA Technical Reports Server (NTRS)

Al-Yaari, A.; Wigernon, J.-P.; Kerr, Y.; Rodriguez-Fernandez, N.; O'Neill, P. E.; Jackson, T. J.; De Lannoy, G. J. M.; Al Bitar, A.; Mialon, A.; Richaume, P.;

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets.

PubMed

Al-Yaari, A; Wigneron, J-P; Kerr, Y; Rodriguez-Fernandez, N; O'Neill, P E; Jackson, T J; De Lannoy, G J M; Al Bitar, A; Mialon, A; Richaume, P; Walker, J P; Mahmoodi, A; Yueh, S

2017-05-01

Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d'études spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Données) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40° incidence angle, over the 2013 - 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE), Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in situ

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

2016-01-01

Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval

SMOS disaggregated soil moisture product at 1 km resolution: processor overview and first validation results

USDA-ARS?s Scientific Manuscript database

The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of ~50 km. However, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution SM...

Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products

NASA Astrophysics Data System (ADS)

Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.

2016-12-01

The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. The goal of the SMAP mission is to produce soil moisture with accuracy better than 0.04 m3/m3 with a revisit frequency of 2-3 days. The validated standard SMAP passive soil moisture product (L2SMP) with a spatial resolution of 36 km was released in May 2016. Soil moisture observations from in situ sensors are typically used to validate the satellite estimates. But, in situ observations provide ground truth for limited amount of landcover and climatic conditions. Although each mission will have its own issues, observations by other satellite instruments can be play a role in the calibration and validation of SMAP. SMAP, SMOS and GCOM-W missions share some commonnalities because they are currently providing operational brightness temperature and soil moisture products. SMAP and SMOS operate at L-band but GCOM-W uses X-band observations for soil moisture estimation. All these missions use different ancillary data sources, parameterization and algorithm to retrieve soil moisture. Therefore, it is important to validate and to compare the consistency of these products. Soil moisture products from the different missions will be compared with the in situ observations. SMAP soil moisture products will be inter-compared at global scales with SMOS and GCOM-W soil moisture products. The major contribution of satellite product inter-comparison is that it allows the assessment of the quality of the products over wider geographical and climate domains. Rigorous assessment will lead to a more reliable and accurate soil moisture product from all the missions.

Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

2016-04-01

Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico

Mesoscale Turbulence in the Ocean and Synergy of Variables: Merging of Smos and Aquarius SSS Maps Using New, Non-Parametric Methods

NASA Astrophysics Data System (ADS)

Turiel, A.; Umbert, M.; Hoareau, N.; Ballabrera-Poy, J.; Font, J.

2012-12-01

Remote sensing platforms onboard satellites provide synoptic maps of ocean surface and thus an accurate picture of many processes taking place in the ocean at mesoscale and sub-mesoscale levels mainly can be gained. Since the first ocean observation satellites these images has been exploited to assess ocean processes; however, extracting further dynamic information from remote sensing maps generally implies a higher degree of processing complexity, involving the use of numerical models and assimilation schemes. A critical variable for the understanding the climate system is Sea Surface Salinity (SSS). The arrival of SMOS and Aquarius missions has given us access to SSS in a regular basis. However, those images still suffer of many acquisition and processing issues, what precludes gaining a complete picture of ocean surface dynamics. In order to favor the oceanographic exploitation of SMOS and Aquarius maps new filtering schemes need to be devised. During the last years a new branch of image processing techniques applied to ocean observation has arisen with force, namely multiscale/multifractal analysis. Different scalars submitted to the action of the ocean flow develop an identical inner structure (multifractal structure) that can be revealed by means of the appropriate analysis tools (singularity analysis). These tools allow for instance to characterize surface currents from snapshots of different scalars (Turiel et al, Ocean Sciences, 2009). In this work we go further away, with the introduction of a new method to blend different types of scalar in a single map of improved quality. The method does not imply the introduction of any parameter, nor relies in any numerical model, but in the assumption that the action of the oceanic flow leads to the same multifractal structure in any ocean variable. The method allows, for instance, to use the multifractal structure coming from SST images to improve the quality of SSS maps (as illustrated in the figure). It can also

Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

USDA-ARS?s Scientific Manuscript database

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

Evaluating soil moisture retrievals from ESA’s SMOS and NASA’s SMAP brightness temperature datasets

PubMed Central

Al-Yaari, A.; Wigneron, J.-P.; Kerr, Y.; Rodriguez-Fernandez, N.; O’Neill, P. E.; Jackson, T. J.; De Lannoy, G.J.M.; Al Bitar, A; Mialon, A.; Richaume, P.; Walker, JP; Mahmoodi, A.; Yueh, S.

2018-01-01

Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d’études spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Données) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40° incidence angle, over the 2013 – 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE), Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in

Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca

2016-04-01

Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas

SMOS first results over land

NASA Astrophysics Data System (ADS)

Kerr, Yann; Waldteufel, Philippe; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Bitar, Ahmad Al; Mamhoodi, Ali; Delwart, Steven; Wigneron, Jean-Pierre

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 consists mainly of angular brightness temperatures while level 2 consists of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to

Monthly Sea Surface Salinity and Freshwater Flux Monitoring

NASA Astrophysics Data System (ADS)

Ren, L.; Xie, P.; Wu, S.

2017-12-01

Taking advantages of the complementary nature of the Sea Surface Salinity (SSS) measurements from the in-situ (CTDs, shipboard, Argo floats, etc.) and satellite retrievals from Soil Moisture Ocean Salinity (SMOS) satellite of the European Space Agency (ESA), the Aquarius of a joint venture between US and Argentina, and the Soil Moisture Active Passive (SMAP) of national Aeronautics and Space Administration (NASA), a technique is developed at NOAA/NCEP/CPC to construct an analysis of monthly SSS, called the NOAA Blended Analysis of Sea-Surface Salinity (BASS). The algorithm is a two-steps approach, i.e. to remove the bias in the satellite data through Probability Density Function (PDF) matching against co-located in situ measurements; and then to combine the bias-corrected satellite data with the in situ measurements through the Optimal Interpolation (OI) method. The BASS SSS product is on a 1° by 1° grid over the global ocean for a 7-year period from 2010. Combined with the NOAA/NCEP/CPC CMORPH satellite precipitation (P) estimates and the Climate Forecast System Reanalysis (CFSR) evaporation (E) fields, a suite of monthly package of the SSS and oceanic freshwater flux (E and P) was developed to monitor the global oceanic water cycle and SSS on a monthly basis. The SSS in BASS product is a suite of long-term SSS and fresh water flux data sets with temporal homogeneity and inter-component consistency better suited for the examination of the long-term changes and monitoring. It presents complete spatial coverage and improved resolution and accuracy, which facilitates the diagnostic analysis of the relationship and co-variability among SSS, freshwater flux, mixed layer processes, oceanic circulation, and assimilation of SSS into global models. At the AGU meeting, we will provide more details on the CPC salinity and fresh water flux data package and its applications in the monitoring and analysis of SSS variations in association with the ENSO and other major climate

SMAP Salinity Artifacts Associated With Presence of Rain

NASA Astrophysics Data System (ADS)

Jacob, M. M.; Santos-Garcia, A.; Jones, L.

2016-02-01

The Soil Moisture Active Passive (SMAP) satellite carries an L-band radiometer, which measures sea surface salinity (SSS) over a swath of 1000 km @ 40 km resolution. SMAP can extend the Aquarius (AQ) salinity data record with improved temporal/spatial sampling. Previous studies [see references] have demonstrated significant differences between satellite and in-situ salinity measurements during rain. In the presence of precipitation, salinity stratification exists near the sea surface, which nullifies the presumption of a well-mixed salinity. In general, these salinity gradients last only a few hours and the upper layer becomes slightly fresher in salinity. This paper describes the Rain Impact Model (RIM) that simulates the effects of rain accumulation on the SSS [Santos-Garcia et al., 2014] applied to SMAP. This model incorporates rainfall information for the previous 24 hours to the measurement sample (in this case SMAP) and uses as initialization the Hybrid Coordinate Ocean Model (HYCOM) data. Given the better resolution of SMAP, the goal of this paper is to continue the analysis previously done with AQ to better understand the effects of the instantaneous and accumulated rain on the salinity measurements. Boutin, J., N. Martin, G. Reverdin, X. Yin, and F. Gaillard (2013), Sea surface freshening inferred from SMOS and ARGO salinity: Impact of rain, Ocean Sci., 9(1), 183-192, doi:10.5194/os-9-183-2013. Santos-Garcia, A., M. Jacob, L. Jones, W. Asher, Y. Hejazin, H. Ebrahimi, and M. Rabolli (2014), Investigation of rain effects on Aquarius Sea Surface Salinity measurements, J. Geophys. Res. Oceans, 119, 7605-7624, doi:10.1002/2014JC010137. Tang, W., S.H Yueh, A. Hayashi, A.G. Fore, W.L. Jones, A. Santos-Garcia, and M.M. Jacob, (2015), Rain-Induced Near Surface Salinity Stratification and Rain Roughness Correction for Aquarius SSS Retrieval, in Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 8(99), 1-11, doi: 10.1109/JSTARS.2015.2463768.

Fresh Water River discharges as observed by SMOS in the Arabian Sea and the Bay of Bengal

NASA Astrophysics Data System (ADS)

Olmedo, Estrella; Ballabrera-Poy, Joaquim; Turiel, Antonio

2017-04-01

The Bay of Bengal (BoB) and the Arabian Sea (AS) are two peculiar regions in the Indian Ocean exhibiting a wide range of Sea Surface Salinity (SSS) values. In the BoB, the strong summer monsoon rainfall and the continental run-offs into these semi-enclosed basins result in an intense dilution of the surface seawater in the northern part of the Bay, thereby inducing some of the lowest SSS water masses found in the tropical belt. In the AS, because of the intense variability associated with the monsoon cycle, water mass structure in the upper layers of the AS shows enormous variability in the space and time. As such, the role of the salinity in these regions is crucial in the ocean dynamics of these regions. After more than 7 years in orbit, the Soil Moisture and Ocean Salinity (SMOS) mission [1] continues to provide a series of salinity data that could be used to monitor the SSS variations in these climatically relevant regions, provided that systematic errors due to land contamination are reduced. Recently-developed algorithms for SSS retrieval [2] have improved the filtering criteria and the mitigation of the systematic bias, providing coherent SSS retrievals close to the land masses. In this work we have analyzed the SSS in 2-degree boxes located at the mouth of the main rivers in the BoB: Ganges-Brahmaputra, Irrawady, Mahanadi, Godovari; and in the AS: Indus. We have first tried to validate the SMOS salinity retrievals with in situ measurements. Since there is few available in situ data, we have also compared the climatological SSS behavior derived from SMOS with the ones provided by the World Ocean Atlas [3]. We have also compared the SMOS SSS data with historical data of discharges [4] and [5], ocean currents from the Ocean Surface Current Analyses Real-time (OSCAR) [6], Sea Surface Temperature from Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) [7],[8] and [9] and Chlorophyll data [10]. The conclusion of this work is that, when the proper

The ESA SMOS Validation Rehearsal Campaign at the Valencia Anchor Station Area in the Framework of the SMOS Cal/Val AO Project no. 3252

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.

2009-04-01

Institute of Maritime Research, FIMR). Together with the ground soil moisture measurements, other ground and meteorological measurements from the Valencia Anchor Station area, kindly provided by other institutions, are currently been used to simulate passive microwave brightness temperature to have satellite "match ups" for validation purposes and to test the retrieval algorithms. The spatialization of the ground measurements up to a SMOS pixel is carried out by using a Soil-Vegetation-Atmosphere-Transfer (SVAT) model (SURFEX, SURFace EXternalisée) from Météo France. Output data, particularly soil moisture, will then be used to simulate the L-band surface emission through the use of the L-MEB (L-band Microwave Emission of the Biosphere) model. For that purpose, the microwave model uses specific ground information regarding the soil and vegetation properties provided by the validation teams. The aggregation of the brightness temperatures at the SMOS pixel scale is then carried out in an operational way taking into account the SMOS viewing configuration and antenna properties. This paper presents an overview of the ESA SMOS Validation Rehearsal Campaign at the Valencia Anchor Station area making more emphasis on the development of the ground activities which are significant for the performance of the different validation components and giving an outline of the methodology to be used for the whole SMOS Reference Pixel.

Mitigation of biases in SMOS Level 2 soil moisture retrieval algorithm

NASA Astrophysics Data System (ADS)

Mahmoodi, Ali; Richaume, Philippe; Kerr, Yann

2017-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA) relies on the L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer models to retrieve soil moisture (SM). These models require, as input, parameters which characterize the target like soil water content and temperature. The Soil Water Volume at Level 1 (SWVL1) from the European Centre for Medium-Range Weather Forecast (ECMWF) is used in the SMOS Level 2 SM algorithms as both an initial guess for SM in the iterative retrieval process and to compute fixed contributions from the so called "default" fractions. In case of mixed fractions of nominal (low vegetation land) and forest, retrieval is performed over one fraction while the contribution of the other is assumed to be fixed and known based on ECMWF data. Studies have shown that ECMWF SWVL1 is biased when compared to SMOS SM and represents values at a deeper layer of soil ( 7 cm) than that represented by SMOS ( 2 to 5 cm). This study uses a well know bias reduction technique based on matching of the Cumulative Distribution Functions (CDF) of the two distributions to help reduce the biases. Early results using a linear matching method provide very encouraging results. A complication with respect to performing CDF matching is that SMOS SM values are not available where they are needed, i.e. over the default fractions. In order to remedy this, we treat mixed fractions as homogeneous targets to retrieve SM over the whole target. The obtained values are then used to derive the CDF matching coefficients. A set of CDF coefficients derived using average and standard deviation of soil moisture values for 2014 has been used in reprocessing SMOS data for 2014 and 2015, as well as over selected sites (with in-situ data) over a longer period. The 2014 was selected due to its lower Radio Frequency Interference (RFI) contamination in comparison with other years. The application of CDF coefficients has lead to a wetter SM for

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

NASA Technical Reports Server (NTRS)

LeVine, David M; Abraham, Saji; Wentz, F; Lagerloef, G S

2005-01-01

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.

Using SMOS observations in the development of the SMAP level 4 surface and root-zone soil moisture project

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity (SMOS; [1]) mission was launched by ESA in November 2009 and has since been observing L-band (1.4 GHz) upwelling passive microwaves. Along with these brightness temperature observations, ESA also disseminates retrievals of surface soil moisture that are derived ...

Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data

NASA Astrophysics Data System (ADS)

Zawadzki, Jaroslaw; Kędzior, Mateusz

2016-03-01

Monitoring of temporal and spatial soil moisture variability is an important issue, both from practical and scientific point of view. It is well known that passive, L-band, radiometric measurements provide best soil moisture estimates. Unfortunately as it was observed during Soil Moisture and Ocean Salinity (SMOS) mission, which was specially dedicated to measure soil moisture, these measurements suffer significant data loss. It is caused mainly by radio frequency interference (RFI) which strongly contaminates Central Europe and even in particularly unfavorable conditions, might prevent these data from being used for regional or watershed scale analysis. Nevertheless, it is highly awaited by researchers to receive statistically significant information on soil moisture over the area of a big watershed. One of such watersheds, the Odra (Oder) river watershed, lies in three European countries - Poland, Germany and the Czech Republic. The area of the Odra river watershed is equal to 118,861 km2 making it the second most important river in Poland as well as one of the most significant one in Central Europe. This paper examines the SMOS soil moisture data in the Odra river watershed in the period from 2010 to 2012. This attempt was made to check the possibility of assessing, from the low spatial resolution observations of SMOS, useful information that could be exploited for practical aims in watershed scale, for example, in water storage models even while moderate RFI takes place. Such studies, performed over the area of a large watershed, were recommended by researchers in order to obtain statistically significant results. To meet these expectations, Centre Aval de Traitement des Donnes SMOS (CATDS), 3-days averaged data, together with Global Land Data Assimilation System (GLDAS) National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab (NOAH) model 0.25 soil moisture values were used for statistical analyses and mutual

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to

Investigation of Lake Water Salinity by Using Four-Band Salinity Algorithm on WorldView-2 Satellite Image for a Saline Industrial Lake

NASA Astrophysics Data System (ADS)

Budakoǧlu, Murat; Karaman, Muhittin; Damla Uça Avcı, Z.; Kumral, Mustafa; Geredeli (Yılmaz), Serpil

2014-05-01

Salinity of a lake is an important characteristic since, these are potentially industrial lakes and the degree of salinity can significantly be used for determination of mineral resources and for the production management. In the literature, there are many studies of using satellite data for salinity related lake studies such as determination of salinity distribution and detection of potential freshwater sources in less salt concentrated regions. As the study area Lake Acigol, located in Denizli (Turkey) was selected. With it's saline environment, it's the major sodium sulphate production resource of Turkey. In this study, remote sensing data and data from a field study was used and correlated. Remote sensing is an efficient tool to monitor and analyze lake properties by using it complementary to field data. Worldview-2 satellite data was used in this study which consists of 8 bands. At the same time with the satellite data acquisition, a field study was conducted to collect the salinity values in 17 points of the laker with using YSI 556 Multiparametre for measurements. The values were measured as salinity amount in grams per kilogram solution and obtained as ppt unit. It was observed that the values vary from 34 ppt - 40.1 ppt and the average is 38.056 ppt. In Thalassic serie, the lake was in mixoeuhaline state in the time of issue. As a first step, ATCOR correction was performed on satellite image for atmospheric correction. There were some clouds on the lake field, hence it was decided to continue the study by using the 12 sampling points which were clear on the image. Then, for each sampling point, a spectral value was obtained by calculating the average at a 11*11 neighborhood. The relation between the spectral reflectance values and the salinity was investigated. The 4-band algorithm, which was used for determination of chlorophyll-a distribution in highly turbid coastal environment by Wei (2012) was applied. Salinity α (Λi-1 / Λj-1) * (Λk-1 / Λm-1) (i

Long-term ELBARA-II Assistance to SMOS Land Product and Algorithm Validation at the Valencia Anchor Station (MELBEX Experiment 2010-2013)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto; Wigneron, Jean-Pierre; Schwank, Mike; Miernecki, Maciej; Kerr, Yann; Casal, Tania; Delwart, Steven; Fernandez-Moran, Roberto; Mecklenburg, Susanne; Coll Pajaron, M. Amparo; Salgado Hernanz, Paula

The main activity of the Valencia Anchor Station (VAS) is currently now to support the validation of SMOS (Soil Moisture and Ocean Salinity) Level 2 and 3 land products (soil moisture, SM, and vegetation optical depth, TAU). With this aim, the European Space Agency (ESA) has provided the Climatology from Satellites Group of the University of Valencia with an ELBARA-II microwave radiometer under a loan agreement since September 2009. During this time, brightness temperatures (TB) have continuously been acquired, except during normal maintenance or minor repair interruptions. ELBARA-II is an L-band dual-polarization radiometer with two channels (1400-1418 MHz, 1409-1427 MHz). It is continuously measuring over a vineyard field (El Renegado, Caudete de las Fuentes, Valencia) from a 15 m platform with a constant protocol for calibration and angular scanning measurements with the aim to assisting the validation of SMOS land products and the calibration of the L-MEB (L-Band Emission of the Biosphere) -basis for the SMOS Level 2 Land Processor- over the VAS validation site. One of the advantages of using the VAS site is the possibility of studying two different environmental conditions along the year. While the vine cycle extends mainly between April and October, during the rest of the year the area remains under bare soil conditions, adequate for the calibration of the soil model. The measurement protocol currently running has shown to be robust during the whole operation time and will be extended in time as much as possible to continue providing a long-term data set of ELBARA-II TB measurements and retrieved SM and TAU. This data set is also showing to be useful in support of SMOS scientific activities: the VAS area and, specifically the ELBARA-II site, offer good conditions to control the long-term evolution of SMOS Level 2 and Level 3 land products and interpret eventual anomalies that may obscure sensor hidden biases. In addition, SM and TAU that are currently

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

NASA Technical Reports Server (NTRS)

Kim, Edward

2012-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

How Different are SMOS Morning and Evening Observations?

NASA Astrophysics Data System (ADS)

Rowlandson, T. L.; Hornbuckle, B. K.

2010-12-01

The Soil Moisture Ocean Salinity (SMOS) satellite was launched by the European Space Agency in November, 2009, to make measurements of soil moisture at L-band in a 40 km x 40 km footprint, making passes over the north central region of the United States at 6am and 6pm approximately, with the intent of having passes at least every 3 days. No comparisons between 6am and 6pm have been made. The NASA Soil Moisture Active Passive (SMAP) intends to use only 6am data because of concerns of the quality of the data for 6pm passes. Brightness temperature outputs of the SMOS data were examined for both the 6am and 6pm passes to determine if changes in measurement exist for days when there is no rainfall. Changes in the brightness temperature can result from changes in internal water content of the crop, which we currently do not have the ability to accurately determine, presence of external water on the canopy, which in this study will be limited to dew, changes in canopy and soil temperature, and changes in soil moisture. The first step taken in this project was to investigating changes between the 6am and 6pm measurements that may result from the presence of dew on the canopy. Land and airborne L-band radiometers have shown that dew on a crop canopy provides a source of error in the measurements of surface soil moisture. The magnitude and sign of the error appears to be crop dependent. The empirical model of RH>90% has been used extensively to simulate dew duration. At the Iowa Validation site in Ames, Iowa, relative humidity was measured above the crop canopy, in both corn and soybeans, and within the crop canopy. Comparisons were made between the relative humidity measured above the canopy to that measured within the canopy at 3 locations within the field. These values were also compared to relative humidity measured at a standard weather station near the field site. These measurements were used to define a more appropriate relative humidity threshold for the central

Soil salinity assessment through satellite thermography for different irrigated and rainfed crops

NASA Astrophysics Data System (ADS)

Ivushkin, Konstantin; Bartholomeus, Harm; Bregt, Arnold K.; Pulatov, Alim; Bui, Elisabeth N.; Wilford, John

2018-06-01

The use of canopy thermography is an innovative approach for salinity stress detection in plants. But its applicability for landscape scale studies using satellite sensors is still not well investigated. The aim of this research is to test the satellite thermography soil salinity assessment approach on a study area with different crops, grown both in irrigated and rainfed conditions, to evaluate whether the approach has general applicability. Four study areas in four different states of Australia were selected to give broad representation of different crops cultivated under irrigated and rainfed conditions. The soil salinity map was prepared by the staff of Geoscience Australia and CSIRO Land and Water and it is based on thorough soil sampling together with environmental modelling. Remote sensing data was captured by the Landsat 5 TM satellite. In the analysis we used vegetation indices and brightness temperature as an indicator for canopy temperature. Applying analysis of variance and time series we have investigated the applicability of satellite remote sensing of canopy temperature as an approach of soil salinity assessment for different crops grown under irrigated and rainfed conditions. We concluded that in all cases average canopy temperatures were significantly correlated with soil salinity of the area. This relation is valid for all investigated crops, grown both irrigated and rainfed. Nevertheless, crop type does influence the strength of the relations. In our case cotton shows only minor temperature difference compared to other vegetation classes. The strongest relations between canopy temperature and soil salinity were observed at the moment of a maximum green biomass of the crops which is thus considered to be the best time for application of the approach.

Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates

NASA Astrophysics Data System (ADS)

Sánchez-Ruiz, Sergio; Piles, María; Sánchez, Nilda; Martínez-Fernández, José; Vall-llossera, Mercè; Camps, Adriano

2014-08-01

Sensors in the range of visible and near-shortwave-thermal infrared regions can be used in combination with passive microwave observations to provide soil moisture maps at much higher spatial resolution than the original resolution of current radiometers. To do so, a new downscaling algorithm ultimately based on the land surface temperature (LST) - Normalized Difference Vegetation Index (NDVI) - Brightness Temperature (TB) relationship is used, in which shortwave infrared indices are used as vegetation descriptors, instead of the more common near infrared ones. The theoretical basis of those indices, calculated as the normalized ratio of the 1240, 1640 and 2130 nm shortwave infrared (SWIR) bands and the 858 nm near infrared (NIR) band indicate that they are able to provide estimates of the vegetation water content. These so-called water indices extracted from MODIS products, have been used together with MODIS LST, and SMOS TB to improve the spatial resolution of ∼40 km SMOS soil moisture estimates. The aim was to retrieve soil moisture maps with the same accuracy as SMOS, but at the same resolution of the MODIS dataset, i.e., 500 m, which were then compared against in situ measurements from the REMEDHUS network in Spain. Results using two years of SMOS and MODIS data showed a similar performance for the four indices, with slightly better results when using the index derived from the first SWIR band. For the areal-average, a coefficient of correlation (R) of ∼0.61 and ∼0.72 for the morning and afternoon orbits, respectively, and a centered root mean square difference (cRMSD) of ∼0.04 m3 m-3 for both orbits was obtained. A twofold improvement of the current versions of this downscaling approach has been achieved by using more frequent and higher spatial resolution water indexes as vegetation descriptors: (1) the spatial resolution of the resulting soil moisture maps can be enhanced from ∼40 km up to 500 m, and (2) more accurate soil moisture maps (in terms

Clarifications on the "Comparison Between SMOS, VUA, ASCAT, and ECMWF Soil Moisture Products Over Four Watersheds in U.S."

NASA Technical Reports Server (NTRS)

Wagner, Wolfgang; Luca, Brocca; Naeimi, Vahid; Reichle, Rolf; Draper, Clara; de Jeu, Richard; Ryu, Dongryeol; Su, Chun-Hsu; Western, Andrew; Calvet, Jean-Christophe;

Assimilation of Smos Observations to Generate a Prototype SMAP Level 4 Surface and Root-Zone Soil Moisture Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Crow, Wade T.; Koster, Randal D.; Kimball, John

2012-01-01

The Soil Moisture Active and Passive (SMAP; [1]) mission is being implemented by NASA for launch in October 2014. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high-resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. The Soil Moisture and Ocean Salinity (SMOS; [2]) mission was launched by ESA in November 2009 and has since been observing L-band (1.4 GHz) upwelling passive microwaves. In this paper we describe our use of SMOS brightness temperature observations to generate a prototype of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product [5].

A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

NASA Astrophysics Data System (ADS)

Fernandez-Moran, R.; Wigneron, J.-P.; De Lannoy, G.; Lopez-Baeza, E.; Parrens, M.; Mialon, A.; Mahmoodi, A.; Al-Yaari, A.; Bircher, S.; Al Bitar, A.; Richaume, P.; Kerr, Y.

2017-10-01

This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 - 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = -1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08-0.12 and 0.1-0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = -0.019 m3 m-3, ubRMSE = 0.062 m3 m-3 for the IGBP-based calibration; against R = 0.54, bias = -0.034 m3 m-3 and ubRMSE = 0.070 m3 m-3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the

Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

NASA Astrophysics Data System (ADS)

Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

2016-12-01

Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

NASA Technical Reports Server (NTRS)

Kim, Edward

2011-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

Precipitation estimation using L-Band and C-Band soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...

Snow depth retrieval from L-band satellite measurements on Arctic and Antarctic sea ice

NASA Astrophysics Data System (ADS)

Maaß, N.; Kaleschke, L.; Wever, N.; Lehning, M.; Nicolaus, M.; Rossmann, H. L.

2017-12-01

The passive microwave mission SMOS provides daily coverage of the polar regions and measures at a low frequency of 1.4 GHz (L-band). SMOS observations have been used to operationally retrieve sea ice thickness up to 1 m and to estimate snow depth in the Arctic for thicker ice. Here, we present how SMOS-retrieved snow depths compare with airborne measurements from NASA's Operation IceBridge mission (OIB) and with AMSR-2 satellite retrievals at higher frequencies, and we show first applications to Antarctic sea ice. In previous studies, SMOS and OIB snow depths showed good agreement on spatial scales from 50 to 1000 km for some days and disagreement for other days. Here, we present a more comprehensive comparison of OIB and SMOS snow depths in the Arctic for 2011 to 2015. We find that the SMOS retrieval works best for cold conditions and depends on auxiliary information on ice surface temperature, here provided by MODIS thermal imagery satellite data. However, comparing SMOS and OIB snow depths is difficult because of the different spatial resolutions (SMOS: 40 km, OIB: 40 m). Spatial variability within the SMOS footprint can lead to different snow conditions as seen from SMOS and OIB. Ideally the comparison is made for uniform conditions: Low lead and open water fraction, low spatial and temporal variability of ice surface temperature, no mixture of multi- and first-year ice. Under these conditions and cold temperatures (surface temperatures below -25°C), correlation coefficients between SMOS and OIB snow depths increase from 0.3 to 0.6. A finding from the comparison with AMSR-2 snow depths is that the SMOS-based maps depend less on the age of the sea ice than the maps derived from higher frequencies. Additionally, we show first results of SMOS snow depths for Antarctic sea ice. SMOS observations are compared to measurements of autonomous snow buoys drifting in the Weddell Sea since 2014. For a better comparability of these point measurements with SMOS data, we use

SMOS brightness temperature assimilation into the Community Land Model

NASA Astrophysics Data System (ADS)

Rains, Dominik; Han, Xujun; Lievens, Hans; Montzka, Carsten; Verhoest, Niko E. C.

2017-11-01

SMOS (Soil Moisture and Ocean Salinity mission) brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM) across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF) as well as to the Community Microwave Emission Model (CMEM). Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010-2015). Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 %) for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

Comparison Between AQUARIUS and SMOS brightness temperatures for Heterogeneous Land Areas

NASA Astrophysics Data System (ADS)

Benlloch, Amparo; Lopez-Baeza, Ernesto; Tenjo, Carolina; Navarro, Enrique

2016-07-01

Intercomparison between Aquarius and SMOS brightness temperatures (TBs) over land surfaces is more challenging than over oceans because land footprints are more heterogeneous. In this work we are comparing Aquarius and SMOS TBs under coherente conditions obtained both by considering similar areas, according to land uses and by stratifying by means of TVDI (Temperature Vegetation Dryness Index) that accounts for the dynamics of the vegetation instead of assuming static characteristics as in the previous approches. The area of study was chosen in central Spain where we could get a significant number of matches between both instruments. The study period corresponded to 2012-2014. SMOS level-3 data were obtained from the Centre Aval de Traitement des Données SMOS (CATDS) and Aquarius' from the Physical Oceanography Distributed Active Archive Center (PODAAC). Land uses were obtained from the Spanish SIOSE facility (Sistema de Informacion de Ocupacion del Suelo en España) that uses a scale of 1:25.000 and polygon geometrical structure layer. SIOSE is based on panchromatic and multispectral 2.5 m resolution SPOT-5 images together with Landsat-5 images and orthophotos from the Spanish Nacional Plan of Aerial Orthophotography (PNOA). TVDI values were obtained from MODIS operational products of land surface temperature and NDVI. SMOS ascending TBs were compared to inner-beam Aquarius descending half-orbit TBs coinciding over the study area at 06:00 h. The Aquarius inner beam has an incidence angle of 28,7º and SMOS data were considered for the 27,5º incidence angle. The SMOS products corresponded to version 2.6x (data before 31st Oct 2013) and version 2.7x (data after 1st Jan 2014). Intersections between both footprints were analysed under conditions of similar areas, land uses and TVDI values. For the latter (land uses/TVDI), a linear combination of SMOS land uses/TVDI was obtained to match the larger Aquarius footprint. A more physical approach is also under way

A Proposed Extension to the Soil Moisture and Ocean Salinity Level 2 Algorithm for Mixed Forest and Moderate Vegetation Pixels

NASA Technical Reports Server (NTRS)

Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward

2011-01-01

The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November 2009, provides global maps of soil moisture and ocean salinity by measuring the L-band (1.4 GHz) emission of the Earth's surface with a spatial resolution of 40-50 km.Uncertainty in the retrieval of soilmoisture over large heterogeneous areas such as SMOS pixels is expected, due to the non-linearity of the relationship between soil moisture and the microwave emission. The current baseline soilmoisture retrieval algorithm adopted by SMOS and implemented in the SMOS Level 2 (SMOS L2) processor partially accounts for the sub-pixel heterogeneity of the land surface, by modelling the individual contributions of different pixel fractions to the overall pixel emission. This retrieval approach is tested in this study using airborne L-band data over an area the size of a SMOS pixel characterised by a mix Eucalypt forest and moderate vegetation types (grassland and crops),with the objective of assessing its ability to correct for the soil moisture retrieval error induced by the land surface heterogeneity. A preliminary analysis using a traditional uniform pixel retrieval approach shows that the sub-pixel heterogeneity of land cover type causes significant errors in soil moisture retrieval (7.7%v/v RMSE, 2%v/v bias) in pixels characterised by a significant amount of forest (40-60%). Although the retrieval approach adopted by SMOS partially reduces this error, it is affected by errors beyond the SMOS target accuracy, presenting in particular a strong dry bias when a fraction of the pixel is occupied by forest (4.1%v/v RMSE,-3.1%v/v bias). An extension to the SMOS approach is proposed that accounts for the heterogeneity of vegetation optical depth within the SMOS pixel. The proposed approach is shown to significantly reduce the error in retrieved soil moisture (2.8%v/v RMSE, -0.3%v/v bias) in pixels characterised by a critical amount of forest (40-60%), at the limited cost of only a crude estimate of the

Evaluation of the validated soil moisture product from the SMAP radiometer

USDA-ARS?s Scientific Manuscript database

In this study, we used a multilinear regression approach to retrieve surface soil moisture from NASA’s Soil Moisture Active Passive (SMAP) satellite data to create a global dataset of surface soil moisture which is consistent with ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite retrieved sur...

SMOS Instrument Performance and Calibration after 3 Years in Orbit

NASA Astrophysics Data System (ADS)

Martin-Neira, Manuel; Corbella, Ignasi; Torres, Francesc; Kainulainen, Juha; Oliva, Roger; Closa, Josep; Cabot, François; Castro, Rita; Barbosa, Jose; Gutierrez, Antonio; Anterrieu, Eric; Tenerelli, Joe; Martin-Porqueras, Fernando; Buenadicha, Guillermo; Delwart, Steven; Crapolicchio, Raffaele; Suess, Martin

2013-04-01

ESA's Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit for already over 3 years which has allowed the calibration and data processing team consolidating both the calibration strategy and the Level-1 processor which transforms the raw visibility samples into polarimetric brightness temperature images. The payload on board SMOS, MIRAS, is quite unique in that it is the first microwave radiometer in space ever capable to generate wide field of view images at every snapshot measurement. This means that most of the calibration as well as image processing techniques are being developed for the first time with little heritage from any previous space mission. Issues intrinsically attached to its wide field of view such as spatial ripples across the snapshot images are particular to MIRAS and to no other earlier radiometer. Even the fundamental theory behind the instrument was put at test, first on ground inside an electromagnetic compatibility chamber, and now in orbit when imaging the Cosmic Microwave Background Radiation of the cold sky. A groundbreaking effort is being carried out by the SMOS project team to understand and master all calibration and image reconstruction issues of this novel microwave interferometer payload. MIRAS in-orbit performance is driven by the amplitude of spatial ripples across the image and orbital and seasonal radiometer stability. Spatial ripples are unique to interferometric radiometers and are produced by (a) a limited knowledge of the antenna patterns and, in general, of the model of the instrument, (b) some fundamental limitations related to the inverse problem of image reconstruction in undetermined conditions and (c) subtle data processing inconsistencies which are discovered and corrected. To reduce the spatial ripples sea surface salinity retrievals are performed by first removing the brightness temperature spatial errors using a uniform region of the Pacific Ocean. However soil moisture retrievals cannot benefit of

The role of sea surface salinity in ENSO related water cycle anomaly

NASA Astrophysics Data System (ADS)

Tang, Wenqing; Yueh, Simon

2017-04-01

This study investigates the role of sea surface salinity (SSS) in the water cycle anomaly associated with El Niño Southern Oscillation (ENSO). The 2015-16 El Niño, one of the strongest ENSO events observed in centuries, coincident with unprecedented coverage of spacebased remote sensing of SSS over global oceans. We analyze three SSS data sets: from the NASA's missions of SMAP and Aquarius, and the ESA's Soil Moisture and Ocean Salinity (SMOS). One typical characteristics of an ENSO event is the zonal displacement of the Western equatorial Pacific Fresh Pool (WPFP). The edge of the pool extends eastward during El Niño, retreats westward during La Niña. For super El Niño, the eastern edge of WPFP extends much more east across the equatorial Pacific. Indeed, SSS from SMAP reveals much stronger eastward migration of WPFP starting in April 2015. The eastern edge of WPFP reached 140°W in March 2016, about 40° more eastward extension than Aquarius observed in previous years. In the following months from March to June 2016, WPFP retreated westward, coincident with the ending of this strong El Niño event [WMO, El Nino/La Nina update, 2016]. SMOS data shows similar feature, confirming that there is no systematic biases between SMAP and Aquarius retrievals. We examine the linkage between the observed SSS variation and ENSO related water cycle anomaly by integrated analysis of SSS data sets in conjunction with other satellite and in situ measurements on rain, wind, evaporation and ocean currents. Based on the governing equation of the mixed layer salt budget, the freshwater exchange between air-sea interfaces is estimated as residual of the mixed-layer salinity (MLS) temporal change and advection (Focean), as an alternative to evaporation minus precipitation (FE-P). We analyzed the spatial and temporal variation of Focean and FE-P to explore the anomalous signature in the oceanic and atmospheric branches of the water cycle associated with 2015/16 ENSO. The maximum

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

NASA Technical Reports Server (NTRS)

Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco

2010-01-01

Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An

Uncertainty Quantification of GEOS-5 L-band Radiative Transfer Model Parameters Using Bayesian Inference and SMOS Observations

NASA Technical Reports Server (NTRS)

DeLannoy, Gabrielle J. M.; Reichle, Rolf H.; Vrugt, Jasper A.

2013-01-01

Uncertainties in L-band (1.4 GHz) radiative transfer modeling (RTM) affect the simulation of brightness temperatures (Tb) over land and the inversion of satellite-observed Tb into soil moisture retrievals. In particular, accurate estimates of the microwave soil roughness, vegetation opacity and scattering albedo for large-scale applications are difficult to obtain from field studies and often lack an uncertainty estimate. Here, a Markov Chain Monte Carlo (MCMC) simulation method is used to determine satellite-scale estimates of RTM parameters and their posterior uncertainty by minimizing the misfit between long-term averages and standard deviations of simulated and observed Tb at a range of incidence angles, at horizontal and vertical polarization, and for morning and evening overpasses. Tb simulations are generated with the Goddard Earth Observing System (GEOS-5) and confronted with Tb observations from the Soil Moisture Ocean Salinity (SMOS) mission. The MCMC algorithm suggests that the relative uncertainty of the RTM parameter estimates is typically less than 25 of the maximum a posteriori density (MAP) parameter value. Furthermore, the actual root-mean-square-differences in long-term Tb averages and standard deviations are found consistent with the respective estimated total simulation and observation error standard deviations of m3.1K and s2.4K. It is also shown that the MAP parameter values estimated through MCMC simulation are in close agreement with those obtained with Particle Swarm Optimization (PSO).

Near-surface temperature and salinity stratification as observed with dual-sensor Lagrangian drifters deployed during SPURS-2 field campaign

NASA Astrophysics Data System (ADS)

Volkov, Denis; Dong, Shenfu; Goni, Gustavo; Lumpkin, Rick; Foltz, Greg

2017-04-01

Despite the importance of sea surface salinity (SSS) as an indicator of the hydrological cycle, many details of air-sea interaction responsible for freshwater fluxes and processes determining the near-surface salinity stratification and its variability are still poorly understood. This is primarily due to the lack of dedicated observations. The advent of satellites capable of monitoring SSS, such as the Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active-Passive (SMAP) missions, has greatly advanced our knowledge of SSS distribution and variability. However, the spatial resolution of satellite retrievals is too coarse to study the upper-ocean salinity changes due to patchy and transient rain events. Furthermore, the satellites measure salinity within the upper 1 cm skin layer, which can significantly differ from in situ SSS measured at 5 m depth by most Argo floats. Differences between the Aquarius and Argo SSS can be as large as ±0.5 psu. In order to study the near-surface salinity structure in great detail and to link the satellite observations of SSS with all the oceanic and atmospheric processes that control its variability, the National Aeronautics and Space Administration has initiated two field campaigns within the framework of Salinity Processes in the Upper-Ocean Regional Study (SPURS) project (http://spurs.jpl.nasa.gov/). The first campaign, SPURS-1, took place in the evaporation-dominated subtropical North Atlantic Ocean in 2012-2013. The second campaign, SPURS-2, focused on a 3×3° domain in the Inter-Tropical Convergence Zone (ITCZ) in the eastern equatorial Pacific (123.5-126.5°W and 8.5-11.5°N), where the near-surface salinity is strongly dominated by precipitation. The first SPURS-2 cruise took place in Aug-Sep 2016 on board the R/V Roger Revelle, during which a complex multi-instrument oceanographic survey was conducted. As part of this field campaign, we deployed 6 dual-sensor Lagrangian drifters, specifically designed

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from

Use of Physio-Hydrological Units for SMOS Validation at the Valencia Anchor Station Study Area

NASA Astrophysics Data System (ADS)

Millán-Scheiding, C.; Antolín, C.; Marco, J.; Soriano, M. P.; Torre, E.; Requena, F.; Carbó, E.; Cano, A.; Lopez-Baeza, E.

2009-04-01

The SMOS space mission will soil moisture over the continents and ocean surface salinity with the sufficient resolution to be used in global climate change studies. With the aim of validating SMOS land data and products at the Valencia Anchor Station site (VAS) in a Mediterranean Ecosystem area of Spain, we have designed a sample methodology using a subdivision of the landscape in environmental units related to the spatial variability of soil moisture (Millán-Scheiding, 2006; Lopez-Baeza, et al. 2008). These physio-hydrological units are heterogeneously structured entities which present a certain degree of internal uniformity of hydrological parameters. The units are delimited by integrating areas with the same physio-morphology, soil type, vegetation, geology and topography (Flugel, et al 2003; Millán-Scheiding et al, 2007). Each of these units presented over the same pedological characteristics, vegetation cover, and landscape position should have a certain degree of internal uniformity in its hydrological parameters and therefore similar soil moisture (SM). The main assumption for each unit is that the dynamical variation of the hydrological parameters within one unit should be minimum compared to the dynamics of another unit. This methodology will hopefully provide an effective sampling design consisting of a reduced number of measuring points, sparsely distributed over the area, or alternatively, using SM validation networks where each sampling point is located where it is representative of the mean soil moisture of a complete unit area. The Experimental Plan for the SMOS Validation Rehearsal Campaign at the VAS area of April-May 2008 used this environmental subdivision in the selection and sampling of over 21.000 soil moisture points in a control area of 10 x 10 km2. The ground measurements were carried out during 4 nights corresponding to a drying out period of the soil. The sampling consisted of 700 plots with 4 volumetric SM cylinders and 7 Delta-T Theta

Mapping the low salinity Changjiang Diluted Water using satellite-retrieved colored dissolved organic matter (CDOM) in the East China Sea during high river flow season

NASA Astrophysics Data System (ADS)

Sasaki, Hiroaki; Siswanto, Eko; Nishiuchi, Kou; Tanaka, Katsuhisa; Hasegawa, Toru; Ishizaka, Joji

2008-02-01

Absorption coefficients of colored dissolved organic matter (CDOM) [a g(λ)] were measured and relationship with salinity was derived in the East China Sea (ECS) during summer when amount of the Changjiang River discharge is large. Low salinity Changjiang Diluted Water (CDW) was observed widely in the shelf region and was considered to be the main origin of CDOM, resulting in a strong relationship between salinity and a g(λ). Error of satellite a g(λ) estimated by the present ocean color algorithm could be corrected by satellite-retrieved chlorophyll data. Satellite-retrieved salinity could be predicted with about +/-1.0 accuracy from satellite a g(λ) and the relation between salinity and a g(λ). Our study suggests that satellite-derived a g(λ) can be an indicator of the low salinity CDW during summer.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Potential of bias correction for downscaling passive microwave and soil moisture data

USDA-ARS?s Scientific Manuscript database

Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

MIRAS characterization and monitoring during the SMOS In-Orbit Commissioning Phase

NASA Astrophysics Data System (ADS)

Corbella, I.; Torres, F.; Martin-Neira, M.; Duffo, N.; González-Gambau, V.; Camps, A.; Vall-Llossera, M.

2009-04-01

1 Introduction The Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) is the single payload of the Soil Moisture and Ocean Salinity (SMOS) mission. The instrument was completed in early 2007 and thoroughly tested both in anechoic chamber and vacuum thermal chamber during 2007. It was integrated to the platform in early 2008 and re-tested, including compatibility, during 2008. At present, the whole satellite is stowed and waiting to be launched during 2009. In two weeks after launch, the satellite will be in the final orbit with all deployments completed. Then the In-Orbit Commissioning Phase will start, having an estimated duration of 5.5 months. During this phase, the instrument modes of operation will be systematically checked and the calibration parameters will be fully characterized in real conditions. Also, the first brightness temperature images will be obtained in order to assess the overall retrieval procedures including inversion. In the end, the objective of the In-Orbit Commissioning Phase is to provide verification that the payload meets the scientific requirements of the mission. The general design and planning of the In-Orbit Commissioning Phase is given in [1]. This abstract presents the foreseen activities to be performed during this phase by the UPC team. Just after the start of the In-Orbit Commissioning Phase, the instrument will be commanded to perform a sequence of operations oriented at providing a full characterization in terms of calibration parameters. The idea is to reproduce the results obtained during the tests carried out on ground [2]. In particular, the following issues will be covered: Thermal Stability: To provide understanding of both the intra-orbit and inter-orbit temperature variations. The instrument will be continuously operating during a number of orbits while all temperature sensors being monitored. Electrical Stability: To re-compute all internal calibration parameters (gains, offsets, receiver noise temperatures

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Neural network retrieval of soil moisture: application to SMOS

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Kolasssa, Jana; Jimenez, Carlos; Cabot, Francois; Mahmoodi, Ali

2014-05-01

We present an efficient statistical soil moisture (SM) retrieval method using SMOS brightness temperatures (BTs) complemented with MODIS NDVI and ASCAT backscattering data. The method is based on a feed-forward neural network (hereafter NN) trained with SM from ECMWF model predictions or from the SMOS operational algorithm. The best compromise to retrieve SM with NNs from SMOS brightness temperatures in a large fraction of the swath (~ 670 km) is to use incidence angles from 25 to 60 degrees (in 7 bins of 5 deg width) for both H and V polarizations. The correlation coefficient (R) of the SM retrieved by the NN and the reference SM dataset (ECMWF or SMOS L3) is 0.8. The correlation coefficient increases to 0.91 when adding as input MODIS NDVI, ECOCLIMAP sand and clay fractions and one of the following data: (i) active microwaves observations (ASCAT backscattering coefficient at 40 deg incidence angle), (ii) ECMWF soil temperature. Finally, the correlation coefficient increases to R=0.94 when using a normalization index computed locally for each latitude-longitude point with the maximum and minimum BTs and the associated SM values from the local time series. Global maps of SM obtained with NNs reproduce well the spatial structures present in the reference SM datasets, implying that the NN works well for a wide range of ecosystems and physical conditions. In addition, the results of the NNs have been evaluated at selected locations for which in situ measurements are available such as the USDA-ARS watersheds (USA), the OzNet network (AUS) and USDA-NRCS SCAN network (USA). The time series of SM obtained with NNs reproduce the temporal behavior measured with in situ sensors. For well known sites where the in situ measurement is representative of a 40 km scale like the Little Washita watershed, the NN models show a very high correlation of (R = 0.8-0.9) and a low standard deviation of 0.02-0.04 m3/m3 with respect to the in situ measurements. When comparing with all the in

Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain)

NASA Astrophysics Data System (ADS)

González-Zamora, Ángel; Sánchez, Nilda; Martínez-Fernández, José; Gumuzzio, Ángela; Piles, María; Olmedo, Estrella

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture and the new L3 product from the Barcelona Expert Center (BEC) were validated from January 2010 to June 2014 using two in situ networks in Spain. The first network is the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS), which has been extensively used for validating remotely sensed observations of soil moisture. REMEDHUS can be considered a small-scale network that covers a 1300 km2 region. The second network is a large-scale network that covers the main part of the Duero Basin (65,000 km2). At an existing meteorological network in the Castilla y Leon region (Inforiego), soil moisture probes were installed in 2012 to provide data until 2014. Comparisons of the temporal series using different strategies (total average, land use, and soil type) as well as using the collocated data at each location were performed. Additionally, spatial correlations on each date were computed for specific days. Finally, an improved version of the Triple Collocation (TC) method, i.e., the Extended Triple Collocation (ETC), was used to compare satellite and in situ soil moisture estimates with outputs of the Soil Water Balance Model Green-Ampt (SWBM-GA). The results of this work showed that SMOS estimates were consistent with in situ measurements in the time series comparisons, with Pearson correlation coefficients (R) and an Agreement Index (AI) higher than 0.8 for the total average and the land-use averages and higher than 0.85 for the soil-texture averages. The results obtained at the Inforiego network showed slightly better results than REMEDHUS, which may be related to the larger scale of the former network. Moreover, the best results were obtained when all networks were jointly considered. In contrast, the spatial matching produced worse results for all the cases studied. These results showed that the recent reprocessing of the L2 products (v5.51) improved

Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

NASA Astrophysics Data System (ADS)

Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.

2017-04-01

From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only

Mechanisms for Seasonal and Interannual Sea Surface Salinity Variability in the Indian Ocean

NASA Astrophysics Data System (ADS)

Köhler, J.; Stammer, D.; Serra, N.; Bryan, F.

2016-12-01

Space-borne salinity data in the Indian Ocean are analyzed over the period 2000-2015 based on data from the European Space Agency's (ESA) "Soil Moisture and Ocean Salinity" (SMOS) and the National Aeronautical Space Agency's (NASA) "Aquarius/SAC-D" missions. The seasonal variability is the dominant mode of sea surface salinity (SSS) variability in the Indian Ocean, accounting for more than 50% of salinity variance. Through a combined analysis of the satellite and ARGO data, dominant forcing terms for seasonal salinity changes are identified. It is found, that E-P controls seasonal salinity tendency in the western Indian Ocean, where the ITCZ has a strong seasonal cycle. In contrast, Ekman advection is the dominant term in the northern and eastern equatorial Indian Ocean. The influence of vertical processes on the salinity tendency is enhanced in coastal upwelling regions and south of the equator due to mid-ocean upwelling. Jointly those processes can explain most of the observed seasonal cycle with a correlation of 0.85 and an RMS difference of 0.07/month. However, the detailed composition of driving terms depends on underlying data products. In general, our study confirms previous results from Lisan Yu (2011); however, in the eastern Indian Ocean contrasting results indicate the leading role of meridional Ekman advection to the seasonal salinity tendency instead of surface external forces due to precipitation. The inferred dominant salinity budget terms are confirmed by results obtained from a high resolution NCAR Core model run driven by NCEP forcing fields. From an EOF analysis of the salinity fields after substracting the annual and semiannual cycle we found that the first EOF mode explains more than 20% of salinity variance. The first principal component of SSS EOF is correlated with the Indian Ocean Dipole Mode Index. Nevertheless the EOF pattern shows a meridional tripole structure, while the IOD describes a zonal SST dipole (Saji et al, 1999).

L-band Dielectric Constant Measurements of Seawater (Oral presentation and SMOS Poster)

NASA Technical Reports Server (NTRS)

Lang, Roger H.; Utku, Cuneyt; LeVine, David M.

2003-01-01

This paper describes a resonant cavity technique for the measurement of the dielectric constant of seawater as a function of its salinity. Accurate relationships between salinity and dielectric constant (which determines emissivity) are needed for sensor systems such as SMOS and Aquarius that will monitor salinity from space in the near future. The purpose of the new measurements is to establish the dependence of the dielectric constant of seawater on salinity in contemporary units (e.g. psu) and to take advantage of modern instrumentation to increase the accuracy of these measurements. The measurement device is a brass cylindrical cavity 16cm in diameter and 7cm in height. The seawater is introduced into the cavity through a slender glass tube having an inner diameter of 0.1 mm. By assuming that this small amount of seawater slightly perturbs the internal fields in the cavity, perturbation theory can be employed. A simple formula results relating the real part of the dielectric constant to the change in resonant frequency of the cavity. In a similar manner, the imaginary part of the dielectric constant is related to the change in the cavity s Q. The expected accuracy of the cavity technique is better than 1% for the real part and 1 to 2% for the imaginary part. Presently, measurements of methanol have been made and agree with precision measurements in the literature to within 1% in both real and imaginary parts. Measurements have been made of the dielectric constant of seawater samples from Ocean Scientific in the United Kingdom with salinities of 10, 30, 35 and 38 psu. All measurements were made at room temperature. Plans to make measurements at a range of temperatures and salinities will be discussed.

Comparisons of evening and morning SMOS passes over the Midwest United States

USDA-ARS?s Scientific Manuscript database

This study investigates differences in the soil moisture product and brightness temperatures between 6 pm and 6 am local solar time, when the SMOS passes for a region in north-central Iowa. This region consists of 69 SMOS pixels and has uniform land-cover, consisting of maize and soybean row crops. ...

Soil moisture on Polish territory - comparison of satellite and ground-based measurements

NASA Astrophysics Data System (ADS)

Rojek, Edyta; Łukowski, Mateusz; Marczewski, Wojciech; Usowicz, Bogusław

2014-05-01

Assessment of water resources due to changing climatic conditions in time and space is still very uncertain. The territory of Poland has a limited resource of waters, occasionally resulting in small agricultural droughts. From the other side intense rainfalls, floods or run-offs, causing soil erosion are observed. Therefore, it is important to predict and prevent of this adverse phenomena. Huge spatial variability of soil moisture does not allow for accurate estimation of its distribution using ground-based measurements. SMOS soil moisture data are quite much inherently consistent in time and space, but their validation is still a challenge for further use in the climate and hydrology studies. This is the motivation for the research: to examine soil moisture from SMOS and ground based stations of the SWEX network held over eastern Poland. The presented results are related to changes of the soil moisture on regional scales for Poland in the period 2010-2013. Some results with SMOS L2 data are extended on continental scales for Europe. Time series from ground and satellite SMOS data sources were compared by regression methods. The region of Poland indicates clearly some genetic spatial distributions in weekly averaged values. In continental scales, the country territory contrasts evidently to Lithuania and in Polesie, and indicates seasonal cycling observed in archives and well known traditional records. The central part of Poland is repeatedly susceptible on droughts with soil moisture values ranging from about 0.02 to 0.20 m3 m-3. SMOS data allows on creating systematic drought data for Poland and watching annual changes, and differences to other drought services kept on national scales for agricultural purposes. We bound that drought susceptibility to the content of sand clay components and the land use there. Lack of rainfall in the late 2011 summer, caused a significant deficit of water in soil moisture content (below 0.05 m3 m-3) throughout the entire country

Salinity Remote Sensing and the Study of the Global Water Cycle

NASA Technical Reports Server (NTRS)

Lagerloef, G. S. E.; LeVine, David M.; Chao, Y.; Colomb, F. Raul; Font, J.

2007-01-01

The SMOS and AquariusISAC-D satellite missions will begin a new era to map the global sea surface salinity (SSS) field and its variability from space within the next twothree years. They will provide critical data needed to study the interactions between the ocean circulation, global water cycle and climate. Key scientific issues to address are (1) mapping large expanses of the ocean where conventional SSS data do not yet exist, (2) understanding the seasonal and interannual SSS variations and the link to precipitation, evaporation and sea-ice patterns, (3) links between SSS and variations in the oceanic overturning circulation, (4) air-sea coupling processes in the tropics that influence El Nino, and (4) closing the marine freshwater budget. There is a growing body of oceanographic evidence in the form of salinity trends that portend significant changes in the hydrologic cycle. Over the past several decades, highlatitude oceans have become fresher while the subtropical oceans have become saltier. This change is slowly spreading into the subsurface ocean layers and may be affecting the strength of the ocean's therrnohaline overturning circulation. Salinity is directly linked to the ocean dynamics through the density distribution, and provides an important signature of the global water cycle. The distribution and variation of oceanic salinity is therefore attracting increasing scientific attention due to the relationship to the global water cycle and its influence on circulation, mixing, and climate processes. The oceans dominate the water cycle by providing 86% of global surface evaporation (E) and receiving 78% of global precipitation (P). Regional differences in E-P, land runoff, and the melting or freezing of ice affect the salinity of surface water. Direct observations of E-P over the ocean have large uncertainty, with discrepancies between the various state-of-the-art precipitation analyses of a factor of two or more in many regions. Quantifying the climatic

SMOS and AMSR-2 soil moisture evaluation using representative monitoring sites in southern Australia

NASA Astrophysics Data System (ADS)

Walker, J. P.; Mei Sun, M. S.; Rudiger, C.; Parinussa, R.; Koike, T.; Kerr, Y. H.

2016-12-01

The performance of soil moisture products from AMSR-2 and SMOS were evaluated against representative surface soil moisture stations within the Yanco study area in the Murrumbidgee Catchment, in southeast Australia. AMSR-2 Level 3 (L3) soil moisture products retrieved from two sets of brightness temperatures using the Japanese Aerospace exploration Agency (JAXA) and the Land Parameter Retrieval Model (LPRM) algorithms were included. For the LPRM algorithm, two different parameterization methods were applied. In the case of SMOS, two versions of the SMOS L3 soil moisture product were assessed. Results based on using "random" and representative stations to evaluate the products were contrasted. The latest versions of the JAXA (JX2) and LPRM (LP3) products were found to perform better than the earlier versions (JX1, LP1 and LP2). Moreover, soil moisture retrieval based on the latter version of brightness temperature and parameterization scheme improved when C-band observations were used, as opposed to the X-band data. Yet, X-band retrievals were found to perform better than C-band. Inter-comparing AMSR-2 X-band products from different acquisition times showed a better performance for 1:30 pm overpasses whereas SMOS 6:00 am retrievals were found to perform the best. The mean average error (MAE) goal accuracy of the AMSR-2 mission (MAE < 0.08 m3/m3) was met by both versions of the JAXA products, the LPRM X-band products retrieved from the reprocessed version of brightness temperatures, and both versions of SMOS products. Nevertheless, none of the products achieved the SMOS target accuracy of 0.04 m3/m3. Finally, the product performance depended on the statistics used in their evaluation; based on temporal and absolute accuracy JX2 is recommended, whereas LP3 X-band 1:30 pm and SMOS2 6:00 am are recommended based on temporal accuracy alone.

Seasonal Variability of Salt Transports in the Northern Indian Ocean

NASA Astrophysics Data System (ADS)

D'Addezio, J. M.; Bulusu, S.

2016-02-01

Due to limited observational data in the Indian Ocean compared to other regions of the global ocean, past work on the Northern Indian Ocean (NIO) has relied heavily upon model analysis to study the variability of regional salinity advection caused by the monsoon seasons. With the launch of the Soil Moisture and Ocean Salinity (SMOS) satellite in 2009 and the Aquarius SAC-D mission in 2011 (ended on June 7, 2011), remotely sensed, synoptic scale sea surface salinity (SSS) data is now readily available to study this dynamic region. The new observational data has allowed us to revisit the region to analyze seasonal variability of salinity advection in the NIO using several modeled products, the Aquarius and SMOS satellites, and Argo floats data. The model simulations include the Consortium for Estimating the Circulation and Climate of the Ocean (ECCO2), European Centre for Medium-Range Weather Forecasts - Ocean Reanalysis System 4 (ECMWF-ORSA4), Simple Ocean Data Assimilation (SODA) Reanalysis, and HYbrid Coordinate Ocean Model (HYCOM). Our analyses of salinity at the surface and at depths up to 200 m, surface salt transport in the top 5 m layer, and depth-integrated salt transports revealed different salinity processes in the NIO that are dominantly related to the semi-annual monsoons. Aquarius and SMOS prove useful tools for observing this dynamic region, and reveal some aspects of SSS that Argo cannot resolve. Meridional depth-integrated salt transports using the modeled products along 6°N revealed dominant advective processes from the surface towards near-bottom depths. Finally, a difference in subsurface salinity stratification causes many of the modeled products to incorrectly estimate the magnitude and seasonality of NIO barrier layer thickness (BLT) when compared to the Argo solution. This problem is also evident in model output from the Seychelles-Chagos Thermocline Ridge (SCTR), a region with strong air-sea teleconnections with the Arabian Sea.

Strategies for Validating and Directions for Employing SMOS Data, in the Cal-Val Project SWEX (3275)

NASA Astrophysics Data System (ADS)

Marczewski, Wojciech; Usowicz, Boguslaw; Usowicz, Jerzy; Romanov, Sergey; Maryskevych, Oksana; Nastula, Jolanta; Slominski, Jan; Zawadzki, Jaroslaw

2009-11-01

Earth land surface target of observations is naturally diversified in its physical and bio-physical properties. SMOS observation of SM (Soil Moisture) is highly dependent on proper physical and environmental data necessary, because SM is retrieved from the directly observable BT (Brightness Temperature) on the basis of these external data. That way, SMOS realizes a real data fusion performed NRT (Nearly Real Time) and thus needs validating. Global range of SMOS observations makes it generalizing the diversity on complex way engaging technical, modelling and organizational means. That is a new quality of EO (Earth Observations) in the matter of managing diversity of the target. The paper presents several proofs on employing external data by means of the SMOS software tools, for L1c and L2 data levels. Authors take validation in few selected sites in Poland, and describe their strategy for employing external data from ASAR, MERIS, and other auxiliary sources. Finally the conclusions come to understanding of a use of SMOS data, and seek ways of referencing SM in large scales to known results of the gravitational Mission GRACE.

L-Band Microwave Experiment On Russian Investigational Satellite, First Results And Comparison With SMOS Data

NASA Astrophysics Data System (ADS)

Smirnov, M.; Khaldin, A.

2013-12-01

The main scientific objective of mission with Zond-PP on Russian investigational satellite MKA-FKI No1 is development of techniques for retrieval: sea salinity in open oceans, soil moisture in global scales, vegetation state characteristics, sea ice characteristics. At the beginning stage of space experiments the main goals were to develop and test new space microwave radiometric instrument in order to solve technical objectives: investigation of RFI in L-band all over the globe, development and testing in-flight calibration techniques and others. First obtained results of our observations are presented. Zond-PP results were compared with MIRAS. For comparison were used results of brightness temperatures measurements obtained from Zond-PP and MIRAS in the same regions with minimal time difference. Results of comparison show general accordance in the brightness temperatures levels.

A technique for the determination of Louisiana marsh salinity zone from vegetation mapped by multispectral scanner data: A comparison of satellite and aircraft data

NASA Technical Reports Server (NTRS)

Butera, M. K.

1977-01-01

Vegetation in selected study areas on the Louisiana coast was mapped using low altitude aircraft and satellite (LANDSAT) multispectral scanner data. Fresh, brackish, and saline marshes were then determined from the remotely sensed presence of dominant indicator plant associations. Such vegetational classifications were achieved from data processed through a standard pattern recognition computer program. The marsh salinity zone maps from the aircraft and satellite data compared favorably within the broad salinity regimes. The salinity zone boundaries determined by remote sensing compared favorably with those interpolated from line-transect field observations from an earlier year.

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Sure, A.; Dikshit, O.

2017-12-01

Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

NASA Technical Reports Server (NTRS)

Magagi, Ramata; Berg, Aaron; Goita, Kalifa; Belair, Stephane; Jackson, Tom; Toth, B.; Walker, A.; McNairn, H.; O'Neill, P.; Moghdam. M;

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over Valencia Anchor Station by Using Downscaling Technique

NASA Astrophysics Data System (ADS)

Ansari Amoli, Abdolreza; Lopez-Baeza, Ernesto; Mahmoudi, Ali; Mahmoodi, Ali

2016-07-01

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over the Valencia Anchor Station by Using a Downscaling Technique Ansari Amoli, A.(1),Mahmoodi, A.(2) and Lopez-Baeza, E.(3) (1) Department of Earth Physics and Thermodynamics, University of Valencia, Spain (2) Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France (3) Department of Earth Physics and Thermodynamics, University of Valencia, Spain Soil moisture products from active sensors are not operationally available. Passive remote sensors return more accurate estimates, but their resolution is much coarser. One solution to overcome this problem is the synergy between radar and radiometric data by using disaggregation (downscaling) techniques. Few studies have been conducted to merge high resolution radar and coarse resolution radiometer measurements in order to obtain an intermediate resolution product. In this paper we present an algorithm using combined available SMAP (Soil Moisture Active and Passive) radar and SMOS (Soil Moisture and Ocean Salinity) radiometer measurements to estimate surface soil moisture over the Valencia Anchor Station (VAS), Valencia, Spain. The goal is to combine the respective attributes of the radar and radiometer observations to estimate soil moisture at a resolution of 3 km. The algorithm disaggregates the coarse resolution SMOS (15 km) radiometer brightness temperature product based on the spatial variation of the high resolution SMAP (3 km) radar backscatter. The disaggregation of the radiometer brightness temperature uses the radar backscatter spatial patterns within the radiometer footprint that are inferred from the radar measurements. For this reason the radar measurements within the radiometer footprint are scaled by parameters that are derived from the temporal fluctuations in the radar and radiometer measurements.

Four Decades of Microwave Satellite Soil Moisture Observations: Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.

2017-12-01

The satellite based passive and active microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Signifying the four decades of microwave remote sensing of soil moisture, this work aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy of retrieving soil moisture. We considered daily coverage, temporal performance, and spatial performance to assess the accuracy of products corresponding to eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product), using 1058 ISMN in-situ stations and the VIC LSM soil moisture simulations (VICSM) over the CONUS. Our analysis indicated that the daily coverage has increased from 30 % during 1980s to 85 % (during non-winter months) with the launch of dedicated soil moisture missions SMOS and SMAP. The temporal validation of passive and active soil moisture products with the ISMN data place the range of median RMSE as 0.06-0.10 m3/m3 and median correlation as 0.20-0.68. When TMI, AMSR-E and WindSAT are evaluated, the AMSR-E sensor is found to have produced the brightness temperatures with better quality, given that these sensors are paired with same retrieval algorithm (LPRM). The ASCAT product shows a significant improvement during the temporal validation of retrievals compared to its predecessor ERS, thanks to enhanced sensor configuration. The SMAP mission, through its improved sensor design and RFI handling, shows a high retrieval accuracy under all-topography conditions

Spatiotemporal monitoring of soil salinization in irrigated Tadla Plain (Morocco) using satellite spectral indices

NASA Astrophysics Data System (ADS)

El Harti, Abderrazak; Lhissou, Rachid; Chokmani, Karem; Ouzemou, Jamal-eddine; Hassouna, Mohamed; Bachaoui, El Mostafa; El Ghmari, Abderrahmene

2016-08-01

Soil salinization is major environmental issue in irrigated agricultural production. Conventional methods for salinization monitoring are time and money consuming and limited by the high spatiotemporal variability of this phenomenon. This work aims to propose a spatiotemporal monitoring method of soil salinization in the Tadla plain in central Morocco using spectral indices derived from Thematic Mapper (TM) and Operational Land Imager (OLI) data. Six Landsat TM/OLI satellite images acquired during 13 years period (2000-2013) coupled with in-situ electrical conductivity (EC) measurements were used to develop the proposed method. After radiometric and atmospheric correction of TM/OLI images, a new soil salinity index (OLI-SI) is proposed for soil EC estimation. Validation shows that this index allowed a satisfactory EC estimation in the Tadla irrigated perimeter with coefficient of determination R2 varying from 0.55 to 0.77 and a Root Mean Square Error (RMSE) ranging between 1.02 dS/m and 2.35 dS/m. The times-series of salinity maps produced over the Tadla plain using the proposed method show that salinity is decreasing in intensity and progressively increasing in spatial extent, over the 2000-2013 period. This trend resulted in a decrease in agricultural activities in the southwestern part of the perimeter, located in the hydraulic downstream.

Interannual and Decadal Changes in Salinity in the Oceanic Subtropical Gyres

NASA Astrophysics Data System (ADS)

Bulusu, Subrahmanyam

2017-04-01

There is evidence that the global water cycle has been undergoing an intensification over several decades as a response to increasing atmospheric temperatures, particularly in regions with skewed evaporation - precipitation (E-P) patterns such as the oceanic subtropical gyres. Moreover, observational data (rain gauges, etc.) are quite sparse over such areas due to the inaccessibility of open ocean regions. In this work, a comparison of observational and model simulations are conducted to highlight the potential applications of satellite derived salinity from NASA Aquarius Salinity mission, NASA Soil Moisture and Ocean Salinity (SMOS), and ESA's Soil Moisture Active Passive (SMAP). We explored spatial and temporal salinity changes (and trends) in surface and subsurface in the oceanic subtropical gyres using Argo floats salinity data, Simple Ocean Data Assimilation (SODA) reanalysis, Estimating the Circulations & Climate of the Ocean GECCO (German ECCO) model simulations, and Hybrid Coordinate Ocean Model (HYCOM). Our results based on SODA reanalysis reveals that a positive rising trend in sea surface salinity in the subtropical gyres emphasizing evidence for decadal intensification in the surface forcing in these regions. Zonal drift in the location of the salinity maximum of the south Pacific, north Atlantic, and south Indian regions implies a change in the mean near-surface currents responsible for advecting high salinity waters into the region. Also we found out that an overall salinity increase within the mixed layer, and a subsurface salinity decrease at depths greater than 200m in the global subtropical gyres over 61 years. We determine that freshwater fluxes at the air-sea interface are the primary drivers of the sea surface salinity (SSS) signature over these open ocean regions by quantifying the advective contribution within the surface layer. This was demonstrated through a mixed layer salinity budget in each subtropical gyre based on the vertically

Eddy-induced Sea Surface Salinity changes in the tropical Pacific

NASA Astrophysics Data System (ADS)

Delcroix, T. C.; Chaigneau, A.; Soviadan, D.; Boutin, J.

2017-12-01

We analyse the Sea Surface Salinity (SSS) signature of westward propagating mesoscale eddies in the tropical Pacific by collocating 5 years (2010-2015) of SMOS (Soil Moisture and Ocean Salinity) SSS and altimetry-derived sea level anomalies. The main characteristics of mesoscale eddies are first identified in SLA maps. Composite analyses in the Central and Eastern ITCZ regions then reveal regionally dependent impacts with opposite SSS anomalies for the cyclonic and anticyclonic eddies. In the Central region (where we have the largest meridional SSS gradient), we found dipole-like SSS changes with maximum anomalies on the leading edge of the eddy. In the Eastern region (where we have the largest near-surface vertical salinity gradient) we found monopole-like SSS changes with maximum anomalies in the eddy centre. These dipole/monopole patterns and the rotational sense of eddies suggest the dominant role of horizontal and vertical advection in the Central and Eastern ITCZ regions, respectively.

Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

NASA Technical Reports Server (NTRS)

Girotto, Manuela

2018-01-01

Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).

Dynamics of the Seychelles-Chagos Thermocline Ridge

NASA Astrophysics Data System (ADS)

Bulusu, S.

2016-02-01

The southwest tropical Indian Ocean (SWTIO) features a unique, seasonal upwelling of the thermocline also known as the Seychelles-Chagos Thermocline Ridge (SCTR). More recently, this ridge or "dome"-like feature in the thermocline depth at (55°E-65°E, 5°S-12°S) in the SWTIO has been linked to interannual variability in the semi-annual Indian Ocean monsoon seasons as well as the Madden-Julian Oscillation (MJO) and El Niño Southern Oscillation (ENSO). The SCTR is a region where the MJO is associated with strong SST variability. Normally more cyclones are found generated in this SCTR region when the thermocline is deeper, which has a positive relation to the arrival of a downwelling Rossby wave from the southeast tropical Indian Ocean. Previous studies have focused their efforts solely on sea surface temperature (SST) because they determined salinity variability to be low, but with the Soil Moisture and Ocean Salinity (SMOS), and Aquarius salinity missions new insight can be shed on the effects that the seasonal upwelling of the thermocline has on Sea Surface Salinity (SSS). Seasonal SSS anomalies these missions will reveal the magnitude of seasonal SSS variability, while Argo depth profiles will show the link between changes in subsurface salinity and temperature structure. A seasonal increase in SST and a decrease in SSS associated with the downwelling of the thermocline have also been shown to occasionally generate MJO events, an extremely important part of climate variability in the Indian ocean. Satellite derives salinity and Argo data can help link changes in surface and subsurface salinity structure to the generation of the important MJO events. This study uses satellite derived salinity from Soil Moisture and Ocean Salinity (SMOS), and Aquarius to see if these satellites can yield new information on seasonal and interannual surface variability. In this study barrier layer thickness (BLT) estimates will be derived from satellite measurements using a

The global SMOS Level 3 daily soil moisture and brightness temperature maps

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Mialon, Arnaud; Kerr, Yann H.; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Quesney, Arnaud; Mahmoodi, Ali; Tarot, Stéphane; Parrens, Marie; Al-Yaari, Amen; Pellarin, Thierry; Rodriguez-Fernandez, Nemesio; Wigneron, Jean-Pierre

2017-06-01

The objective of this paper is to present the multi-orbit (MO) surface soil moisture (SM) and angle-binned brightness temperature (TB) products for the SMOS (Soil Moisture and Ocean Salinity) mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS) makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD) compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD) using multi-angular dual-polarisation TB from MO. A subsidiary angle-binned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive) TB. The Level 3 SM V300 product is compared to the single-orbit (SO) retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM) are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an open licence and

Joint Assimilation of SMOS Brightness Temperature and GRACE Terrestrial Water Storage Observations for Improved Soil Moisture Estimation

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Rodell, Matthew

2017-01-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Joint assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for improved soil moisture estimation

NASA Astrophysics Data System (ADS)

Girotto, M.; Reichle, R. H.; De Lannoy, G.; Rodell, M.

2017-12-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0-5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Soil moisture extremes drive tree canopy death in 2011 Texas drought: multispectral (Landsat, NAIP) and L-band passive microwave remote sensing (SMOS-IC)

NASA Astrophysics Data System (ADS)

Swenson, J. J.; Schwantes, A. M.; Johnson, D. M.; Domec, J. C.; Wigneron, J. P.

2017-12-01

Climate change is bringing more frequent and intense droughts that are causing broad scale tree mortality events. Detecting regional drought stress is now more frequently monitored with passive microwave satellite sensing of soil moisture (SM) and vegetation water status (through the vegetation optical depth (VOD) index), that can be validated with in-situ measurements of soil moisture or corroborated with satellite multispectral indices of greenness. The detection of canopy death however marks the passing of a definitive physiological threshold. We compare soil moisture from the L-band SMOS-IC passive microwave product (2010-20176) to an accurate and detailed (30-m spatial resolution) map of canopy loss across the US state of Texas during the record breaking 2011 drought. The SMOS-IC product (25 km) is a new and simpler product of soil moisture and VOD that has been shown to be more accurate than past SMOS products and it is independent of ancillary data. Canopy loss was mapped from Landsat imagery trained with 186, 41 km2 subplots of classified National Agriculture Inventory Program color infrared aerial imagery recorded before and after the drought. Bringing these two datasets of disparate spatial resolution together and averaging them across the state, we find that areas with at least 25% tree cover that experienced the most canopy loss (highest quartile) had lower soil moisture compared to areas with less canopy loss in 2011. These areas with the most loss, experienced up to 9 weeks of the growing season at < 0.05 SM (m3/m3), while the rest of Texas forests, experienced just 1 week at that SM. The following years, 2012 - 2016, dropped below 0.05 SM very rarely (two weeks each in 2012 and 2015, and never for 2013, 2014, 2016). Forests during the drought of 2011 experienced the absolute lowest SM (0.031) and had the earliest onset of low SM across the 6 years analyzed. Analyzing areas of drought induced canopy loss with SM preceding and during drought across a

Evaluation of three different data fusion approaches that uses satellite soil moisture from different passive microwave sensors to construct one consistent climate record

NASA Astrophysics Data System (ADS)

van der Schalie, Robin; de Jeu, Richard; Kerr, Yann; Wigneron, Jean-Pierre; Rodríguez-Fernández, Nemesio; Al-Yaari, Amen; Drusch, Matthias; Mecklenburg, Susanne; Dolman, Han

2016-04-01

Datasets that are derived from satellite observations are becoming increasingly important for measuring key parameters of the Earth's climate and are therefore crucial in research on climate change, giving the opportunity to researchers to detect anomalies and long-term trends globally. One of these key parameters is soil moisture (SM), which has a large impact on water, energy and biogeochemical cycles worldwide. A long-term SM data record from active and passive microwave satellite observations was developed as part of ESA's Climate Change Initiative (ESA-CCI-SM, http://www.esa-soilmoisture-cci.org/). Currently the dataset covers a period from 1978 to 2014 and is updated regularly, observations from a several microwave satellites including: ERS-1, ERS-2, METOP-A, Nimbus 7 SMMR, DMSP SSM/I, TRMM TMI, Aqua AMSRE, Coriolis WindSat, and GCOM-W1 AMSR2. In 2009, ESA launched the Soil Moisture and Ocean Salinity (SMOS, Kerr et al., 2010) mission, carrying onboard a unique L-band radiometer, but its SM retrievals are not yet part of this dataset. Due to the different radiometric characteristics of SMOS, integrating SMOS into the ESA-CCI-SM dataset is not straight forward. Therefore several approaches have been tested to fuse soil moisture retrievals from SMOS and AMSRE, which currently forms the basis of the passive microwave part within ESA-CCI-SM project. These approaches are: 1. A Neural Network Fusion approach (Rodríguez-Fernández et al., 2015), 2. A regression approach (Wigneron et al., 2004; Al-Yaari et al., 2015) and 3. A radiative transfer based approach, using the Land Parameter Retrieval Model (Van der Schalie et al., 2016). This study evaluates the three different approaches and tests their skills against multiple datasets, including MERRA-Land, ERA-Interim/Land, the current ESA-CCI-SM v2.2 and in situ measurements from the International Soil Moisture Network and present a recommendation for the potential integration of SMOS soil moisture into the ESA

Validation of SURFEX Simulated Soil Moisture over the Valencia Anchor Station using SMOS products and in situ measurements.

NASA Astrophysics Data System (ADS)

Coll, M. Amparo; Khodayar, Samiro; Lopez-Baeza, Ernesto

2014-05-01

Soil moisture is an important variable in agriculture, hydrology, meteorology and related disciplines. Despite its importance, it is complicated to obtain an appropriate representation of this variable, mainly because of its high temporal and spatial variability. SVAT (Soil-Vegetation-Atmosphere-Transfer) models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the SURFEX (Surface Externalisée) model developed at the Centre National de Recherches Météorologiques (CNRM) at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the Valencia Anchor Station. SURFEX integrates the ISBA (Interaction Sol-Biosphère-Atmosphère; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) and we introduced the ECOCLIMAP for the description of land covers. The Valencia Anchor Station was chosen as a validation site for the SMOS (Soil Moisture and Ocean Salinity) mission and as one of the hydrometeorological sites for the HyMeX (HYdrological cycle in Mediterranean EXperiment) programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few number of small industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry-sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields to be compared with level-2 and level-3 soil moisture maps generated

Validation of the SMOS-MIRAS Soil Moisture Product (SML2UDP) in the Pampean Region of Argentina

NASA Astrophysics Data System (ADS)

Niclòs, Raquel; Rivas, Raúl; Sánchez, Juan Manuel; García-Santos, Vicente; Doña, Carolina; Valor, Enric; Holzman, Mauro; Bayala, Martín Ignacio; Carmona, Facundo; Ocampo, Dora; Soldano, Alvaro; Thibeault, Marc

2014-05-01

A validation campaign was carried out to evaluate the SMOS-MIRAS Soil Moisture (SM) SML2UDP product (v5.51) in the Pampean Region of Argentina on February 2013. The study area was selected because it is a vast area of flatlands containing quite homogeneous rainfed croplands, with prevalence of soybean crops, considered SMOS nominal land uses (i.e., crops with vegetation heights not exceeding 1 to 2 m by opposition to trees). Transects of ground SM measurements were collected by Delta-T ThetaProbe ML2x SM probes within four ISEA-4H9 DGG SMOS nodes. The SM data obtained by each probe transect in each parcel were checked by collecting soil samples in the same parcels at the same time and measuring their masses. The gravimetric method was used to obtain reference values. An uncertainty of ± 0.03 m3m-3 was obtained for the ML2x probes. Additionally, they were calibrated in the laboratory for different SMs by saturating and drying a specific and representative variety of soil samples collected from the experimental parcels (loam, clay loam and silt loam samples). This calibration showed again accurate operations for the ML2x probes, which even attain uncertainties of ±0.01 m3m-3, in agreement with the manufacturer. The comparison of the SM transect data collected during the campaign with the SMOS-MIRAS SML2UDP product values showed a negative bias between concurrent SMOS data and ground SM measurements, which means a slight SMOS-MIRAS underestimation, and a standard deviation of ± 0.06 m3m-3. The validation sites were selected taking as reference the locations of permanent SM stations property of the Argentinean Comisión Nacional de Actividades Espaciales (CONAE, National Commission of Space Activities), Instituto Nacional de Tecnología Agropecuaria (INTA, National Institute of Farming Technology) and Instituto de Hidrología de Llanuras (IHLLA, Plain Hydrology Institute). During the campaign several transects were carried out in the parcels where permanent SM

Satellite passive microwaves for monitoring deforestation and drought-induced carbon losses in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Brandt, M.; Wigneron, J. P.; Chave, J.; Tagesson, T.; Penuelas, J.; Ciais, P.; Rasmussen, K.; Tian, F.; Mbow, C.; Al-Yaari, A.; Rodriguez-Fernandez, N.; Zhang, W.; Kerr, Y. H.; Tucker, C. J.; Mialon, A.; Verger, A.; Fensholt, R.

2017-12-01

The African continent is facing one of the driest periods in the past three decades and continuing deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for an operational tool for monitoring carbon stock dynamics. Knowledge of the amount, distribution, and turnover of carbon in African vegetation is crucial for understanding the effects of human pressure and climate change, but the shortcomings of optical and radar satellite products and the lack of systematic field inventories have led to considerable uncertainty in documenting patterns and dynamics of carbon stocks, in particular for drylands. Static carbon maps have been developed, but the temporal dynamics of carbon stocks cannot be derived from the benchmark maps, impeding timely, repeated, and reliable carbon assessments. The Soil Moisture and Ocean Salinity (SMOS) mission launched in 2009 was the first passive microwave-based satellite system operating at L-band (1.4 GHz) frequency. The low frequencies allow the satellite to sense deep within the canopy layer with less influence by the green non-woody plant components. The vegetation optical depth (VOD) derived from SMOS, henceforth L-VOD, is thus less sensitive to saturation effects, marking an important step forward in the monitoring of carbon as a natural resource. In this study, we apply for the first time L-VOD to quantify the inter-annual dynamics of aboveground carbon stocks for the period 2010-2016. We use this new technique to document patterns of carbon gains and losses in sub-Saharan Africa with a focus of dryland response to recent dry years. Results show that drylands lost carbon at a rate of -0.06 Pg C y-1 associated with drying trends, while humid areas lost only -0.02 Pg C y-1. These trends reflect a high inter-annual variability with a very wet (2011) and a very dry year (2016) associated with carbon gains and losses respectively. This study demonstrates, first, the operational applicability of L

SOIL moisture data intercomparison

NASA Astrophysics Data System (ADS)

Kerr, Yann; Rodriguez-Frenandez, Nemesio; Al-Yaari, Amen; Parens, Marie; Molero, Beatriz; Mahmoodi, Ali; Mialon, Arnaud; Richaume, Philippe; Bindlish, Rajat; Mecklenburg, Susanne; Wigneron, Jean-Pierre

2016-04-01

The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. Subsequently, the satellite has been in operation for over 6 years while the retrieval algorithms from Level 1 to Level 2 underwent significant evolutions as knowledge improved. Other approaches for retrieval at Level 2 over land were also investigated while Level 3 and 4 were initiated. In this présentation these improvements are assessed by inter-comparisons of the current Level 2 (V620) against the previous version (V551) and new products either using neural networks or Level 3. In addition a global evaluation of different SMOS soil moisture (SM) products is performed comparing products with those of model simulations and other satellites (AMSR E/ AMSR2 and ASCAT). Finally, all products were evaluated against in situ measurements of soil moisture (SM). The study demonstrated that the V620 shows a significant improvement (including those at level1 improving level2)) with respect to the earlier version V551. Results also show that neural network based approaches can yield excellent results over areas where other products are poor. Finally, global comparison indicates that SMOS behaves very well when compared to other sensors/approaches and gives consistent results over all surfaces from very dry (African Sahel, Arizona), to wet (tropical rain forests). RFI (Radio Frequency Interference) is still an issue even though detection has been greatly improved while RFI sources in several areas of the world are significantly reduced. When compared to other satellite products, the analysis shows that SMOS achieves its expected goals and is globally consistent over different eco climate regions from low to high latitudes and throughout the seasons.

Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

2016-01-01

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products

USDA-ARS?s Scientific Manuscript database

The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...

Temporal variations of natural soil salinity in an arid environment using satellite images

NASA Astrophysics Data System (ADS)

Gutierrez, M.; Johnson, E.

2010-11-01

In many remote arid areas the scarce amount of conventional soil salinity data precludes detailed analyses of salinity variations for the purpose of predicting its impact on agricultural production. A tool that is an appropriate surrogate for on-ground testing in determining temporal variations of soil salinity is Landsat satellite data. In this study six Landsat scenes over El Cuervo, a closed basin adjacent to the middle Rio Conchos basin in northern Mexico, were used to show temporal variation of natural salts from 1986 to 2005. Natural salts were inferred from ground reference data and spectral responses. Transformations used were Tasseled Cap, Principal Components and several (band) ratios. Classification of each scene was performed from the development of Regions Of Interest derived from geochemical data collected by SGM, spectral responses derived from ENVI software, and a small amount of field data collected by the authors. The resultant land cover classes showed a relationship between climatic drought and areal coverage of natural salts. When little precipitation occurred three months prior to the capture of the Landsat scene, approximately 15%-20% of the area was classified as salt. This is compared to practically no classified salt in the wetter years of 1992 and 2005 Landsat scenes.

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

NASA Technical Reports Server (NTRS)

Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

2015-01-01

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

Satellite observations of rainfall effect on sea surface salinity in the waters adjacent to Taiwan

NASA Astrophysics Data System (ADS)

Ho, Chung-Ru; Hsu, Po-Chun; Lin, Chen-Chih; Huang, Shih-Jen

2017-10-01

Changes of oceanic salinity are highly related to the variations of evaporation and precipitation. To understand the influence of rainfall on the sea surface salinity (SSS) in the waters adjacent to Taiwan, satellite remote sensing data from the year of 2012 to 2014 are employed in this study. The daily rain rate data obtained from Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission's Microwave Imager (TRMM/TMI), Advanced Microwave Scanning Radiometer (AMSR), and WindSat Polarimetric Radiometer. The SSS data was derived from the measurements of radiometer instruments onboard the Aquarius satellite. The results show the average values of SSS in east of Taiwan, east of Luzon and South China Sea are 33.83 psu, 34.05 psu, and 32.84 psu, respectively, in the condition of daily rain rate higher than 1 mm/hr. In contrast to the rainfall condition, the average values of SSS are 34.07 psu, 34.26 psu, and 33.09 psu in the three areas, respectively at no rain condition (rain rate less than 1 mm/hr). During the cases of heavy rainfall caused by spiral rain bands of typhoon, the SSS is diluted with an average value of -0.78 psu when the average rain rate is higher than 4 mm/hr. However, the SSS was increased after temporarily decreased during the typhoon cases. A possible reason to explain this phenomenon is that the heavy rainfall caused by the spiral rain bands of typhoon may dilute the sea surface water, but the strong winds can uplift the higher salinity of subsurface water to the sea surface.

Assimilation of Satellite Sea Surface Salinity Fields: Validating Ocean Analyses and Identifying Errors in Surface Buoyancy Fluxes

NASA Astrophysics Data System (ADS)

Mehra, A.; Nadiga, S.; Bayler, E. J.; Behringer, D.

2014-12-01

Recently available satellite sea-surface salinity (SSS) fields provide an important new global data stream for assimilation into ocean forecast systems. In this study, we present results from assimilating satellite SSS fields from NASA's Aquarius mission into the National Oceanic and Atmospheric Administration's (NOAA) operational Modular Ocean Model version 4 (MOM4), the oceanic component of NOAA's operational seasonal-interannual Climate Forecast System (CFS). Experiments on the sensitivity of the ocean's overall state to different relaxation time periods were run to evaluate the importance of assimilating high-frequency (daily to mesoscale) and low-frequency (seasonal) SSS variability. Aquarius SSS data (Aquarius Data Processing System (ADPS) version 3.0), mapped daily fields at 1-degree spatial resolution, were used. Four model simulations were started from the same initial ocean condition and forced with NOAA's daily Climate Forecast System Reanalysis (CFSR) fluxes, using a relaxation technique to assimilate daily satellite sea surface temperature (SST) fields and selected SSS fields, where, except as noted, a 30-day relaxation period is used. The simulations are: (1) WOAMC, the reference case and similar to the operational setup, assimilating monthly climatological SSS from the 2009 NOAA World Ocean Atlas; (2) AQ_D, assimilating daily Aquarius SSS; (3) AQ_M, assimilating monthly Aquarius SSS; and (4) AQ_D10, assimilating daily Aquarius SSS, but using a 10-day relaxation period. The analysis focuses on the tropical Pacific Ocean, where the salinity dynamics are intense and dominated by El Niño interannual variability in the cold tongue region and by high-frequency precipitation events in the western Pacific warm pool region. To assess the robustness of results and conclusions, we also examine the results for the tropical Atlantic and Indian Oceans. Preliminary validation studies are conducted using observations, such as satellite sea-surface height (SSH

Multiangular L-band Datasets for Soil Moisture and Sea Surface Salinity Retrieval Measured by Airborne HUT-2D Synthetic Aperture Radiometer

NASA Astrophysics Data System (ADS)

Kainulainen, J.; Rautiainen, K.; Seppänen, J.; Hallikainen, M.

2009-04-01

SMOS is the European Space Agency's next Earth Explorer satellite due for launch in 2009. It aims for global monitoring of soil moisture and ocean salinity utilizing a new technology concept for remote sensing: two-dimensional aperture synthesis radiometry. The payload of SMOS is Microwave Imaging Radiometer by Aperture Synthesis, or MIRAS. It is a passive instrument that uses 72 individual L-band receivers for measuring the brightness temperature of the Earth. From each acquisition, i.e. integration time or snapshot, MIRAS provides two-dimensional brightness temperature of the scene in the instrument's field of view. Thus, consecutive snapshots provide multiangular measurements of the target once the instrument passes over it. Depending on the position of the target in instrument's swath, the brightness temperature of the target at incidence angles from zero up to 50 degrees can be measured with one overpass. To support the development MIRAS instrument, its calibration, and soil moisture and sea surface salinity retrieval algorithm development, Helsinki University of Technology (TKK) has designed, manufactured and tested a radiometer which operates at L-band and utilizes the same two-dimensional methodology of interferometery and aperture synthesis as MIRAS does. This airborne instrument, called HUT-2D, was designed to be used on board the University's research aircraft. It provides multiangular measurements of the target in its field of view, which spans up to 30 degrees off the boresight of the instrument, which is pointed to the nadir. The number of independent measurements of each target point depends on the flight speed and altitude. In addition to the Spanish Airborne MIRAS demonstrator (AMIRAS), HUT-2D is the only European airborne synthetic aperture radiometer. This paper presents the datasets and measurement campaigns, which have been carried out using the HUT-2D radiometer and are available for the scientific community. In April 2007 HUT-2D participated

SURFEX modeling of soil moisture fields over the Valencia Anchor Station and their comparison to different SMOS products and in situ measurements

NASA Astrophysics Data System (ADS)

Coll Pajaron, M. Amparo; Lopez-Baeza, Ernesto; Fernandez-Moran, Roberto; Samiro Khodayar-Pardo, D.

2016-07-01

Soil moisture is a difficult variable to obtain proper representation because of its high temporal and spatial variability. It is a significant parameter in agriculture, hydrology, meteorology and related disciplines. {it SVAT (Soil-Vegetation-Atmosphere-Transfer)} models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the {bf SURFEX (Surface Externalisée)} model developed at the {it Centre National de Recherches Météorologiques (CNRM)} at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the {bf Valencia Anchor Station}. SURFEX integrates the {bf ISBA (Interaction Sol-Biosphère-Atmosphère}; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) that have been adapted to describe the land covers of our study area. The Valencia Anchor Station was chosen as a core validation site for the {it SMOS (Soil Moisture and Ocean Salinity)} mission and as one of the hydrometeorological sites for the {it HyMeX (HYdrological cycle in Mediterranean EXperiment)} programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few small scattered industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields over the Valencia Anchor Station to be compared with SMOS level-2

Spatial and Temporal Analysis of Sea Surface Salinity Using Satellite Imagery in Gulf of Mexico

NASA Astrophysics Data System (ADS)

Rajabi, S.; Hasanlou, M.; Safari, A. R.

2017-09-01

The recent development of satellite sea surface salinity (SSS) observations has enabled us to analyse SSS variations with high spatiotemporal resolution. In this regards, The Level3-version4 data observed by Aquarius are used to examine the variability of SSS in Gulf of Mexico for the 2012-2014 time periods. The highest SSS value occurred in April 2013 with the value of 36.72 psu while the lowest value (35.91 psu) was observed in July 2014. Based on the monthly distribution maps which will be demonstrated in the literature, it was observed that east part of the region has lower salinity values than the west part for all months mainly because of the currents which originate from low saline waters of the Caribbean Sea and furthermore the eastward currents like loop current. Also the minimum amounts of salinity occur in coastal waters where the river runoffs make fresh the high saline waters. Our next goal here is to study the patterns of sea surface temperature (SST), chlorophyll-a (CHLa) and fresh water flux (FWF) and examine the contributions of them to SSS variations. So by computing correlation coefficients, the values obtained for SST, FWF and CHLa are 0.7, 0.22 and 0.01 respectively which indicated high correlation of SST on SSS variations. Also by considering the spatial distribution based on the annual means, it found that there is a relationship between the SSS, SST, CHLa and the latitude in the study region which can be interpreted by developing a mathematical model.

Satellite observed global variations in ecosystem-scale plant water storage

NASA Astrophysics Data System (ADS)

Tian, F.; Wigneron, J. P.; Brandt, M.; Fensholt, R.

2017-12-01

Plant water storage is a key component in ecohydrological processes and tightly coupled with global carbon and energy budgets. Field measurements of individual trees have revealed diurnal and seasonal variations in plant water storage across different tree species and sizes. However, global estimation of plant water storage is challenged by up-scaling from individual trees to an ecosystem scale. The L-band passive microwaves are sensitive to water stored in the stems, branches and leaves, with dependence on the vegetation structure. Thus, the L-band vegetation optical depth (L-VOD) parameter retrieved from satellite passive microwave observations can be used as a proxy for ecosystem-scale plant water storage. Here, we employ the recently developed SMOS (Soil Moisture and Ocean Salinity) L-VOD dataset to investigate spatial patterns in global plant water storage and its diurnal and seasonal variations. In addition, we compare the spatiotemporal patterns between plant water storage and canopy greenness (i.e., enhanced vegetation indices, EVI) to gain ecohydrological insights among different territorial biomes, including boreal forest and tropical woodland. Generally, seasonal dynamics of plant water storage is much smaller than canopy greenness, yet the temporal coupling of these two traits is totally different between boreal and tropical regions, which could be related to their strategies in plant water regulation.

Posterior uncertainty of GEOS-5 L-band radiative transfer model parameters and brightness temperatures after calibration with SMOS observations

NASA Astrophysics Data System (ADS)

De Lannoy, G. J.; Reichle, R. H.; Vrugt, J. A.

2012-12-01

Simulated L-band (1.4 GHz) brightness temperatures are very sensitive to the values of the parameters in the radiative transfer model (RTM). We assess the optimum RTM parameter values and their (posterior) uncertainty in the Goddard Earth Observing System (GEOS-5) land surface model using observations of multi-angular brightness temperature over North America from the Soil Moisture Ocean Salinity (SMOS) mission. Two different parameter estimation methods are being compared: (i) a particle swarm optimization (PSO) approach, and (ii) an MCMC simulation procedure using the differential evolution adaptive Metropolis (DREAM) algorithm. Our results demonstrate that both methods provide similar "optimal" parameter values. Yet, DREAM exhibits better convergence properties, resulting in a reduced spread of the posterior ensemble. The posterior parameter distributions derived with both methods are used for predictive uncertainty estimation of brightness temperature. This presentation will highlight our model-data synthesis framework and summarize our initial findings.

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

Retrieving marine inherent optical properties from satellites using temperature and salinity-dependent backscattering by seawater.

PubMed

Werdell, P Jeremy; Franz, Bryan A; Lefler, Jason T; Robinson, Wayne D; Boss, Emmanuel

2013-12-30

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

NASA Technical Reports Server (NTRS)

Werdell, Paul J.; Franz, Bryan Alden; Lefler, Jason Travis; Robinson, Wayne D.; Boss, Emmanuel

2013-01-01

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA Technical Reports Server (NTRS)

Njoku, Eni; Entekhabi, Dara; O'Neill, Peggy; Jackson, Tom; Kellogg, Kent; Entin, Jared

2011-01-01

NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors

Impact of Satellite Remote Sensing Data on Simulations of ...

EPA Pesticide Factsheets

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the

Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions

NASA Astrophysics Data System (ADS)

Ebrahimi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-02-01

The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. Avoiding the empirical estimation of VOD, the SMOS algorithm is used to retrieve simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

NASA Astrophysics Data System (ADS)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical

A Wiener-Wavelet-Based filter for de-noising satellite soil moisture retrievals

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Ciabatta, Luca; Moramarco, Tommaso; Su, Chun-Hsu; Ryu, Dongryeol; Wagner, Wolfgang

2014-05-01

The reduction of noise in microwave satellite soil moisture (SM) retrievals is of paramount importance for practical applications especially for those associated with the study of climate changes, droughts, floods and other related hydrological processes. So far, Fourier based methods have been used for de-noising satellite SM retrievals by filtering either the observed emissivity time series (Du, 2012) or the retrieved SM observations (Su et al. 2013). This contribution introduces an alternative approach based on a Wiener-Wavelet-Based filtering (WWB) technique, which uses the Entropy-Based Wavelet de-noising method developed by Sang et al. (2009) to design both a causal and a non-causal version of the filter. WWB is used as a post-retrieval processing tool to enhance the quality of observations derived from the i) Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), ii) the Advanced SCATterometer (ASCAT), and iii) the Soil Moisture and Ocean Salinity (SMOS) satellite. The method is tested on three pilot sites located in Spain (Remedhus Network), in Greece (Hydrological Observatory of Athens) and in Australia (Oznet network), respectively. Different quantitative criteria are used to judge the goodness of the de-noising technique. Results show that WWB i) is able to improve both the correlation and the root mean squared differences between satellite retrievals and in situ soil moisture observations, and ii) effectively separates random noise from deterministic components of the retrieved signals. Moreover, the use of WWB de-noised data in place of raw observations within a hydrological application confirms the usefulness of the proposed filtering technique. Du, J. (2012), A method to improve satellite soil moisture retrievals based on Fourier analysis, Geophys. Res. Lett., 39, L15404, doi:10.1029/ 2012GL052435 Su,C.-H.,D.Ryu, A. W. Western, and W. Wagner (2013), De-noising of passive and active microwave satellite soil moisture time

Microwave-derived soil moisture over Mediterranean land uses: from ground-based radiometry to SMOS first observations

NASA Astrophysics Data System (ADS)

Saleh, Kauzar; Antolín, Carmen; Juglea, Silvia; Kerr, Yann; Millán-Scheiding, Cristina; Novello, Nathalie; Pardé, Mickael; Wigneron, Jean-Pierre; Zribi, Mehrez; López-Baeza, Ernesto

2010-05-01

This communication will present the main results of a series of airborne and ground-based experiments conducted at the Valencia Anchor Station (VAS) site for the implementation of the SMOS emission model L-MEB (L-band Microwave Emission model of the Biosphere, Wigneron et al., 2007), and will evaluate the performance of L-MEB against SMOS measurements. The L-MEB model has been implemented in the context of the SMOS mission and through numerous radiometry experiments over different land uses. Within L-MEB, each land use is characterised by model parameterisations that are used to describe the radiative transfer at L-band. They describe, for instance, the attenuation properties of different canopies, or the effect of soil roughness on the surface emission. In recent years, the Valencia Anchor Station site (VAS) has hosted various radiometry experiments. These were performed at different scales, from the plot scale to the regional scale (up to 50 km), using ground-based and airborne-based radiometry. The main results are discussed in this communication, and some preliminary comparisons with SMOS measurements are presented. 1) Ground-based experiments. MELBEX-I was a ground-radiometry experiment run in 2005 using the L-band radiometer EMIRAD over a plot of shrub land. We will present results from this experiment (Cano et al., 2009), that highlighted a constant (and small) contribution of Mediterranean shrub land to the overall emission, and investigated the role of exposed rocks in the surface emission. MELBEX-II was a ground-radiometry experiment run in 2007 using the EMIRAD L-band radiometer over a plot of vineyards throughout the whole vegetation cycle. Vineyards are the main land use at the VAS site, therefore parameterisations for vineyards are key for the validation of SMOS data at VAS. This communication will discuss, in particular, estimates of microwave surface roughness throughout the crop year, and changes in the canopy microwave properties throughout the

Sea Surface Salinity: The Next Remote Sensing Challenge

NASA Technical Reports Server (NTRS)

Lagerloef, Gary S. E.; Swift, Calvin T.; LeVine, David M.

1995-01-01

A brief history of salinity remote sensing is presented. The role of sea surface salinity (SSS) in the far north Atlantic and the influence of salinity variations on upper ocean dynamics in the tropics are described. An assessment of the present state of the technology of the SSS satellite remote sensing is given.

Spatial distribution of soil moisture obtained from gravimetric and TDR methods for SMOS validation, at the Polesie test site SVRT 3275, in Poland

NASA Astrophysics Data System (ADS)

Usowicz, B.; Marczewski, W.; Lipiec, J.; Usowicz, J. B.; Sokolowska, Z.; Dabkowska-Naskret, H.; Hajnos, M.; Lukowski, M. I.

2009-04-01

The purpose is obtaining trustful ground based measurement data of SM (Soil Moisture) for validating SMOS, respectively to spatial and temporal distribution and variations. A use of Time Domain Reflectometric (TDR) method is fast, simple and less destructive, to the soil matter, than a usual standard gravimetric method. TDR tools operate efficiently, enable nearly instant measurements, and allow on collecting many measurements from numerous sites, even when operated manually in short time intervals. The method enables also very frequent sampling of SM at few selected fixed sites, when long terms of temporal variations are needed. In effect one obtains reasonably large data base for determining spatial and temporal distributions of SM. The study is devoted to determining a plan on collecting TDR data, in the scales of small and large field areas, and checking their relevance to those available from gravimetric methods. Finally, the ground based SM distributions are needed for validating other SM distributions, available remotely in larger scales, from the satellite data of ENVISAT-ASAR, and from SMOS (Soil Moisture and Ocean Salinity Mission) when it becomes operational. The ground based evaluations are served mainly by geo-statistical analysis. The space borne estimations are retrieved by image processing and physical models, proper to relevant Remote Sensing (RS) instruments on the orbit. Finally, validation must engage again the geo-statistical evaluations, to assess the agreement between direct and remote sensing means, and provide a measure of trust for extending the limited scales of the ground based data, on concluding the agreement in scales proper to the satellite data. The study is focused mainly on trustful evaluating data from the ground, provided independently on satellite data sources. SM ground based data are collected permanently at 2 selected tests sites, and temporary in areas around the tests sites, in one day sessions, repeated several times per

Seasonal to Interannual Surface Ocean Salinity Trends With Aquarius Data

NASA Astrophysics Data System (ADS)

Lagerloef, G. S. E.; Kao, H. Y.; Carey, D.

2017-12-01

An important scientific goal for satellite salinity observations is to document oceanic climate trends and their link to changes in the water cycle. This study is a re-examination of seasonal to interannual sea surface salinity (SSS) variations from more recent analyses of V5.0 reprocessing of the Aquarius satellite data, Sep 2011 to May 2015. Sensor calibration over these time scales has been a concern, and the V5.0 includes improved calibration reference data compared to previous versions, which will be explained. Orthogonal mode analyses show that the annual cycle dominates the variability, and is strongest in the tropics. Interannual trends indicate the principal salinity patterns during onset of the 2015-16 El Niño. Recognizing that the Aquarius data record is now finite (Sep 2011 through May 2015) due to the mission failure in early June 2015, we will conclude with a status summary of the disposition of the Aquarius data and the prospects for continuing satellite salinity measurements.

ELBARA II, an L-band radiometer system for soil moisture research.

PubMed

Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

2010-01-01

L-band (1-2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user.

ELBARA II, an L-Band Radiometer System for Soil Moisture Research

PubMed Central

Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

2010-01-01

L-band (1–2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user. PMID:22315556

A study on atmospheric and oceanic processes in the north Indian Ocean

NASA Astrophysics Data System (ADS)

Felton, Clifford S.

Studies on oceanic and atmospheric processes in the Indian Ocean are an active and important area of scientific research. Understanding how intraseasonal and interannual variations impact both the ocean and atmosphere will aid in delineating potential feedback mechanisms and global teleconnections. Thanks to recent efforts focused on expanding observational capabilities and developing models for this region, researchers have been able to begin investigating atmospheric and oceanic processes in the Indian Ocean. This study focuses on the impact of the El Nino Southern Oscillation (ENSO) on tropical cyclone activity over the Bay of Bengal (BoB) and on developing a method for estimating the barrier layer thickness (BLT) in the Indian Ocean from satellite observations. National Center for Environmental Prediction (NCEP-2) and Simple Ocean Data Assimilation (SODA) reanalysis data are used to investigate the alterations in atmospheric and oceanic conditions that impact tropical cyclones during ENSO events over a 33-year time frame (1979-2011). Atmospheric conditions are shown to be more favorable for tropical cyclone development during La Nina over the BoB due to the favorable alteration of large-scale wind, moisture, and vorticity distributions. By combining multiple satellite observations, including the recently launched Soil Moisture and Ocean Salinity (SMOS) and Aquarius SAC-D salinity missions, BLT estimates for the Indian Ocean are generated with the use of a multilinear regression model (MRM). The performance of the MRM is evaluated for the Southeast Arabian Sea (SEAS), Bay of Bengal (BoB), and Eastern Equatorial Indian Ocean (EEIO) where barrier layer formation is most rigorous. Results from the MRM suggest that salinity measurements obtained from Aquarius and SMOS can be useful for tracking and predicting the BLT in the Indian Ocean.

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

NASA Technical Reports Server (NTRS)

LeVine, D. M.; Lang, R.; Wentz, F.; Messiner, T.

2012-01-01

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.

Evaluation and qualification of commercial opto-electronic components for the MOHA subsystem in ESA's SMOS mission

NASA Astrophysics Data System (ADS)

Gutierrez, Francisco; Cordero, Enrique; Sánchez, Carolina; Barbero, Juan; Mosberger, Martin; Boehle, Peter; Tornell, Manuel; Lundmark, Karin

2017-11-01

A dedicated evaluation and qualification campaign has been performed on several optical COTS components in order to use them on ESA's SMOS mission. The evaluation phase consisted of a set of critical tests and analyses and led to the selection of the flight lot component. After selection of the components, one lot of each component has been qualified for the SMOS mission. The overall approach is presented together with a summary of all activities performed. The whole task has been handled in a joint effort between ESA, EADS CASA Espacio (prime contractor), Contraves Space AG (MOHA subsystem), TECNOLOGICA SA (component qualification experts) and the respective manufacturers, each party providing their specific know-how. Test results are presented and the issues discovered and lessons learned are addressed. Special emphasis is given to particular tests for which dedicated setups had to be designed due to the unavailability of standard equipment.

Assimilation of neural network soil moisture in land surface models

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

2017-04-01

In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests

SMAP Data Assimilation at NASA SPoRT

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.

2016-01-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

Rain Impact Model Assessment of Near-Surface Salinity Stratification Following Rainfall

NASA Astrophysics Data System (ADS)

Drushka, K.; Jones, L.; Jacob, M. M.; Asher, W.; Santos-Garcia, A.

2016-12-01

Rainfall over oceans produces a layer of fresher surface water, which can have a significant effect on the exchanges between the surface and the bulk mixed layer and also on satellite/in-situ comparisons. For satellite sea surface salinity (SSS) measurements, the standard is the Hybrid Coordinate Ocean Model (HYCOM), but there is a significant difference between the remote sensing sampling depth of 0.01 m and the typical range of 5-10 m of in-situ instruments. Under normal conditions the upper layer of the ocean is well mixed and there is uniform salinity; however, under rainy conditions, there is a dilution of the near-surface salinity that mixes downward by diffusion and by mechanical mixing (gravity waves/wind speed). This significantly modifies the salinity gradient in the upper 1-2 m of the ocean, but these transient salinity stratifications dissipate in a few hours, and the upper layer becomes well mixed at a slightly fresher salinity. Based upon research conducted within the NASA/CONAE Aquarius/SAC-D mission, a rain impact model (RIM) was developed to estimate the change in SSS due to rainfall near the time of the satellite observation, with the objective to identify the probability of salinity stratification. RIM uses HYCOM (which does not include the short-term rain effects) and a NOAA global rainfall product CMORPH to model changes in the near-surface salinity profile in 0.5 h increments. Based upon SPURS-2 experimental near-surface salinity measurements with rain, this paper introduces a term in the RIM model that accounts for the effect of wind speed in the mechanical mixing, which translates into a dynamic vertical diffusivity; whereby a Generalized Ocean Turbulence Model (GOTM) is used to investigate the response to rain events of the upper few meters of the ocean. The objective is to determine how rain and wind forcing control the thickness, stratification strength, and lifetime of fresh lenses and to quantify the impacts of rain-formed fresh lenses

Spatial and Temporal Patterns of SMAP Brightness Temperatures for Use in Level 1 TB Characterization

NASA Astrophysics Data System (ADS)

Kim, E. J.

2015-12-01

1. IntroductionThe recent launch of NASA's Soil Moisture Active Passive (SMAP) mission [Entekhabi, et al] has opened the door to improved brightness temperature (TB) calibration of satellite L-band microwave radiometers, through the use of SMAP's lower noise performance and better immunity to man-made interference (vs. ESA's Soil Moisture Ocean Salinity (SMOS) mission [Kerr, et al]), better spatial resolution (vs. NASA's Aquarius sea surface salinity mission [Le Vine, et al]), and cleaner antenna pattern (vs. SMOS). All three radiometers use/used large homogeneous places on Earth's surface as calibration targets—parts of the ocean, Antarctica, and tropical forests. Despite the recent loss of Aquarius data, there is still hope for creating a longer-term L-band data set that spans the timeframe of all 3 missions. 2. Description of Analyses and Expected Results In this paper, we analyze SMAP brightness temperature data to quantify the spatial and temporal characteristics of external target areas in the oceans, Antarctica, forests, and other areas. Existing analyses have examined these targets in terms of averages, standard deviations, and other basic statistics (for Aquarius & SMOS as well). This paper will approach the problem from a signal processing perspective. Coupled with the use of SMAP's novel RFI-mitigated TBs, and the aforementioned lower noise and cleaner antenna pattern, it is expected that of the 3 L-band missions, SMAP should do the best job of characterizing such external targets. The resulting conclusions should be useful to extract the best possible TB calibration from all 3 missions, helping to inter-compare the TB from the 3 missions, and to eventually inter-calibrate the TBs into a single long-term dataset.

Global retrieval of soil moisture and vegetation properties using data-driven methods

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Kerr, Yann

2017-04-01

Data-driven methods such as neural networks (NNs) are a powerful tool to retrieve soil moisture from multi-wavelength remote sensing observations at global scale. In this presentation we will review a number of recent results regarding the retrieval of soil moisture with the Soil Moisture and Ocean Salinity (SMOS) satellite, either using SMOS brightness temperatures as input data for the retrieval or using SMOS soil moisture retrievals as reference dataset for the training. The presentation will discuss several possibilities for both the input datasets and the datasets to be used as reference for the supervised learning phase. Regarding the input datasets, it will be shown that NNs take advantage of the synergy of SMOS data and data from other sensors such as the Advanced Scatterometer (ASCAT, active microwaves) and MODIS (visible and infra red). NNs have also been successfully used to construct long time series of soil moisture from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and SMOS. A NN with input data from ASMR-E observations and SMOS soil moisture as reference for the training was used to construct a dataset sharing a similar climatology and without a significant bias with respect to SMOS soil moisture. Regarding the reference data to train the data-driven retrievals, we will show different possibilities depending on the application. Using actual in situ measurements is challenging at global scale due to the scarce distribution of sensors. In contrast, in situ measurements have been successfully used to retrieve SM at continental scale in North America, where the density of in situ measurement stations is high. Using global land surface models to train the NN constitute an interesting alternative to implement new remote sensing surface datasets. In addition, these datasets can be used to perform data assimilation into the model used as reference for the training. This approach has recently been tested at the European Centre

Accomplishments of Aquarius: NASA's first global Sea Surface Salinity Mission: a review of the technical findings to date

NASA Astrophysics Data System (ADS)

Sen, Amit

2014-10-01

Launched 10 June 2011, the NASA's Aquarius instrument onboard the Argentine built and managed Satélite de Aplicaciones Científicas (SAC-D) has been tirelessly observing the open oceans, confirming and adding new knowledge to the not so vast measured records of our Earth's global oceans. This paper reviews the data collected over the last 3 years, it's findings, challenges and future work that is at hand for the sleepless oceanographers, hydrologists and climate scientists. Although routine data is being collected, a snapshot is presented from almost 3-years of flawless operations showing new discoveries and possibilities of lot more in the future. Repetitive calibration and validation of measurements from Aquarius continue together with comparison of the data to the existing array of Argo temperature/salinity profiling floats, measurements from the recent Salinity Processes in the Upper Ocean Regional Study (SPURS) in-situ experiment and research, and to the data collected from the European Soil Moisture Ocean Salinity (SMOS) mission. This all aids in the optimization of computer model functions to improve the basic understanding of the water cycle over the oceans and its ties to climate. The Aquarius mission operations team also has been tweaking and optimizing algorithms, reprocessing data as needed, and producing salinity movies that has never been seen before. A brief overview of the accomplishments, technical findings to date will be covered in this paper.

Analysis of L-band radiometric data over the Mediterranean Sea from the SMOS Validation Rehearsal campaign

NASA Astrophysics Data System (ADS)

Gabarro, C.; Talone, M.; Font, J.

2009-04-01

L-band radiometric data obtained with a real aperture airborne radiometer during SMOS validation Rehearsal campaign (April-May 2008) over the NW Mediterranean Sea have been analysed. EMIRAD, a fully polarimetric radiometer developed by the Technical University of Denmark operating in the 1400 - 1427 MHz band, was mounted on board a Skyvan aircraft from the Helsinki University of Technology. Two antennas were used: one facing nadir with 37.6° full aperture at half-power; and one placed towards the rear of the aircraft at 40° zenith angle with 30.6° full aperture at half-power. Two transit flights over the sea from Marseille to Valencia (19 April 2008) and from Valencia to Marseille (3 May 2008) have been studied. Two meteorological and oceanographic buoys were moored 40 Km offshore in front of Tarragona and were overflown during these transits. Additionally, information on sea surface temperature (SST) and sea surface salinity (SSS) was obtained from operational model outputs (Mediterranean Forecasting System - Mediterranean Operational Oceanography Network) and wind speed from QuikSCAT. Measured brightness temperatures (Tb) have been compared with modelled Tb, using a semi-empirical emissivity model: Klein and Swift model is used to define the dielectric constant and Hollinger model for the rough sea emissivity contribution. Comparisons show that in general measured Tb variability fits with modelled variability, although a bias is observed in the aft V channel.

Infrared thermal remote sensing for soil salinity assessment on landscape scale

NASA Astrophysics Data System (ADS)

Ivushkin, Konstantin; Bartholomeus, Harm; Bregt, Arnold K.; Pulatov, Alim; Bui, Elisabeth N.; Wilford, John

2017-04-01

Soil salinity is considered as one of the most severe land degradation aspects. An increased soil salt level inhibits growth and development of crops. Therefore, up to date soil salinity information is vital for appropriate management practices and reclamation strategies. This information is required at increasing spatial and temporal resolution for appropriate management adaptations. Conventional soil sampling and associated laboratory analyses are slow, expensive, and often cannot deliver the temporal and spatial resolution required. The change of canopy temperature is one of the stress indicators in plants. Its behaviour in response to salt stress on individual plant level is well studied in laboratory and greenhouse experiments, but its potential for landscape scale studies using remote sensing techniques is not investigated yet. In our study, possibilities of satellite thermography for landscape scale soil salinity assessment of cropped areas were studied. The performance of satellite thermography is compared with other approaches that have been used before, like Normalised Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The study areas were Syrdarya province of Uzbekistan and four study areas in four Australian states namely, Western Australia, South Australia, Queensland and New South Wales. The diversity of the study areas allowed us to analyse behaviour of canopy temperature of different crops (wheat, cotton, barley) and different agriculture practices (rain fed and irrigated). MODIS and Landsat TM multiannual satellite images were used to measure canopy temperature. As ground truth for Uzbekistan study area we used a provincial soil salinity map. For the Australian study areas we used the EC map for the whole country. ANOVA was used to analyse relations between the soil salinity maps and canopy temperature, NDVI, EVI. Time series graphs were created to analyse the dynamics of the indicators during the growing season. The results

Stable near-surface ocean salinity stratifications due to evaporation observed during STRASSE

NASA Astrophysics Data System (ADS)

Asher, William E.; Jessup, Andrew T.; Clark, Dan

2014-05-01

Under conditions with a large solar flux and low wind speed, a stably stratified warm layer forms at the ocean surface. Evaporation can then lead to an increase in salinity in the warm layer. A large temperature gradient will decrease density enough to counter the density increase caused by the salinity increase, forming a stable positive salinity anomaly at the surface. If these positive salinity anomalies are large in terms of the change in salinity from surface to the base of the gradient, if their areal coverage is a significant fraction of the satellite footprint, and if they persist long enough to be in the satellite field of view, they could be relevant for calibration and validation of L-band microwave salinity measurements. A towed, surface-following profiler was deployed from the N/O Thalassa during the Subtropical Atlantic Surface Salinity Experiment (STRASSE). The profiler measured temperature and conductivity in the surface ocean at depths of 10, 50, and 100 cm. The measurements show that positive salinity anomalies are common at the ocean surface for wind speeds less than 4 m s-1 when the average daily insolation is >300 W m-2 and the sea-to-air latent heat flux is greater than zero. A semiempirical model predicts the observed dependence of measured anomalies on environmental conditions. However, the model results and the field data suggest that these ocean surface salinity anomalies are not large enough in terms of the salinity difference to significantly affect microwave radiometric measurements of salinity.

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

NASA Technical Reports Server (NTRS)

Miernecki, Maciej; Wigneron, Jean-Pierre; Lopez-Baeza, Ernesto; Kerr, Yann; DeJeu, Richard; DeLannoy, Gabielle J. M.; Jackson, Tom J.; O'Neill, Peggy E.; Shwank, Mike; Moran, Roberto Fernandez;

Simultaneous retrieval of sea ice thickness and snow depth using concurrent active altimetry and passive L-band remote sensing data

NASA Astrophysics Data System (ADS)

Zhou, L.; Xu, S.; Liu, J.

2017-12-01

The retrieval of sea ice thickness mainly relies on satellite altimetry, and the freeboard measurements are converted to sea ice thickness (hi) under certain assumptions over snow loading. The uncertain in snow depth (hs) is a major source of uncertainty in the retrieved sea ice thickness and total volume for both radar and laser altimetry. In this study, novel algorithms for the simultaneous retrieval of hi and hs are proposed for the data synergy of L-band (1.4 GHz) passive remote sensing and both types of active altimetry: (1) L-band (1.4GHz) brightness temperature (TB) from Soil Moisture Ocean Salinity (SMOS) satellite and sea ice freeboard (FBice) from radar altimetry, (2) L-band TB data and snow freeboard (FBsnow) from laser altimetry. Two physical models serve as the forward models for the retrieval: L-band radiation model, and the hydrostatic equilibrium model. Verification with SMOS and Operational IceBridge (OIB) data is carried out, showing overall good retrieval accuracy for both sea ice parameters. Specifically, we show that the covariability between hs and FBsnow is crucial for the synergy between TB and FBsnow. Comparison with existing algorithms shows lower uncertainty in both sea ice parameters, and that the uncertainty in the retrieved sea ice thickness as caused by that of snow depth is spatially uncorrelated, with the potential reduction of the volume uncertainty through spatial sampling. The proposed algorithms can be applied to the retrieval of sea ice parameters at basin-scale, using concurrent active and passive remote sensing data based on satellites.

The Aquarius Mission: Sea Surface Salinity from Space

NASA Technical Reports Server (NTRS)

Koblinsky, Chester; Chao, Y.; deCharon, A.; Edelstein, W.; Hildebrand, P.; Lagerloef, G.; LeVine, D.; Pellerano, F.; Rahmat-Samii, Y.; Ruf, C.

2001-01-01

Aquarius is a new satellite mission concept to study the impact of the global water cycle on the ocean, including the response of the ocean to buoyancy forcing and the subsequent feedback of the ocean on the climate. The measurement objective of Aquarius is sea surface salinity, which reflects the concentration of freshwater at the ocean surface. Salinity affects the dielectric constant of sea water and, consequently, the radiometric emission of the sea surface to space. Rudimentary space observations with an L-band radiometer were first made from Skylab in the mid-70s and numerous aircraft missions of increasing quality and improved technology have been conducted since then. Technology is now available to carry out a global mission, which includes both an accurate L band (1.413 Ghz) radiometer and radar system in space and a global array of in situ observations for calibration and validation, in order to address key NASA Earth Science Enterprise questions about the global cycling of water and the response of the ocean circulation to climate change. The key scientific objectives of Aquarius examine the cycling of water at the ocean's surface, the response of the ocean circulation to buoyancy forcing, and the impact of buoyancy forcing on the ocean's thermal feedback to the climate. Global surface salinity will also improve our ability to model the surface solubility chemistry needed to estimate the air-sea exchange of CO2. In order to meet these science objectives, the NASA Salinity Sea Ice Working Group over the past three years has concluded that the mission measurement goals should be better than 0.2 practical salinity units (psu) accuracy, 100 km resolution, and weekly to revisits. The Aquarius mission proposes to meet these measurement requirements through a real aperture dual-polarized L band radiometer and radar system. This system can achieve the less than 0.1 K radiometric temperature measurement accuracy that is required. A 3 m antenna at approx. 600km

RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Gholian, Armen; Bradley, Damon C.; Wong, Mark; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.

2016-01-01

Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

2013-04-01

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

Modelling the Passive Microwave Signature from Land Surfaces: A Review of Recent Results and Application to the L-Band SMOS SMAP Soil Moisture Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Wigneron, J.-P.; Jackson, T. J.; O'Neill, P.; De Lannoy, G.; De Rosnay, P.; Walker, J. P.; Ferrazzoli, P.; Mironov, V.; Bircher, S.; Grant, J. P.;

Aquarius Radiometer and Scatterometer Weekly Polar-Gridded Products to Monitor Ice Sheets, Sea Ice, and Frozen Soil

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel; Koenig, Lora

2014-01-01

Space-based microwave sensors have been available for several decades, and with time more frequencies have been offered. Observations made at frequencies between 7 and 183 GHz were often used for monitoring cryospheric properties (e.g. sea ice concentration, snow accumulation, snow melt extent and duration). Since 2009, satellite observations are available at the low frequency of 1.4 GHz. Such observations are collected by the Soil Moisture and Ocean Salinity (SMOS) mission, and the Aquarius/SAC-D mission. Even though these missions have been designed for the monitoring of soil moisture and sea surface salinity, new applications are being developed to study the cryosphere. For instance, L-band observations can be used to monitor soil freeze/thaw (e.g. Rautiainen et al., 2012), and thin sea ice thickness (e.g. Kaleschke et al., 2010, Huntemann et al., 2013). Moreover, with the development of satellite missions comes the need for calibration and validation sites. These sites must have stable characteristics, such as the Antarctic Plateau (Drinkwater et al., 2004, Macelloni et al., 2013). Therefore, studying the cryosphere with 1.4 GHz observations is relevant for both science applications, and remote sensing applications.

Aquarius Radiometer and Scatterometer Weekly-Polar-Gridded Products to Monitor Ice Sheets, Sea Ice, and Frozen Soil

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel; Koenig, Lora

2014-01-01

Space-based microwave sensors have been available for several decades, and with time more frequencies have been offered. Observations made at frequencies between 7 and 183 GHz were often used for monitoring cryospheric properties (e.g. sea ice concentration, snow accumulation, snow melt extent and duration). Since 2009, satellite observations are available at the low frequency of 1.4 GHz. Such observations are collected by the Soil Moisture and Ocean Salinity (SMOS) mission, and the AquariusSAC-D mission. Even though these missions have been designed for the monitoring of soil moisture and sea surface salinity, new applications are being developed to study the cryosphere. For instance, L-band observations can be used to monitor soil freezethaw (e.g. Rautiainen et al., 2012), and thin sea ice thickness (e.g. Kaleschke et al., 2010, Huntemann et al., 2013). Moreover, with the development of satellite missions comes the need for calibration and validation sites. These sites must have stable characteristics, such as the Antarctic Plateau (Drinkwater et al., 2004, Macelloni et al., 2013). Therefore, studying the cryosphere with 1.4 GHz observations is relevant for both science applications, and remote sensing applications.

Total Electron Content Retrieved From L-Band Radiometers and Potential Improvements to the IGS Model

NASA Astrophysics Data System (ADS)

Soldo, Yan; Hong, Liang; El-Nimri, Salem; Le Vine, David M.

2018-04-01

In recent years, several L-band microwave instruments have been launched into Earth's orbit to measure soil moisture and ocean salinity (e.g., Soil Moisture and Ocean Salinity [SMOS], Aquarius, and Soil Moisture Active/Passive [SMAP]). As the microwave signal travels through the ionosphere, the polarization vector rotates (Faraday rotation) and it is possible to estimate the total electron content (TEC) along the path by measuring this change. A comparison is presented of the TEC retrieved from Aquarius and SMAP over the ocean with the values provided by the IGS (International Global Navigation Satellite System Service (GNSS)). The TEC retrieved from Aquarius and SMAP measurements show good agreement with each other and, on a global scale, are in agreement with the TEC provided by the IGS. However, there are cases in which the TEC from the two satellite sensors are in good agreement with each other but differ significantly from the IGS TEC. The comparison suggests that the L-band instruments are a reliable source of TEC over the ocean and could be a valuable supplementary source of TEC values that could be assimilated in the IGS models, especially over the ocean, where GNSS ground stations are sparse.

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf

EPA Science Inventory

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the ...

New developments in satellite oceanography and current measurements

NASA Technical Reports Server (NTRS)

Huang, N. E.

1979-01-01

Principal satellite remote sensing techniques and instruments are described and attention is given to the application of such techniques to ocean current measurement. The use of radiometers, satellite tracking drifters, and altimeters for current measurement is examined. Consideration is also given to other applications of satellite remote sensing in physical oceanography, including measurements of surface wind stress, sea state, tides, ice, sea surface temperature, salinity, ocean color, and oceanic leveling.

Integrating SMOS brightness temperatures with a new conceptual spatially distributed hydrological model for improving flood and drought predictions at large scale.

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Rains, Dominik; Chini, Marco; Lievens, Hans; Verhoest, Niko E. C.; Matgen, Patrick

2017-04-01

Motivated by climate change and its impact on the scarcity or excess of water in many parts of the world, several agencies and research institutions have taken initiatives in monitoring and predicting the hydrologic cycle at a global scale. Such a monitoring/prediction effort is important for understanding the vulnerability to extreme hydrological events and for providing early warnings. This can be based on an optimal combination of hydro-meteorological models and remote sensing, in which satellite measurements can be used as forcing or calibration data or for regularly updating the model states or parameters. Many advances have been made in these domains and the near future will bring new opportunities with respect to remote sensing as a result of the increasing number of spaceborn sensors enabling the large scale monitoring of water resources. Besides of these advances, there is currently a tendency to refine and further complicate physically-based hydrologic models to better capture the hydrologic processes at hand. However, this may not necessarily be beneficial for large-scale hydrology, as computational efforts are therefore increasing significantly. As a matter of fact, a novel thematic science question that is to be investigated is whether a flexible conceptual model can match the performance of a complex physically-based model for hydrologic simulations at large scale. In this context, the main objective of this study is to investigate how innovative techniques that allow for the estimation of soil moisture from satellite data can help in reducing errors and uncertainties in large scale conceptual hydro-meteorological modelling. A spatially distributed conceptual hydrologic model has been set up based on recent developments of the SUPERFLEX modelling framework. As it requires limited computational efforts, this model enables early warnings for large areas. Using as forcings the ERA-Interim public dataset and coupled with the CMEM radiative transfer model

Global Variability and Changes in Ocean Total Alkalinity from Aquarius Satellite

NASA Astrophysics Data System (ADS)

Fine, R. A.; Willey, D. A.; Millero, F. J., Jr.

2016-02-01

To document effects of ocean acidification it is important to have an understanding of the processes and parameters that influence alkalinity. Alkalinity is a gauge on the ability of seawater to neutralize acids. We use Aquarius satellite data, which allow unprecedented global mapping of surface total alkalinity as it correlates strongly with salinity and to a lesser extent with temperature. Spatial variability in total alkalinity and salinity exceed temporal variability, the latter includes seasonal and differences compared to climatological data. The northern hemisphere has more spatial and monthly variability in total alkalinity and salinity, while less variability in Southern Ocean alkalinity is due to less salinity variability and upwelling of waters enriched in alkalinity. Satellite alkalinity data are providing a global baseline that can be used for comparing with future carbon data, and for evaluating spatial and temporal variability and past trends. For the first time it is shown that recent satellite derived total alkalinity in the subtropics have increased as compared with climatological data; this is reflective of large scale changes in the global water cycle. Total alkalinity increases imply increased dissolution of calcareous minerals and difficulty for calcifying organisms to make their shells.

Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.

2017-11-01

Soil moisture is widely recognized as an important land surface variable that provides a deeper knowledge of land-atmosphere interactions and climate change. Space-borne passive and active microwave sensors have become valuable and essential sources of soil moisture observations at global scales. Over the past four decades, several active and passive microwave sensors have been deployed, along with the recent launch of two fully dedicated missions (SMOS and SMAP). Signifying the four decades of microwave remote sensing of soil moisture, this Part 2 of the two-part review series aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy for retrieving soil moisture. The first part discusses the developments made in active and passive microwave soil moisture retrieval algorithms. We assess the evolution of the products of various sensors over the last four decades, in terms of daily coverage, temporal performance, and spatial performance, by comparing the products of eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product) with the International Soil Moisture Network (ISMN) in-situ stations and the Variable Infiltration Capacity (VIC) land surface model simulations over the Contiguous United States (CONUS). In the process, the regional impacts of vegetation conditions on the spatial and temporal performance of soil moisture products are investigated. We also carried out inter-satellite comparisons to study the roles of sensor design and algorithms on the retrieval accuracy. We find that substantial improvements have been made over recent years in this field in terms of daily coverage, retrieval accuracy, and temporal dynamics. We conclude that the microwave soil moisture products have significantly evolved in the last four decades and will

New Passive Instruments Developed for Ocean Monitoring at the Remote Sensing Lab—Universitat Politècnica de Catalunya

PubMed Central

Camps, Adriano; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Marchán-Hernández, Juan F.; Rodríguez, Nereida; Valencia, Enric; Tarongi, Jose M.; Aguasca, Albert; Acevo, René

2009-01-01

Lack of frequent and global observations from space is currently a limiting factor in many Earth Observation (EO) missions. Two potential techniques that have been proposed nowadays are: (1) the use of satellite constellations, and (2) the use of Global Navigation Satellite Signals (GNSS) as signals of opportunity (no transmitter required). Reflectometry using GNSS opportunity signals (GNSS-R) was originally proposed in 1993 by Martin-Neira (ESA-ESTEC) for altimetry applications, but later its use for wind speed determination has been proposed, and more recently to perform the sea state correction required in sea surface salinity retrievals by means of L-band microwave radiometry (TB). At present, two EO space-borne missions are currently planned to be launched in the near future: (1) ESA's SMOS mission, using a Y-shaped synthetic aperture radiometer, launch date November 2nd, 2009, and (2) NASA-CONAE AQUARIUS/SAC-D mission, using a three beam push-broom radiometer. In the SMOS mission, the multi-angle observation capabilities allow to simultaneously retrieve not only the surface salinity, but also the surface temperature and an “effective” wind speed that minimizes the differences between observations and models. In AQUARIUS, an L-band scatterometer measuring the radar backscatter (σ0) will be used to perform the necessary sea state corrections. However, none of these approaches are fully satisfactory, since the effective wind speed captures some sea surface roughness effects, at the expense of introducing another variable to be retrieved, and on the other hand the plots (TB-σ0) present a large scattering. In 2003, the Passive Advance Unit for ocean monitoring (PAU) project was proposed to the European Science Foundation in the frame of the EUropean Young Investigator Awards (EURYI) to test the feasibility of GNSS-R over the sea surface to make sea state measurements and perform the correction of the L-band brightness temperature. This paper: (1) provides an

New passive instruments developed for ocean monitoring at the remote sensing lab-universitat politècnica de catalunya.

PubMed

Camps, Adriano; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Marchán-Hernández, Juan F; Rodríguez, Nereida; Valencia, Enric; Tarongi, Jose M; Aguasca, Albert; Acevo, René

2009-01-01

Lack of frequent and global observations from space is currently a limiting factor in many Earth Observation (EO) missions. Two potential techniques that have been proposed nowadays are: (1) the use of satellite constellations, and (2) the use of Global Navigation Satellite Signals (GNSS) as signals of opportunity (no transmitter required). Reflectometry using GNSS opportunity signals (GNSS-R) was originally proposed in 1993 by Martin-Neira (ESA-ESTEC) for altimetry applications, but later its use for wind speed determination has been proposed, and more recently to perform the sea state correction required in sea surface salinity retrievals by means of L-band microwave radiometry (T(B)). At present, two EO space-borne missions are currently planned to be launched in the near future: (1) ESA's SMOS mission, using a Y-shaped synthetic aperture radiometer, launch date November 2nd, 2009, and (2) NASA-CONAE AQUARIUS/SAC-D mission, using a three beam push-broom radiometer. In the SMOS mission, the multi-angle observation capabilities allow to simultaneously retrieve not only the surface salinity, but also the surface temperature and an "effective" wind speed that minimizes the differences between observations and models. In AQUARIUS, an L-band scatterometer measuring the radar backscatter (σ(0)) will be used to perform the necessary sea state corrections. However, none of these approaches are fully satisfactory, since the effective wind speed captures some sea surface roughness effects, at the expense of introducing another variable to be retrieved, and on the other hand the plots (T(B)-σ(0)) present a large scattering. In 2003, the Passive Advance Unit for ocean monitoring (PAU) project was proposed to the European Science Foundation in the frame of the EUropean Young Investigator Awards (EURYI) to test the feasibility of GNSS-R over the sea surface to make sea state measurements and perform the correction of the L-band brightness temperature. This paper: (1

GLEAM v3: satellite-based land evaporation and root-zone soil moisture

NASA Astrophysics Data System (ADS)

Martens, Brecht; Miralles, Diego G.; Lievens, Hans; van der Schalie, Robin; de Jeu, Richard A. M.; Fernández-Prieto, Diego; Beck, Hylke E.; Dorigo, Wouter A.; Verhoest, Niko E. C.

2017-05-01

The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980-2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003-2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011-2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil

Long Term Surface Salinity Measurements

NASA Technical Reports Server (NTRS)

Schmitt, Raymond W.; Brown, Neil L.

2005-01-01

Our long-term goal is to establish a reliable system for monitoring surface salinity around the global ocean. Salinity is a strong indicator of the freshwater cycle and has a great influence on upper ocean stratification. Global salinity measurements have potential to improve climate forecasts if an observation system can be developed. This project is developing a new internal field conductivity cell that can be protected from biological fouling for two years. Combined with a temperature sensor, this foul-proof cell can be deployed widely on surface drifters. A reliable in-situ network of surface salinity sensors will be an important adjunct to the salinity sensing satellite AQUARIUS to be deployed by NASA in 2009. A new internal-field conductivity cell has been developed by N Brown, along with new electronics. This sensor system has been combined with a temperature sensor to make a conductivity - temperature (UT) sensor suitable for deployment on drifters. The basic sensor concepts have been proven on a high resolution CTD. A simpler (lower cost) circuit has been built for this application. A protection mechanism for the conductivity cell that includes antifouling protection has also been designed and built. Mr. A.Walsh of our commercial partner E-Paint has designed and delivered time-release formulations of antifoulants for our application. Mr. G. Williams of partner Clearwater Instrumentation advised on power and communication issues and supplied surface drifters for testing.

Modelling the passive microwave signature from land surfaces: a review of recent results and application to the SMOS & SMAP soil moisture retrieval algorithms

USDA-ARS?s Scientific Manuscript database

Two passive microwave missions are currently operating at L-band to monitor surface soil moisture (SM) over continental surfaces. The SMOS sensor, based on an innovative interferometric technology enabling multi-angular signatures of surfaces to be measured, was launched in November 2009....

Salinity and turbidity distributions in the Brisbane River estuary, Australia

NASA Astrophysics Data System (ADS)

Yu, Yingying; Zhang, Hong; Lemckert, Charles

2014-11-01

The Brisbane River estuary (BRE) in Australia not only plays a vital role in ecosystem health, but is also of importance for people who live nearby. Comprehensive investigations, both in the short- and long-term, into the salinity and turbidity distributions in the BRE were conducted. Firstly, the analysis of numerical results revealed that the longitudinal salinity varied at approximately 0.45 and 0.61 psu/h during neap and spring tides, respectively. The turbidity stayed at a higher level and was less impacted by tide in the upper estuary, however, the water cleared up while the tide changed from flood to ebb in the mid and lower estuary. The second investigation into the seasonal variations of salinity and turbidity in the BRE was conducted, using ten-year field measurement data. A fourth-order polynomial equation was proposed, describing the longitudinal variation in salinity dilution changes as the upstream distance in the BRE during the wet and dry seasons. From the observation, the mid and upper estuaries were vertically well-mixed during both seasons, but the lower BRE was stratified, particularly during the wet season. The estuary turbidity maximum (ETM) zone was about 10 km longer during the wet season than the dry season. Particular emphasis was given to the third investigation into the use of satellite remote sensing techniques for estimation of the turbidity level in the BRE. A linear relationship between satellite observed water reflectance and surface turbidity level in the BRE was validated with an R2 of 0.75. The application of satellite-observed water reflectance therefore provided a practical solution for estimating surface turbidity levels of estuarine rivers not only under normal weather conditions, but also during flood events. The results acquired from this study are valuable for further hydrological research in the BRE and particularly prominent for immediate assessment of flood impacts.

Regional-scale Assessment of Soil Salinity in the Red River Valley Using Multi-year MODIS EVI

USDA-ARS?s Scientific Manuscript database

The ability to inventory and map soil salinity at regional scales remains a significant challenge to soil, environmental, and natural resource scientists. Previous attempts to use satellite or aerial imagery to assess and map soil salinity have resulted in limited success due, in part, to the inabi...

Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were

Commercial applications of satellite oceanography

NASA Technical Reports Server (NTRS)

Montgomery, D. R.

1981-01-01

It is shown that in the next decade the oceans' commercial users will require an operational oceanographic satellite system or systems capable of maximizing real-time coverage over all ocean areas. Seasat studies suggest that three spacecraft are required to achieve this. Here, the sensor suite would measure surface winds, wave heights (and spectral energy distribution), ice characteristics, sea-surface temperature, ocean colorimetry, height of the geoid, salinity, and subsurface thermal structure. The importance of oceanographic data being distributed to commercial users within two hours of observation time is stressed. Also emphasized is the importance of creating a responsive oceanographic satellite data archive. An estimate of the potential dollar benefits of such an operational oceanographic satellite system is given.

Considering Combined or Separated Roughness and Vegetation Effects in Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Parrens, Marie; Wigernon, Jean-Pierre; Richaume, Philippe; Al Bitar, Ahmad; Mialon, Arnaud; Fernandez-Moran, Roberto; Al-Yarri, Amen; O'Neill, Peggy; Kerr, Yann

2016-01-01

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (tau(sub nad)) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB),soil roughness is modeled with a semi-empirical equation using four main parameters (Q(sub r), H(sub r), N(sub rp), with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N(sub rp) and H(sub r) on the SM and tau(sub nad) retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that N(sub rH)= N(sub rV). The retrievals were performed by varying N(sub rp) from -1 to 2 by steps of 1 and H(sub r) from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth

SMOS L1PP Performance Analysis from Commissioning Phase - Improved Algorithms and Major Results

NASA Astrophysics Data System (ADS)

Castro, Rita; Oliva, Roger; Gutiérrez, Antonio; Barbosa, José; Catarino, Nuno; Martin-Neira, Manuel; Zundo, Michele; Cabot, François

2010-05-01

Following the Soil Moisture and Ocean Salinity (SMOS) launch in November 2009, a Commissioning Phase has taken place for six months, having Deimos closely cooperated with the European Space Agency's (ESA) Level 1 team. During these six months several studies have been conducted on calibration optimization, image reconstruction improvement, geolocation assessment and the impact on scientific results, in particular to insure optimal input to Level 2 Soil Moisture and Ocean Salinity retrieval. In parallel with the scientific studies, some new algorithms/mitigation techniques had to be developed, tested and implemented during the Commissioning Phase. Prior to launch, the Level 1 Prototype Processor (L1PP) included already several experimental algorithms different from the ones existent in the operational chain. These algorithms were tested during Commissioning and some were included in the final processing baseline as a result of the planned studies. Some unforeseen algorithms had to be defined, implemented and tested during the Commissioning Phase itself and these will also be described below. In L1a, for example, the calibration of the Power Measuring Systems (PMS) can be done using a cold target as reference, i.e., the Sky at ~3 K. This has been extensively analyzed and the results will be presented here. At least two linearity corrections to the PMS response function have been tested and compared. The deflection method was selected for inclusion on the operational chain and the results leading to this decision will be also presented. In Level 1B, all the foreign sources algorithms have been tested and validated using real data. The System Response Function (G-matrix) computed for different events has been analyzed and criteria for validation of its pseudo inverse, the J+ matrix, have been defined during the Commissioning Phase. The impact of errors in the J+ matrix has been studied and well characterized. The effects of the Flat Target Response (FTR) have also been

Salinization and Saline Environments

NASA Astrophysics Data System (ADS)

Vengosh, A.

2003-12-01

One of the most conspicuous phenomena of water-quality degradation, particularly in arid and semi-arid zones, is salinization of water and soil resources. Salinization is a long-term phenomenon, and during the last century many aquifers and river basins have become unsuitable for human consumption owing to high levels of salinity. Future exploitation of thousands of wells in the Middle East and in many other water-scarce regions in the world depends, to a large extent, on the degree and rate of salinization. Moreover, every year a large fraction of agricultural land is salinized and becomes unusable.Salinization is a global environmental phenomenon that affects many different aspects of our life (Williams, 2001a, b): changing the chemical composition of natural water resources (lakes, rivers, and groundwater), degrading the quality of water supply to the domestic and agriculture sectors, contribution to loss of biodiversity, taxonomic replacement by halotolerant species ( Williams, 2001a, b), loss of fertile soil, collapse of agricultural and fishery industries, changing of local climatic conditions, and creating severe health problems (e.g., the Aral Basin). The damage due to salinity in the Colorado River Basin alone, for example, ranges between 500 and 750 million per year and could exceed 1 billion per year if the salinity in the Imperial Dam increases from 700 mg L-1 to 900 mg L-1 (Bureau of Reclamation, 2003, USA). In Australia, accelerating soil salinization has become a massive environmental and economic disaster. Western Australia is "losing an area equal to one football oval an hour" due to spreading salinity ( Murphy, 1999). The annual cost for dryland salinity in Australia is estimated as AU700 million for lost land and AU$130 million for lost production ( Williams et al., 2002). In short, the salinization process has become pervasive.Salinity in water is usually defined by the chloride content (mg L-1) or total dissolved solids content (TDS, mg L-1or g

Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

NASA Astrophysics Data System (ADS)

Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

2012-04-01

Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite

Aquarius reveals salinity structure of tropical instability waves

NASA Astrophysics Data System (ADS)

Lee, Tong; Lagerloef, Gary; Gierach, Michelle M.; Kao, Hsun-Ying; Yueh, Simon; Dohan, Kathleen

2012-06-01

Sea surface salinity (SSS) measurements from the Aquarius/SAC-D satellite during September-December 2011 provide the first satellite observations of the salinity structure of tropical instability waves (TIWs) in the Pacific. The related SSS anomaly has a magnitude of approximately ±0.5 PSU. Different from sea surface temperature (SST) and sea surface height anomaly (SSHA) where TIW-related propagating signals are stronger a few degrees away from the equator, the SSS signature of TIWs is largest near the equator in the eastern equatorial Pacific where salty South Pacific water meets the fresher Inter-tropical Convergence Zone water. The dominant westward propagation speed of SSS near the equator is approximately 1 m/s. This is twice as fast as the 0.5 m/s TIW speed widely reported in the literature, typically from SST and SSHA away from the equator. This difference is attributed to the more dominant 17-day TIWs near the equator that have a 1 m/s dominant phase speed and the stronger 33-day TIWs away from the equator that have a 0.5 m/s dominant phase speed. The results demonstrate the important value of Aquarius in studying TIWs.

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre

2018-01-01

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

The implementation of sea ice model on a regional high-resolution scale

NASA Astrophysics Data System (ADS)

Prasad, Siva; Zakharov, Igor; Bobby, Pradeep; McGuire, Peter

2015-09-01

The availability of high-resolution atmospheric/ocean forecast models, satellite data and access to high-performance computing clusters have provided capability to build high-resolution models for regional ice condition simulation. The paper describes the implementation of the Los Alamos sea ice model (CICE) on a regional scale at high resolution. The advantage of the model is its ability to include oceanographic parameters (e.g., currents) to provide accurate results. The sea ice simulation was performed over Baffin Bay and the Labrador Sea to retrieve important parameters such as ice concentration, thickness, ridging, and drift. Two different forcing models, one with low resolution and another with a high resolution, were used for the estimation of sensitivity of model results. Sea ice behavior over 7 years was simulated to analyze ice formation, melting, and conditions in the region. Validation was based on comparing model results with remote sensing data. The simulated ice concentration correlated well with Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Ocean and Sea Ice Satellite Application Facility (OSI-SAF) data. Visual comparison of ice thickness trends estimated from the Soil Moisture and Ocean Salinity satellite (SMOS) agreed with the simulation for year 2010-2011.

Salinity fronts in the tropical Pacific Ocean.

PubMed

Kao, Hsun-Ying; Lagerloef, Gary S E

2015-02-01

This study delineates the salinity fronts (SF) across the tropical Pacific, and describes their variability and regional dynamical significance using Aquarius satellite observations. From the monthly maps of the SF, we find that the SF in the tropical Pacific are (1) usually observed around the boundaries of the fresh pool under the intertropical convergence zone (ITCZ), (2) stronger in boreal autumn than in other seasons, and (3) usually stronger in the eastern Pacific than in the western Pacific. The relationship between the SF and the precipitation and the surface velocity are also discussed. We further present detailed analysis of the SF in three key tropical Pacific regions. Extending zonally around the ITCZ, where the temperature is nearly homogeneous, we find the strong SF of 1.2 psu from 7° to 11°N to be the main contributor of the horizontal density difference of 0.8 kg/m 3 . In the eastern Pacific, we observe a southward extension of the SF in the boreal spring that could be driven by both precipitation and horizontal advection. In the western Pacific, the importance of these newly resolved SF associated with the western Pacific warm/fresh pool and El Niño southern oscillations are also discussed in the context of prior literature. The main conclusions of this study are that (a) Aquarius satellite salinity measurements reveal the heretofore unknown proliferation, structure, and variability of surface salinity fronts, and that (b) the fine-scale structures of the SF in the tropical Pacific yield important new information on the regional air-sea interaction and the upper ocean dynamics.

Impact of river discharge on the California coastal ocean circulation and variability

NASA Astrophysics Data System (ADS)

Leiva, J.; Chao, Y.; Farrara, J. D.; Zhang, H.

2016-12-01

A real-time California coastal ocean nowcast and forecast system is used to quantify the impact of river discharge on the California coastal ocean circulation and variability. River discharge and freshwater runoff is monitored by an extensive network of stream gages maintained through the U.S. Geological Survey, that offers archived stream flow records as well as real-time datasets. Of all the rivers monitored by the USGS, 25 empty into the Pacific Ocean and contribute a potential source of runoff data. Monthly averages for the current water year yield discharge estimates as high as 6,000 cubic meters per second of additional freshwater input into our present model. Using Regional Ocean Modeling System (ROMS), we performed simulations from October 2015 to May 2016 with and without the river discharge. Results of these model simulations are compared with available observations including both in situ and satellite. Particular attention is paid to the salinity simulation. Validation is done with comparisons to sea glider data available through Oregon State University and UC San Diego, which provides depth profiles along the California coast during this time period. Additional validation is performed through comparisons with sea surface salinity measurements from the Soil Moisture and Ocean Salinity (SMOS) mission. Continued testing for previous years, e.g. between 2011 and 2015, is being made using the Aquarius sea surface salinity data. Discharge data collected by the USGS stream gages provides a necessary source of freshwater input that must be accounted for. Incorporating a new runoff source produces a more robust model that generates improved forecasts. Following validation with available sea glider and satellite data, the enhanced model can be adapted to real-time forecasting.

Modelling of the L-band brightness temperatures measured with ELBARA III radiometer on Bubnow wetland

NASA Astrophysics Data System (ADS)

Gluba, Lukasz; Sagan, Joanna; Lukowski, Mateusz; Szlazak, Radoslaw; Usowicz, Boguslaw

2017-04-01

Microwave radiometry has become the main tool for investigating soil moisture (SM) with remote sensing methods. ESA - SMOS (Soil Moisture and Ocean Salinity) satellite operating at L-band provides global distribution of soil moisture. An integral part of SMOS mission are calibration and validation activities involving measurements with ELBARA III which is an L-band microwave passive radiometer. It is done in order to improve soil moisture retrievals - make them more time-effective and accurate. The instrument is located at Bubnow test-site, on the border of cultivated field, fallow, meadow and natural wetland being a part of Polesie National Park (Poland). We obtain both temporal and spatial dependences of brightness temperatures for varied types of land covers with the ELBARA III directed at different azimuths. Soil moisture is retrieved from brightness temperature using L-band Microwave Emission of the Biosphere (L-MEB) model, the same as currently used radiative transfer model for SMOS. Parametrization of L-MEB, as well as input values are still under debate. We discuss the results of SM retrievals basing on data obtained during first year of the radiometer's operation. We analyze temporal dependences of retrieved SM for one-parameter (SM), two-parameter (SM, τ - optical depth) and three-parameter (SM, τ, Hr - roughness parameter) retrievals, as well as spatial dependences for specific dates. Special case of Simplified Roughness Parametrization, combining the roughness parameter and optical depth, is considered. L-MEB processing is supported by the continuous measurements of soil moisture and temperature obtained from nearby agrometeorological station, as well as studies on the soil granulometric composition of the Bubnow test-site area. Furthermore, for better estimation of optical depth, the satellite-derived Normalized Difference Vegetation Index (NDVI) was employed, supported by measured in situ vegetation parameters (such as Leaf Area Index and Vegetation

ENSO related sea surface salinity variability in the equatorial Pacific

NASA Astrophysics Data System (ADS)

Qu, T.

2016-12-01

Recently available satellite and Argo data have shown coherent, large-scale sea surface salinity (SSS) variability in the equatorial Pacific. Based on this variability, several SSS indices of El Nino have been introduced by previous studies. Combining results from an ocean general circulation model with available satellite and in-situ observations, this study investigates the SSS variability and its associated SSS indices in the equatorial Pacific. The ocean's role and in particular the vertical entrainment of subtropical waters in this variability are discussed, which suggests that the SSS variability in the equatorial Pacific may play some active role in ENSO evolution.

L-band radiometry for sea ice applications

NASA Astrophysics Data System (ADS)

Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.

2009-04-01

.g. on sea ice concentration and temperature. External calibration: to combine SMOS ice information with statistics on temperature and salinity variations derived from a suitable ocean model to identify ocean targets for a vicarious target calibration of the SMOS radiometer. Such a target can be identified most reliably in cold waters as suggested by Ruf (2000) before. At higher microwave frequencies the advantage of the Ruf method is that the absolute minimum of the observed brightness temperatures is a universal constant and can be used for external calibration. However, in the L band the salinity variations may shift the minimum to both directions so that suitable regions of low salinity variations need to be identified. For finding areas with fairly stable, at least known cold temperatures, one has to analyze existing prior (external) knowledge available from ocean observations (in situ and satellite) and from numerical models. From statistics based on daily AMSR SST fields and model simulations, the best area seems to be between Svalbard and Ocean Weather Ship Station (OWS) Mike, at 66N, 02E. However, variations in SST are still comparably large and the area can hardly be used for instrument calibration. It is suggested to deploy a number of drifters in a limited area representing a SMOS footprint to obtain accurate estimates of SSS and SST.

Submesoscale-selective compensation of fronts in a salinity-stratified ocean.

PubMed

Spiro Jaeger, Gualtiero; Mahadevan, Amala

2018-02-01

Salinity, rather than temperature, is the leading influence on density in some regions of the world's upper oceans. In the Bay of Bengal, heavy monsoonal rains and runoff generate strong salinity gradients that define density fronts and stratification in the upper ~50 m. Ship-based observations made in winter reveal that fronts exist over a wide range of length scales, but at O(1)-km scales, horizontal salinity gradients are compensated by temperature to alleviate about half the cross-front density gradient. Using a process study ocean model, we show that scale-selective compensation occurs because of surface cooling. Submesoscale instabilities cause density fronts to slump, enhancing stratification along-front. Specifically for salinity fronts, the surface mixed layer (SML) shoals on the less saline side, correlating sea surface salinity (SSS) with SML depth at O(1)-km scales. When losing heat to the atmosphere, the shallower and less saline SML experiences a larger drop in temperature compared to the adjacent deeper SML on the salty side of the front, thus correlating sea surface temperature (SST) with SSS at the submesoscale. This compensation of submesoscale fronts can diminish their strength and thwart the forward cascade of energy to smaller scales. During winter, salinity fronts that are dynamically submesoscale experience larger temperature drops, appearing in satellite-derived SST as cold filaments. In freshwater-influenced regions, cold filaments can mark surface-trapped layers insulated from deeper nutrient-rich waters, unlike in other regions, where they indicate upwelling of nutrient-rich water and enhanced surface biological productivity.

Submesoscale-selective compensation of fronts in a salinity-stratified ocean

PubMed Central

Spiro Jaeger, Gualtiero; Mahadevan, Amala

2018-01-01

Salinity, rather than temperature, is the leading influence on density in some regions of the world’s upper oceans. In the Bay of Bengal, heavy monsoonal rains and runoff generate strong salinity gradients that define density fronts and stratification in the upper ~50 m. Ship-based observations made in winter reveal that fronts exist over a wide range of length scales, but at O(1)-km scales, horizontal salinity gradients are compensated by temperature to alleviate about half the cross-front density gradient. Using a process study ocean model, we show that scale-selective compensation occurs because of surface cooling. Submesoscale instabilities cause density fronts to slump, enhancing stratification along-front. Specifically for salinity fronts, the surface mixed layer (SML) shoals on the less saline side, correlating sea surface salinity (SSS) with SML depth at O(1)-km scales. When losing heat to the atmosphere, the shallower and less saline SML experiences a larger drop in temperature compared to the adjacent deeper SML on the salty side of the front, thus correlating sea surface temperature (SST) with SSS at the submesoscale. This compensation of submesoscale fronts can diminish their strength and thwart the forward cascade of energy to smaller scales. During winter, salinity fronts that are dynamically submesoscale experience larger temperature drops, appearing in satellite-derived SST as cold filaments. In freshwater-influenced regions, cold filaments can mark surface-trapped layers insulated from deeper nutrient-rich waters, unlike in other regions, where they indicate upwelling of nutrient-rich water and enhanced surface biological productivity. PMID:29507874

Integrated Stewardship of NASA Satellite and Field Campaign Data

NASA Astrophysics Data System (ADS)

Hausman, J.; Tsontos, V. M.; Hardman, S. H.

2016-02-01

The Physical Oceanography Distributed Active Archive Center (PO.DAAC) is NASA's archive, steward and distributor for physical oceanographic satellite data. Those data are typically organized along the lines of single parameters, such as Sea Surface Temperature, Ocean Winds, Salinity, etc. However there is a need supplement satellite data with in situ and various other remote sensing data to provide higher spatial and temporal sampling and information on physical processes that the satellites are not capable of measuring. This presentation will discuss how PO.DAAC is creating a stewardship and distribution plan that will accommodate satellite, in situ and other remote sensing data that can be used to solve a more integrated approach to data access and utilization along thematic lines in support of science and applications, specifically those posed by Salinity Processes in the Upper Ocean Regional Study (SPURS) and Oceans Melting Greenland (OMG) projects. SPURS used shipboard data, moorings and in situ instruments to investigate changes in salinity and how that information can be used in explaining the water cycle. OMG is studying ice melt in Greenland and how it contributes to changes in sea level through shipboard measurements, airborne and a variety of in situ instruments. PO.DAAC plans on adapting to stewarding and distributing these varieties of data through applications of file format and metadata standards (so data are discoverable and interoperable), extend the internal data system (to allow for better archiving, collection generation and querying of in situ and airborne data) and integration into tools (visualization and data access). We are also working on Virtual Collections with ESDWG, which could provide access to relevant data across DAACs/Agencies along thematic lines. These improvements will improve long-term data management and make it easier for users of various background, regardless if remote sensing or in situ, to discover and use the data.

Detection and variability of the Congo River plume from satellite derived sea surface temperature, salinity, ocean colour and sea level

NASA Astrophysics Data System (ADS)

Hopkins, Jo; Lucas, Marc; Dufau, Claire; Sutton, Marion; Lauret, Olivier

2013-04-01

The Congo River in Africa has the world's second highest annual mean daily freshwater discharge and is the second largest exporter of terrestrial organic carbon into the oceans. It annually discharges an average of 1,250 × 109 m3 of freshwater into the southeast Atlantic producing a vast fresh water plume, whose signature can be traced hundreds of kilometres from the river mouth. Large river plumes such as this play important roles in the ocean carbon cycle, often functioning as carbon sinks. An understanding of their extent and seasonality is therefore essential if they are to be realistically accounted for in global assessments of the carbon cycle. Despite its size, the variability and dynamics of the Congo plume are minimally documented. In this paper we analyse satellite derived sea surface temperature, salinity, ocean colour and sea level anomaly to describe and quantify the extent, strength and variability of the far-field plume and to explain its behaviour in relation to winds, ocean currents and fresh water discharge. Empirical Orthogonal Function analysis reveals strong seasonal and coastal upwelling signals, potential bimodal seasonality of the Angola Current and responses to fresh water discharge peaks in all data sets. The strongest plume-like signatures however were found in the salinity and ocean colour where the dominant sources of variability come from the Congo River itself, rather than from the wider atmosphere and ocean. These two data sets are then analysed using a statistically based water mass detection technique to isolate the behaviour of the plume. The Congo's close proximity to the equator means that the influence of the earth's rotation on the fresh water inflow is relatively small and the plume tends not to form a distinct coastal current. Instead, its behaviour is determined by wind and surface circulation patterns. The main axis of the plume between November and February, following peak river discharge, is oriented northwest, driven

AQUARIUS: A Passive/Active Microwave Sensor to Monitor Sea Surface Salinity Globally from Space

NASA Technical Reports Server (NTRS)

LeVine, David; Lagerloef, Gary S. E.; Colomb, F. Raul; Chao, Yi

2004-01-01

Salinity is important for understanding ocean dynamics, energy exchange with the atmosphere and the global water cycle. Existing data is limited and much of the ocean has never even been sampled. Sea surface salinity can be measured remotely by satellite and a three year mission for this purpose called AquariudSAC-D has recently been selected by NASA's Earth System Science Pathfinder (ESSP) program. The objective is to map the salinity field globally with a spatial resolution of 100 km and a monthly average accuracy of 0.2 psu. The mission, scheduled for launch in 2008, is a partnership of the United States National Aeronautics and Space Agency (NASA) and the Argentine Comision National de Actividades Epaciales (CONAE).

Monitoring the Impact of Climate Change on Soil Salinity in Agricultural Areas Using Ground and Satellite Sensors

NASA Astrophysics Data System (ADS)

Corwin, D. L.; Scudiero, E.

2017-12-01

Changes in climatic patterns have had dramatic influence on agricultural areas worldwide, particularly in irrigated arid-zone agricultural areas subjected to recurring drought, such as California's San Joaquin Valley (SJV), or areas receiving above average rainfall for a decade or more, such as Minnesota's Red River Valley (RRV). Climate change has impacted water availability with an under or over abundance, which subsequently has impacted soil salinity levels in the root zone primarily from the upward movement of salts from shallow water tables. Inventorying and monitoring the impact of climate change on soil salinity is crucial to evaluate the extent of the problem, to recognize trends, and to formulate state-wide and field-scale irrigation, drainage, and crop management strategies that will sustain the agricultural productivity of the SJV and RRV. Over the past 3 decades, Corwin and colleagues at the U.S. Salinity Laboratory have developed proximal sensor (i.e., electrical resistivity and electromagnetic induction) and remote imagery (i.e., MODIS and Landsat 7) methodologies for assessing soil salinity at multiple scales: field (0.5 ha to 3 km2), landscape (3 to 10 km2), and regional (10 to 105 km2) scales. The purpose of this presentation is to provide an overview of these scale-dependent salinity assessment technologies. Case studies for SJV and RRV are presented to demonstrate at multiple scales the utility of these approaches in assessing soil salinity changes due to management-induced changes and to changes in climate patterns, and in providing site-specific irrigation management information for salinity control. Decision makers in state and federal agencies, irrigation and drainage district managers, soil and water resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of this information.

Mechanisms of Mixed-Layer Salinity Seasonal Variability in the Indian Ocean

NASA Astrophysics Data System (ADS)

Köhler, Julia; Serra, Nuno; Bryan, Frank O.; Johnson, Benjamin K.; Stammer, Detlef

2018-01-01

Based on a joint analysis of an ensemble mean of satellite sea surface salinity retrievals and the output of a high-resolution numerical ocean circulation simulation, physical processes are identified that control seasonal variations of mixed-layer salinity (MLS) in the Indian Ocean, a basin where salinity changes dominate changes in density. In the northern and near-equatorial Indian Ocean, annual salinity changes are mainly driven by respective changes of the horizontal advection. South of the equatorial region, between 45°E and 90°E, where evaporation minus precipitation has a strong seasonal cycle, surface freshwater fluxes control the seasonal MLS changes. The influence of entrainment on the salinity variance is enhanced in mid-ocean upwelling regions but remains small. The model and observational results reveal that vertical diffusion plays a major role in precipitation and river runoff dominated regions balancing the surface freshwater flux. Vertical diffusion is important as well in regions where the advection of low salinity leads to strong gradients across the mixed-layer base. There, vertical diffusion explains a large percentage of annual MLS variance. The simulation further reveals that (1) high-frequency small-scale eddy processes primarily determine the salinity tendency in coastal regions (in particular in the Bay of Bengal) and (2) shear horizontal advection, brought about by changes in the vertical structure of the mixed layer, acts against mean horizontal advection in the equatorial salinity frontal regions. Observing those latter features with the existing observational components remains a future challenge.

Improving River Flow Predictions from the NOAA NCRFC Forecasting Model by Incorporating Satellite Observations

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Jacobs, J. M.; Restrepo, P. J.; Deweese, M. M.; Connelly, B.; Buan, S.

2016-12-01

The NOAA National Weather Service North Central River Forecast Center (NCRFC) is responsible for issuing river flow forecasts for parts of the Upper Mississippi, Great Lakes, and Hudson Bay drainages, including the Red River of the North basin (RRB). The NCRFC uses an operational hydrologic modeling infrastructure called the Community Hydrologic Prediction System (CHPS) for its operational forecasts, which currently links the SNOW-17 snow accumulation and ablation model, to the Sacramento-Soil Moisture Accounting (SAC-SMA) rainfall-runoff model, to a number of hydrologic and hydraulic flow routing models. The operational model is lumped and requires only area-averaged precipitation and air temperature as inputs. NCRFC forecasters use observational data of hydrological state variables as a source of supplemental information during forecasting, and can use professional judgment to modify the model states in real time. In a few recent years (e.g. 2009, 2013), the RRB exhibited unexpected anomalous hydrologic behavior, resulting in overestimation of peak flood discharge by up to 70% and highlighting the need for observations with high temporal and spatial coverage. Unfortunately, observations of hydrological states (e.g. soil moisture, snow water equivalent (SWE)) are relatively scarce in the RRB. Satellite remote sensing can fill this need. We use Minnesota's Buffalo River watershed within the RRB as a test case and update the operational CHPS model using modifications based on satellite observations, including AMSR-E SWE and SMOS soil moisture estimates. We evaluate the added forecasting skill of the satellite-enhanced model compared to measured streamflow using hindcasts from 2010-2013.

Enhancing begetation productivity forecasting using remotely-sensed surface soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

With the onset of data availability from the ESA Soil Moisture and Ocean Salinity (SMOS) mission (Kerr and Levine, 2008) and the expected 2015 launch of the NASA Soil Moisture Active and Passive (SMAP) mission (Entekhabi et al., 2010), the next five years should see a significant expansion in our ab...

Impact of realistic soil moisture initialization on the representation of extreme events in the western Mediterranean

NASA Astrophysics Data System (ADS)

Helgert, Sebastian; Khodayar, Samiro

2017-04-01

precipitation in the WMED. For the realistic SM initialization different state-of-art high-resolution SM products (25km up to 1km grid spacing) of the Soil Moisture Ocean Salinity mission (SMOS) are examined. A CDF-matching method is applied to reduce the bias between model and SMOS-satellite observation. Moreover, techniques to estimate the initial soil moisture profile from satellite data are tested.

Assessing the Potential to Derive Air-Sea Freshwater Fluxes from Aquarius-Like Observations of Surface Salinity

NASA Technical Reports Server (NTRS)

Zhen, Li; Adamec, David

2009-01-01

A state-of-the-art numerical model is used to investigate the possibility of determining freshwater flux fields from temporal changes io sea-surface salinity (SSS), a goal of the satellite salinity-measuring mission, Aquarius/SAC-D. Because the estimated advective temporal scale is usually longer than the Aquarius/SAC-D revisit time, the possibility of producing freshwater flux estimates from temporal salinity changes is first examined by using a correlation analysis. For the mean seasonal cycle, the patterns of the correlations between the freshwater fluxes and surface salinity temporal tendencies are mainly zonally oriented, and are highest where the local precipitation is also relatively high. Nonseasonal (deviations from the monthly mean) correlations are highest along mid-latitude moon tracks and are relatively small in the tropics. The complex correlation patterns presented here suggest that a global retrieval of the difference between evaporation and precipitation (E-P) from salinity changes requires more complex techniques than a simple consideration of local balance with surface forcing.

Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China.

PubMed

Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain

2008-11-07

This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years salt-affected areas were detected using a normal supervised classification method. Corresponding cropped areas were detected from NVDI (Normalized Difference Vegetation Index) values using an unsupervised method. Field samples and agricultural statistics were used to estimate the accuracy of the classification. Historical data concerning irrigation/drainage and the groundwater table were used to analyze the relation between changes in soil salinity and land and water management practices. Results showed that: (1) the overall accuracy of remote sensing in detecting soil salinity was 90.2%, and in detecting cropped area, 98%; (2) the installation/innovation of the drainage system did help to control salinity; and (3) a low ratio of cropped land helped control salinity in the Hetao Irrigation District. These findings suggest that remote sensing is a useful tool to detect soil salinity and has potential in evaluating and improving land and water management practices.

Tools, Services & Support of NASA Salinity Mission Data Archival Distribution through PO.DAAC

NASA Astrophysics Data System (ADS)

Tsontos, V. M.; Vazquez, J.

2017-12-01

The Physical Oceanography Distributed Active Center (PO.DAAC) serves as the designated NASA repository and distribution node for all Aquarius/SAC-D and SMAP sea surface salinity (SSS) mission data products in close collaboration with the projects. In addition to these official mission products, that by December 2017 will include the Aquarius V5.0 end-of-mission data, PO.DAAC archives and distributes high-value, principal investigator led satellite SSS products, and also datasets from NASA's "Salinity Processes in the Upper Ocean Regional Study" (SPURS 1 & 2) field campaigns in the N. Atlantic salinity maximum and high rainfall E. Tropical Pacific regions. Here we report on the status of these data holdings at PO.DAAC, and the range of data services and access tools that are provided in support of NASA salinity. These include user support and data discovery services, OPeNDAP and THREDDS web services for subsetting/extraction, and visualization via LAS and SOTO. Emphasis is placed on newer capabilities, including PODAAC's consolidated web services (CWS) and advanced L2 subsetting tool called HiTIDE.

Global soil moisture from the aquarius satellite: Description and initial assessment

USDA-ARS?s Scientific Manuscript database

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 scop...

Impact of Aquarius and SMAP Sea Surface Salinity Observations on Seasonal Predictions of the 2015 El Nino

NASA Technical Reports Server (NTRS)

Hackert, E.; Kovach, R.; Marshak, J.; Borovikov, A.; Molod, A.; Vernieres, G.

2018-01-01

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts for the big 2015 El Nino event. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP (Soil Moisture Active Passive Mission), allows a unique opportunity to compare and contrast forecasts generated with the benefit of these two satellite SSS observation types. Four distinct experiments are presented that include 1) freely evolving model SSS (i.e. no satellite SSS), relaxation to 2) climatological SSS (i.e. WOA13 SSS), 3) Aquarius, and 4) SMAP initialization. Coupled hindcasts are then generated from these initial conditions for March 2015. These forecasts are then validated against observations and evaluated with respect to the observed El Nino development.

Linking water and carbon cycles through salinity observed from space

NASA Astrophysics Data System (ADS)

Xie, X.; Liu, W. T.

2017-12-01

The association of ocean surface salinity in global hydrological cycle and climate change has been traditionally studied through the examination of its tendency and advection as manifestation of ocean's heat and water fluxes with the atmosphere. The variability of surface heat and water fluxes are linked to top of atmosphere radiation, whose imbalance is the main cause of global warming. Besides the link of salinity to greenhouse warming through water balance, this study will focus on the effect of changing salinity on carbon dioxide flux between the ocean and the atmosphere. We have built statistical models to estimate the partial pressure of carbon dioxide (pCO2) and ocean acidification (in terms of total alkalinity and pH) using spacebased data. PCO2 is a critical parameter governing ocean as source and sink of the accumulated greenhouse gas in the atmosphere. The exchange also causes ocean acidification, which is detrimental to marine lives and ecology. Before we had sufficient spacebased salinity measurements coincident with in situ pCO2 measurement, we trained our statistical models to use satellite sea surface temperature and chlorophyll, with one model using salinity climatology and the other without. We found significant differences between the two models in regions of strong water input through river discharge and surface water flux. The pCO2 output follows the seasonal salinity advection of the Amazon outflow. The seasonal salinity advection between Bay of Bengal and Arabian Sea are followed by change of pCO2 and total alkalinity. At shorter time scales, the signatures of rain associated with intraseasonal organized convection of summer monsoon can be detected. We have observed distribution agreement of among pCO2, surface salinity, and surface water flux for variation from a few days to a few years under the Pacific ITCZ; the agreement varies slightly with season and longitudes and the reason is under study.

Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.

2014-01-01

As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model

Microwave Interferometric Radiometry in Remote Sensing: an Invited Historical Review

NASA Technical Reports Server (NTRS)

Martin-Neira, M.; LeVine, D. M.; Kerr, Y.; Skou, N.; Peichl, M.; Camps, A.; Corbella, I.; Hallikainen, M.; Font, J.; Wu, J.;

Continental hydrology from satellite multi-sensor data and in situ observations

NASA Astrophysics Data System (ADS)

Kouraev, A. V.

2009-04-01

Continental waters represent a tiny part of the total water amount on Earth, but play a major role in climate variability and have paramount importance for terrestrial ecosystems and human needs. They are an integral part of the global climate system with important links and feedbacks generated through its influence on surface energy and moisture fluxes between continental water, atmosphere and oceans. It is important to well understand what are temporal and spatial scales of variability of continental waters, what are teleconnections, feedbacks and mechanisms responsible for the changes, what are natural and anthropogenic causes of recent and historical changes in the hydrometeorological parameters. In this respect, continental hydrology is one of the research fields where acquired knowledge and understanding of natural processes will benefit from combination of conventional observations with data from SMOS and other Earth Observation satellites. We present studies of two key regions where SMOS data have the potential to significantly expand the potential of scientific and applied studies: a) Western Siberia and b) Euphrates-Tigris river system. Main part of the Western Siberia is covered by Ob' river system; which will be the main object of study for this region. This river basin is characterised by large flooded areas, frequently described as the biggest world swamp. Wetlands are also an important source of methane and source/sink for the CO2. Although wetlands played a key role in the natural variations of carbon cycle during the last climatic cycles, their temporal and spatial variations are still poorly modelled. As a consequence, it is very difficult to predict the effect of their variations with climate change and the resulting effect on the carbon cycle for the next decades. Water resources of the extensive Euphrates-Tigris (ET) river basin have vital importance for people living on its watershed, and for its ecosystems. This river basin also provides

The vertical dependence in the horizontal variability of salinity and temperature at the ocean surface

NASA Astrophysics Data System (ADS)

Asher, W.; Drushka, K.; Jessup, A. T.; Clark, D.

2016-02-01

Satellite-mounted microwave radiometers measure sea surface salinity (SSS) as an area-averaged quantity in the top centimeter of the ocean over the footprint of the instrument. If the horizontal variability in SSS is large inside this footprint, sub-grid-scale variability in SSS can affect comparison of the satellite-retrieved SSS with in situ measurements. Understanding the magnitude of horizontal variability in SSS over spatial scales that are relevant to the satellite measurements is therefore important. Horizontal variability of SSS at the ocean surface can be studied in situ using data recorded by thermosalinographs (TSGs) that sample water from a depth of a few meters. However, it is possible measurements made at this depth might underestimate the horizontal variability at the surface because salinity and temperature can become vertically stratified in a very near surface layer due to the effects of rain, solar heating, and evaporation. This vertical stratification could prevent horizontal gradients from propagating to the sampling depths of ship-mounted TSGs. This presentation will discuss measurements made using an underway salinity profiling system installed on the R/V Thomas Thompson that made continuous measurements of SSS and SST in the Pacific Ocean. The system samples at nominal depths of 2-m, 3-m, and 5-m, allowing the depth dependence of the horizontal variability in SSS and SST to be measured. Horizontal variability in SST is largest at low wind speeds during daytime, when a diurnal warm layer forms. In contrast, the diurnal signal in the variability of SSS was smaller with variability being slightly larger at night. When studied as a function of depth, the results show that over 100-km scales, the horizontal variability in both SSS and SST at a depth of 2 m is approximately a factor of 4 higher than the variability at 5 m.

Three Years of Aquarius Salinity Measurements: Algorithm, Validation and Applications

NASA Astrophysics Data System (ADS)

Meissner, T.; Wentz, F. J.; Le Vine, D. M.; Lagerloef, G. S. E.

2014-12-01

Aquarius is an L-band radiometer/scatterometer (i.e. active/passive) system designed to provide monthly salinity maps at 150 km spatial scale to an accuracy of 0.2 psu. The sensor was launched on June 10, 2011 as part of the Aquarius/SAC-D mission and has been collecting data since August 25, 2011. Version 3 of the data product was released in June 2014 and provides a major milestone towards reaching the mission requirement of 0.2 psu. This presentation reports the status of the Aquarius salinity retrieval algorithm highlighting the advances that have been made for and since the Version 3 release. The most important ones are: 1) An improved surface roughness correction that is based on Aquarius scatterometer observations; 2) A reduction in ascending/descending differences due to galactic background radiation reflected from the ocean surface; 3) A refinement of the quality control flags and masks that indicate degradation under certain environmental conditions. The Aquarius salinity algorithm also retrieves wind speed as part of the roughness correction with an accuracy comparable to the products from other satellites such as WindSat, SSMIS, ASCAT, and QuikSCAT. Validation of the salinity retrievals is accomplished using measurements from ARGO drifters measuring at 5 m depth and in the tropics also from moored buoys measuring at 1 m depth which are co-located with the nearest Aquarius footprint. In the most recent work an effort has also been made to identify areas with frequent rain to isolate potential issues with rain freshening in the upper ocean layer. Results in rain-free regions indicate that on monthly basis and 150 km grid, the V3 Aquarius salinity maps have an accuracy of about 0.13 psu in the tropics and 0.22 psu globally. Comparing Aquarius with ARGO and moored buoy salinity measurements during and after rain events permits a quantitative assessment of the effect of salinity stratification within the first 5 m of the upper ocean layer.

CAROLS: a new airborne L-band radiometer for ocean surface and land observations.

PubMed

Zribi, Mehrez; Pardé, Mickael; Boutin, Jacquline; Fanise, Pascal; Hauser, Daniele; Dechambre, Monique; Kerr, Yann; Leduc-Leballeur, Marion; Reverdin, Gilles; Skou, Niels; Søbjærg, Sten; Albergel, Clement; Calvet, Jean Christophe; Wigneron, Jean Pierre; Lopez-Baeza, Ernesto; Rius, Antonio; Tenerelli, Joseph

2011-01-01

The "Cooperative Airborne Radiometer for Ocean and Land Studies" (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer-STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity.

Sensor-Based Assessment of Soil Salinity during the First Years of Transition from Flood to Sprinkler Irrigation.

PubMed

Casterad, Mª Auxiliadora; Herrero, Juan; Betrán, Jesús A; Ritchie, Glen

2018-02-17

A key issue for agriculture in irrigated arid lands is the control of soil salinity, and this is one of the goals for irrigated districts when changing from flood to sprinkling irrigation. We combined soil sampling, proximal electromagnetic induction, and satellite data to appraise how soil salinity and its distribution along a previously flood-irrigated field evolved after its transformation to sprinkling. We also show that the relationship between NDVI (normalized difference vegetation index) and ECe (electrical conductivity of the soil saturation extracts) mimics the production function between yield and soil salinity. Under sprinkling, the field had a double crop of barley and then sunflower in 2009 and 2011. In both years, about 50% of the soil of the entire studied field-45 ha-had ECe < 8 dS m-1, i.e., allowing barley cultivation, while the percent of surface having ECe ≥ 16 dS m-1 increased from 8.4% in 2009 to 13.7% in 2011. Our methodology may help monitor the soil salinity oscillations associated with irrigation management. After quantifying and mapping the soil salinity in 2009 and 2011, we show that barley was stunted in places of the field where salinity was higher. Additionally, the areas of salinity persisted after the subsequent alfalfa cropping in 2013. Application of differential doses of water to the saline patches is a viable method to optimize irrigation water distribution and lessen soil salinity in sprinkler-irrigated agriculture.

Sensor-Based Assessment of Soil Salinity during the First Years of Transition from Flood to Sprinkler Irrigation

PubMed Central

Herrero, Juan; Betrán, Jesús A.; Ritchie, Glen

2018-01-01

A key issue for agriculture in irrigated arid lands is the control of soil salinity, and this is one of the goals for irrigated districts when changing from flood to sprinkling irrigation. We combined soil sampling, proximal electromagnetic induction, and satellite data to appraise how soil salinity and its distribution along a previously flood-irrigated field evolved after its transformation to sprinkling. We also show that the relationship between NDVI (normalized difference vegetation index) and ECe (electrical conductivity of the soil saturation extracts) mimics the production function between yield and soil salinity. Under sprinkling, the field had a double crop of barley and then sunflower in 2009 and 2011. In both years, about 50% of the soil of the entire studied field—45 ha—had ECe < 8 dS m−1, i.e., allowing barley cultivation, while the percent of surface having ECe ≥ 16 dS m−1 increased from 8.4% in 2009 to 13.7% in 2011. Our methodology may help monitor the soil salinity oscillations associated with irrigation management. After quantifying and mapping the soil salinity in 2009 and 2011, we show that barley was stunted in places of the field where salinity was higher. Additionally, the areas of salinity persisted after the subsequent alfalfa cropping in 2013. Application of differential doses of water to the saline patches is a viable method to optimize irrigation water distribution and lessen soil salinity in sprinkler-irrigated agriculture. PMID:29462981

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

An evaluation of hyperspectral vegetation indices for detecting soil salinity in sugarcane fields using EO-1 Hyperion Data

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; Alavi Panah, S. K.; Bartholomeus, H.; Mojaradi, B.; Clevers, J.; Behzad, M.

2012-04-01

Sugarcane is the major agricultural crops in the Khuzestan province, in the southwest of Iran. But soil salinity is a major problem affecting the sugarcane yield, and therefore, monitoring and assessment of soil salinity is necessary. This research was carried out to investigate the performance of several hyperspectral vegetation indices to assess salinity stress in sugarcane fields and to determine the suitable indicators and statistical models for detecting various soil salinity levels. For this purpose one Hyperion image was acquired on Sept 2, 2010 and soil salinity was measured in 108 points 5 to 15 days from this date. 60 Samples were used for modeling and 48 samples were used for validation. Values of the soil salinity were linked with the corresponding pixel at the satellite imagery and 16 (hyperspectral) spectral indices were calculated. Then, the potential of these indices for estimating the soil salinity were analyzed and results show that soil salinity can well be estimated by vegetation indices derived from Hyperion data. Indices that are based on the chlorophyll and water absorption bands have medium to high relationship with soil salinity, while indices that only use visible bands or combination of visible and NIR bands don't perform well. From the investigated indices the Optimized Soil-Adjusted Vegetation Index (OSAVI) has the strongest relationship (R2 = 0.69) with soil salinity, because this index minimizes the variations in reflectance characteristics of soil background.

3D Dynamics of the Near-Surface Layer of the Ocean in the Presence of Freshwater Influx

NASA Astrophysics Data System (ADS)

Dean, C.; Soloviev, A.

2015-12-01

Freshwater inflow due to convective rains or river runoff produces lenses of freshened water in the near surface layer of the ocean. These lenses are localized in space and typically involve both salinity and temperature anomalies. Due to significant density anomalies, strong pressure gradients develop, which result in lateral spreading of freshwater lenses in a form resembling gravity currents. Gravity currents inherently involve three-dimensional dynamics. The gravity current head can include the Kelvin-Helmholtz billows with vertical density inversions. In this work, we have conducted a series of numerical experiments using computational fluid dynamics tools. These numerical simulations were designed to elucidate the relationship between vertical mixing and horizontal advection of salinity under various environmental conditions and potential impact on the pollution transport including oil spills. The near-surface data from the field experiments in the Gulf of Mexico during the SCOPE experiment were available for validation of numerical simulations. In particular, we observed a freshwater layer within a few-meter depth range and, in some cases, a density inversion at the edge of the freshwater lens, which is consistent with the results of numerical simulations. In conclusion, we discuss applicability of these results to the interpretation of Aquarius and SMOS sea surface salinity satellite measurements. The results of this study indicate that 3D dynamics of the near-surface layer of the ocean are essential in the presence of freshwater inflow.

A soil moisture index derived from thermal infrared sensor on-board geostationary satellites over Europe, Africa and Australia

NASA Astrophysics Data System (ADS)

Ghilain, Nicolas; Trigo, Isabel; Arboleda, Alirio; Barrios, Jose-Miguel; Batelaan, Okke; Gellens-Meulenberghs, Françoise

2017-04-01

Soil moisture plays a central role in the water cycle. In particular, it is a major component which variability controls the evapotranspiration process. Over the past years, there has been a large commitment of the remote sensing research community to develop satellites and retrieval algorithm for soil moisture monitoring over continents. Most of those rely on the observation in the microwave lengths, making use either of passive, active or both methods combined. However, the available derived products are given at a relatively low spatial resolution for applications at the kilometer scale over entire continents, and with a revisit time that may not be adequate for all applications, as for example agriculture. Thermal infrared observations from a combination of geostationary satellites offer a global view of continents every hour (or even at higher frequency) at a few kilometers resolution, which makes them attractive as another, and potentially complementary, source of information of surface soil moisture. In this study, the Copernicus LST and the LSA-SAF LST are used to derive soil moisture over entire continents (Europe, Africa, Australia). The derived soil moisture is validated against in-situ observations and compared to other available products from remote sensing (SMOS, ASCAT) and from numerical weather prediction (ECMWF). We will present the result of this validation, and will show how it could be used in continental scale evapotranspiration monitoring.

Passive Microwave Measurements of Salinity: The Gulf Stream Experiment

NASA Technical Reports Server (NTRS)

LeVine, D. M.; Koblinsky, C.; Haken, M.; Howden, S.; Bingham, F.; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

Passive microwave sensors at L-band (1.4 GHz) operating from aircraft have demonstrated that salinity can be measured with sufficient accuracy (I psu) to be scientifically meaningful in coastal waters. However, measuring salinity in the open ocean presents unresolved issues largely because of the much greater accuracy (approximately 0.2 psu) required of global maps to be scientifically viable. The development of a satellite microwave instrument to make global measurements of SSS (Sea Surface Salinity) is the focus of a joint JPL/GSFC/NASA ocean research program called Aquarius. In the summer of 1999 a series of measurements called, The Gulf Stream Experiment, were conducted as part of research at the Goddard Space Flight Center to test the potential for passive microwave remote sensing of salinity in the open ocean. The measurements consisted of airborne microwave instruments together with ships and drifters for surface truth. The study area was a 200 km by 100 km rectangle about 250 km east of Delaware Bay between the continental shelf waters and north wall of the Gulf Stream. The primary passive instruments were the ESTAR radiometer (L-band, H-pol) and the SLFMR radiometer (L-band, V-pol). In addition, the instruments on the aircraft included a C-band radiometer (ACMR), an ocean wave scatterometer (ROWS) and an infrared radiometer (for surface temperature). These instruments were mounted on the NASA P-3 Orion aircraft. Sea surface measurements consisted of thermosalinograph data provided by the R/V Cape Henlopen and the MN Oleander, and data from salinity and temperature sensors on three surface drifters deployed from the R/V Cape Henlopen. The primary experiment period was August 26-September 2, 1999. During this period the salinity field within the study area consisted of a gradient on the order of 2-3 psu in the vicinity of the shelf break and a warm core ring with a gradient of 1-2 psu. Detailed maps were made with the airborne sensors on August 28 and 29 and

A Comparison of the Pac-X Trans-Pacific Wave Glider Data and Satellite Data (MODIS, Aquarius, TRMM and VIIRS)

PubMed Central

Villareal, Tracy A.; Wilson, Cara

2014-01-01

Four wave-propelled autonomous vehicles (Wave Gliders) instrumented with a variety of oceanographic and meteorological sensors were launched from San Francisco, CA in November 2011 for a trans-Pacific (Pac-X) voyage to test platform endurance. Two arrived in Australia, one in Dec 2012 and one in February 2013, while the two destined for Japan both ran into technical difficulties and did not arrive at their destination. The gliders were all equipped with sensors to measure temperature, salinity, turbidity, oxygen, and both chlorophyll and oil fluorescence. Here we conduct an initial assessment of the data set, noting necessary quality control steps and instrument utility. We conduct a validation of the Pac-X dataset by comparing the glider data to equivalent, or near-equivalent, satellite measurements. Sea surface temperature and salinity compared well to satellite measurements. Chl fluorescence from the gliders was more poorly correlated, with substantial between glider variability. Both turbidity and oil CDOM sensors were compromised to some degree by interfering processes. The well-known diel cycle in chlorophyll fluorescence was observed suggesting that mapping physiological data over large scales is possible. The gliders captured the Pacific Ocean’s major oceanographic features including the increased chlorophyll biomass of the California Current and equatorial upwelling. A comparison of satellite sea surface salinity (Aquarius) and glider-measured salinity revealed thin low salinity lenses in the southwestern Pacific Ocean. One glider survived a direct passage through a tropical cyclone. Two gliders traversed an open ocean phytoplankton bloom; extensive spiking in the chlorophyll fluorescence data is consistent with aggregation and highlights another potential future use for the gliders. On long missions, redundant instrumentation would aid in interpreting unusual data streams, as well as a means to periodically image the sensor heads. Instrument placement

A comparison of the Pac-X trans-Pacific Wave Glider data and satellite data (MODIS, Aquarius, TRMM and VIIRS).

PubMed

Villareal, Tracy A; Wilson, Cara

2014-01-01

Four wave-propelled autonomous vehicles (Wave Gliders) instrumented with a variety of oceanographic and meteorological sensors were launched from San Francisco, CA in November 2011 for a trans-Pacific (Pac-X) voyage to test platform endurance. Two arrived in Australia, one in Dec 2012 and one in February 2013, while the two destined for Japan both ran into technical difficulties and did not arrive at their destination. The gliders were all equipped with sensors to measure temperature, salinity, turbidity, oxygen, and both chlorophyll and oil fluorescence. Here we conduct an initial assessment of the data set, noting necessary quality control steps and instrument utility. We conduct a validation of the Pac-X dataset by comparing the glider data to equivalent, or near-equivalent, satellite measurements. Sea surface temperature and salinity compared well to satellite measurements. Chl fluorescence from the gliders was more poorly correlated, with substantial between glider variability. Both turbidity and oil CDOM sensors were compromised to some degree by interfering processes. The well-known diel cycle in chlorophyll fluorescence was observed suggesting that mapping physiological data over large scales is possible. The gliders captured the Pacific Ocean's major oceanographic features including the increased chlorophyll biomass of the California Current and equatorial upwelling. A comparison of satellite sea surface salinity (Aquarius) and glider-measured salinity revealed thin low salinity lenses in the southwestern Pacific Ocean. One glider survived a direct passage through a tropical cyclone. Two gliders traversed an open ocean phytoplankton bloom; extensive spiking in the chlorophyll fluorescence data is consistent with aggregation and highlights another potential future use for the gliders. On long missions, redundant instrumentation would aid in interpreting unusual data streams, as well as a means to periodically image the sensor heads. Instrument placement is

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

USDA-ARS?s Scientific Manuscript database

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Near-surface Salinity and Temperature structure Observed with Dual-Sensor Drifters in the Subtropical South Pacific

NASA Astrophysics Data System (ADS)

Dong, S.; Volkov, D.; Goni, G. J.; Lumpkin, R.; Foltz, G. R.

2017-12-01

Three surface drifters equipped with temperature and salinity sensors at 0.2 m and 5 m depths were deployed in April/May 2015 in the subtropical South Pacific with the objective of measuring near-surface salinity differences seen by satellite and in situ sensors and examining the causes of these differences. Measurements from these drifters indicate that water at a depth of 0.2 m is about 0.013 psu fresher than at 5 m and about 0.024°C warmer. Events with large temperature and salinity differences between the two depths are caused by anomalies in surface freshwater and heat fluxes, modulated by wind. While surface freshening and cooling occurs during rainfall events, surface salinification is generally observed under weak wind conditions (≤4 m/s). Further examination of the drifter measurements demonstrates that (i) the amount of surface freshening and strength of the vertical salinity gradient heavily depend on wind speed during rain events, (ii) salinity differences between 0.2 m and 5 m are positively correlated with the corresponding temperature differences for cases with surface salinification, and (iii) temperature exhibits a diurnal cycle at both depths, whereas the diurnal cycle of salinity is observed only at 0.2 m when the wind speed is less than 6 m/s. The amplitudes of the diurnal cycles of temperature at both depths decrease with increasing wind speed. The mean diurnal cycle of surface salinity is dominated by events with winds less than 2 m/s.

Near-surface salinity and temperature structure observed with dual-sensor drifters in the subtropical South Pacific

NASA Astrophysics Data System (ADS)

Dong, Shenfu; Volkov, Denis; Goni, Gustavo; Lumpkin, Rick; Foltz, Gregory R.

2017-07-01

Three surface drifters equipped with temperature and salinity sensors at 0.2 and 5 m depths were deployed in April/May 2015 in the subtropical South Pacific with the objective of measuring near-surface salinity differences seen by satellite and in situ sensors and examining the causes of these differences. Measurements from these drifters indicate that water at a depth of 0.2 m is about 0.013 psu fresher than at 5 m and about 0.024°C warmer. Events with large temperature and salinity differences between the two depths are caused by anomalies in surface freshwater and heat fluxes, modulated by wind. While surface freshening and cooling occurs during rainfall events, surface salinification is generally observed under weak wind conditions (≤4 m/s). Further examination of the drifter measurements demonstrates that (i) the amount of surface freshening and strength of the vertical salinity gradient heavily depend on wind speed during rain events, (ii) salinity differences between 0.2 and 5 m are positively correlated with the corresponding temperature differences for cases with surface salinification, and (iii) temperature exhibits a diurnal cycle at both depths, whereas the diurnal cycle of salinity is observed only at 0.2 m when the wind speed is less than 6 m/s. The amplitudes of the diurnal cycles of temperature at both depths decrease with increasing wind speed. The mean diurnal cycle of surface salinity is dominated by events with winds less than 2 m/s.

Salinity monitoring in Western Australia using remotely sensed and other spatial data.

PubMed

Furby, Suzanne; Caccetta, Peter; Wallace, Jeremy

2010-01-01

The southwest of Western Australia is affected by dryland salinity that results in the loss of previously productive agricultural land, damage to buildings, roads, and other infrastructure, decline in pockets of remnant vegetation and biodiversity, and reduction in water quality. Accurate information on the location and rate of change of the extent of saline land over the region is required by resource managers. For the first time, comprehensive, spatially explicit maps of dryland salinity and its change over approximately 10 yr for the southwest agricultural region of Western Australia have been produced operationally in the 'Land Monitor' project. The methods rely on an integrated analysis of long-term sequences of Landsat TM satellite image data together with variables derived from digital elevation models (DEMs). Understanding of the physical process and surface expression of salinity provided by experts was used to guide the analyses. Ground data-the delineation of salt-affected land by field experts-was collected for training and validation. The results indicate that the land area currently affected by salinity in Western Australia's southwest is about 1 million hectares (in 1996) and the annual rate of increase is about 14,000 ha. This is a lesser extent than many previous estimates and lower rate of change than generally predicted from limited hydrological data. The results are widely distributed and publicly available. The key to providing accurate mapping and monitoring information was the incorporation of time series classification of a sequence of images over several years combined with landform information.

Study of the Formation and Evolution of Precipitation Induced Sea Surface Salinity Minima in the Tropical Pacific Using HYCOM

NASA Astrophysics Data System (ADS)

Gallagher, R. L.

2016-02-01

During heavy rain events in the tropics, areas of relatively low salinity water collect on the ocean surface. Rainfall events increase the buoyancy of the ocean surface and impact upper ocean salinity and temperature profiles. This resists downward mixing and as a result can persist (SPURS II planning group, 2012; Oceanography 28(1) 150-159). Salinity at the surface adjusts through advective and diffusive mixing processes (Scott, J. et al, 2013; AGU Fall meeting abstracts). This project investigates the upper ocean salinity response in both advection and diffusion dominated regions. The changes in ocean surface salinity are tracked before, during, and after rainfall events. Data from a standard oceanographic model, HYCOM, are used to identify areas where each surface process is significant. Rainfall events are identified using a TRMM dataset. It provides a tropical rainfall analysis which uses amalgamated satellite data to develop detailed global precipitation grids between 50 o north and south latitude. TRMM is useful due its high temporal and spatial resolutions. The salinity response in HYCOM is tested against simple theoretical advective and diffusive mixing models. The magnitude of sea surface salinity minima, their persistence and the precision by which HYCOM can resolve these phenomena are of interest.

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

2016-04-01

The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS

Predictive spatial modelling for mapping soil salinity at continental scale

NASA Astrophysics Data System (ADS)

Bui, Elisabeth; Wilford, John; de Caritat, Patrice

2017-04-01

Soil salinity is a serious limitation to agriculture and one of the main causes of land degradation. Soil is considered saline if its electrical conductivity (EC) is > 4 dS/m. Maps of saline soil distribution are essential for appropriate land development. Previous attempts to map soil salinity over extensive areas have relied on satellite imagery, aerial electromagnetic (EM) and/or proximally sensed EM data; other environmental (climate, topographic, geologic or soil) datasets are generally not used. Having successfully modelled and mapped calcium carbonate distribution over the 0-80 cm depth in Australian soils using machine learning with point samples from the National Geochemical Survey of Australia (NGSA), we took a similar approach to map soil salinity at 90-m resolution over the continent. The input data were the EC1:5 measurements on the < 2mm fraction at 1315 georeferenced points across the continent at two depth intervals (TOS, 0-10 cm, and BOS, 60-80 cm) (see http://www.ga.gov.au/energy/projects/national-geochemical-survey/atlas.html) were log-transformed and combined with values for climate, elevation and terrain attributes, soil and lithology classes, geophysics, and MODIS vegetation indices extracted at the same locations which were used as predictors in decision tree models. The machine learning software 'Cubist' (www.rulequest.com) was used as the inference engine for the modelling, a 90:10 training:test set data split was used to validate results, and 100 randomly sampled trees were built using the training data. The results were good with an average internal correlation (r) of 0.88 between predicted and measured logEC1:5 (training data), an average external correlation of 0.48 (test subset), and a Lin's concordance correlation coefficient (which evaluates the 1:1 fit) of 0.61. Therefore, the rules derived were mapped and the mean prediction for each 90-m pixel was used for the final logEC1:5 map. This is the most detailed picture of soil salinity

A method for soil moisture probes calibration and validation of satellite estimates.

PubMed

Holzman, Mauro; Rivas, Raúl; Carmona, Facundo; Niclòs, Raquel

2017-01-01

Optimization of field techniques is crucial to ensure high quality soil moisture data. The aim of the work is to present a sampling method for undisturbed soil and soil water content to calibrated soil moisture probes, in a context of the SMOS (Soil Moisture and Ocean Salinity) mission MIRAS Level 2 soil moisture product validation in Pampean Region of Argentina. The method avoids soil alteration and is recommended to calibrated probes based on soil type under a freely drying process at ambient temperature. A detailed explanation of field and laboratory procedures to obtain reference soil moisture is shown. The calibration results reflected accurate operation for the Delta-T thetaProbe ML2x probes in most of analyzed cases (RMSE and bias ≤ 0.05 m 3 /m 3 ). Post-calibration results indicated that the accuracy improves significantly applying the adjustments of the calibration based on soil types (RMSE ≤ 0.022 m 3 /m 3 , bias ≤ -0.010 m 3 /m 3 ). •A sampling method that provides high quality data of soil water content for calibration of probes is described.•Importance of calibration based on soil types.•A calibration process for similar soil types could be suitable in practical terms, depending on the required accuracy level.

L-MEB Model Calibration Over the Valencia Anchor Station Area

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.

2009-04-01

In the framework of ESA's SMOS (Soil Moisture and Ocean Salinity) Mission, several studies are being carried out over different types of land surfaces to study their microwave L-band emission (1.4 GHz). These studies are being integrated in the SMOS emission model (L-MEB, L-band Microwave Emission of the Biosphere, Wigneron et al. 2007), which is the core of the SMOS algorithm for the retrieval of land surface parameters from SMOS data. To contribute to Cal/Val activities at the Valencia Anchor Station (VAS) area (Caudete de las Fuentes, Valencia, Spain), one of the primary validation areas for SMOS land data and products (ESA SMOS Cal/Val AO, Project ID 3252, Lopez-Baeza et al., 2005), a number of experiments have been carried out to study the vegetation influence over the L-band emission proceeding from the soil surface. In the VAS area, a reduced number of homogeneous units have been defined according to the type and use of the soil, mainly, shrubs, vineyards, orchards (almond-and olive-trees) and Mediterranean pine forests. In order to implement the SMOS algorithm over this reference area, it is necessary to characterize and calibrate the L-MEB model for the different cover types. This work is significantly contributing to the definition of the VAS site as a validation area for SMOS land products of the size of a SMOS pixel (SMOS reference pixel). Shrubs and vineyards are the two most significant vegetation types which cover a large percentage of the area and for which very little information at L-band is available in the literature. These two types of vegetation covers have been studied in two separate dedicated experiments under the common name of MELBEX (Mediterranean Ecosystem L-Band characterisation EXperiment). The first one (MELBEX-I) took place over a shrub area characterised by a significant proportion of bare soil with superficial stones. The second one (MELBEX-II) was carried out from March to December 2007 over a large vineyard area. During the time

Consistent Transition of Salinity Retrievals From Aquarius to SMAP

NASA Astrophysics Data System (ADS)

Mears, C. A.; Meissner, T.; Wentz, F. J.; Manaster, A.

2017-12-01

The Aquarius Version 5.0 release in late 2017 has achieved an excellent level of accuracy and significantly mitigated most of the regional and seasonal biases that had been observed in prior releases. The SMAP NASA/RSS Version 2.0 release does not quite yet reach that level of accuracy. Our presentation discusses the necessary steps that need to be undertaken in the upcoming V 3.0 of the SMAP salinity retrieval algorithm to achieve a seamless transition between the salinity products from the two instruments. We also discuss where fundamental differences in the sensors make it difficult to reach complete consistency. In the Aquarius V 4.0 and earlier releases, comparison with ARGO floats have revealed small fresh biases at low latitudes and larger seasonally varying salty biases at high latitudes. These biases have been tracked back to inaccuracies in the models that are used for correcting the absorption by atmospheric oxygen and for correcting the wind induced roughness. The geophysical models have been changed in Aquarius V5.0, which resulted in a significant improvement of these biases. The upcoming SMAP V3 release will implement the same geophysical model. In deriving the changes of the geophysical model, monthly ARGO analyzed fields from Scripps are now being used consistently as reference salinity for both Aquarius V5.0 and the upcoming SMAP V3.0 releases. Earlier versions had used HYOCM as reference salinity field. The development of the Aquarius V 5.0 algorithm has already strongly benefited from the full 360o look capability of SMAP. This aided in deriving the correction of the reflected galaxy, which is a strong spurious signal for both sensors. Consistent corrections for the galactic signal are now used for both Aquarius and SMAP. It is also important to filter out rain when developing the GMF and when validating the satellite salinities versus in-situ measurements on order to avoid mismatches due to salinity stratification in the upper ocean layer. One

Regional assessment of lake ecological states using Landsat: A classification scheme for alkaline-saline, flamingo lakes in the East African Rift Valley

NASA Astrophysics Data System (ADS)

Tebbs, E. J.; Remedios, J. J.; Avery, S. T.; Rowland, C. S.; Harper, D. M.

2015-08-01

In situ reflectance measurements and Landsat satellite imagery were combined to develop an optical classification scheme for alkaline-saline lakes in the Eastern Rift Valley. The classification allows the ecological state and consequent value, in this case to Lesser Flamingos, to be determined using Landsat satellite imagery. Lesser Flamingos depend on a network of 15 alkaline-saline lakes in East African Rift Valley, where they feed by filtering cyanobacteria and benthic diatoms from the lakes' waters. The classification developed here was based on a decision tree which used the reflectance in Landsat ETM+ bands 2-4 to assign one of six classes: low phytoplankton biomass; suspended sediment-dominated; microphytobenthos; high cyanobacterial biomass; cyanobacterial scum and bleached cyanobacterial scum. The classification accuracy was 77% when verified against in situ measurements. Classified imagery and timeseries were produced for selected lakes, which show the different ecological behaviours of these complex systems. The results have highlighted the importance to flamingos of the food resources offered by the extremely remote Lake Logipi. This study has demonstrated the potential of high spatial resolution, low spectral resolution sensors for providing ecologically valuable information at a regional scale, for alkaline-saline lakes and similar hypereutrophic inland waters.

Detecting the influence of ocean process on the moisture supply for India summer monsoon from Satellite Sea Surface Salinity

NASA Astrophysics Data System (ADS)

Tang, W.; Yueh, S. H.; Liu, W. T.; Fore, A.; Hayashi, A.

2016-02-01

A strong contrast in the onset of Indian summer monsoon was observed by independent satellites: average rain rate over India subcontinent (IS) in June was more than doubled in 2013 than 2012 (TRMM); also observed are larger area of wet soil (Aquarius) and high water storage (GRACE). The difference in IS rainfall was contributed to the moisture inputs through west coast of India, estimated from ocean wind (OSCAT2) and water vapor (TMI). This is an interesting testbed for studying the role of ocean on terrestrial water cycle, in particular the Indian monsoon, which has tremendous social-economical impact. What is the source of extra moisture in 2013 or deficit in 2012 for the monsoon onset? Is it possible to quantify the contribution of ocean process that maybe responsible for redistributing the freshwater in favor of the summer monsoon moisture supply? This study aims to identify the influence of ocean processes on the freshwater exchange between air-sea interfaces, using Aquarius sea surface salinity (SSS). We found two areas in Indian Ocean with high correlation between IS rain rate and Aquarius SSS: one area is in the Arabian Sea adjacent to IS, another area is a horizontal patch from 60°E to 100°E centered around 10°S. On the other hand, E-P (OAflux, TRMM) shows no similar correlation patterns with IS rain. Based on the governing equation of the salt budget in the upper ocean, we define the freshwater flux, F, from the oceanic branch of the water cycle, including contributions from salinity tendency, advection, and subsurface process. The tendency and advection terms are estimated using Aquarius SSS and OSCAR ocean current. We will present results of analyzing the spatial and temporal variability of F and evidence of and hypothesis on how the oceanic processes may enhance the moisture supply for summer Indian monsoon onset in 2013 comparing with 2012. The NASA Soil Moisture Active Passive (SMAP) has been producing the global soil moisture (SM) every 2-3 days

Absolute Salinity, ''Density Salinity'' and the Reference-Composition Salinity Scale: present and future use in the seawater standard TEOS-10

NASA Astrophysics Data System (ADS)

Wright, D. G.; Pawlowicz, R.; McDougall, T. J.; Feistel, R.; Marion, G. M.

2011-01-01

Salinity plays a key role in the determination of the thermodynamic properties of seawater and the new TEOS-101 standard provides a consistent and effective approach to dealing with relationships between salinity and these thermodynamic properties. However, there are a number of practical issues that arise in the application of TEOS-10, both in terms of accuracy and scope, including its use in the reduction of field data and in numerical models. First, in the TEOS-10 formulation for IAPSO Standard Seawater, the Gibbs function takes the Reference Salinity as its salinity argument, denoted SR, which provides a measure of the mass fraction of dissolved material in solution based on the Reference Composition approximation for Standard Seawater. We discuss uncertainties in both the Reference Composition and the Reference-Composition Salinity Scale on which Reference Salinity is reported. The Reference Composition provides a much-needed fixed benchmark but modified reference states will inevitably be required to improve the representation of Standard Seawater for some studies. However, the Reference-Composition Salinity Scale should remain unaltered to provide a stable representation of salinity for use with the TEOS-10 Gibbs function and in climate change detection studies. Second, when composition anomalies are present in seawater, no single salinity variable can fully represent the influence of dissolved material on the thermodynamic properties of seawater. We consider three distinct representations of salinity that have been used in previous studies and discuss the connections and distinctions between them. One of these variables provides the most accurate representation of density possible as well as improvements over Reference Salinity for the determination of other thermodynamic properties. It is referred to as "Density Salinity" and is represented by the symbol SAdens; it stands out as the most appropriate representation of salinity for use in dynamical physical

Absolute Salinity, "Density Salinity" and the Reference-Composition Salinity Scale: present and future use in the seawater standard TEOS-10

NASA Astrophysics Data System (ADS)

Wright, D. G.; Pawlowicz, R.; McDougall, T. J.; Feistel, R.; Marion, G. M.

2010-08-01

Salinity plays a key role in the determination of the thermodynamic properties of seawater and the new TEOS-101 standard provides a consistent and effective approach to dealing with relationships between salinity and these thermodynamic properties. However, there are a number of practical issues that arise in the application of TEOS-10, both in terms of accuracy and scope, including its use in the reduction of field data and in numerical models. First, in the TEOS-10 formulation for IAPSO Standard Seawater, the Gibbs function takes the Reference Salinity as its salinity argument, denoted SR, which provides a measure of the mass fraction of dissolved material in solution based on the Reference Composition approximation for Standard Seawater. We discuss uncertainties in both the Reference Composition and the Reference-Composition Salinity Scale on which Reference Salinity is reported. The Reference Composition provides a much-needed fixed benchmark but modified reference states will inevitably be required to improve the representation of Standard Seawater for some studies. The Reference-Composition Salinity Scale should remain unaltered to provide a stable representation of salinity for use with the TEOS-10 Gibbs function and in climate change detection studies. Second, when composition anomalies are present in seawater, no single salinity variable can fully represent the influence of dissolved material on the thermodynamic properties of seawater. We consider three distinct representations of salinity that have been used in previous studies and discuss the connections and distinctions between them. One of these variables provides the most accurate representation of density possible as well as improvements over Reference Salinity for the determination of other thermodynamic properties. It is referred to as "Density Salinity" and is represented by the symbol SAdens; it stands out as the most appropriate representation of salinity for use in dynamical physical

Indicators: Salinity

EPA Pesticide Factsheets

Salinity is the dissolved salt content of a body of water. Excess salinity, due to evaporation, water withdrawal, wastewater discharge, and other sources, is a chemical sterssor that can be toxic for aquatic environments.

Saline infusion sonohysterography.

PubMed

2004-01-01

Saline infusion sonohysterography consists of ultrasonographic imaging of the uterus and uterocervical cavity, using real-time ultrasonography during injection of sterile saline into the uterus. When properly performed, saline infusion sonohysterography can provide information about the uterus and endometrium. The most common indication for sonohysterography is abnormal uterine bleeding. sonohysterography should not be performed in a woman who is pregnant or could be pregnant or in a woman with a pelvic infection or unexplained pelvic tenderness. Physicians who perform or supervise diagnostic saline infusion sonohysterograpy should have training, experience, and demonstrated competence in gynecologic ultrasonography and saline infusion sonohysterography. Portions of this document were developed jointly with the American College of Radiology and the American Institute of Ultrasound in Medicine.

Regional-scale assessment of soil salinity in the Red River Valley using multi-year MODIS EVI and NDVI.

PubMed

Lobell, D B; Lesch, S M; Corwin, D L; Ulmer, M G; Anderson, K A; Potts, D J; Doolittle, J A; Matos, M R; Baltes, M J

2010-01-01

The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10-10(5) km(2)) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.

Soil moisture remote sensing: State of the science

USDA-ARS?s Scientific Manuscript database

Satellites (e.g., SMAP, SMOS) using passive microwave techniques, in particular at L band frequency, have shown good promise for global mapping of near-surface (0-5 cm) soil moisture at a spatial resolution of 25-40 km and temporal resolution of 2-3 days. C- and X-band soil moisture records date bac...

Nandrolone decanoate increases satellite cell numbers in the chicken pectoralis muscle.

PubMed

Allouh, Mohammed Z; Rosser, Benjamin W C

2010-02-01

The anabolic androgenic steroid nandrolone decanoate has minimal androgenic effects and, thus, is widely used to induce muscle hypertrophy in both patients and athletes. Although increases in satellite cell numbers and satellite cells giving rise to new myonuclei are associated with hypertrophy in many experimental models, the relationship between nandrolone and satellite cells is poorly understood. Here we test the hypothesis that nandrolone administration is associated with an increase in satellite cell numbers in muscle. Nandrolone was injected at weekly intervals for four weeks into the right pectoralis muscle of female white leghorn chickens aged 63 days post hatch. Age/size/sex matched control birds received saline injections. The contralateral pectoralis was excised for study from each control and nandrolone treated bird. An antibody against Pax7 and immunocytochemical techniques were used to identify satellite cells. Nandrolone significantly increased mean pectoralis mass by approximately 22%, and mean fiber diameter by about 24%. All satellite cell indices that were quantified increased significantly in chicken pectoralis with administration of nandrolone. Nandrolone injected birds had on average higher satellite cell frequencies (#SC nuclei/all nuclei within basal lamina), number of satellite cells per millimeter of fiber, and satellite cell concentrations (closer together). Myonuclei were further apart (less concentrated) in nandrolone injected muscle. However, an overall increase in myonuclear numbers was revealed by a significantly greater mean number of myonuclei per millimeter of fiber in nandrolone injected muscle. Our results suggest that satellite cells may be key cellular vectors for nandrolone induced muscle fiber hypertrophy.

Sea Surface Salinity Variability in Response to the Congo River Discharge

NASA Astrophysics Data System (ADS)

Moller, D.; Chao, Y.; Farrara, J. D.; Schumann, G.; Andreadis, K.

2014-12-01

Sea surface salinity (SSS) variability associated with the Congo River discharge is examined using Aquarius satellite-retrieved SSS data and vertical profiles of salinity measured by the Argo floats. The Congo River plume can be clearly identified in the Aquarius SSS data with a westward extension of 500 to 1000 km off the coast of the Democratic Republic of Congo (DRC). The peak amplitude of the SSS variability associated with the Congo River discharge exceeds 2.0 psu. Using the first two years of Aquarius data, a well-defined seasonal cycle is described: maximum fresh-water anomalies are found in the boreal winter and spring seasons. The fresh-water anomalies during the 2012-2013 winter and spring seasons are significantly fresher than the 2011-2012 winter and spring seasons. Vertical profiles of salinity derived from the Argo floats reveal that these fresh-water anomalies can be traced to 40 meters below the sea surface. Combining the Aquarius SSS data with the Argo vertical profiles of salinity, the 3D volume of these fresh-water anomalies can be inferred and used to estimate the Congo River discharge. Reasonably good agreement is found between the Congo River discharge as observed by a stream gauge at Kinshasa and that estimated from the combined Aquarius and Argo data, indicating that Aquarius data can be used to close the fresh-water budget between the coastal ocean and the Congo River. The precipitation minus evaporation portion of the freshwater flux is found to play a secondary role in this region.

Use of IRI to Model the Effect of Ionosphere Emission on Earth Remote Sensing at L-Band

NASA Technical Reports Server (NTRS)

Abraham, Saji; LeVine, David M.

2004-01-01

Microwave remote sensing in the window at 1.413 GHz (L-band) set aside for passive use only is important for monitoring sea surface salinity and soil moisture. These parameters are important for understanding ocean dynamics and energy exchange between the surface and atmosphere, and both NASA and ESA plan to launch satellite sensors to monitor these parameters at L-band (Aquarius, Hydros and SMOS). The ionosphere is an important source of error for passive remote sensing at this frequency. In addition to Faraday rotation, emission from the ionosphere is also a potential source of error at L-band. As an aid for correcting for emission, a regression model is presented that relates ionosphere emission to the integrated electron density (TEC). The goal is to use TEC from sources such as TOPEX, JASON or GPS to obtain estimates of emission over the oceans where the electron density profiles needed to compute emission are not available. In addition, data will also be presented to evaluate the use of the IRI for computing emission over the ocean.

Evaluation of Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) for Water Quality Monitoring: A Case Study for the Estimation of Salinity

NASA Astrophysics Data System (ADS)

Nazeer, Majid; Bilal, Muhammad

2018-04-01

Landsat-5 Thematic Mapper (TM) dataset have been used to estimate salinity in the coastal area of Hong Kong. Four adjacent Landsat TM images were used in this study, which was atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer code. The atmospherically corrected images were further used to develop models for salinity using Ordinary Least Square (OLS) regression and Geographically Weighted Regression (GWR) based on in situ data of October 2009. Results show that the coefficient of determination ( R 2) of 0.42 between the OLS estimated and in situ measured salinity is much lower than that of the GWR model, which is two times higher ( R 2 = 0.86). It indicates that the GWR model has more ability than the OLS regression model to predict salinity and show its spatial heterogeneity better. It was observed that the salinity was high in Deep Bay (north-western part of Hong Kong) which might be due to the industrial waste disposal, whereas the salinity was estimated to be constant (32 practical salinity units) towards the open sea.

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

NASA Technical Reports Server (NTRS)

Yueh, Simon H.

2004-01-01

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Trend Analysis of Soil Salinity in Different Land Cover Types Using Landsat Time Series Data (case Study Bakhtegan Salt Lake)

NASA Astrophysics Data System (ADS)

Taghadosi, M. M.; Hasanlou, M.

2017-09-01

Soil salinity is one of the main causes of desertification and land degradation which has negative impacts on soil fertility and crop productivity. Monitoring salt affected areas and assessing land cover changes, which caused by salinization, can be an effective approach to rehabilitate saline soils and prevent further salinization of agricultural fields. Using potential of satellite imagery taken over time along with remote sensing techniques, makes it possible to determine salinity changes at regional scales. This study deals with monitoring salinity changes and trend of the expansion in different land cover types of Bakhtegan Salt Lake district during the last two decades using multi-temporal Landsat images. For this purpose, per-pixel trend analysis of soil salinity during years 2000 to 2016 was performed and slope index maps of the best salinity indicators were generated for each pixel in the scene. The results of this study revealed that vegetation indices (GDVI and EVI) and also salinity indices (SI-1 and SI-3) have great potential to assess soil salinity trends in vegetation and bare soil lands respectively due to more sensitivity to salt features over years of study. In addition, images of May had the best performance to highlight changes in pixels among different months of the year. A comparative analysis of different slope index maps shows that more than 76% of vegetated areas have experienced negative trends during 17 years, of which about 34% are moderately and highly saline. This percent is increased to 92% for bare soil lands and 29% of salt affected soils had severe salinization. It can be concluded that the areas, which are close to the lake, are more affected by salinity and salts from the lake were brought into the soil which will lead to loss of soil productivity ultimately.

Climatology and seasonality of upper ocean salinity: a three-dimensional view from argo floats

NASA Astrophysics Data System (ADS)

Chen, Ge; Peng, Lin; Ma, Chunyong

2018-03-01

Primarily due to the constraints of observation technologies (both field and satellite measurements), our understanding of ocean salinity is much less mature compared to ocean temperature. As a result, the characterizations of the two most important properties of the ocean are unfortunately out of step: the former is one generation behind the latter in terms of data availability and applicability. This situation has been substantially changed with the advent of the Argo floats which measure the two variables simultaneously on a global scale since early this century. The first decade of Argo-acquired salinity data are analyzed here in the context of climatology and seasonality, yielding the following main findings for the global upper oceans. First, the six well-defined "salty pools" observed around ±20° in each hemisphere of the Pacific, Atlantic and Indian Oceans are found to tilt westward vertically from the sea surface to about 600 m depth, forming six saline cores within the subsurface oceans. Second, while potential temperature climatology decreases monotonically to the bottom in most places of the ocean, the vertical distribution of salinity can be classified into two categories: A double-halocline type forming immediately above and below the local salinity maximum around 100-150 m depths in the tropical and subtropical oceans, and a single halocline type existing at about 100 m depth in the extratropical oceans. Third, in contrast to the midlatitude dominance for temperature, seasonal variability of salinity in the oceanic mixed layer has a clear tropical dominance. Meanwhile, it is found that a two-mode structure with annual and semiannual periodicities can effectively penetrate through the upper ocean into a depth of 2000 m. Fourth, signature of Rossby waves is identified in the annual phase map of ocean salinity within 200-600 m depths in the tropical oceans, revealing a strongly co-varying nature of ocean temperature and salinity at specific depths

Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints

NASA Astrophysics Data System (ADS)

Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.

2018-01-01

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

Application of a Topological Metric for Assessing Numerical Ocean Models with Satellite Observations

NASA Astrophysics Data System (ADS)

Morey, S. L.; Dukhovskoy, D. S.; Hiester, H. R.; Garcia-Pineda, O. G.; MacDonald, I. R.

2015-12-01

Satellite-based sensors provide a vast amount of observational data over the world ocean. Active microwave radars measure changes in sea surface height and backscattering from surface waves. Data from passive radiometers sensing emissions in multiple spectral bands can directly measure surface temperature, be combined with other data sources to estimate salinity, or processed to derive estimates of optically significant quantities, such as concentrations of biochemical properties. Estimates of the hydrographic variables can be readily used for assimilation or assessment of hydrodynamic ocean models. Optical data, however, have been underutilized in ocean circulation modeling. Qualitative assessments of oceanic fronts and other features commonly associated with changes in optically significant quantities are often made through visual comparison. This project applies a topological approach, borrowed from the field of computer image recognition, to quantitatively evaluate ocean model simulations of features that are related to quantities inferred from satellite imagery. The Modified Hausdorff Distance (MHD) provides a measure of the similarity of two shapes. Examples of applications of the MHD to assess ocean circulation models are presented. The first application assesses several models' representation of the freshwater plume structure from the Mississippi River, which is associated with a significant expression of color, using a satellite-derived ocean color index. Even though the variables being compared (salinity and ocean color index) differ, the MHD allows contours of the fields to be compared topologically. The second application assesses simulations of surface oil transport driven by winds and ocean model currents using surface oil maps derived from synthetic aperture radar backscatter data. In this case, maps of time composited oil coverage are compared between the simulations and satellite observations.

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

NASA Technical Reports Server (NTRS)

Roy, A.; Royer, A.; Derksen, C.; Brucker, L.; Langlois, A.; Mailon, A.; Kerr, Y.

2015-01-01

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

Numerical study of hydrodynamic and salinity transport processes in the Pink Beach wetlands of the Liao River estuary, China

NASA Astrophysics Data System (ADS)

Qiao, Huiting; Zhang, Mingliang; Jiang, Hengzhi; Xu, Tianping; Zhang, Hongxing

2018-06-01

Interaction studies of vegetation within flow environments are essential for the determination of bank protection, morphological characteristics and ecological conditions for wetlands. This paper uses the MIKE 21 hydrodynamic and salinity model to simulate the hydrodynamic characteristics and salinity transport processes in the Pink Beach wetlands of the Liao River estuary. The effect of wetland plants on tidal flow in wetland areas is represented by a varying Manning coefficient in the bottom friction term. Acquisition of the vegetation distribution is based on Landsat TM satellites by remote sensing techniques. Detailed comparisons between field observation and simulated results of water depth, salinity and tidal currents are presented in the vegetated domain of the Pink Beach wetlands. Satisfactory results were obtained from simulations of both flow characteristics and salinity concentration, with or without vegetation. A numerical experiment was conducted based on variations in vegetation density, and compared with the tidal currents in non-vegetated areas; the computed current speed decreased remarkably with an increase in vegetation density. The impact of vegetation on water depth and salinity was simulated, and the findings revealed that wetland vegetation has an insignificant effect on the water depth and salinity in this wetland domain. Several stations (from upstream to downstream) in the Pink Beach wetlands were selected to estimate the longitudinal variation of salinity under different river runoff conditions; the results showed that salinity concentration decreases with an increase in river runoff. This study can consequently help increase the understanding of favourable salinity conditions for particular vegetation growth in the Pink Beach wetlands of the Liao River estuary. The results also provide crucial guidance for related interaction studies of vegetation, flow and salinity in other wetland systems.

On the freshwater budget in the eastern tropical Atlantic during the development of the cold tongue

NASA Astrophysics Data System (ADS)

Schlundt, Michael; Krahmann, Gerd; Brandt, Peter; Karstensen, Johannes

2013-04-01

The most striking sea surface temperature (SST) phenomenon in the tropical Atlantic is the seasonal appearance of the Atlantic Cold Tongue (ACT). Onset, duration, spatial extent and strength of cooling are subject to significant interannual variability. The ACT onset is also associated with remarkable changes in upper ocean salinity. To examine the different contributions to these changes we here focus on and present a mixed layer freshwater budget in the eastern tropical Atlantic. Our investigation is based on an exceptionally large set of observations during the onset of the ACT in late boreal spring/ early boreal summer 2011: more than 5400 CTD-profiles acquired by seven gliders running simultaneously to two research cruises, 180 ship based CTD-profiles, time series data from the PIRATA buoy array as well as measurements from the Argo float program are used to derive mixed layer depth, lateral and vertical salinity gradients. To derive turbulent mixing and inferred diapycnal salt flux, microstructure observations are taken into account. Furthermore satellite measurements of sea surface salinity (SSS) by the SMOS mission and of SST by the TMI radiometer as well as atmospheric reanalysis data and the OSCAR project products are implemented. Freshwater budget terms were calculated for different sub-regions. These sub-regions are chosen using pre-defined thresholds in SSS, SST or mixed layer depth. Overall the freshwater budget is dominated by the net surface freshwater flux and horizontal advection by strong zonal currents. Other terms, like entrainment and diapycnal mixing are found to be regionally important. In particular, the observed increase in salinity in the near-equatorial region during ACT onset is found to be the result of the northward migration of the ITCZ associated with reduced net surface freshwater flux at the equator as well as mixing of salty subsurface waters into the surface mixed layer.

Salinity modeling by remote sensing in central and southern Iraq

NASA Astrophysics Data System (ADS)

Wu, W.; Mhaimeed, A. S.; Platonov, A.; Al-Shafie, W. M.; Abbas, A. M.; Al-Musawi, H. H.; Khalaf, A.; Salim, K. A.; Chrsiten, E.; De Pauw, E.; Ziadat, F.

2012-12-01

level of 95% in a stepwise (forward) manner. The results reveal that soil salinity and EM38 readings are negatively correlated with the different vegetation indices, especially, GDVI and NDVI, and positively correlated with T. The models obtained for the pilot sites are presented in Table 1. Although we are still waiting for more laboratory analytical result and satellite imagery for more comprehensive analysis, it is clearly possible to build up salinity models by remote sensing, on which further salinity mapping and assessment can be based. It is also noted that among all the vegetation indices, GDVI is the best salinity indicator followed by NDVI and T. RapidEye image shows lower correlation with EM38 measurements and EC because fallow and crop rotation issue cannot be sorted out by one acquisition image.Table 1: Salinity models obtained from the pilot sitesNote: EMV- Vertical reading of EM38, EC - Electrical conductivity in dS/m

Global relation between microwave satellite vegetation products and vegetation productivity

NASA Astrophysics Data System (ADS)

Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Miralles, Diego G.; Dorigo, Wouter A.

2017-04-01

The occurrence of unfavourable environmental conditions like droughts commonly reduces the photosynthetic activity of ecosystems and, hence, their potential to take up carbon from the atmosphere. Ecosystem photosynthetic activity is commonly determined using remote sensing observations in the optical domain, which however have limitations particularly in regions of frequent cloud cover, e.g. the tropics. In this study, we explore the potential of vegetation optical depth (VOD) from microwave satellite observations as an alternative source for assessing vegetation productivity. VOD serves as an estimate for vegetation density and water content, which has an impact on plant physiological processes and hence should potentially provide a link to gross primary production (GPP). However, to date, it is unclear how microwave-retrieved VOD data and GPP data are related. We compare seasonal dynamics and anomalies of VOD retrievals from different satellite sensors and microwave frequencies with site level and global GPP estimates. We use VOD observations from active (ASCAT) and passive microwave sensors (AMSR-E, SMOS). We include eddy covariance measurements from the FLUXNET2015 dataset to assess the VOD products at site level. For a global scale analysis, we use the solar-induced chlorophyll fluorescence (SIF) observations from GOME-2 as a proxy for GPP and the FLUXCOM GPP product, which presents an upscaling of site measurements based on remote sensing data. Our results demonstrate that in general a good agreement between VOD and GPP or SIF exists. However, the strength of these relations depends on the microwave frequency, land cover type, and the time within the growing season. Correlations between anomalies of VOD and GPP or SIF support the assumption that microwave-derived VOD can be used to monitor vegetation productivity dynamics. The study is performed as part of the EOWAVE project funded by the Vienna University of Technology (http://eowave.geo.tuwien.ac.at/) and

Extracting Ocean-Generated Tidal Magnetic Signals from Swarm Data Through Satellite Gradiometry

NASA Technical Reports Server (NTRS)

Sabaka, Terence J.; Tyler, Robert H.; Olsen, Nils

2016-01-01

Ocean-generated magnetic field models of the Principal Lunar, M2, and the Larger Lunar elliptic, N2, semidiurnal tidal constituents were estimated through a "Comprehensive Inversion" of the first 20.5 months of magnetic measurements from European Space Agency's (ESA) Swarm satellite constellation mission. While the constellation provides important north-south along-track gradiometry information, it is the unique low-spacecraft pair that allows for east-west cross-track gradiometry. This latter type is crucial in delivering an M2 estimate of similar quality with that derived from over 10 years of CHAMP satellite data but over a shorter interval, at higher altitude, and during more magnetically disturbed conditions. Recovered N2 contains nonoceanic signal but is highly correlated with theoretical models in regions of maximum oceanic amplitude. Thus, satellite magnetic gradiometry may eventually enable the monitoring of ocean electrodynamic properties at temporal resolutions of 1 to 2 years, which may have important implications for the inference of ocean temperature and salinity.

SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

NASA Astrophysics Data System (ADS)

Fang, B.; Lakshmi, V.

2016-12-01

Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

Towards Improved Satellite-In Situ Oceanographic Data Interoperability and Associated Value Added Services at the Podaac

NASA Astrophysics Data System (ADS)

Tsontos, V. M.; Huang, T.; Holt, B.

2015-12-01

The earth science enterprise increasingly relies on the integration and synthesis of multivariate datasets from diverse observational platforms. NASA's ocean salinity missions, that include Aquarius/SAC-D and the SPURS (Salinity Processes in the Upper Ocean Regional Study) field campaign, illustrate the value of integrated observations in support of studies on ocean circulation, the water cycle, and climate. However, the inherent heterogeneity of resulting data and the disparate, distributed systems that serve them complicates their effective utilization for both earth science research and applications. Key technical interoperability challenges include adherence to metadata and data format standards that are particularly acute for in-situ data and the lack of a unified metadata model facilitating archival and integration of both satellite and oceanographic field datasets. Here we report on efforts at the PO.DAAC, NASA's physical oceanographic data center, to extend our data management and distribution support capabilities for field campaign datasets such as those from SPURS. We also discuss value-added services, based on the integration of satellite and in-situ datasets, which are under development with a particular focus on DOMS. The distributed oceanographic matchup service (DOMS) implements a portable technical infrastructure and associated web services that will be broadly accessible via the PO.DAAC for the dynamic collocation of satellite and in-situ data, hosted by distributed data providers, in support of mission cal/val, science and operational applications.

Improving an Atlantic Fisheries DSS using Sea Surface Salinity Data from NASA's Aquarius Mission

NASA Technical Reports Server (NTRS)

Guest, DeNeice

2007-01-01

This report assesses the capacity of incorporating NASA#s Aquarius SSS (sea surface salinity) data into the SMAST (School of Marine Science and Technology) DSS for Fisheries Science. This data will enhance the SMAST DSS by providing SSS over a large area. Aquarius is a focused satellite mission designed to measure global SSS. SSS mapping is limited because conventional in situ SSS sampling is too sparse to give a large-scale view of the salinity variability. Aquarius will resolve missing physical processes that link the water cycle, the climate, and the ocean. The SMAST Fisheries program provides a DSS for fisheries science. It collects fisheries and environmental data, integrates them into a suite of data assimilation ocean models, and provides hindcasts, nowcasts, and forecasts for fisheries research, fisheries management, and the fishery industry. Currently, SMAST is using SSS data from the National Oceanic and Atmospheric Administration#s National Data Buoy Center. The SMAST DSS would be enhanced with SSS data from the Aquarius mission.

Limitations and potential of satellite imagery to monitor environmental response to coastal flooding

USGS Publications Warehouse

Ramsey, Elijah W.; Werle, Dirk; Suzuoki, Yukihiro; Rangoonwala, Amina; Lu, Zhong

2012-01-01

Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensing data collected before and after Hurricanes Gustav and Ike in 2008. These included synthetic aperture radar (SAR) data obtained from the (1) C-band advance SAR (ASAR) aboard the Environmental Satellite, (2) phased-array type L-band SAR (PALSAR) aboard the Advanced Land Observing Satellite, and (3) optical data obtained from Thematic Mapper (TM) sensor aboard the Land Satellite (Landsat). In estuarine marshes, L-band SAR and C-band ASAR provided accurate flood extent information when depths averaged at least 80 cm, but only L-band SAR provided consistent subcanopy detection when depths averaged 50 cm or less. Low performance of inundation mapping based on C-band ASAR was attributed to an apparent inundation detection limit (>30 cm deep) in tall Spartina alterniflora marshes, a possible canopy collapse of shoreline fresh marsh exposed to repeated storm-surge inundations, wind-roughened water surfaces where water levels reached marsh canopy heights, and relatively high backscatter in the near-range portion of the SAR imagery. A TM-based vegetation index of live biomass indicated that the severity of marsh dieback was linked to differences in dominant species. The severest impacts were not necessarily caused by longer inundation but rather could be caused by repeated exposure of the palustrine marsh to elevated salinity floodwaters. Differential impacts occurred in estuarine marshes. The more brackish marshes on average suffered higher impacts than the more saline marshes, particularly the nearshore coastal marshes occupied by S. alterniflora.

Earth Observation and Geospatial techniques for Soil Salinity and Land Capability Assessment over Sundarban Bay of Bengal Coast, India

NASA Astrophysics Data System (ADS)

Das, Sumanta; Choudhury, Malini Roy; Das, Subhasish; Nagarajan, M.

2016-12-01

To guarantee food security and job creation of small scale farmers to commercial farmers, unproductive farms in the South 24 PGS, West Bengal need land reform program to be restructured and evaluated for agricultural productivity. This study established a potential role of remote sensing and GIS for identification and mapping of salinity zone and spatial planning of agricultural land over the Basanti and Gosaba Islands(808.314sq. km) of South 24 PGS. District of West Bengal. The primary data i.e. soil pH, Electrical Conductivity (EC) and Sodium Absorption ratio (SAR) were obtained from soil samples of various GCP (Ground Control Points) locations collected at 50 mts. intervals by handheld GPS from 0-100 cm depths. The secondary information is acquired from the remotely sensed satellite data (LANDSAT ETM+) in different time scale and digital elevation model. The collected field samples were tested in the laboratory and were validated with Remote Sensing based digital indices analysisover the temporal satellite data to assess the potential changes due to over salinization. Soil physical properties such as texture, structure, depth and drainage condition is stored as attributes in a geographical soil database and linked with the soil map units. The thematic maps are integrated with climatic and terrain conditions of the area to produce land capability maps for paddy. Finally, The weighted overlay analysis was performed to assign theweights according to the importance of parameters taken into account for salineareaidentification and mapping to segregate higher, moderate, lower salinity zonesover the study area.

Finding a solution: Heparinised saline versus normal saline in the maintenance of invasive arterial lines in intensive care.

PubMed

Everson, Matthew; Webber, Lucy; Penfold, Chris; Shah, Sanjoy; Freshwater-Turner, Dan

2016-11-01

We assessed the impact of heparinised saline versus 0.9% normal saline on arterial line patency. Maintaining the patency of arterial lines is essential for obtaining accurate physiological measurements, enabling blood sampling and minimising line replacement. Use of heparinised saline is associated with risks such as thrombocytopenia, haemorrhage and mis-selection. Historical studies draw variable conclusions but suggest that normal saline is at least as effective at maintaining line patency, although recent evidence has questioned this. We conducted a prospective analysis of the use of heparinised saline versus normal saline on unselected patients in the intensive care of our hospital. Data concerning duration of 471 lines insertion and reason for removal was collected. We found a higher risk of blockage for lines flushed with normal saline compared with heparinised saline (RR = 2.15, 95% CI 1.392-3.32, p  ≤ 0.001). Of the 56 lines which blocked initially (19 heparinised saline and 37 normal saline lines), 16 were replaced with new lines; 5 heparinised saline lines and 11 normal saline lines were reinserted; 5 of these lines subsequently blocked again, 3 of which were flushed with normal saline. Our study demonstrates a clinically important reduction in arterial line longevity due to blockages when flushed with normal saline compared to heparinised saline. We have determined that these excess blockages have a significant clinical impact with further lines being inserted after blockage, resulting in increased risks to patients, wasted time and cost of resources. Our findings suggest that the current UK guidance favouring normal saline flushes should be reviewed.

Remote sensing of salinity

NASA Technical Reports Server (NTRS)

Thomann, G. C.

1975-01-01

The complex dielectric constant of sea water is a function of salinity at 21 cm wavelength, and sea water salinity can be determined by a measurement of emissivity at 21 cm along with a measurement of thermodynamic temperature. Three aircraft and one helicopter experiments using two different 21 cm radiometers were conducted under different salinity and temperature conditions. Single or multiple ground truth measurements were used to calibrate the data in each experiment. It is inferred from these experiments that accuracies of 1 to 2%/OO are possible with a single surface calibration point necessary only every two hours if the following conditions are met--water temperatures above 20 C, salinities above 10%/OO, and level plane flight. More frequent calibration, constraint of the aircraft's orientation to the same as it was during calibration, and two point calibration (at a high and low salinity level) rather than single point calibration may give even better accuracies in some instances.

Stochastic Modeling of Soil Salinity

NASA Astrophysics Data System (ADS)

Suweis, Samir; Rinaldo, Andrea; van der Zee, Sjoerd E. A. T. M.; Maritan, Amos; Porporato, Amilcare

2010-05-01

Large areas of cultivated land worldwide are affected by soil salinity. Estimates report that 10% of arable land in over 100 countries, and nine million km2 are salt affected, especially in arid and semi-arid regions. High salinity causes both ion specific and osmotic stress effects, with important consequences for plant production and quality. Salt accumulation in the root zone may be due to natural factors (primary salinization) or due to irrigation (secondary salinization). Simple (e.g., vertically averaged over the soil depth) coupled soil moisture and salt balance equations have been used in the past. Despite their approximations, these models have the advantage of parsimony, thus allowing a direct analysis of the interplay of the main processes. They also provide the ideal starting point to include external, random hydro-climatic fluctuations in the analysis of long-term salinization trends. We propose a minimalist stochastic model of primary soil salinity, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In fact, soil salinity statistics are obtained as a function of climate, soil and vegetation parameters. These, in turn, can be combined with soil moisture statistics to obtain a full characterization of soil salt concentrations and the ensuing risk of primary salinization. In particular, the solutions show the existence of two quite distinct regimes, the first one where the mean salt mass remains nearly constant with increasing rainfall frequency, and the

Salinity of the Delaware Estuary

USGS Publications Warehouse

Cohen, Bernard; McCarthy, Leo T.

1962-01-01

The purpose of this investigation was to obtain data on and study the factors affecting the salinity of the Delaware River from Philadelphia, Pa., to the Appoquinimink River, Del. The general chemical quality of water in the estuary is described, including changes in salinity in the river cross section and profile, diurnal and seasonal changes, and the effects of rainfall, sea level, and winds on salinity. Relationships are established of the concentrations of chloride and dissolved solids to specific conductance. In addition to chloride profiles and isochlor plots, time series are plotted for salinity or some quantity representing salinity, fresh-water discharge, mean river level, and mean sea level. The two major variables which appear to have the greatest effect on the salinity of the estuary are the fresh-water flow of the river and sea level. The most favorable combination of these variables for salt-water encroachment occurs from August to early October and the least favorable combination occurs between December and May.

Salinity Trends in the Upper Colorado River Basin Upstream From the Grand Valley Salinity Control Unit, Colorado, 1986-2003

USGS Publications Warehouse

Leib, Kenneth J.; Bauch, Nancy J.

2008-01-01

In 1974, the Colorado River Basin Salinity Control Act was passed into law. This law was enacted to address concerns regarding the salinity content of the Colorado River. The law authorized various construction projects in selected areas or 'units' of the Colorado River Basin intended to reduce the salinity load in the Colorado River. One such area was the Grand Valley Salinity Control Unit in western Colorado. The U. S. Geological Survey has done extensive studies and research in the Grand Valley Salinity Control Unit that provide information to aid the U.S. Bureau of Reclamation and the Natural Resources Conservation Service in determining where salinity-control work may provide the best results, and to what extent salinity-control work was effective in reducing salinity concentrations and loads in the Colorado River. Previous studies have indicated that salinity concentrations and loads have been decreasing downstream from the Grand Valley Salinity Control Unit, and that the decreases are likely the result of salinity control work in these areas. Several of these reports; however, also document decreasing salinity loads upstream from the Grand Valley Salinity Control Unit. This finding was important because only a small amount of salinity-control work was being done in areas upstream from the Grand Valley Salinity Control Unit at the time the findings were reported (late 1990?s). As a result of those previous findings, the U.S. Bureau of Reclamation entered into a cooperative agreement with the U.S. Geological Survey to investigate salinity trends in selected areas bracketing the Grand Valley Salinity Control Unit and regions upstream from the Grand Valley Salinity Control Unit. The results of the study indicate that salinity loads were decreasing upstream from the Grand Valley Salinity Control Unit from 1986 through 2003, but the rates of decrease have slowed during the last 10 years. The average rate of decrease in salinity load upstream from the Grand Valley

Measuring Salinity by Conductivity.

ERIC Educational Resources Information Center

Lapworth, C. J.

1981-01-01

Outlines procedures for constructing an instrument which uses an electrode and calibration methods to measure the salinity of waters in environments close to and affected by a saline estuary. (Author/DC)

The Aquarius Salinity Retrieval Algorithm: Early Results

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.; Lagerloef, Gary; LeVine, David

2012-01-01

(cal/val) activity needs to be completed. This is necessary in order to tune the inputs to the algorithm and remove biases that arise due to the instrument calibration, foremost the values of the noise diode injection temperatures and the losses that occur in the feedhorns. This is the subject of the second part of our presentation. The basic tool is to analyze the observed difference between the Aquarius measured TA and an expected TA that is computed from a reference salinity field. It is also necessary to derive a relation between the scatterometer backscatter measurements and the radiometer emissivity that is induced by surface winds. In order to do this we collocate Aquarius radiometer and scatterometer measurements with wind speed retrievals from the WindSat and SSMIS F17 microwave radiometers. Both of these satellites fly in orbits that have the same equatorial ascending crossing time (6 pm) as the Aquarius/SAC-D observatory. Rain retrievals from WindSat and SSMIS F 17 can be used to remove Aquarius observations that are rain contaminated. A byproduct of this analysis is a prediction for the wind-induced sea surface emissivity at L-band.

[Investigation and canonical correspondence analysis of salinity contents in secondary salinization greenhouse soils in Shanghai suburb].

PubMed

Tang, Dong; Mao, Liang; Zhi, Yue-e; Zhang, Jin-Zhong; Zhou, Pei; Chai, Xiao-Tong

2014-12-01

The salinity characteristics of greenhouse soils with cropping obstacles in Shanghai suburb were investigated and analyzed. The salinity contents of the salinization greenhouse soils showed a trend of first increasing and then decreasing with the increasing cropping duration. The salinized soils mainly included slightly salted, mildly salted and salted soils, which accounted for 17.39%, 56.52% and 13.04%, respectively. Among them, the degree of salinity in greenhouse soil planted with asparagus in Chongming County was the highest. Among the salt ions in greenhouse soils, the cations were mainly Ca2+ and Na+, while the anions were mainly NO3- and SO4(2-). The degree of salinity was mainly influenced by fertilization mode, cropping duration, crop type and management level, which led to the great variation in the salinity contents and salt ions. Canonical correspondence analysis found that the contents of Ca2+, Mg2+ and NO3- in greenhouse soils were greatly affected by cropping duration, and the degree of salinity would be enhanced and attenuated with long-term application of single fertilizer and mixed application of chemical fertilizer and organic manure, respectively. The greenhouse soils in Shanghai suburb could be classified as four patterns influenced by the relationship between salinity ions and samples, and the most soils were influenced by Ca2+, Mg2+, NO3- and Cl-, which required to be primarily controlled.

An inversion method for retrieving soil moisture information from satellite altimetry observations

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

2016-04-01

Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i

On the Use of Satellite Altimetry to Detect Ocean Circulation's Magnetic Signals

NASA Astrophysics Data System (ADS)

Saynisch, J.; Irrgang, C.; Thomas, M.

2018-03-01

Oceanic magnetic signals are sensitive to ocean velocity, salinity, and heat content. The detection of respective signals with global satellite magnetometers would pose a very valuable source of information. While tidal magnetic fields are already detected, electromagnetic signals of the ocean circulation still remain unobserved from space. We propose to use satellite altimetry to construct proxy magnetic signals of the ocean circulation. These proxy time series could subsequently be fitted to satellite magnetometer data. The fitted data could be removed from the observations or the fitting constants could be analyzed for physical properties of the ocean, e.g., the heat budget. To test and evaluate this approach, synthetic true and proxy magnetic signals are derived from a global circulation model of the ocean. Both data sets are compared in dependence of location and time scale. We study and report when and where the proxy data describe the true signal sufficiently well. Correlations above 0.6 and explained variances of above 80% can be reported for large parts of the Antarctic ocean, thus explaining the major part of the global, subseasonal magnetic signal.

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matt

2007-01-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

Mapping Solid and Liquid Meltwater Retention on the Greenland and Antarctic Ice Sheets from Space

NASA Astrophysics Data System (ADS)

Miller, J.; Bringer, A.; Jezek, K. C.; Johnson, J. T.; Scambos, T.; Forster, R. R.; Long, D. G.

2017-12-01

We use satellite and airborne microwave radiometry to explore the potential for mapping both solid (infiltration ice) and liquid (firn aquifers) meltwater retention on ice sheets. Meltwater retention in firn is currently poorly understood, especially on an ice sheet-scale, however, critical to understanding the ultimate fate of liquid meltwater produced at the surface of ice sheets. Is it contributing to sea level? Or, is it being buffered prior to escaping into the ocean? We previously developed a simple satellite retrieval technique to map firn aquifers on the Greenland ice sheet using distinct L-band brightness temperature signatures that decrease on timescales of months following surface freeze-up, however, similar L-band brightness temperature signatures that decrease on timescales ranging from weeks to days are also present throughout the percolation facies of both the Greenland and Antarctic ice sheets. We hypothesize this characteristic family of temporal signatures represents meltwater retention within firn, where slowly decreasing signatures are characteristic of meltwater retention within perennial firn aquifers, and rapidly decreasing signatures are characteristic of meltwater retention as superimposed ice. Decreasing signatures on timescales between likely represent a continuum of firn characteristics, such as transient firn aquifers, perched firn aquifers, ice layers, ice pipes and lenses, and iced firn. To investigate these temporal signatures, we use L-band (1.4 GHz) brightness temperature observations collected over the Greenland and Antarctic ice sheets by the interferometric MIRAS instrument aboard ESA's Soil Moisture and Ocean Salinity (SMOS) satellite, and the radiometer aboard NASA's Soil Moisture Active Passive (SMAP) satellite. We will also investigate spectral signatures using multi-frequency L-band brightness temperature data (0.5-2 GHz) to be collected over several firn aquifer areas on the Greenland ice sheet by the Ohio State University

Saline Sinus Rinse Recipe

MedlinePlus

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Durum wheat seedlings in saline conditions: Salt spray versus root-zone salinity

NASA Astrophysics Data System (ADS)

Spanò, Carmelina; Bottega, Stefania

2016-02-01

Salinity is an increasingly serious problem with a strong negative impact on plant productivity. Though many studies have been made on salt stress induced by high NaCl concentrations in the root-zone, few data concern the response of plants to saline aerosol, one of the main constraints in coastal areas. In order to study more in depth wheat salinity tolerance and to evaluate damage and antioxidant response induced by various modes of salt application, seedlings of Triticum turgidum ssp. durum, cv. Cappelli were treated for 2 and 7 days with salt in the root-zone (0, 50 and 200 mM NaCl) or with salt spray (400 mM NaCl + 0 or 200 mM NaCl in the root-zone). Seedlings accumulated Na+ in their leaves and therefore part of their ability to tolerate high salinity seems to be due to Na+ leaf tissue tolerance. Durum wheat, confirmed as a partially tolerant plant, shows a higher damage under airborne salinity, when both an increase in TBA-reactive material (indicative of lipid peroxidation) and a decrease in root growth were recorded. A different antioxidant response was activated, depending on the type of salt supply. Salt treatment induced a depletion of the reducing power of both ascorbate and glutathione while the highest contents of proline were detected under salt spray conditions. In the short term catalase and ascorbate peroxidase co-operated with glutathione peroxidase in the scavenging of hydrogen peroxide, in particular in salt spray-treated plants. From our data, the durum wheat cultivar Cappelli seems to be sensitive to airborne salinity.

Coherent mesoscale eddies in the North Atlantic subtropical gyre: 3-D structure and transport with application to the salinity maximum

NASA Astrophysics Data System (ADS)

Amores, Angel; Melnichenko, Oleg; Maximenko, Nikolai

2017-01-01

The mean vertical structure and transport properties of mesoscale eddies are investigated in the North Atlantic subtropical gyre by combining historical records of Argo temperature/salinity profiles and satellite sea level anomaly data in the framework of the eddy tracking technique. The study area is characterized by a low eddy kinetic energy and sea surface salinity maximum. Although eddies have a relatively weak signal at surface (amplitudes around 3-7 cm), the eddy composites reveal a clear deep signal that penetrates down to at least 1200 m depth. The analysis also reveals that the vertical structure of the eddy composites is strongly affected by the background stratification. The horizontal patterns of temperature/salinity anomalies can be reconstructed by a linear combination of a monopole, related to the elevation/depression of the isopycnals in the eddy core, and a dipole, associated with the horizontal advection of the background gradient by the eddy rotation. A common feature of all the eddy composites reconstructed is the phase coherence between the eddy temperature/salinity and velocity anomalies in the upper ˜300 m layer, resulting in the transient eddy transports of heat and salt. As an application, a box model of the near-surface layer is used to estimate the role of mesoscale eddies in maintaining a quasi-steady state distribution of salinity in the North Atlantic subtropical salinity maximum. The results show that mesoscale eddies are able to provide between 4 and 21% of the salt flux out of the area required to compensate for the local excess of evaporation over precipitation.

Detecting crop yield reduction due to irrigation-induced soil salinization in South-West Russia

NASA Astrophysics Data System (ADS)

Argaman, E.; Beets, W.; Croes, J.; Keesstra, S.; Verzandvoort, S.; Zeiliguer, A.

2012-04-01

The South-European part of the Russian Federation has experienced serious land degradation in the form of soil salinization since the 1960s. This land degradation was caused by intensive, large-scale irrigation on reclaimed land in combination with the salt-rich nature of the substrate. Alkaline soil salinity is believed to be an important factor decreasing crop yield in this area. A large research effort has been directed to the effects of soil salinity on crops, there is a need for simple, easily determinable indicators of crop health and soil salinity in irrigated systems, that can help to detect crop water stress in an early stage. The objectives of this research were to study the effects of soil salinity and vegetation water stress on the performance of alfalfa crop yield and physiological crop properties, and to study the possibility to measure soil salinity and alkalinity and the crop water stress index at plot level using a thermal gun and a regular digital camera. The study area was located in Saratov District, in the South-West part of Russia. Variables on the surface energy balance, crop properties, soil properties and visible reflectance were measured on plots with alfalfa cultures in two fields with and without signs of alkaline soil salinity, and with and without irrigation in July 2009. The research showed no clear adverse effects of soil salinity and soil alkalinity on crop yield and physiological crop properties. Soil salinity, as reflected by the electric conductivity, positively affected the root biomass of alfalfa in the range of 0.15 to 1.52 dS/m . This was a result of EC levels being below the documented threshold to negatively affect Alfalfa, as would be the case in truly saline soils. The soil pH also showed a positive correlation with root biomass within the range of pH 6.2 and 8.5 . From the literature these pH values are generally believed to be too high to exhibit a positive relationship with root biomass. No relationship was found

A global algorithm for estimating Absolute Salinity

NASA Astrophysics Data System (ADS)

McDougall, T. J.; Jackett, D. R.; Millero, F. J.; Pawlowicz, R.; Barker, P. M.

2012-12-01

The International Thermodynamic Equation of Seawater - 2010 has defined the thermodynamic properties of seawater in terms of a new salinity variable, Absolute Salinity, which takes into account the spatial variation of the composition of seawater. Absolute Salinity more accurately reflects the effects of the dissolved material in seawater on the thermodynamic properties (particularly density) than does Practical Salinity. When a seawater sample has standard composition (i.e. the ratios of the constituents of sea salt are the same as those of surface water of the North Atlantic), Practical Salinity can be used to accurately evaluate the thermodynamic properties of seawater. When seawater is not of standard composition, Practical Salinity alone is not sufficient and the Absolute Salinity Anomaly needs to be estimated; this anomaly is as large as 0.025 g kg-1 in the northernmost North Pacific. Here we provide an algorithm for estimating Absolute Salinity Anomaly for any location (x, y, p) in the world ocean. To develop this algorithm, we used the Absolute Salinity Anomaly that is found by comparing the density calculated from Practical Salinity to the density measured in the laboratory. These estimates of Absolute Salinity Anomaly however are limited to the number of available observations (namely 811). In order to provide a practical method that can be used at any location in the world ocean, we take advantage of approximate relationships between Absolute Salinity Anomaly and silicate concentrations (which are available globally).

Saline-water resources of Texas

USGS Publications Warehouse

Winslow, Allen George; Kister, Lester Ray

1956-01-01

Most of the aquifers in Texas contain saline water in some parts, and a few are capable of producing large quantities of saline water. Of the early Paleozoic formations, the Hickory sandstone member of the Riley formation of Cambrian age and the Ellenburger group of Ordovician age are potential sources of small to moderate supplies of saline water in parts of central and west-central Texas.

Sea-ice transport driving Southern Ocean salinity and its recent trends.

PubMed

Haumann, F Alexander; Gruber, Nicolas; Münnich, Matthias; Frenger, Ivy; Kern, Stefan

2016-09-01

Recent salinity changes in the Southern Ocean are among the most prominent signals of climate change in the global ocean, yet their underlying causes have not been firmly established. Here we propose that trends in the northward transport of Antarctic sea ice are a major contributor to these changes. Using satellite observations supplemented by sea-ice reconstructions, we estimate that wind-driven northward freshwater transport by sea ice increased by 20 ± 10 per cent between 1982 and 2008. The strongest and most robust increase occurred in the Pacific sector, coinciding with the largest observed salinity changes. We estimate that the additional freshwater for the entire northern sea-ice edge entails a freshening rate of -0.02 ± 0.01 grams per kilogram per decade in the surface and intermediate waters of the open ocean, similar to the observed freshening. The enhanced rejection of salt near the coast of Antarctica associated with stronger sea-ice export counteracts the freshening of both continental shelf and newly formed bottom waters due to increases in glacial meltwater. Although the data sources underlying our results have substantial uncertainties, regional analyses and independent data from an atmospheric reanalysis support our conclusions. Our finding that northward sea-ice freshwater transport is also a key determinant of the mean salinity distribution in the Southern Ocean further underpins the importance of the sea-ice-induced freshwater flux. Through its influence on the density structure of the ocean, this process has critical consequences for the global climate by affecting the exchange of heat, carbon and nutrients between the deep ocean and surface waters.

Estuarine Salinity Mapping From Airborne Radiometry

NASA Astrophysics Data System (ADS)

Walker, J. P.; Gao, Y.; Cook, P. L. M.; Ye, N.

2016-12-01

Estuaries are critical ecosystems providing both ecological habitat and human amenity including boating and recreational fishing. Salinity gradients, caused by the mixing of fresh and salt water, exert an overwhelming control on estuarine ecology and biogeochemistry as well as being a key tracer for model calibration. At present, salinity monitoring within estuaries typically uses point measurements or underway boat-based methods, which makes sensing of localised phenomena such as upwelling of saline bottom water difficult. This study has pioneered the use of airborne radiometry (passive microwave) sensing as a new method to remotely quantify estuarine salinity, allowing rapid production of high resolution surface salinity maps. The airborne radiometry mapping was conducted for the Gippsland Lakes, the largest estuary in Australia, in February, July, October and November of 2015, using the Polarimetric L-band Microwave Radiometer (PLMR). Salinity was retrieved from the brightness temperature collected by PLMR with results validated against boat sampling conducted concurrently with each flight. Results showed that the retrieval accuracy of the radiative transfer model was better than 5 ppt for most flights. The spatial, temporal and seasonal variations of salinity observed in this study are also analysed and discussed.

Application of the Coastal and Marine Ecological Classification Standard using Satellite-derived and Modeled Data Products for Pelagic Habitats in the Northern Gulf of Mexico

EPA Science Inventory

Satellite-derived data for sea surface temperature, salinity, chlorophyll; euphotic depth; and modeled bottom to surface temperature differences (Delta t) were evaluated to assess the utility of these products as proxies for in situ measurements. The data were used to classify su...

Near-surface Salinity and Temperature Structure Observed with Dual-Sensor Drifters in the Subtropical South Pacific

NASA Astrophysics Data System (ADS)

Dong, Shenfu; Goni, Gustavo; Volkov, Denis; Lumpkin, Rick; Foltz, Gregory

2017-04-01

Three surface drifters equipped with temperature and salinity sensors at 0.2 m and 5 m depths were deployed in April/May 2015 in the subtropical South Pacific Ocean with the objective of measuring near-surface salinity differences seen by satellite and in situ sensors and examining the causes of the differences. Measurements from these drifters indicate that, on average, water at a depth of 0.2 m is about 0.013 psu fresher than at 5 m and about 0.024°C warmer. Events with large temperature and salinity differences between the two depths often occur when surface winds are weak. In addition to the expected surface freshening and cooling during rainfall events, surface salinification occurs under weak wind conditions when there is strong surface warming that enhances evaporation and upper ocean stratification. Further examination of the drifter measurements demonstrate that (i) the amount of surface freshening and vertical salinity gradient heavily depend on wind speed during rain events, (ii) salinity differences between 0.2 m and 5 m are positively correlated with the corresponding temperature differences, and (iii) temperature exhibits a diurnal cycle at both depths, whereas the diurnal cycle of salinity is observed only at 0.2 m when the wind speed is less than 4 m/s. Its phase is consistent with diurnal changes in surface temperature-induced evaporation. Below a wind speed of 6 m/s, the amplitudes of the diurnal cycles of temperature at both depths decrease with increasing wind speed. Wind speed also affects the phasing of the diurnal cycle of T5m with the time of maximum T5m increasing gradually with decreasing wind speed. Wind speed does not affect the phasing of the diurnal cycle of T0.2m. At 0.2 m and 5 m, the diurnal cycle of temperature also depends on surface solar radiation, with the amplitude and time of diurnal maximum increasing as solar radiation increases.

Are Low Salinity Waters the Remedy to Noctiluca scintillans Blooms in the Arabian Sea?

NASA Astrophysics Data System (ADS)

Gibson, J.

2017-12-01

Noctiluca scintillans (Noctiluca) is a mixotrophic, green dinoflagellate that for the past two decades has been producing problematic algal blooms in the Arabian Sea (AS). As a mixotroph, Noctiluca obtains energy from both consumption of phytoplankton as well as its intracellular photosynthesizing endosymbionts named, Pedinomonas noctilucae. It is this autotrophic and heterotrophic dual capability that has largely enabled Noctiluca to be a highly dominant species at the planktonic trophic layer in the AS. Exacerbated by non-point source/point-source pollution in the AS, ocean acidification, and intensified monsoons, Noctiluca currently algal blooms can be as big as three times the size of Texas. By depleting the AS of oxygen, clogging the gills of fish, and altering the AS food web, these algal blooms result in mass fish die offs. In turn this propagates financial and food insecurity issues in countless coastal communities. However, through satellite imaging over the years, it has been observed that the proliferation of Noctiluca is precluded or encounters a "wall" about mid-way along the west coast of India. It is theorized that this "wall" is due to a significant change in salinity. Snow from atop the Himalayan Mountains melts and adds fresh water to the Bay of Bengal (BB), and in winter the East Indian Coastal Current (EICC) carries this fresher water around the southern tip of India and towards the AS. It is believed that this dilution effect impedes the growth of Noctiluca further south. Ultimately, in this study the salinity gradient from the Bay of Bengal (BB) around the horn of India into the AS was replicated in six pairs of culture bottles. Noctiluca was grown in six different salinities including 26, 28, 30, 32, 34, and 38 psu. Algae grown in the 34 and 38 psu bottles, were healthier and 38 psu treated Noctiluca provided optimal conditions for its photosynthesizing endosymbionts. Noctiluca does not grow well at lower salinities, thus applications of low

Salinity Management in Agriculture

USDA-ARS?s Scientific Manuscript database

Existing guidelines and standards for reclamation of saline soils and management to control salinity exist but have not been updated for over 25 years. In the past few years a looming water scarcity has resulted in questioning of the long term future of irrigation projects in arid and semi arid regi...

Retrieving Temperature Anomaly in the Global Subsurface and Deeper Ocean From Satellite Observations

NASA Astrophysics Data System (ADS)

Su, Hua; Li, Wene; Yan, Xiao-Hai

2018-01-01

Retrieving the subsurface and deeper ocean (SDO) dynamic parameters from satellite observations is crucial for effectively understanding ocean interior anomalies and dynamic processes, but it is challenging to accurately estimate the subsurface thermal structure over the global scale from sea surface parameters. This study proposes a new approach based on Random Forest (RF) machine learning to retrieve subsurface temperature anomaly (STA) in the global ocean from multisource satellite observations including sea surface height anomaly (SSHA), sea surface temperature anomaly (SSTA), sea surface salinity anomaly (SSSA), and sea surface wind anomaly (SSWA) via in situ Argo data for RF training and testing. RF machine-learning approach can accurately retrieve the STA in the global ocean from satellite observations of sea surface parameters (SSHA, SSTA, SSSA, SSWA). The Argo STA data were used to validate the accuracy and reliability of the results from the RF model. The results indicated that SSHA, SSTA, SSSA, and SSWA together are useful parameters for detecting SDO thermal information and obtaining accurate STA estimations. The proposed method also outperformed support vector regression (SVR) in global STA estimation. It will be a useful technique for studying SDO thermal variability and its role in global climate system from global-scale satellite observations.

The Role of Anchor Stations in the Validation of Earth Observation Satellite Data and Products. The Valencia and the Alacant Anchor Stations

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto; Geraldo Ferreira, A.; Saleh-Contell, Kauzar

. Measurements are made of meteorological and hydrological background data, and of quantities not readily assessed at operational stations. Anchor Stations also offer infrastructure to undertake validation experi-ments. These are more detailed measurements over shorter intensive observation periods. The Valencia Anchor Station is showing its capabilities and conditions as a reference validation site in the framework of low spatial resolution remote sensing missions such as CERES, GERB and SMOS. The Alacant Anchor Station is a reference site in studies on the interactions between desertification and climate. This paper presents the activities so far carried out at both Anchor Stations, the precise and detailed ground and aircraft experiments carefully designed to develop a specific methodology to validate low spatial resolution satellite data and products, and the knowledge exchange currently being exercised between the University of Valencia, Spain, and FUNCEME, Brazil, in common objectives of mutual interest.

Effects of salinity on baldcypress seedlings: Physiological responses and their relation to salinity tolerance

USGS Publications Warehouse

Allen, J.A.; Chambers, J.L.; Pezeshki, S.R.

1997-01-01

Growth and physiological responses of 15 open-pollinated families of baldcypress (Taxodium distichum var. distichum) subjected to flooding with saline water were evaluated in this study. Ten of the families were from coastal sites in Louisiana and Alabama, USA that have elevated levels of soil-water salinity. The other five families were from inland, freshwater sites in Louisiana. Seedlings from all families tolerated flooding with water of low (2 g l-1) salinity. Differences in biomass among families became most apparent at the highest salinity levels (6 and 8 g l-1). Overall, increasing salinity reduced leaf biomass more than root biomass, which in turn was reduced more than stem biomass. A subset of seedlings from the main greenhouse experiment was periodically placed indoors under artificial light, and measurements were made of gas exchange and leaf water potential. Also, tissue concentrations of Cl-, Na+, K+, and Ca2+ were determined at the end of the greenhouse experiment. Significant intraspecific variation was found for nearly all the physiological parameters evaluated, but only leaf concentrations of Na+ and Cl- were correlated with an index of family-level differences in salt tolerance.

Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

2016-01-01

Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

Groundwater-saline lakes interaction - The contribution of saline groundwater circulation to solute budget of saline lakes: a lesson from the Dead Sea

NASA Astrophysics Data System (ADS)

Kiro, Yael; Weinstein, Yishai; Starinsky, Abraham; Yechieli, Yoseph

2013-04-01

Saline lakes act as base level for both surface water and groundwater. Thus, a change in lake levels is expected to result in changes in the hydrogeological system in its vicinity, exhibited in groundwater levels, location of the fresh-saline water interface, sub-lacustrine groundwater discharge (SGD) and saline water circulation. All these processes were observed in the declining Dead Sea system, whose water level dropped by ~35 meters in the last 50 years. This work focuses mainly on the effect of circulation of Dead Sea water in the aquifer, which continues even in this very rapid base level drop. In general, seawater circulation in coastal aquifers is now recognized as a major process affecting trace element mass balances in coastal areas. Estimates of submarine groundwater discharge (SGD) vary over several orders of magnitude (1-1000000 m3/yr per meter shoreline). These estimates are sensitive to fresh-saline SGD ratios and to the temporal and spatial scales of the circulation. The Dead Sea system is an excellent natural field lab for studying seawater-groundwater interaction and large-scale circulation due to the absence of tides and to the minor role played by waves. During Dead Sea water circulation in the aquifer several geochemical reactions occur, ranging from short-term adsorption-desorption reactions and up to long-term precipitation and dissolution reactions. These processes affect the trace element distribution in the saline groundwater. Barite and celestine, which are supersaturated in the lake water, precipitate during circulation in the aquifer, reducing barium (from 5 to 1.5 mg/L), strontium (from 350 to 300 mg/L) and the long-lived 226Ra (from 145 to 60 dpm/L) in the saline groundwater. Redox-controlled reactions cause a decrease in uranium from 2.4 to 0.1 μg/L, and an increase in iron from 1 to 13 mg/L. 228Ra (t1/2=5.75 yr) activity in the Dead Sea is ~1 dpm/L and increase gradually as the saline water flows further inland until reaching

Polymer tensiometers in a saline environment.

NASA Astrophysics Data System (ADS)

van der Ploeg, Martine; Gooren, H. P. A.; Bakker, G.; Russell, W.; Hoogendam, C. W.; Huiskes, C.; Shouse, P.; de Rooij, G. H.

2010-05-01

It is estimated that 20% of all cultivated land and nearly half of the irrigated land is salt-affected, which pose major economic and environmental problems. Salinity may be the result of two processes; dryland and irrigation salinity. Dryland salinity is caused by a rise in the groundwater table, which occurs as a result of the replacement of deep-rooted, perennial native vegetation by shallow-rooted annual species meant for production. Irrigation salinity may occur as a result of poor water quality, poor drainage, or inefficient use of water. Consequently, new strategies to enhance crop yield stability on saline soils represent a major research priority (Botella et al. 2005). At the same time, native vegetation is capable of thriving under saline and/or dry conditions. The plant physiology of such vegetation has been investigated thoroughly, but the relation with in situ soil properties (soil moisture and salinity) may be more difficult to unravel as soil moisture sensors are less sensitive in dry soil, and the signal of most soil moisture content sensors is strongly attenuated by soil salinity. Recently, polymer tensiometer were developed that are able to measure matric potentials (closely related to a soil's moisture status) in dry soils. Polymer tensiometers consist of a solid ceramic, a stainless steel cup and a pressure transducer. The ceramic consist of a support layer and a membrane with 2 nm pore-size to prevent polymer leakage. Between the ceramic membrane and the pressure transducer a tiny chamber is located, which contains the polymer solution. The polymer's osmotic potential strongly reduces the total water potential inside the polymer tensiometer, which causes build-up of osmotic pressure. Polymer tensiometers would thus be an ideal instrument to measure in dry soil, if the polymer inside the tensiometer is not affected by the salts in the soil solution. We will address some key issues regarding the use of POTs in saline environments by showing

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

PubMed

Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

2017-02-01

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

Electrocapillary Phenomena at Edible Oil/Saline Interfaces.

PubMed

Nishimura, Satoshi; Ohzono, Takuya; Shoji, Kohei; Yagihara, Shin; Hayashi, Masafumi; Tanaka, Hisao

2017-03-01

Interfacial tension between edible oil and saline was measured under applied electric fields to understand the electrocapillary phenomena at the edible oil/saline interfaces. The electric responses of saline droplets in edible oil were also observed microscopically to examine the relationship between the electrocapillary phenomena and interfacial polarization. When sodium oleate (SO) was added to edible oil (SO-oil), the interfacial tension between SO-oil and saline decreased. However, no decrease was observed for additive-free oil or oleic acid (OA)-added oil (OA-oil). Microscopic observations suggested that the magnitude of interfacial polarization increased in the order of additive-free oil < OA-oil < SO-oil. The difference in electrocapillary phenomena between OA- and SO-oils was closely related to the polarization magnitude. In the case of SO-oil, the decrease in interfacial tension was remarkably larger for saline (pH 5.4~5.6) than that for phosphate-buffered saline (PBS, pH 7.2~7.4). However, no difference was observed between the electric responses of PBS and saline droplets in SO-oil. The difference in electrocapillary phenomena for PBS and saline could not be simply explained in terms of polarization magnitude. The ratio of ionized and non-ionized OA at the interfaces changed with the saline pH, possibly leading to the above difference.

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, T.

2016-12-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatio-temporal scales are important to applications, capability assessment, and future mission design. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in October 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1°x1°, 3°x3°, and 10°x10°. Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10°x10°) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space.

Last Glacial Maximum Salinity Reconstruction

NASA Astrophysics Data System (ADS)

Homola, K.; Spivack, A. J.

2016-12-01

It has been previously demonstrated that salinity can be reconstructed from sediment porewater. The goal of our study is to reconstruct high precision salinity during the Last Glacial Maximum (LGM). Salinity is usually determined at high precision via conductivity, which requires a larger volume of water than can be extracted from a sediment core, or via chloride titration, which yields lower than ideal precision. It has been demonstrated for water column samples that high precision density measurements can be used to determine salinity at the precision of a conductivity measurement using the equation of state of seawater. However, water column seawater has a relatively constant composition, in contrast to porewater, where variations from standard seawater composition occur. These deviations, which affect the equation of state, must be corrected for through precise measurements of each ion's concentration and knowledge of apparent partial molar density in seawater. We have developed a density-based method for determining porewater salinity that requires only 5 mL of sample, achieving density precisions of 10-6 g/mL. We have applied this method to porewater samples extracted from long cores collected along a N-S transect across the western North Atlantic (R/V Knorr cruise KN223). Density was determined to a precision of 2.3x10-6 g/mL, which translates to salinity uncertainty of 0.002 gms/kg if the effect of differences in composition is well constrained. Concentrations of anions (Cl-, and SO4-2) and cations (Na+, Mg+, Ca+2, and K+) were measured. To correct salinities at the precision required to unravel LGM Meridional Overturning Circulation, our ion precisions must be better than 0.1% for SO4-/Cl- and Mg+/Na+, and 0.4% for Ca+/Na+, and K+/Na+. Alkalinity, pH and Dissolved Inorganic Carbon of the porewater were determined to precisions better than 4% when ratioed to Cl-, and used to calculate HCO3-, and CO3-2. Apparent partial molar densities in seawater were

Magnetically-driven oceans on Jovian satellites

NASA Astrophysics Data System (ADS)

Gissinger, C.; Petitdemange, L.

2017-12-01

During the last decade, data from Galileo space missions have added strong support for the existence of subsurface liquid oceans on several moons of Jupiter. For instance, it is now commonly accepted that an electrically conducting fluid beneath the icy crust of Europa's surface may explain the variations of the induced field measured near the satellite. These observations have raised many questions regarding the size and the salinity of such subsurface ocean, or how and why the water remains liquid. In addition, the hydrodynamics of such oceans is mostly unknown. These questions are of primary importance since Europa is often considered as a good candidate for the presence of life beyond the Earth. Here, we present the first numerical modeling of the rapidly-rotating magnetohydrodynamic (MHD) flow generated in Europa's interior: due to Jupiter's rotation with respect to Europa, we show that the Lorentz force induced by the time-varying Jovian magnetic field is able to generate an oceanic flow of a few km/h. Our results are understood in the framework of a simple theoretical model and we obtain a scaling law for the prediction of the mean oceanic velocity and the total heating generated inside the ocean of Europa. Finally, by comparing our simulations to Galileo observations, we make predictions on both the thickness and the electrical conductivity of the ocean of different Jovian's satellites.

Corrosion of dental aluminium bronze in neutral saline and saline lactic acid.

PubMed

Tibballs, J E; Erimescu, Raluca

2006-09-01

To compare the corrosion behaviours of two aluminium bronze, dental casting alloys during a standard immersion test and for immersion in neutral saline. Cast specimens of aluminium bronzes with 1.4 wt% Fe (G) and 4 wt% Fe (N) were subject to progressively longer periods (up to in total 7 days) immersed in 0.1 M saline, 0.1 M lactic acid solutions and examined by scanning electron microscopy with EDX analysis. Immersion in 0.1M neutral saline was for 7 days. In the acidic solution, exposed interdendritic volumes in alloy N corroded completely away in 7 days with dissolution of Ni-enriched precipitate species as well as the copper-rich matrix. Alloy G begins to corrode more slowly but by a similar mechanism. The number density of an Fe-enriched species is insufficient to maintain a continuous galvanic potential to the copper matrix, and dissolution becomes imperceptible. In neutral saline solution, galvanic action alone caused pit-etching, without the dissolution of either precipitate species. The upper limit for the total dissolution of metallic ions in the standard immersion test can be set at 200 microg cm(-2). Aluminium bronze dental alloys can be expected to release both copper and nickel ions into an acidic oral environment.

Evaluating physiological responses of plants to salinity stress

PubMed Central

Negrão, S.; Schmöckel, S. M.; Tester, M.

2017-01-01

Background Because soil salinity is a major abiotic constraint affecting crop yield, much research has been conducted to develop plants with improved salinity tolerance. Salinity stress impacts many aspects of a plant’s physiology, making it difficult to study in toto. Instead, it is more tractable to dissect the plant’s response into traits that are hypothesized to be involved in the overall tolerance of the plant to salinity. Scope and conclusions We discuss how to quantify the impact of salinity on different traits, such as relative growth rate, water relations, transpiration, transpiration use efficiency, ionic relations, photosynthesis, senescence, yield and yield components. We also suggest some guidelines to assist with the selection of appropriate experimental systems, imposition of salinity stress, and obtaining and analysing relevant physiological data using appropriate indices. We illustrate how these indices can be used to identify relationships amongst the proposed traits to identify which traits are the most important contributors to salinity tolerance. Salinity tolerance is complex and involves many genes, but progress has been made in studying the mechanisms underlying a plant’s response to salinity. Nevertheless, several previous studies on salinity tolerance could have benefited from improved experimental design. We hope that this paper will provide pertinent information to researchers on performing proficient assays and interpreting results from salinity tolerance experiments. PMID:27707746

Effect of hypersaline cooling canals on aquifer salinization

USGS Publications Warehouse

Hughes, Joseph D.; Langevin, Christian D.; Brakefield-Goswami, Linzy

2010-01-01

The combined effect of salinity and temperature on density-driven convection was evaluated in this study for a large (28 km2) cooling canal system (CCS) at a thermoelectric power plant in south Florida, USA. A two-dimensional cross-section model was used to evaluate the effects of hydraulic heterogeneities, cooling canal salinity, heat transport, and cooling canal geometry on aquifer salinization and movement of the freshwater/saltwater interface. Four different hydraulic conductivity configurations, with values ranging over several orders of magnitude, were evaluated with the model. For all of the conditions evaluated, aquifer salinization was initiated by the formation of dense, hypersaline fingers that descended downward to the bottom of the 30-m thick aquifer. Saline fingers reached the aquifer bottom in times ranging from a few days to approximately 5 years for the lowest hydraulic conductivity case. Aquifer salinization continued after saline fingers reached the aquifer bottom and coalesced by lateral movement away from the site. Model results showed that aquifer salinization was most sensitive to aquifer heterogeneity, but was also sensitive to CCS salinity, temperature, and configuration.

Microstrip Patch Sensor for Salinity Determination.

PubMed

Lee, Kibae; Hassan, Arshad; Lee, Chong Hyun; Bae, Jinho

2017-12-18

In this paper, a compact microstrip feed inset patch sensor is proposed for measuring the salinities in seawater. The working principle of the proposed sensor depends on the fact that different salinities in liquid have different relative permittivities and cause different resonance frequencies. The proposed sensor can obtain better sensitivity to salinity changes than common sensors using conductivity change, since the relative permittivity change to salinity is 2.5 times more sensitive than the conductivity change. The patch and ground plane of the proposed sensor are fabricated by conductive copper spray coating on the masks made by 3D printer. The fabricated patch and the ground plane are bonded to a commercial silicon substrate and then attached to 5 mm-high chamber made by 3D printer so that it contains only 1 mL seawater. For easy fabrication and testing, the maximum resonance frequency was selected under 3 GHz and to cover salinities in real seawater, it was assumed that the salinity changes from 20 to 35 ppt. The sensor was designed by the finite element method-based ANSYS high-frequency structure simulator (HFSS), and it can detect the salinity with 0.01 ppt resolution. The designed sensor has a resonance frequency separation of 37.9 kHz and reflection coefficients under -20 dB at the resonant frequencies. The fabricated sensor showed better performance with average frequency separation of 48 kHz and maximum reflection coefficient of -35 dB. By comparing with the existing sensors, the proposed compact and low-cost sensor showed a better detection capability. Therefore, the proposed patch sensor can be utilized in radio frequency (RF) tunable sensors for salinity determination.

Response of Stream Biodiversity to Increasing Salinization

NASA Astrophysics Data System (ADS)

Hawkins, C. P.; Vander Laan, J. J.; Olson, J. R.

2014-12-01

We used a large data set of macroinvertebrate samples collected from streams in both reference-quality (n = 68) and degraded (n = 401) watersheds in the state of Nevada, USA to assess relationships between stream biodiversity and salinity. We used specific electrical conductance (EC)(μS/cm) as a measure of salinity, and applied a previously developed EC model to estimate natural, baseflow salinity at each stream. We used the difference between observed and predicted salinity (EC-Diff) as a measure of salinization associated with watershed degradation. Observed levels of EC varied between 22 and 994 μS/cm across reference sites and 22 to 3,256 uS/cm across non-reference sites. EC-Diff was as high as 2,743 μS/cm. We used a measure of local biodiversity completeness (ratio of observed to expected number of taxa) to assess ecological response to salinity. This O/E index decreased nearly linearly up to about 25% biodiversity loss, which occurred at EC-Diff of about 300 μS/cm. Too few sites had EC-Diff greater than 300 μS/cm to draw reliable inferences regarding biodiversity response to greater levels of salinization. EC-Diff increased with % agricultural land use, mine density, and % urban land use in the watersheds implying that human activities have been largely responsible for increased salinization in Nevada streams and rivers. Comparison of biological responses to EC and other stressors indicates that increased salinization may be the primary stressor causing biodiversity loss in these streams and that more stringent salinity water quality standards may be needed to protect aquatic life.

Hurricane-induced failure of low salinity wetlands

PubMed Central

Howes, Nick C.; FitzGerald, Duncan M.; Hughes, Zoe J.; Georgiou, Ioannis Y.; Kulp, Mark A.; Miner, Michael D.; Smith, Jane M.; Barras, John A.

2010-01-01

During the 2005 hurricane season, the storm surge and wave field associated with Hurricanes Katrina and Rita eroded 527 km2 of wetlands within the Louisiana coastal plain. Low salinity wetlands were preferentially eroded, while higher salinity wetlands remained robust and largely unchanged. Here we highlight geotechnical differences between the soil profiles of high and low salinity regimes, which are controlled by vegetation and result in differential erosion. In low salinity wetlands, a weak zone (shear strength 500–1450 Pa) was observed ∼30 cm below the marsh surface, coinciding with the base of rooting. High salinity wetlands had no such zone (shear strengths > 4500 Pa) and contained deeper rooting. Storm waves during Hurricane Katrina produced shear stresses between 425–3600 Pa, sufficient to cause widespread erosion of the low salinity wetlands. Vegetation in low salinity marshes is subject to shallower rooting and is susceptible to erosion during large magnitude storms; these conditions may be exacerbated by low inorganic sediment content and high nutrient inputs. The dramatic difference in resiliency of fresh versus more saline marshes suggests that the introduction of freshwater to marshes as part of restoration efforts may therefore weaken existing wetlands rendering them vulnerable to hurricanes. PMID:20660777

Groundwater studies in arid areas in Egypt using LANDSAT satellite images

NASA Technical Reports Server (NTRS)

Elshazly, E. M.; Abdelhady, M. A.; Elshazly, M. M.

1977-01-01

Various features are interpreted which have strong bearing on groundwater in the arid environment. These include the nature of geological and lithologic units, structural lineaments, present and old drainage systems, distribution and form of water pools, geomorphologic units, weathering surfaces and other weathering phenomena, desert soils, sand dunes and dune sand accumulations, growths of natural vegetation and agriculture, and salt crusts and other expressions of salinization. There are many impressive examples which illustrate the significance of satellite image interpretation on the regional conditions of groundwater which could be traced and interconnected over several tens or even several hundreds of kilometers. This is especially true in the northern Western Desert of Egypt where ground water issuing from deep strata comes to the surface along ENE-WSW and ESE-WNW fault lines and fracture systems. Another striking example is illustrated by the occurrence of fresh to brackish groundwater on the Mediterranean Sea Coastal Zone of the Western Desert where the groundwater is found in the form of lenses floating on the saline sea water.

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

Effects of salinity on baldcypress seedlings: responses and their relation to salinity tolerance physiological

Treesearch

James A. Allen; Jim L. Chambers; S. Reza Pezeshki

1997-01-01

Taxodium distichum var.distichum) subjected to flooding with saline water were evaluated in this study. Ten of the families were from coastal sites in Louisiana and Alabama, USA that have elevated levels of soil-water salinity. The other five families were from inland, freshwater sites in Louisiana. Seedlings from all families...

Does salinity change determine zooplankton variability in the saline Qarun Lake (Egypt)?

NASA Astrophysics Data System (ADS)

El-Shabrawy, Gamal M.; Anufriieva, Elena V.; Germoush, Mousa O.; Goher, Mohamed E.; Shadrin, Nickolai V.

2015-11-01

Zooplankton and 14 abiotic variables were studied during August 2011 at 10 stations in Lake Qarun, Egypt. Stations with the lowest salinity and highest nutrient concentrations and turbidity were close to the discharge of waters from the El-Bats and El-Wadi drainage systems. A total of 15 holozooplankton species were identified. The salinity in Lake Qarun increased and fluctuated since 1901: 12 g/L in 1901; 8.5 g/L in 1905; 12.0 g/L in 1922; 30.0 g/L in 1985; 38.7 g/L in 1994; 35.3 g/L in 2006, and 33.4 g/L in 2011. The mean concentration of nutrients (nitrate, nitrite and orthophosphate) gradually increased from 35, 0.16 and 0.38 µg/L, respectively, in 1953-1955 to 113, 16.4, and 30.26 µg/L in 2011. From 1999-2003 some decrease of species diversity occurred. Average total zooplankton density was 30 000 ind./m3 in 1974-1977; 356 125 ind./m3 in 1989; 534 000 ind./m3 in 1994-1995; from 965 000 to 1 452 000 ind./m3 in 2006, and 595 000 ind./m3 in 2011. A range of long-term summer salinity variability during the last decades was very similar to a range of salinity spatial variability in summer 2011. There is no significant correlation between zooplankton abundance and salinity in spatial and long-term changes. We conclude that salinity fluctuations since at least 1955 did not directly drive the changes of composition and abundance of zooplankton in the lake. A marine community had formed in the lake, and it continues to change. One of the main drivers of this change is a regular introduction and a pressure of alien species on the existent community. Eutrophication also plays an important role. The introduction of Mnemiopsis leidyi, first reported in 2014, may lead to a start of a new stage of the biotic changes in Lake Qarun, when eutrophication and the population dynamics of this ctenophore will be main drivers of the ecosystem change.

Estuarine turbidity, flushing, salinity, and circulation

NASA Technical Reports Server (NTRS)

Pritchard, D. W.

1972-01-01

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.

Saline Systems highlights for 2005

PubMed Central

2006-01-01

On the 4th of July, 2005, the Saline Systems editorial group launched the new online open access journal, Saline Systems, with BioMed Central as the publisher. The scope of the journal includes both basic and applied research on halophilic organisms and saline environments, from gene systems to ecosystems. The stated goal of the journal is to meet publication needs for researchers working in coastal and inland saline environments and provide an interdisciplinary and readily accessible forum for scientists worldwide. The inaugural volume of the journal contains a significant number of high quality original research papers and reviews on a wide range of relevant topics. At the end of the launch period, from January 1, 2006 onwards, the journal will be introducing article-processing charges to cover the cost of publication. Charges will be partly or completely waived for authors from BioMed Central institutional subscribers and in cases of financial hardship. PMID:16417635

Arctic Sea ice studies with passive microwave satellite observations

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.

1988-01-01

The objectives of this research are: (1) to improve sea ice concentration determinations from passive microwave space observations; (2) to study the role of Arctic polynyas in the production of sea ice and the associated salinization of Arctic shelf water; and (3) to study large scale sea ice variability in the polar oceans. The strategy is to analyze existing data sets and data acquired from both the DMSP SSM/I and recently completed aircraft underflights. Special attention will be given the high resolution 85.5 GHz SSM/I channels for application to thin ice algorithms and processes studies. Analysis of aircraft and satellite data sets is expected to provide a basis for determining the potential of the SSM/I high frequency channels for improving sea ice algorithms and for investigating oceanic processes. Improved sea ice algorithms will aid the study of Arctic coastal polynyas which in turn will provide a better understanding of the role of these polynyas in maintaining the Arctic watermass structure. Analysis of satellite and archived meteorological data sets will provide improved estimates of annual, seasonal and shorter-term sea ice variability.

Salinity: Electrical conductivity and total dissolved solids

USDA-ARS?s Scientific Manuscript database

The measurement of soil salinity is a quantification of the total salts present in the liquid portion of the soil. Soil salinity is important in agriculture because salinity reduces crop yields by reducing the osmotic potential making it more difficult for the plant to extract water, by causing spe...

L-Band Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel; Picard, Ghislain; Champollion, Nicolas

2014-01-01

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GigaHertz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

Aquarius Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface. [29

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel Phillippe; Picard, Ghislain; Champollion, Nicolas

2014-01-01

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GHz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

Continuous salinity and temperature data from san francisco estuary, 19822002: Trends and the salinity-freshwater inflow relationship

USGS Publications Warehouse

Shellenbarger, G.G.; Schoellhamer, D.H.

2011-01-01

The U.S. Geological Survey and other federal and state agencies have been collecting continuous temperature and salinity data, two critical estuarine habitat variables, throughout San Francisco estuary for over two decades. Although this dynamic, highly variable system has been well studied, many questions remain relating to the effects of freshwater inflow and other physical and biological linkages. This study examines up to 20 years of publically available, continuous temperature and salinity data from 10 different San Francisco Bay stations to identify trends in temperature and salinity and quantify the salinityfreshwater inflow relationship. Several trends in the salinity and temperature records were identified, although the high degree of daily and interannual variability confounds the analysis. In addition, freshwater inflow to the estuary has a range of effects on salinity from -0.0020 to -0.0096 (m3 s-1) -1 discharge, depending on location in the estuary and the timescale of analyzed data. Finally, we documented that changes in freshwater inflow to the estuary that are within the range of typical management actions can affect bay-wide salinities by 0.61.4. This study reinforces the idea that multidecadal records are needed to identify trends from decadal changes in water management and climate and, therefore, are extremely valuable. ?? 2011 Coastal Education & Research Foundation.

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data

NASA Astrophysics Data System (ADS)

Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin

2018-03-01

The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With

The U.S. Salinity Laboratory (USDA-ARS) guidelines for assessing multi-scale soil salinity with proximal and remote sensing

USDA-ARS?s Scientific Manuscript database

Soil salinity is a major threat to sustainable agriculture, especially in arid and semi-arid regions. Updated and accurate inventories of salinity in agronomically and environmentally relevant ranges (i.e., <20 dS/m, when salinity is measured as electrical conductivity of the saturation extract, ECe...

Soil salinity decreases global soil organic carbon stocks.

PubMed

Setia, Raj; Gottschalk, Pia; Smith, Pete; Marschner, Petra; Baldock, Jeff; Setia, Deepika; Smith, Jo

2013-11-01

Saline soils cover 3.1% (397 million hectare) of the total land area of the world. The stock of soil organic carbon (SOC) reflects the balance between carbon (C) inputs from plants, and losses through decomposition, leaching and erosion. Soil salinity decreases plant productivity and hence C inputs to the soil, but also microbial activity and therefore SOC decomposition rates. Using a modified Rothamsted Carbon model (RothC) with a newly introduced salinity decomposition rate modifier and a plant input modifier we estimate that, historically, world soils that are currently saline have lost an average of 3.47 tSOC ha(-1) since they became saline. With the extent of saline soils predicted to increase in the future, our modelling suggests that world soils may lose 6.8 Pg SOC due to salinity by the year 2100. Our findings suggest that current models overestimate future global SOC stocks and underestimate net CO2 emissions from the soil-plant system by not taking salinity effects into account. From the perspective of enhancing soil C stocks, however, given the lower SOC decomposition rate in saline soils, salt tolerant plants could be used to sequester C in salt-affected areas. Copyright © 2012 Elsevier B.V. All rights reserved.

Integrated Satellite Control in REIMEI (INDEX) Satellite

NASA Astrophysics Data System (ADS)

Fukuda, Seisuke; Mizuno, Takahide; Sakai, Shin-Ichiro; Fukushima, Yousuke; Saito, Hirobumi

REIMEI/INDEX (INnovative-technology Demonstration EXperiment) is a 70kg class small satellite which the Institute of Space and Astronautical Science, Japan Exploration Agency, ISAS/JAXA, has developed for observation of auroral small-scale dynamics as well as demonstration of advanced satellite technologies. An important engineering mission of REIMEI is integrated satellite control using commercial RISC CPUs with a triple voting system in order to ensure fault-tolerance against radiation hazards. Software modules concerning every satellite function, such as attitude control, data handling, and mission applications, work cooperatively so that highly sophisticated satellite control can be performed. In this paper, after a concept of the integrated satellite control is introduced, the Integrated Controller Unit (ICU) is described in detail. Also unique topics in developing the integrated control system are shown.

Enhancing the USDA Global Crop Assessment Decision Support System Using SMAP Soil Moisture Data

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Mladenova, I. E.; Crow, W. T.; Reynolds, C. A.

2016-12-01

The Foreign Agricultural Services (FAS) is a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected crop supply and demand estimates. Knowledge of the amount of water in the root zone is an essential source of information for the crop analysts as it governs the crop development and crop growth, which in turn determine the end-of-season yields. USDA FAS currently relies on root zone soil moisture (RZSM) estimates generated using the modified two-layer Palmer Model (PM). PM is a simple water-balance hydrologic model that is driven by daily precipitation observations and minimum and maximum temperature data. These forcing data are based on ground meteorological station measurements from the World Meteorological Organization (WMO), and gridded weather data from the former U.S. Air Force Weather Agency (AFWA), currently called U.S. Air Force 557th Weather Wing. The PM was extended by adding a data assimilation (DA) unit that provides the opportunity to routinely ingest satellite-based soil moisture observations. This allows us to adjust for precipitation-related inaccuracies and enhance the quality of the PM soil moisture estimates. The current operational DA system is based on a 1-D Ensample Kalman Filter approach and relies on observations obtained from the Soil Moisture Ocean Salinity Mission (SMOS). Our talk will demonstrate the value of assimilating two satellite products (i.e. a passive and active) and discuss work that is done in preparation for ingesting soil moisture observations from the Soil Moisture Active Passive (SMAP) mission.

Implementing DOIs for Oceanographic Satellite Data at PO.DAAC

NASA Astrophysics Data System (ADS)

Hausman, J.; Tauer, E.; Chung, N.; Chen, C.; Moroni, D. F.

2013-12-01

The Physical Oceanographic Distributed Active Archive Center (PO.DAAC) is NASA's archive for physical oceanographic satellite data. It distributes over 500 datasets from gravity, ocean wind, sea surface topography, sea ice, ocean currents, salinity, and sea surface temperature satellite missions. A dataset is a collection of granules/files that share the same mission/project, versioning, processing level, spatial, and temporal characteristics. The large number of datasets is partially due to the number of satellite missions, but mostly because a single satellite mission typically has multiple versions or even temporal and spatial resolutions of data. As a result, a user might mistake one dataset for a different dataset from the same satellite mission. Due to the PO.DAAC'S vast variety and volume of data and growing requirements to report dataset usage, it has begun implementing DOIs for the datasets it archives and distributes. However, this was not as simple as registering a name for a DOI and providing a URL. Before implementing DOIs multiple questions needed to be answered. What are the sponsor and end-user expectations regarding DOIs? At what level does a DOI get assigned (dataset, file/granule)? Do all data get a DOI, or only selected data? How do we create a DOI? How do we create landing pages and manage them? What changes need to be made to the data archive, life cycle policy and web portal to accommodate DOIs? What if the data also exists at another archive and a DOI already exists? How is a DOI included if the data were obtained via a subsetting tool? How does a researcher or author provide a unique, definitive reference (standard citation) for a given dataset? This presentation will discuss how these questions were answered through changes in policy, process, and system design. Implementing DOIs is not a trivial undertaking, but as DOIs are rapidly becoming the de facto approach, it is worth the effort. Researchers have historically referenced the source

Reconstructing Past Ocean Salinity ((delta)18Owater)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guilderson, T P; Pak, D K

2005-11-23

Temperature and salinity are two of the key properties of ocean water masses. The distribution of these two independent but related characteristics reflects the interplay of incoming solar radiation (insolation) and the uneven distribution of heat loss and gain by the ocean, with that of precipitation, evaporation, and the freezing and melting of ice. Temperature and salinity to a large extent, determine the density of a parcel of water. Small differences in temperature and salinity can increase or decrease the density of a water parcel, which can lead to convection. Once removed from the surface of the ocean where 'local'more » changes in temperature and salinity can occur, the water parcel retains its distinct relationship between (potential) temperature and salinity. We can take advantage of this 'conservative' behavior where changes only occur as a result of mixing processes, to track the movement of water in the deep ocean (Figure 1). The distribution of density in the ocean is directly related to horizontal pressure gradients and thus (geostrophic) ocean currents. During the Quaternary when we have had systematic growth and decay of large land based ice sheets, salinity has had to change. A quick scaling argument following that of Broecker and Peng [1982] is: the modern ocean has a mean salinity of 34.7 psu and is on average 3500m deep. During glacial maxima sea level was on the order of {approx}120m lower than present. Simply scaling the loss of freshwater (3-4%) requires an average increase in salinity a similar percentage or to {approx}35.9psu. Because much of the deep ocean is of similar temperature, small changes in salinity have a large impact on density, yielding a potentially different distribution of water masses and control of the density driven (thermohaline) ocean circulation. It is partly for this reason that reconstructions of past salinity are of interest to paleoceanographers.« less

Salinity Energy.

ERIC Educational Resources Information Center

Schmitt, Walter R.

1987-01-01

Discussed are the costs of deriving energy from the earth's natural reserves of salt. Argues that, as fossil fuel supplies become more depleted in the future, the environmental advantages of salinity power may prove to warrant its exploitation. (TW)

Salinity management in the Rio Grande Bosque

Treesearch

Jan M. H. Hendrickx; J. Bruce J. Harrison; Jelle Beekma; Graciela Rodriguez-Marin

1999-01-01

This paper discusses management options for salinity control in the Rio Grande Bosque. First, salt sources are identified and quantified. Capillary rise of ground water is the most important cause for soil salinization in the bosque. Next, a riparian salt balance is presented to explain the different mechanisms for soil salinization. Finally, the advantages and...

Satellite-tracking and earth-dynamics research programs. [NASA Programs on satellite orbits and satellite ground tracks of geodetic satellites

NASA Technical Reports Server (NTRS)

1974-01-01

Observations and research progress of the Smithsonian Astrophysical Observatory are reported. Satellite tracking networks (ground stations) are discussed and equipment (Baker-Nunn cameras) used to observe the satellites is described. The improvement of the accuracy of a laser ranging system of the ground stations is discussed. Also, research efforts in satellite geodesy (tides, gravity anomalies, plate tectonics) is discussed. The use of data processing for geophysical data is examined, and a data base for the Earth and Ocean Physics Applications Program is proposed. Analytical models of the earth's motion (computerized simulation) are described and the computation (numerical integration and algorithms) of satellite orbits affected by the earth's albedo, using computer techniques, is also considered. Research efforts in the study of the atmosphere are examined (the effect of drag on satellite motion), and models of the atmosphere based on satellite data are described.

Multi-sensor data processing method for improved satellite retrievals

NASA Astrophysics Data System (ADS)

Fan, Xingwang

2017-04-01

Satellite remote sensing has provided massive data that improve the overall accuracy and extend the time series of environmental studies. In reflective solar bands, satellite data are related to land surface properties via radiative transfer (RT) equations. These equations generally include sensor-related (calibration coefficients), atmosphere-related (aerosol optical thickness) and surface-related (surface reflectance) parameters. It is an ill-posed problem to solve three parameters with only one RT equation. Even if there are two RT equations (dual-sensor data), the problem is still unsolvable. However, a robust solution can be obtained when any two parameters are known. If surface and atmosphere are known, sensor intercalibration can be performed. For example, the Advanced Very High Resolution Radiometer (AVHRR) was calibrated to the MODerate-resolution Imaging Spectroradiometer (MODIS) in Fan and Liu (2014) [Fan, X., and Liu, Y. (2014). Quantifying the relationship between intersensor images in solar reflective bands: Implications for intercalibration. IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7727-7737.]. If sensor and surface are known, atmospheric data can be retrieved. For example, aerosol data were retrieved using tandem TERRA and AQUA MODIS images in Fan and Liu (2016a) [Fan, X., and Liu, Y. (2016a). Exploiting TERRA-AQUA MODIS relationship in the reflective solar bands for aerosol retrieval. Remote Sensing, 8(12), 996.]. If sensor and atmosphere are known, data consistency can be obtained. For example, Normalized Difference Vegetation Index (NDVI) data were intercalibrated among coarse-resolution sensors in Fan and Liu (2016b) [Fan, X., and Liu, Y. (2016b). A global study of NDVI difference among moderate-resolution satellite sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 121, 177-191.], and among fine-resolution sensors in Fan and Liu (2017) [Fan, X., and Liu, Y. (2017). A generalized model for intersensor NDVI

Salinity affects behavioral thermoregulation in a marine decapod crustacean

NASA Astrophysics Data System (ADS)

Reiser, Stefan; Mues, Annika; Herrmann, Jens-Peter; Eckhardt, André; Hufnagl, Marc; Temming, Axel

2017-10-01

Thermoregulation in aquatic ectotherms is a complex behavioral pattern that is affected by various biotic and abiotic factors with one being salinity. Especially in coastal and estuarine habitats, altering levels of salinity involve osmoregulatory adjustments that affect total energy budgets and may influence behavioral responses towards temperature. To examine the effect of salinity on behavioral thermoregulation in a marine evertebrate ectotherm, we acclimated juvenile and sub-adult common brown shrimp (Crangon crangon, L.) to salinities of 10, 20 and 30 PSU and investigated their thermal preference in an annular chamber system using the gravitational method for temperature preference determination. Thermal preference of individual brown shrimp was considerably variable and brown shrimp selected a wide range of temperatures in each level of salinity as well as within individual experimental trials. However, salinity significantly affected thermal preference with the shrimp selecting higher temperatures at 10 and 20 PSU when compared to 30 PSU of salinity. Body size had no effect on thermal selection and did not interact with salinity. Temperature preference differed by sex and male shrimp selected significantly higher temperatures at 10 PSU when compared to females. The results show that salinity strongly affects thermal selection in brown shrimp and confirms the strong interrelation of temperature and salinity on seasonal migratory movements that has been previously derived from observations in the field. In the field, however, it remains unclear whether salinity drives thermal selection or whether changes in temperature modify salinity preference.

How can present and future satellite missions support scientific studies that address ocean acidification?

USGS Publications Warehouse

Salisbury, Joseph; Vandemark, Douglas; Jonsson, Bror; Balch, William; Chakraborty, Sumit; Lohrenz, Steven; Chapron, Bertrand; Hales, Burke; Mannino, Antonio; Mathis, Jeremy T.; Reul, Nicolas; Signorini, Sergio; Wanninkhof, Rik; Yates, Kimberly K.

2016-01-01

Space-based observations offer unique capabilities for studying spatial and temporal dynamics of the upper ocean inorganic carbon cycle and, in turn, supporting research tied to ocean acidification (OA). Satellite sensors measuring sea surface temperature, color, salinity, wind, waves, currents, and sea level enable a fuller understanding of a range of physical, chemical, and biological phenomena that drive regional OA dynamics as well as the potentially varied impacts of carbon cycle change on a broad range of ecosystems. Here, we update and expand on previous work that addresses the benefits of space-based assets for OA and carbonate system studies. Carbonate chemistry and the key processes controlling surface ocean OA variability are reviewed. Synthesis of present satellite data streams and their utility in this arena are discussed, as are opportunities on the horizon for using new satellite sensors with increased spectral, temporal, and/or spatial resolution. We outline applications that include the ability to track the biochemically dynamic nature of water masses, to map coral reefs at higher resolution, to discern functional phytoplankton groups and their relationships to acid perturbations, and to track processes that contribute to acid variation near the land-ocean interface.

Is bacteriostatic saline superior to normal saline as an echocardiographic contrast agent?

PubMed

Cardozo, Shaun; Gunasekaran, Prasad; Patel, Hena; McGorisk, Timothy; Toosi, Mehrdad; Faraz, Haroon; Zalawadiya, Sandip; Alesh, Issa; Kottam, Anupama; Afonso, Luis

2014-12-01

Objective data on the performance characteristics and physical properties of commercially available saline formulations [normal saline (NS) vs. bacteriostatic normal saline (bNS)] are sparse. This study sought to compare the in vitro physical properties and in vivo characteristics of two commonly employed echocardiographic saline contrast agents in an attempt to assess superiority. Nineteen patients undergoing transesophageal echocardiograms were each administered agitated regular NS and bNS injections in random order and in a blinded manner according to a standardized protocol. Video time-intensity (TI) curves were constructed from a representative region of interest, placed paraseptally within the right atrium, in the bicaval view. TI curves were analyzed for maximal plateau acoustic intensity (Vmax, dB) and dwell time (DT, s), defined as time duration between onset of Vmax and decay of video intensity below clinically useful levels, reflecting the duration of homogenous opacification of the right atrium. To further characterize the physical properties of the bubbles in vitro, fixed aliquots of similarly agitated saline were injected into a glass well slide-cover slip assembly and examined using an optical microscope to determine bubble diameter in microns (µm) and concentration [bubble count/high power field (hpf)]. A higher acoustic intensity (a less negative dB level), higher bubble concentration and longer DT were considered properties of a superior contrast agent. For statistical analysis, a paired t test was conducted to evaluate the differences in means of Vmax and DT. Compared to NS, bNS administration was associated with superior opacification (video intensity -8.69 ± 4.7 vs. -10.46 ± 4.1 dB, P = 0.002), longer DT (17.3 ± 6.1 vs. 10.2 ± 3.7 s) in vivo and smaller mean bubble size (43.4 vs. 58.6 μm) and higher bubble concentration (1,002 vs. 298 bubble/hpf) in vitro. bNS provides higher intensity and more sustained opacification of the right atrium

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

NASA Technical Reports Server (NTRS)

Yueh, Simon H.; Chaubell, Mario J.

2012-01-01

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

Fructans of the saline world.

PubMed

Kırtel, Onur; Versluys, Maxime; Van den Ende, Wim; Öner, Ebru Toksoy

2018-06-20

Saline and hypersaline environments make up the largest ecosystem on earth and the organisms living in such water-restricted environments have developed unique ways to cope with high salinity. As such these organisms not only carry significant industrial potential in a world where freshwater supplies are rapidly diminishing, but they also shed light upon the origins and extremes of life. One largely overlooked and potentially important feature of many salt-loving organisms is their ability to produce fructans, fructose polymers widely found in various mesophilic Eubacteria and plants, with potential functions as storage carbohydrates, aiding stress tolerance, and acting as virulence factors or signaling molecules. Intriguingly, within the whole archaeal domain of life, Archaea possessing putative fructan biosynthetic enzymes were found to belong to the extremely halophilic class of Halobacteria only, indicating a strong, yet unexplored link between the fructan syndrome and salinity. In fact, this link may indeed lead to novel strategies in fighting the global salinization problem. Hence this review explores the unknown world of fructanogenic salt-loving organisms, where water scarcity is the main stress factor for life. Within this scope, prokaryotes and plants of the saline world are discussed in detail, with special emphasis on their salt adaptation mechanisms, the potential roles of fructans and fructosyltransferase enzymes in adaptation and survival as well as future aspects for all fructanogenic salt-loving domains of life. Copyright © 2018. Published by Elsevier Inc.

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, Tong

2017-04-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatiotemporal scales are important to capability assessment, future mission design, and applications to study oceanic phenomena of different spatiotemporal scales. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in late 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1˚ x1˚ , 3˚ x3˚ , and 10˚ x10˚ . Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10˚ x10˚ ) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space. The spatial distribution of the uncertainty estimates is

Predicting Near Real-Time Inundation Occurrence from Complimentary Satellite Microwave Brightness Temperature Observations

NASA Astrophysics Data System (ADS)

Fisher, C. K.; Pan, M.; Wood, E. F.

2017-12-01

Throughout the world, there is an increasing need for new methods and data that can aid decision makers, emergency responders and scientists in the monitoring of flood events as they happen. In many regions, it is possible to examine the extent of historical and real-time inundation occurrence from visible and infrared imagery provided by sensors such as MODIS or the Landsat TM; however, this is not possible in regions that are densely vegetated or are under persistent cloud cover. In addition, there is often a temporal mismatch between the sampling of a particular sensor and a given flood event, leading to limited observations in near real-time. As a result, there is a need for alternative methods that take full advantage of complimentary remotely sensed data sources, such as available microwave brightness temperature observations (e.g., SMAP, SMOS, AMSR2, AMSR-E, and GMI), to aid in the estimation of global flooding. The objective of this work was to develop a high-resolution mapping of inundated areas derived from multiple satellite microwave sensor observations with a daily temporal resolution. This system consists of first retrieving water fractions from complimentary microwave sensors (AMSR-2 and SMAP) which may spatially and temporally overlap in the region of interest. Using additional information in a Random Forest classifier, including high resolution topography and multiple datasets of inundated area (both historical and empirical), the resulting retrievals are spatially downscaled to derive estimates of the extent of inundation at a scale relevant to management and flood response activities ( 90m or better) instead of the relatively coarse resolution water fractions, which are limited by the microwave sensor footprints ( 5-50km). Here we present the training and validation of this method for the 2015 floods that occurred in Houston, Texas. Comparing the predicted inundation against historical occurrence maps derived from the Landsat TM record and MODIS

Satellite Conferences

Science.gov Websites

NOAA- NESDIS Banner Satellite Conferences Collage images of earth, POES and GOES satellites in space HOME Call for Poster Abstracts DOC Logo NOAA Logo Satellite Conferences Welcome to the website for National Oceanic and Atmospheric Administration (NOAA) Satellite Conferences; past, present and future

First micro-satellite and new enhanced small satellite series in DFH Satellite Co. Ltd.

NASA Astrophysics Data System (ADS)

Zhang, Xiaomin; Xie, Bin; Dai, Shoulun; Zhang, Weiwen; Hu, Gefeng; Lan, Ding

2007-06-01

As one important department of CAST (Chinese Academy of Space Technology), with responsibility for small and micro-satellite development, DFH Satellite Co. Ltd. (DFHSat) manufactured and launched six small satellites from 2000 to 2004. Nowadays, DFHSat is developing micro-satellite and new enhanced small satellite series. The first micro-satellite as a basic type is named HummerSat-1. HummerSat-1 is three-axis stabilized with orbit control capability. Information and power control are implemented through an on-board network, GaAs solar cell and Li-ion battery are adopted to obtain and storage power, S-band TT&C and data transmission works are used. The payload of HummerSat-1 has a weight of 60 kg and power consumption of 200 W. The enhanced small satellite series based on technology of HummerSat-1 is planned by DFHSat. It would be aiming to form a continuative product spectrum of 80-200 kg. The enhanced series is focused on satisfying different missions, including earth remote sensing, communication, science exploration, etc.

Genome interrogation for novel salinity tolerant Arabidopsis mutants.

PubMed

van Tol, Niels; Pinas, Johan; Schat, Henk; Hooykaas, Paul J J; van der Zaal, Bert J

2016-12-01

Soil salinity is becoming an increasingly large problem in agriculture. In this study, we have investigated whether a capacity to withstand salinity can be induced in the salinity sensitive plant species Arabidopsis thaliana, and whether it can be maintained in subsequent generations. To this end, we have used zinc finger artificial transcription factor (ZF-ATFs) mediated genome interrogation. Already within a relatively small collection Arabidopsis lines expressing ZF-ATFs, we found 41 lines that were tolerant to 100 mM NaCl. Furthermore, ZF-ATF encoding gene constructs rescued from the most strongly salinity tolerant lines were indeed found to act as dominant and heritable agents for salinity tolerance. Altogether, our data provide evidence that a silent capacity to withstand normally lethal levels of salinity exists in Arabidopsis and can be evoked relatively easily by in trans acting transcription factors like ZF-ATFs. © 2016 John Wiley & Sons Ltd.

The density-salinity relation of standard seawater

NASA Astrophysics Data System (ADS)

Schmidt, Hannes; Seitz, Steffen; Hassel, Egon; Wolf, Henning

2018-01-01

The determination of salinity by means of electrical conductivity relies on stable salt proportions in the North Atlantic Ocean, because standard seawater, which is required for salinometer calibration, is produced from water of the North Atlantic. To verify the long-term stability of the standard seawater composition, it was proposed to perform measurements of the standard seawater density. Since the density is sensitive to all salt components, a density measurement can detect any change in the composition. A conversion of the density values to salinity can be performed by means of a density-salinity relation. To use such a relation with a target uncertainty in salinity comparable to that in salinity obtained from conductivity measurements, a density measurement with an uncertainty of 2 g m-3 is mandatory. We present a new density-salinity relation based on such accurate density measurements. The substitution measurement method used is described and density corrections for uniform isotopic and chemical compositions are reported. The comparison of densities calculated using the new relation with those calculated using the present reference equations of state TEOS-10 suggests that the density accuracy of TEOS-10 (as well as that of EOS-80) has been overestimated, as the accuracy of some of its underlying density measurements had been overestimated. The new density-salinity relation may be used to verify the stable composition of standard seawater by means of routine density measurements.

Salinity Improves Performance and Alters Distribution of Soybean Aphids.

PubMed

Eichele-Nelson, Jaclyn; DeSutter, Thomas; Wick, Abbey F; Harmon, Erin L; Harmon, Jason P

2018-05-24

We know numerous abiotic factors strongly influence crop plants. Yet we often know much less about abiotic effects on closely interacting organisms including herbivorous insects. This lack of a whole-system perspective may lead to underestimating the threats from changing factors. High soil salinity is a specific example that we know threatens crop plants in many places, but we need to know much more about how other organisms are also affected. We investigated how salinity affects the soybean aphid (SBA; Aphis glycines Matsumura; Hemiptera: Aphididae) on soybean plants (Glycine max [L.] Merr.; Fabales: Fabaceae) grown across a range of saline conditions. We performed four complementary greenhouse experiments to understand different aspects of how salinity might affect SBA. We found that as salinity increased both population size and fecundity of SBA increased across electrical conductivity values ranging from 0.84 to 8.07 dS m-1. Tracking individual aphids we also found they lived longer and produced more offspring in high saline conditions compared to the control. Moreover, we found that salinity influenced aphid distribution such that when given the chance aphids accumulated more on high-salinity plants. These results suggest that SBA could become a larger problem in areas with higher salinity and that those aphids may exacerbate the negative effects of salinity for soybean production.

Simplified spatiotemporal electromagnetic induction - salinity multi-field calibration

USDA-ARS?s Scientific Manuscript database

Salinity-affected farmlands are common in arid and semi-arid regions. To assure long-term sustainability of farming practices in these areas, soil salinity (ECe) should be routinely mapped and monitored. Salinity can be measured through soil sampling directed by geospatial measurements of apparent s...

Pore fluids and the LGM ocean salinity-Reconsidered

NASA Astrophysics Data System (ADS)

Wunsch, Carl

2016-03-01

Pore fluid chlorinity/salinity data from deep-sea cores related to the salinity maximum of the last glacial maximum (LGM) are analyzed using estimation methods deriving from linear control theory. With conventional diffusion coefficient values and no vertical advection, results show a very strong dependence upon initial conditions at -100 ky. Earlier inferences that the abyssal Southern Ocean was strongly salt-stratified in the LGM with a relatively fresh North Atlantic Ocean are found to be consistent within uncertainties of the salinity determination, which remain of order ±1 g/kg. However, an LGM Southern Ocean abyss with an important relative excess of salt is an assumption, one not required by existing core data. None of the present results show statistically significant abyssal salinity values above the global average, and results remain consistent, apart from a general increase owing to diminished sea level, with a more conventional salinity distribution having deep values lower than the global mean. The Southern Ocean core does show a higher salinity than the North Atlantic one on the Bermuda Rise at different water depths. Although much more sophisticated models of the pore-fluid salinity can be used, they will only increase the resulting uncertainties, unless considerably more data can be obtained. Results are consistent with complex regional variations in abyssal salinity during deglaciation, but none are statistically significant.

Salinity signature of the Pacific Decadal Oscillation

NASA Astrophysics Data System (ADS)

Overland, James E.; Salo, Sigrid; Adams, Jennifer Miletta

Three sites in the North Pacific have temperature and salinity observations in most months for several years before and after 1977. The Gulf of Alaska station (57°N, 148°W) showed a 2°C warming and a 0.6 freshening in salinity at 10 m depth in the 1980s compared to the 1970s. OWS PAPA (50°N, 145°W) and PAPA line station 7 (49.1°N, 132.4°W) show warming of 0.6°C and 0.9°C, with no major salinity change. The decrease in density and increase in stratification in the Gulf of Alaska after 1977 corresponds primarily to a decrease in salinity in the upper 150 m. We propose that while the Pacific Decadal Oscillation has an east/west character in temperature, the salinity signature will have a NNW/SSE character, similar to the pattern of interannual variability in precipitation.

Salinity tolerance ecophysiology of Equisetum giganteum in South America: a study of 11 sites providing a natural gradient of salinity stress

PubMed Central

Husby, Chad E.; Delatorre, José; Oreste, Vittorio; Oberbauer, Steven F.; Palow, Danielle T.; Novara, Lázaro; Grau, Alfredo

2011-01-01

Background and aims The basic set of adaptations necessary for salinity tolerance in vascular plants remains unknown. Although much has been published on salinity stress, almost all studies deal with spermatophytes. Studies of salinity tolerance in pteridophytes are relatively rare but hold promise for revealing the fundamental adaptations that all salt-tolerant vascular plants may share. The most basal pteridophytes to exhibit salinity tolerance are members of the genus Equisetum, including the giant horsetail, Equisetum giganteum, the only pteridophyte to occur in salinity-affected regions of the Atacama Desert valleys of northern Chile. Here it can constitute a significant vegetation component, forming dense stands of shoots >4 m high. Methodology Physiological parameters (stomatal conductances; efficiency of photosystem II; sap osmotic potential) were measured in E. giganteum populations in northern Chile across a range of groundwater salinities at 11 sites. In addition, Na, K, electrical conductivity and total plant water potential were measured in the plants and groundwater from each site. Principal results Equisetum giganteum exhibits similar stomatal conductances and photochemical efficiencies of photosystem II across a wide range of groundwater salinities. It lowers cell sap osmotic potential with increasing salinity and produces positive root pressure, as evidenced by guttation, at the full range of salinities experienced in the Atacama Desert. Equisetum giganteum maintains low Na concentrations in its xylem fluid and cell sap when soil water Na is high. It also maintains high K/Na ratios in xylem fluid and cell sap when soil water has low K/Na ratios. Conclusions Equisetum giganteum is well adapted to salinity stress. Efficient K uptake and Na exclusion are important adaptations and closely similar to those of the facultative halophyte fern Acrostichum aureum. PMID:22476492

Initiation of small-satellite formations via satellite ejector

NASA Astrophysics Data System (ADS)

McMullen, Matthew G

Small satellites can be constructed at a fraction of the cost of a full-size satellite. One full-size satellite can be replaced with a multitude of small satellites, offering expanded area coverage through formation flight. However, the shortcoming to the smaller size is usually a lack of thrusting capabilities. Furthermore, current designs for small satellite deployment mechanisms are only capable of love deployment velocities (on the order of meters per second). Motivated to address this shortcoming, a conceived satellite ejector would offer a significant orbit change by ejecting the satellite at higher deployment velocities (125-200 m/s). Focusing on the applications of the ejector, it is sought to bridge the gap in prior research by offering a method to initiate formation flight. As a precursor to the initiation, the desired orbit properties to initiate the formation are specified in terms of spacing and velocity change vector. From this, a systematic method is developed to find the relationship among velocity change vector, the desired orbit's orientation, and the spacing required to initiate the formation.

Potential role of salinity in ENSO and MJO predictions

NASA Astrophysics Data System (ADS)

Zhu, J.; Kumar, A.; Murtugudde, R. G.; Xie, P.

2017-12-01

Studies have suggested that ocean salinity can vary in response to ENSO and MJO. For example, during an El Niño event, sea surface salinity decreases in the western and central equatorial Pacific, as a result of zonal advection of low salinity water by anomalous eastward surface currents, and to a lesser extent as a result of a rainfall excess associated with atmospheric convection and warm water displacements. However, the effect of salinity on ENSO and MJO evolutions and their forecasts has been less explored. In this analysis, we explored the potential role of salinity in ENSO and MJO predictions by conducting sensitivity experiments with NCEP CFSv2. Firstly, two forecasts experiments are conducted to explore its effect on ENSO predictions, in which the interannual variability of salinity in the ocean initial states is either included or excluded. Comparisons suggested that the salinity variability is essential to correctly forecast the 2007/08 La Niña starting from April 2007. With realistic salinity initial states, the tendency to decay of the subsurface cold condition during the spring and early summer 2007 was interrupted by positive salinity anomalies in the upper central Pacific, which working together with the Bjerknes positive feedback, contributed to the development of the La Niña event. Our study suggests that ENSO forecasts will benefit from more accurate sustained salinity observations having large-scale spatial coverage. We also assessed the potential role of salinity in MJO by evaluating a long coupled free run that has a relatively realistic MJO simulation and a set of predictability experiment, both based on CFSv2. Diagnostics of the free run suggest that, while the intraseasonal SST variations lead convections by a quarter cycle, they are almost in phase only with changes in barrier layer thickness, thereby suggesting an active role of salinity on SST. Its effect on MJO predictions is further explored by controlling the surface salinity

Growth responses of the mangrove Avicennia marina to salinity: development and function of shoot hydraulic systems require saline conditions

PubMed Central

Nguyen, Hoa T.; Stanton, Daniel E.; Schmitz, Nele; Farquhar, Graham D.; Ball, Marilyn C.

2015-01-01

Background and Aims Halophytic eudicots are characterized by enhanced growth under saline conditions. This study combines physiological and anatomical analyses to identify processes underlying growth responses of the mangrove Avicennia marina to salinities ranging from fresh- to seawater conditions. Methods Following pre-exhaustion of cotyledonary reserves under optimal conditions (i.e. 50 % seawater), seedlings of A. marina were grown hydroponically in dilutions of seawater amended with nutrients. Whole-plant growth characteristics were analysed in relation to dry mass accumulation and its allocation to different plant parts. Gas exchange characteristics and stable carbon isotopic composition of leaves were measured to evaluate water use in relation to carbon gain. Stem and leaf hydraulic anatomy were measured in relation to plant water use and growth. Key Results Avicennia marina seedlings failed to grow in 0–5 % seawater, whereas maximal growth occurred in 50–75 % seawater. Relative growth rates were affected by changes in leaf area ratio (LAR) and net assimilation rate (NAR) along the salinity gradient, with NAR generally being more important. Gas exchange characteristics followed the same trends as plant growth, with assimilation rates and stomatal conductance being greatest in leaves grown in 50–75 % seawater. However, water use efficiency was maintained nearly constant across all salinities, consistent with carbon isotopic signatures. Anatomical studies revealed variation in rates of development and composition of hydraulic tissues that were consistent with salinity-dependent patterns in water use and growth, including a structural explanation for low stomatal conductance and growth under low salinity. Conclusions The results identified stem and leaf transport systems as central to understanding the integrated growth responses to variation in salinity from fresh- to seawater conditions. Avicennia marina was revealed as an obligate halophyte

Sea level change since 2005: importance of salinity

NASA Astrophysics Data System (ADS)

Llovel, W.; Purkey, S.; Meyssignac, B.; Kolodziejczyk, N.; Blazquez, A.; Bamber, J. L.

2017-12-01

Sea level rise is one of the most important consequences of the actual global warming. Global mean sea level has been rising at a faster rate since 1993 (over the satellite altimetry era) than previous decades. This rise is expected to accelerate over the coming decades and century. At global scale, sea level rise is caused by a combination of freshwater increase from land ice melting and land water changes (mass component) and ocean warming (thermal expansion). Estimating the causes is of great interest not only to understand the past sea level changes but also to validate projections based on climate models. In this study, we investigate the global mass contribution to recent sea level changes with an alternative approach by estimating the global ocean freshening. For that purpose, we consider the unprecedented amount of salinity measurements from Argo floats for the past decade (2005-2015). We compare our results to the ocean mass inferred by GRACE data and based on a sea level budget approach. Our results bring new constrains on the global water cycle (ocean freshening) and energy budget (ocean warming) as well as on the global ocean mass directly inferred from GRACE data.

Prediction of plant vulnerability to salinity increase in a coastal ecosystem by stable isotopic composition (δ18O) of plant stem water: a model study

USGS Publications Warehouse

Zhai, Lu; Jiang, Jiang; DeAngelis, Donald L.; Sternberg, Leonel d.S.L

2016-01-01

Sea level rise and the subsequent intrusion of saline seawater can result in an increase in soil salinity, and potentially cause coastal salinity-intolerant vegetation (for example, hardwood hammocks or pines) to be replaced by salinity-tolerant vegetation (for example, mangroves or salt marshes). Although the vegetation shifts can be easily monitored by satellite imagery, it is hard to predict a particular area or even a particular tree that is vulnerable to such a shift. To find an appropriate indicator for the potential vegetation shift, we incorporated stable isotope 18O abundance as a tracer in various hydrologic components (for example, vadose zone, water table) in a previously published model describing ecosystem shifts between hammock and mangrove communities in southern Florida. Our simulations showed that (1) there was a linear relationship between salinity and the δ18O value in the water table, whereas this relationship was curvilinear in the vadose zone; (2) hammock trees with higher probability of being replaced by mangroves had higher δ18O values of plant stem water, and this difference could be detected 2 years before the trees reached a tipping point, beyond which future replacement became certain; and (3) individuals that were eventually replaced by mangroves from the hammock tree population with a 50% replacement probability had higher stem water δ18O values 3 years before their replacement became certain compared to those from the same population which were not replaced. Overall, these simulation results suggest that it is promising to track the yearly δ18O values of plant stem water in hammock forests to predict impending salinity stress and mortality.

Salinity anomaly as a trigger for ENSO events

PubMed Central

Zhu, Jieshun; Huang, Bohua; Zhang, Rong-Hua; Hu, Zeng-Zhen; Kumar, Arun; Balmaseda, Magdalena A.; Marx, Lawrence; Kinter III, James L.

2014-01-01

According to the classical theories of ENSO, subsurface anomalies in ocean thermal structure are precursors for ENSO events and their initial specification is essential for skillful ENSO forecast. Although ocean salinity in the tropical Pacific (particularly in the western Pacific warm pool) can vary in response to El Niño events, its effect on ENSO evolution and forecasts of ENSO has been less explored. Here we present evidence that, in addition to the passive response, salinity variability may also play an active role in ENSO evolution, and thus important in forecasting El Niño events. By comparing two forecast experiments in which the interannually variability of salinity in the ocean initial states is either included or excluded, the salinity variability is shown to be essential to correctly forecast the 2007/08 La Niña starting from April 2007. With realistic salinity initial states, the tendency to decay of the subsurface cold condition during the spring and early summer 2007 was interrupted by positive salinity anomalies in the upper central Pacific, which working together with the Bjerknes positive feedback, contributed to the development of the La Niña event. Our study suggests that ENSO forecasts will benefit from more accurate salinity observations with large-scale spatial coverage. PMID:25352285

Salinity anomaly as a trigger for ENSO events.

PubMed

Zhu, Jieshun; Huang, Bohua; Zhang, Rong-Hua; Hu, Zeng-Zhen; Kumar, Arun; Balmaseda, Magdalena A; Marx, Lawrence; Kinter, James L

2014-10-29

According to the classical theories of ENSO, subsurface anomalies in ocean thermal structure are precursors for ENSO events and their initial specification is essential for skillful ENSO forecast. Although ocean salinity in the tropical Pacific (particularly in the western Pacific warm pool) can vary in response to El Niño events, its effect on ENSO evolution and forecasts of ENSO has been less explored. Here we present evidence that, in addition to the passive response, salinity variability may also play an active role in ENSO evolution, and thus important in forecasting El Niño events. By comparing two forecast experiments in which the interannually variability of salinity in the ocean initial states is either included or excluded, the salinity variability is shown to be essential to correctly forecast the 2007/08 La Niña starting from April 2007. With realistic salinity initial states, the tendency to decay of the subsurface cold condition during the spring and early summer 2007 was interrupted by positive salinity anomalies in the upper central Pacific, which working together with the Bjerknes positive feedback, contributed to the development of the La Niña event. Our study suggests that ENSO forecasts will benefit from more accurate salinity observations with large-scale spatial coverage.

Hydraulic redistribution: limitations for plants in saline soils.

PubMed

Bazihizina, Nadia; Veneklaas, Erik J; Barrett-Lennard, Edward G; Colmer, Timothy D

2017-10-01

Hydraulic redistribution (HR), the movement of water from wet to dry patches in the soil via roots, occurs in different ecosystems and plant species. By extension of the principle that HR is driven by gradients in soil water potential, HR has been proposed to occur for plants in saline soils. Despite the inherent spatial patchiness and salinity gradients in these soils, the lack of direct evidence of HR in response to osmotic gradients prompted us to ask the question: are there physical or physiological constraints to HR for plants in saline environments? We propose that build-up of ions in the root xylem sap and in the leaf apoplast, with the latter resulting in a large predawn disequilibrium of water potential in shoots compared with roots and soil, would both impede HR. We present a conceptual model that illustrates how processes in root systems in heterogeneous salinity with water potential gradients, even if equal to those in non-saline soils, will experience a dampened magnitude of water potential gradients in the soil-plant continuum, minimizing or preventing HR. Finally, we provide an outlook for understanding the relevance of HR for plants in saline environments by addressing key research questions on plant salinity tolerance. © 2017 John Wiley & Sons Ltd.

Plant responses to heterogeneous salinity: growth of the halophyte Atriplex nummularia is determined by the root-weighted mean salinity of the root zone

PubMed Central

Bazihizina, Nadia

2012-01-01

Soil salinity is generally spatially heterogeneous, but our understanding of halophyte physiology under such conditions is limited. The growth and physiology of the dicotyledonous halophyte Atriplex nummularia was evaluated in split-root experiments to test whether growth is determined by: (i) the lowest; (ii) the highest; or (iii) the mean salinity of the root zone. In two experiments, plants were grown with uniform salinities or horizontally heterogeneous salinities (10–450mM NaCl in the low-salt side and 670mM in the high-salt side, or 10mM NaCl in the low-salt side and 500–1500mM in the high-salt side). The combined data showed that growth and gas exchange parameters responded most closely to the root-weighted mean salinity rather than to the lowest, mean, or highest salinity in the root zone. In contrast, midday shoot water potentials were determined by the lowest salinity in the root zone, consistent with most water being taken from the least negative water potential source. With uniform salinity, maximum shoot growth was at 120–230mM NaCl; ~90% of maximum growth occurred at 10mM and 450mM NaCl. Exposure of part of the roots to 1500mM NaCl resulted in an enhanced (+40%) root growth on the low-salt side, which lowered root-weighted mean salinity and enabled the maintenance of shoot growth. Atriplex nummularia grew even with extreme salinity in part of the roots, as long as the root-weighted mean salinity of the root zone was within the 10–450mM range. PMID:23125356

Plant responses to heterogeneous salinity: growth of the halophyte Atriplex nummularia is determined by the root-weighted mean salinity of the root zone.

PubMed

Bazihizina, Nadia; Barrett-Lennard, Edward G; Colmer, Timothy D

2012-11-01

Soil salinity is generally spatially heterogeneous, but our understanding of halophyte physiology under such conditions is limited. The growth and physiology of the dicotyledonous halophyte Atriplex nummularia was evaluated in split-root experiments to test whether growth is determined by: (i) the lowest; (ii) the highest; or (iii) the mean salinity of the root zone. In two experiments, plants were grown with uniform salinities or horizontally heterogeneous salinities (10-450 mM NaCl in the low-salt side and 670 mM in the high-salt side, or 10 mM NaCl in the low-salt side and 500-1500 mM in the high-salt side). The combined data showed that growth and gas exchange parameters responded most closely to the root-weighted mean salinity rather than to the lowest, mean, or highest salinity in the root zone. In contrast, midday shoot water potentials were determined by the lowest salinity in the root zone, consistent with most water being taken from the least negative water potential source. With uniform salinity, maximum shoot growth was at 120-230 mM NaCl; ~90% of maximum growth occurred at 10 mM and 450 mM NaCl. Exposure of part of the roots to 1500 mM NaCl resulted in an enhanced (+40%) root growth on the low-salt side, which lowered root-weighted mean salinity and enabled the maintenance of shoot growth. Atriplex nummularia grew even with extreme salinity in part of the roots, as long as the root-weighted mean salinity of the root zone was within the 10-450 mM range.

Effects of Salinity and Nutrient Addition on Mangrove Excoecaria agallocha

PubMed Central

Chen, Yaping; Ye, Yong

2014-01-01

Effects of salinity on seed germination and growth of young (1 month old) and old (2-year old) seedlings of Excoecaria agallocha were investigated. Combined effects of salinity and nutrient level were also examined on old seedlings. Seed germination was best at 0 and 5 psu salinity. 15 psu salinity significantly delayed root initiation and decreased final establishment rate. All seeds failed to establish at 25 psu salinity. Young seedlings performed best at 0 and 5 psu, but growth was stunned at 15 psu, and all seedlings died within 90 days at 25 psu. Old seedlings grew best at salinities below 5 psu and they survived the whole cultivation at 25 psu. This indicated that E. agallocha increased salt tolerance over time. Gas exchange was significantly compromised by salinities above 15 psu but evidently promoted by high nutrient. Proline accumulated considerably at high nutrient, and its contents increased from 0 to 15 psu but decreased at 25 psu salinity. Lipid peroxidation was aggravated by increasing salinity beyond 15 psu but markedly alleviated by nutrient addition. These responses indicated that E. agallocha was intolerant to high salinity but it can be greatly enhanced by nutrient addition. PMID:24691495

The Role of Ethylene in Plants Under Salinity Stress

PubMed Central

Tao, Jian-Jun; Chen, Hao-Wei; Ma, Biao; Zhang, Wan-Ke; Chen, Shou-Yi; Zhang, Jin-Song

2015-01-01

Although the roles of ethylene in plant response to salinity and other stresses have been extensively studied, there are still some obscure points left to be clarified. Generally, in Arabidopsis and many other terrestrial plants, ethylene signaling is indispensable for plant rapid response and tolerance to salinity stress. However, a few studies showed that functional knock-out of some ACSs increased plant salinity-tolerance, while overexpression of them caused more sensitivity. This seems to be contradictory to the known opinion that ethylene plays positive roles in salinity response. Differently, ethylene in rice may play negative roles in regulating seedling tolerance to salinity. The main positive ethylene signaling components MHZ7/OsEIN2, MHZ6/OsEIL1, and OsEIL2 all negatively regulate the salinity-tolerance of rice seedlings. Recently, several different research groups all proposed a negative feedback mechanism of coordinating plant growth and ethylene response, in which several ethylene-inducible proteins (including NtTCTP, NEIP2 in tobacco, AtSAUR76/77/78, and AtARGOS) act as inhibitors of ethylene response but activators of plant growth. Therefore, in addition to a summary of the general roles of ethylene biosynthesis and signaling in salinity response, this review mainly focused on discussing (i) the discrepancies between ethylene biosynthesis and signaling in salinity response, (ii) the divergence between rice and Arabidopsis in regulation of salinity response by ethylene, and (iii) the possible negative feedback mechanism of coordinating plant growth and salinity response by ethylene. PMID:26640476

Gene expression plasticity in response to salinity acclimation in threespine stickleback ecotypes from different salinity habitats.

PubMed

Gibbons, Taylor C; Metzger, David C H; Healy, Timothy M; Schulte, Patricia M

2017-05-01

Phenotypic plasticity is thought to facilitate the colonization of novel environments and shape the direction of evolution in colonizing populations. However, the relative prevalence of various predicted patterns of changes in phenotypic plasticity following colonization remains unclear. Here, we use a whole-transcriptome approach to characterize patterns of gene expression plasticity in the gills of a freshwater-adapted and a saltwater-adapted ecotype of threespine stickleback (Gasterosteus aculeatus) exposed to a range of salinities. The response of the gill transcriptome to environmental salinity had a large shared component common to both ecotypes (2159 genes) with significant enrichment of genes involved in transmembrane ion transport and the restructuring of the gill epithelium. This transcriptional response to freshwater acclimation is induced at salinities below two parts per thousand. There was also differentiation in gene expression patterns between ecotypes (2515 genes), particularly in processes important for changes in the gill structure and permeability. Only 508 genes that differed between ecotypes also responded to salinity and no specific processes were enriched among this gene set, and an even smaller number (87 genes) showed evidence of changes in the extent of the response to salinity acclimation between ecotypes. No pattern of relative expression dominated among these genes, suggesting that neither gains nor losses of plasticity dominated the changes in expression patterns between the ecotypes. These data demonstrate that multiple patterns of changes in gene expression plasticity can occur following colonization of novel habitats. © 2017 John Wiley & Sons Ltd.

Salinity and temperature tolerance of brown-marbled grouper Epinephelus fuscoguttatus.

PubMed

Cheng, Sha-Yen; Chen, Chih-Sung; Chen, Jiann-Chu

2013-04-01

Grouper have to face varied environmental stressors as a result of drastic changes to water conditions during the storm season. We aimed to test the response of brown-marbled grouper to drastic and gradual changes in temperature and salinity to understand the grouper's basic stress response. The results can improve the culture of grouper. Brown-marbled grouper, Epinephelus fuscoguttatus (6.2 ± 0.8 g) were examined for temperature and salinity tolerances at nine different environmental regimes (10, 20, and 33 ‰ combined with 20, 26 and 32 °C), in which the fish were subjected to both gradual and sudden changes in temperature and salinity. The critical thermal maximum (50 % CTMAX) and the upper incipient lethal temperature (UILT) were in the ranges of 35.9-38.3 and 32.7-36.5 °C, respectively. The critical thermal minimum (50 % CTMIN) and the lower incipient lethal temperature (LILT) were in the ranges of 9.8-12.2 and 14.9-22.3 °C, respectively. The critical salinity maximum (50 % CSMAX) and the upper incipient lethal salinity (UILS) were in the ranges of 67.0-75.5 and 54.2-64.8 ‰, respectively. Fish at temperature of 20 °C and a salinity of 33 ‰ tolerated temperatures as low as 10 °C when the temperature was gradually decreased. Fish acclimated at salinities of 10-33 ‰ and a temperature of 32 °C tolerated salinities of as high as 75-79 ‰. All fish survived from accumulating salinity after acute transfer to 20, 10, 5, and 3 ‰. But all fish died while transferred to 0 ‰. Relationships among the UILT, LILT, 50 % CTMAX, 50 % CTMIN, UILS, 50 % CSMAX, salinity, and temperature were examined. The grouper's temperature and salinity tolerance elevated by increasing acclimation temperature and salinity. On the contrary, the grouper's temperature and salinity tolerance degraded by decreasing acclimation temperature and salinity. The tolerance of temperature and salinity on grouper in gradual changes were higher than in drastic changes.

Dynamic changes in water and salinity in saline-alkali soils after simulated irrigation and leaching.

PubMed

Wang, Shutao; Feng, Qian; Zhou, Yapeng; Mao, Xiaoxi; Chen, Yaheng; Xu, Hao

2017-01-01

Soil salinization is a global problem that limits agricultural development and impacts human life. This study aimed to understand the dynamic changes in water and salinity in saline-alkali soil based on an indoor soil column simulation. We studied the changes in the water and salt contents of soils with different degrees of salinization under various irrigation conditions. The results showed that after seven irrigations, the pH, conductivity and total soluble salt content of the percolation samples after irrigation generally increased initially then decreased with repeated irrigation. The soil moisture did not change significantly after irrigation. The pH, conductivity, and total soluble salt content of each layer of the soil profile exhibited general declining trends. In the soil profile from Changguo Township (CG), the pH decreased from 8.21-8.35 to 7.71-7.88, the conductivity decreased from 0.95-1.14 ms/cm to 0.45-0.68 ms/cm, and the total soluble salt content decreased from 2.63-2.81 g/kg to 2.28-2.51 g/kg. In the soil profile from Zhongjie Industrial Park (ZJ), the pH decreased from 8.36-8.54 to 7.73-7.96, the conductivity decreased from 1.58-1.68 ms/cm to 1.45-1.54 ms/cm, and the total soluble salt decreased from 2.81-4.03 g/kg to 2.56-3.28 g/kg. The transported salt ions were primarily K+, Na+ and Cl-. After several irrigations, a representative desalination effect was achieved. The results of this study can provide technical guidance for the comprehensive management of saline-alkali soils.

Investigations in Marine Chemistry: Salinity II.

ERIC Educational Resources Information Center

Schlenker, Richard M.

Presented is a science activity in which the student investigates methods of calibration of a simple conductivity meter via a hands-on inquiry technique. Conductivity is mathematically compared to salinity using a point slope formula and graphical techniques. Sample solutions of unknown salinity are provided so that the students can sharpen their…

Inter-satellite links for satellite autonomous integrity monitoring

NASA Astrophysics Data System (ADS)

Rodríguez-Pérez, Irma; García-Serrano, Cristina; Catalán Catalán, Carlos; García, Alvaro Mozo; Tavella, Patrizia; Galleani, Lorenzo; Amarillo, Francisco

2011-01-01

A new integrity monitoring mechanisms to be implemented on-board on a GNSS taking advantage of inter-satellite links has been introduced. This is based on accurate range and Doppler measurements not affected neither by atmospheric delays nor ground local degradation (multipath and interference). By a linear combination of the Inter-Satellite Links Observables, appropriate observables for both satellite orbits and clock monitoring are obtained and by the proposed algorithms it is possible to reduce the time-to-alarm and the probability of undetected satellite anomalies.Several test cases have been run to assess the performances of the new orbit and clock monitoring algorithms in front of a complete scenario (satellite-to-satellite and satellite-to-ground links) and in a satellite-only scenario. The results of this experimentation campaign demonstrate that the Orbit Monitoring Algorithm is able to detect orbital feared events when the position error at the worst user location is still under acceptable limits. For instance, an unplanned manoeuvre in the along-track direction is detected (with a probability of false alarm equals to 5 × 10-9) when the position error at the worst user location is 18 cm. The experimentation also reveals that the clock monitoring algorithm is able to detect phase jumps, frequency jumps and instability degradation on the clocks but the latency of detection as well as the detection performances strongly depends on the noise added by the clock measurement system.

Effects of Soil Salinity on Sucrose Metabolism in Cotton Fiber

PubMed Central

Liu, Jingran; Luo, Junyu; Zhao, Xinhua; Dong, Helin; Ma, Yan; Sui, Ning; Zhou, Zhiguo; Meng, Yali

2016-01-01

Cotton (Gosspium hirsutum L.) is classified as a salt tolerant crop. However, its yield and fiber quality are negatively affected by soil salinity. Studies on the enzymatic differences in sucrose metabolism under different soil salinity levels are lacking. Therefore, field experiments, using two cotton cultivars, CCRI-79 (salt-tolerant) and Simian 3 (salt-sensitive), were conducted in 2013 and 2014 at three different salinity levels (1.15 dS m-1 [low soil salinity], 6.00 dS m-1 [medium soil salinity], and 11.46 dS m-1 [high soil salinity]). The objective was to elucidate the effects of soil salinity on sucrose content and the activity of key enzymes that are related to sucrose metabolism in cotton fiber. Results showed that as the soil salinity increased, cellulose content, sucrose content, and sucrose transformation rate declined; the decreases in cellulose content and sucrose transformation rate caused by the increase in soil salinity were more in Simian 3 than those in CCRI-79. With increase in soil salinity, activities of sucrose metabolism enzymes sucrose phophate synthase (SPS), acidic invertase, and alkaline invertase were decreased, whereas sucrose synthase (SuSy) activity increased. However, the changes displayed in the SuSy and SPS activities in response to increase in soil salinity were different and the differences were large between the two cotton cultivars. These results illustrated that suppressed cellulose synthesis and sucrose metabolism under high soil salinity were mainly due to the change in SPS, SuSy, and invertase activities, and the difference in cellulose synthesis and sucrose metabolism in fiber for the two cotton cultivars in response to soil salinity was determined mainly by both SuSy and SPS activities. PMID:27227773

Salinity information in coral δ18O records

NASA Astrophysics Data System (ADS)

Conroy, J. L.; Thompson, D. M.; Dassié, E. P.; Stevenson, S.; Konecky, B. L.; DeLong, K. L.; Sayani, H. R.; Emile-Geay, J.; Partin, J. W.; Abram, N. J.; Martrat, B.

2017-12-01

Coral oxygen isotopic ratios (δ18O) are typically utilized to reconstruct sea surface temperature (SST), or SST-based El Niño-Southern Oscillation metrics (e.g., NIÑO3.4), despite the influence of both SST and the oxygen isotopic composition of seawater (δ18Osw) on coral δ18O. The ideal way to isolate past δ18Osw variations is to develop independent and univariate SST and δ18Osw responders, for instance, via paired coral δ18O and Sr/Ca analyses. Nonetheless, many coral δ18O records without paired Sr/Ca records already exist in the paleoclimatic literature, and these may be able to provide some insight into past δ18Osw and salinity changes due to the nature of the significant positive relationship between instrumental salinity and δ18Osw. Here we use coral δ18O records from the new PAGES Iso2k database to assess the regions in which coral δ18O has the greatest potential to provide salinity information based on the strength of the relationship between instrumental salinity and coral δ18O values. We find from annual pseudocoral similations that corals in the western tropical Pacific share a substantial fraction of their variance with δ18Osw rather than SST. In contrast, in the Indian Ocean and eastern tropical Pacific it is SST that predominantly explains coral δ18O variance. In agreement with this variance decomposition, we find that coral δ18O time series from the western tropical Pacific are significantly correlated with mid to late 20th century salinity. However, variations in the strength of the δ18Osw-salinity relationship across the western tropical Pacific will likely have a significant influence on coral δ18O-based salinity reconstructions. Additionally, in some cases a strong, negative correlation between SST and δ18Osw might not allow their influences to be adequately separated in coral δ18O records without the use of coupled Sr/Ca estimates of the temperature contribution. Overall, we find a range of modern salinity and SST

Climate change and soil salinity: The case of coastal Bangladesh.

PubMed

Dasgupta, Susmita; Hossain, Md Moqbul; Huq, Mainul; Wheeler, David

2015-12-01

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001-2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.

Study of mobile satellite network based on GEO/LEO satellite constellation

NASA Astrophysics Data System (ADS)

Hu, Xiulin; Zeng, Yujiang; Wang, Ying; Wang, Xianhui

2005-11-01

Mobile satellite network with Inter Satellite Links (ISLs), which consists of non-geostationary satellites, has the characteristic of network topology's variability. This is a great challenge to the design and management of mobile satellite network. This paper analyzes the characteristics of mobile satellite network, takes multimedia Quality of Service (QoS) as the chief object and presents a reference model based on Geostationary Earth Orbit (GEO)/ Low Earth Orbit (LEO) satellite constellation which adapts to the design and management of mobile satellite network. In the reference model, LEO satellites constitute service subnet with responsibility for the access, transmission and switch of the multimedia services for mobile users, while GEO satellites constitute management subnet taking on the centralized management to service subnet. Additionally ground control centre realizes the whole monitoring and control via management subnet. Comparing with terrestrial network, the above reference model physically separates management subnet from service subnet, which not only enhances the advantage of centralized management but also overcomes the shortcoming of low reliability in terrestrial network. Routing of mobile satellite network based on GEO/LEO satellite constellation is also discussed in this paper.

Bulk Moisture and Salinity Sensor

NASA Technical Reports Server (NTRS)

Nurge, Mark; Monje, Oscar; Prenger, Jessica; Catechis, John

2013-01-01

Measurement and feedback control of nutrient solutions in plant root zones is critical to the development of healthy plants in both terrestrial and reduced-gravity environments. In addition to the water content, the amount of fertilizer in the nutrient solution is important to plant health. This typically requires a separate set of sensors to accomplish. A combination bulk moisture and salinity sensor has been designed, built, and tested with different nutrient solutions in several substrates. The substrates include glass beads, a clay-like substrate, and a nutrient-enriched substrate with the presence of plant roots. By measuring two key parameters, the sensor is able to monitor both the volumetric water content and salinity of the nutrient solution in bulk media. Many commercially available moisture sensors are point sensors, making localized measurements over a small volume at the point of insertion. Consequently, they are more prone to suffer from interferences with air bubbles, contact area of media, and root growth. This makes it difficult to get an accurate representation of true moisture content and distribution in the bulk media. Additionally, a network of point sensors is required, increasing the cabling, data acquisition, and calibration requirements. measure the dielectric properties of a material in the annular space of the vessel. Because the pore water in the media often has high salinity, a method to measure the media moisture content and salinity simultaneously was devised. Characterization of the frequency response for capacitance and conductance across the electrodes was completed for 2-mm glass bead media, 1- to 2-mm Turface (a clay like media), and 1- to 2-mm fertilized Turface with the presence of root mass. These measurements were then used to find empirical relationships among capacitance (C), the dissipation factor (D), the volumetric water content, and the pore water salinity.

Abacus to determine soils salinity in presence of saline groundwater in arid zones case of the region of Ouargla

NASA Astrophysics Data System (ADS)

Fergougui, Myriam Marie El; Benyamina, Hind; Boutoutaou, Djamel

2018-05-01

In order to remedy the limit of salt intake to the soil surface, it is necessary to study the causes of the soil salinity and find the origin of these salts. The arid areas in the region of Ouargla lie on excessively mineralized groundwater whose level is near the soil surface (0 - 1.5 m). The topography and absence of a reliable drainage system led to the rise of the groundwater beside the arid climatic conditions contributed to the salinization and hydromorphy of the soils. The progress and stabilization of cultures yields in these areas can only occur if the groundwater is maintained (drained) to a depth of 1.6 m. The results of works done to the determination of soil salinity depend mainly on the groundwater's salinity, its depth and the climate.

Pain difference associated with injection of abobotulinumtoxinA reconstituted with preserved saline and preservative-free saline: a prospective, randomized, side-by-side, double-blind study.

PubMed

Allen, Shawn B; Goldenberg, Neil A

2012-06-01

The Food and Drug Administration has approved the reconstitution of botulinum toxin A with preservative-free saline. Reconstitution of onabotulinumtoxinA with preserved saline has been previously reported to decrease the pain of injections. We present the first split-face study investigating differences in subjective pain when using preserved and preservative-free saline as the reconstituent of choice for abobotulinumtoxinA. To determine whether patients notice a difference in pain when injecting abobotulinumtoxinA diluted with preserved saline versus preservative-free saline. A prospective, randomized, double-blind, side-by-side trial was conducted in a private practice dermatology office in Boulder, Colorado. Twenty volunteer patients received injections on one side of their face with abobotulinumtoxinA reconstituted with preservative-free saline and with abobotulinumtoxinA reconstituted with preserved saline on the other side. Patients reported their pain on a 10-point visual analogue pain scale after each side was injected. Patients kept a diary for the first 48 hours after treatment to track any continued pain, onset of action, or adverse events. Patients were seen at a follow-up visit at 2 weeks, and any adverse events were recorded. Ninety percent of patients reported less pain on the side injected with preserved saline than on the side injected with preservative-free saline. Pain on the preserved saline side was 60% less than on the preservative-free side. Neither the patients nor the investigators noted any difference in onset of action between the two sides. Reconstitution of abobotulinumtoxinA with preserved saline results in significantly less pain on injection than with preservative-free saline. Preserved saline may be the reconstituent of choice for reconstitution of abobotulinumtoxinA. © 2012 by the American Society for Dermatologic Surgery, Inc. Published by Wiley Periodicals, Inc.

The long-term salinity field in San Francisco Bay

USGS Publications Warehouse

Uncles, R.J.; Peterson, D.H.

1996-01-01

Data are presented on long-term salinity behaviour in San Francisco Bay, California. A two-level, width averaged model of the tidally averaged salinity and circulation has been written in order to interpret the long-term (days to decades) salinity variability. The model has been used to simulate daily averaged salinity in the upper and lower levels of a 51 segment discretization of the Bay over the 22-yr period 1967-1988. Monthly averaged surface salinity from observations and monthly-averaged simulated salinity are in reasonable agreement. Good agreement is obtained from comparison with daily averaged salinity measured in the upper reaches of North Bay. The salinity variability is driven primarily by freshwater inflow with relatively minor oceanic influence. All stations exhibit a marked seasonal cycle in accordance with the Mediterranean climate, as well as a rich spectrum of variability due to extreme inflow events and extended periods of drought. Monthly averaged salinity intrusion positions have a pronounced seasonal variability and show an approximately linear response to the logarithm of monthly averaged Delta inflow. Although few observed data are available for studies of long-term salinity stratification, modelled stratification is found to be strongly dependent on freshwater inflow; the nature of that dependence varies throughout the Bay. Near the Golden Gate, stratification tends to increase up to very high inflows. In the central reaches of North Bay, modelled stratification maximizes as a function of inflow and further inflow reduces stratification. Near the head of North Bay, lowest summer inflows are associated with the greatest modelled stratification. Observations from the central reaches of North Bay show marked spring-neap variations in stratification and gravitational circulation, both being stronger at neap tides. This spring-neap variation is simulated by the model. A feature of the modelled stratification is a hysteresis in which, for a given

Decline of the world's saline lakes

Treesearch

Wayne A. Wurtsbaugh; Craig Miller; Sarah E. Null; R. Justin DeRose; Peter Wilcock; Maura Hahnenberger; Frank Howe; Johnnie Moore

2017-01-01

Many of the world’s saline lakes are shrinking at alarming rates, reducing waterbird habitat and economic benefits while threatening human health. Saline lakes are long-term basin-wide integrators of climatic conditions that shrink and grow with natural climatic variation. In contrast, water withdrawals for human use exert a sustained reduction in lake inflows and...

Satellite Sensor Requirements for Monitoring Essential Biodiversity Variables of Coastal Ecosystems

NASA Technical Reports Server (NTRS)

Muller-Karger, Frank E.; Hestir, Erin; Ade, Christiana; Turpie, Kevin; Roberts, Dar A.; Siegel, David; Miller, Robert J.; Humm, David; Izenberg, Noam; Keller, Mary;

Weight effect of saline accumulation in surgical drapes.

PubMed

Wiggins, Michael N; Thostenson, Jeff D

2007-10-01

Positive vitreal pressure during phacoemulsification is a known risk factor for posterior capsule rupture. Knowledge of modifiable causes of positive vitreal pressure is imperative to aid in its management intraoperatively. The aim of our study was to determine whether the weight from the accumulation of a large volume of saline in the surgical drapes could have an effect on intraocular pressure in patients. Such an effect could indicate a source of posterior vitreal pressure in patients undergoing prolonged phacoemulsification. In 23 adult patients undergoing phacoemulsification at the Jones Eye Institute at the University of Arkansas for Medical Sciences, intraocular pressure readings were taken before and after the addition of 500 cc of saline to the surgical drapes and taken again after removal of the saline. Statistically significant differences in intraocular pressure were found between the baseline measurement, the measurement with saline, and the measurement after saline removal. No differences in the rise in intraocular pressure were found according to age, race, sex, or which eye was tested. Accumulation of a large volume of saline in surgical drapes has a modest effect on intraocular pressure. This may indicate a contributing cause of posterior vitreal pressure during prolonged phacoemulsification.

"SPURS" in the North Atlantic Salinity Maximum

NASA Astrophysics Data System (ADS)

Schmitt, Raymond

2014-05-01

The North Atlantic Salinity Maximum is the world's saltiest open ocean salinity maximum and was the focus of the recent Salinity Processes Upper-ocean Regional Study (SPURS) program. SPURS was a joint venture between US, French, Irish, and Spanish investigators. Three US and two EU cruises were involved from August, 1012 - October, 2013 as well as surface moorings, glider, drifter and float deployments. Shipboard operations included underway meteorological and oceanic data, hydrographic surveys and turbulence profiling. The goal is to improve our understanding of how the salinity maximum is maintained and how it may be changing. It is formed by an excess of evaporation over precipitation and the wind-driven convergence of the subtropical gyre. Such salty areas are getting saltier with global warming (a record high SSS was observed in SPURS) and it is imperative to determine the relative roles of surface water fluxes and oceanic processes in such trends. The combination of accurate surface flux estimates with new assessments of vertical and horizontal mixing in the ocean will help elucidate the utility of ocean salinity in quantifying the changing global water cycle.

Salinity controls on plant transpiration and soil water balance

NASA Astrophysics Data System (ADS)

Perri, S.; Molini, A.; Suweis, S. S.; Viola, F.; Entekhabi, D.

2017-12-01

Soil salinization and aridification represent a major threat for the food security and sustainable development of drylands. The two problems are deeply connected, and their interplay is expected to be further enhanced by climate change and projected population growth. Salt-affected land is currently estimated to cover around 1.1 Gha, and is particularly widespread in semi-arid to hyper-arid climates. Over 900 Mha of these saline/sodic soils are potentially available for crop or biomass production. Salt-tolerant plants have been recently proposed as valid solution to exploit or even remediate salinized soils. However the effects of salinity on evapotranspiration, soil water balance and the long-term salt mass balance in the soil, are still largely unexplored. In this contribution we analyze the feedback of evapotranspiration on soil salinization, with particular emphasis on the role of vegetation and plant salt-tolerance. The goal is to introduce a simple modeling framework able to shed some light on how (a) soil salinity controls plant transpiration, and (b) salinization itself is favored/impeded by different vegetation feedback. We introduce at this goal a spatially lumped stochastic model of soil moisture and salt mass dynamics averaged over the active soil depth, and accounting for the effect of salinity on evapotranspiration. Here, the limiting effect of salinity on ET is modeled through a simple plant response function depending on both salt concentration in the soil and plant salt-tolerance. The coupled soil moisture and salt mass balance is hence used to obtain the conditional steady-state probability density function (pdf) of soil moisture for given salt tolerance and salinization level, Our results show that salinity imposes a limit in the soil water balance and this limit depends on plant salt-tolerance mainly through the control of the leaching occurrence (tolerant plants exploit water more efficiently than the sensitive ones). We also analyzed the