scholarly journals Assessing Temporal Aliasing in Satellite-Based Surface Salinity Measurements

2012 ◽  
Vol 29 (9) ◽  
pp. 1391-1400 ◽  
Author(s):  
Nadya T. Vinogradova ◽  
Rui M. Ponte
Keyword(s):  
Ocean Model ◽  
Sea Surface Salinity ◽  
Western Boundary ◽  
Boundary Current ◽  
Surface Salinity ◽  
Aliasing Error ◽  
Salinity Variability ◽  
Global Mapping ◽  
Salinity Data

Abstract The Aquarius/Satelite de Aplicaciones Cientificas-D (SAC-D) salinity remote sensing mission is intended to provide global mapping of sea surface salinity (SSS) fields over the next few years. Temporal and spatial averages of the satellite salinity retrievals produce monthly mean fields on 1° grids with target accuracies of 0.2 psu. One issue of relevance for the satellite-derived products is the potential for temporal aliasing of rapid fluctuations into the climate (monthly averaged) values of interest. Global daily SSS fields from a data-assimilating, eddy-resolving Hybrid Coordinate Ocean Model (HYCOM) solution are used to evaluate whether the potential aliasing error is large enough to affect the accuracy of the SSS retrievals. For comparison, salinity data collected at a few in situ stations over the tropical oceans are also used. Based on the HYCOM daily series, over many oceanic regions, a significant part of the total salinity variability is contributed by rapid fluctuations at periods aliased in the satellite retrievals. Estimates of the implicit aliasing error in monthly mean salinity estimates amount to 0.02 psu on average and >0.1 psu in some coastal, tropical, western boundary current, and Arctic regions. Comparison with in situ measurements suggests that HYCOM can underestimate the effect at some locations. While local aliased variance can be significant, the estimated impact of aliasing noise on the overall Aquarius system noise is negligible on average, when combined with effects of other instrument and geophysical errors. Effects of aliased variance are strongest at the shortest periods (<6 months) and become negligible at the annual period.

Sea surface salinity reemergence in an updated North Atlantic in-situ salinity data set

2021 ◽  
pp. 1-49
Author(s):  
Claude Frankignoul ◽  
Elodie Kestenare ◽  
Gilles Reverdin
Keyword(s):  
Large Scale ◽  
Cold Season ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Data Set ◽  
Salinity Data ◽  
Deep Mixed Layer ◽  
Geostrophic Advection

AbstractMonthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1°x1° grid in the Atlantic between 30°S and 50°N in the 1970-2016 period in an update of the data set of Reverdin et al. (2007). Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20°N and 50°N in 5°x5° boxes during the 1993-2016 period, both locally and remotely following the displacements of the deep mixed-layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about half of the boxes, notably in the northeast and southeast, while little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, while only a first SST reemergence is seen. An oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies.

scholarly journals The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data

2021 ◽  
Vol 13 (22) ◽  
pp. 4600
Author(s):  
Sébastien Guimbard ◽  
Nicolas Reul ◽  
Roberto Sabia ◽  
Sylvain Herlédan ◽  
Ziad El Khoury Hanna ◽  
...  
Keyword(s):  
Sea Surface ◽  
Sea Surface Salinity ◽  
Advisory Group ◽  
Surface Salinity ◽  
Sea Level Anomalies ◽  
Science Advisory ◽  
Wide Range ◽  
Salinity Data ◽  
High Precipitation

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity is an ESA initiative originally meant to support and widen the uptake of Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Starting in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data, supporting studies on enhanced validation and scientific process over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: gathering all the data required to exploit satellite sea surface salinity data, systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. The Salinity Pi-MEP is becoming a reference hub for the validation of satellite sea surface salinity missions by providing valuable information on satellite products (SMOS, Aquarius, SMAP), an extensive in situ database (e.g., Argo, thermosalinographs, moorings, drifters) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc.). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools (automatic, user-driven) of the platform are described in detail in this paper. Several dedicated scienctific case studies involving satellite SSS data are also systematically monitored by the platform, including major river plumes, mesoscale signatures in boundary currents, high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific. Since 2019, a partnership in the Salinity Pi-MEP project has been agreed between ESA and NASA to enlarge focus to encompass the entire set of satellite salinity sensors. The two agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from the SPURS campaigns.

scholarly journals Validating Salinity From SMAP With Saildrones and Research Vessel Data During EUREC4A-OA/ATOMIC

2021 ◽  
Author(s):  
Kashawn Hall ◽  
Alton Daley ◽  
Shanice Whitehall ◽  
Sanola Sandiford ◽  
Chelle Leigh Gentemann
Keyword(s):  
Climate Models ◽  
Weather Prediction ◽  
Ocean Model ◽  
Sea Surface Salinity ◽  
Small Scale ◽  
Surface Salinity ◽  
Hybrid Coordinate Ocean Model ◽  
Salinity Variability ◽  
Ocean Atmosphere ◽  
Remote Sensing Systems

The 2020 Elucidating the role of clouds-circulation coupling in climate - Ocean-Atmosphere (EUREC4A-OA) and Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) campaigns sought to improve the knowledge of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign consisted of numerous research technologies, some of which are relatively novel to the scientific community. In this study we used a saildrone uncrewed surface vehicle to validate satellite and modelled sea surface salinity (SSS) products in the Western Tropical Atlantic. These products include the Soil Moisture Active Passive (SMAP) Jet Propulsion Laboratory (JPL), SMAP Remote Sensing Systems (RSS), and Hybrid Coordinate Ocean Model (HYCOM). In addition to the validation, we investigated a fresh tongue south east of Barbados. The saildrones accurately depicted the salinity conditions and all satellite and modelled products performed well in areas that lacked small-scale salinity variability. However, SMAP RSS 70 km outperformed its counterparts in areas with small submesoscale irregularities while RSS 40 km was better at identifying small irregularities in salinity such as a fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product for their application and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Pi-MEP Salinity – an ESA-NASA Platform for sustained satellite surface salinity validation 

2021 ◽  
Author(s):  
Roberto Sabia ◽  
Sebastien Guimbard ◽  
Nicolas Reul ◽  
Tony Lee ◽  
Julian Schanze ◽  
...  
Keyword(s):  
Program Planning ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
In Situ Data ◽  
Sea Level Anomalies ◽  
Ocean Salinity ◽  
Salinity Data ◽  
Planning Group

<p>The Pilot Mission Exploitation Platform (Pi-MEP) for Salinity (www.salinity-pimep.org) has been released operationally in 2019 to the broad oceanographic community, in order to foster satellite sea surface salinity validation and exploitation activities.</p><p>Specifically, the Platform aims at enhancing salinityvalidation, by allowing systematic inter-comparison of various EO datasets with a broad suite of in-situ data, and also at enabling oceanographic process studies by capitalizing on salinity data in synergy with additional spaceborne estimates.</p><p> </p><p>Despite Pi-MEP was originally conceived as an ESA initiative to widen the uptake of the Soil Moisture and Ocean Salinity (SMOS) mission data over ocean, a project partnership with NASA was devised soon after the operational deployment, and an official collaboration endorsed within the ESA-NASA Joint Program Planning Group (JPPG).</p><p> </p><p>The Salinity Pi-MEP has therefore become a reference hub for SMOS, SMAP and Aquarius satellite salinity missions, which are assessed in synergy with additional thematic datasets (e.g., precipitation, evaporation, currents, sea level anomalies, ocean color, sea surface temperature). </p><p>Match-up databases of satellite/in situ (such as Argo, TSG, moorings, drifters) data and corresponding validation reports at different spatiotemporal scales are systematically generated; furthermore, recently-developed dedicated tools allow data visualization, metrics computation and user-driven features extractions.</p><p> </p><p>The Platform is also meant to monitor salinity in selected oceanographic “case studies”, ranging from river plumes monitoring to SSS characterization in challenging regions, such as high latitudes or semi-enclosed basins.</p><p> </p><p>The two Agencies are currently collaborating to widen the Platform features on several technical aspects - ranging from a triple-collocation software implementation to a sustained exploitation of data from the SPURS-1/2 campaigns. In this context, an upgrade of the satellite/in-situ match-up methodology has been recently agreed, resulting into a redefinition of the validation criteria that will be subsequently implemented in the Platform.</p><p> </p><p>A further synthesis of the three satellites salinity algorithms, models and auxiliary data handling is at the core of the ESA Climate Change Initiative (CCI) on Salinity and of ESA-NASA further collaboration.</p>

scholarly journals Mindanao Current and Undercurrent: Thermohaline Structure and Transport from Repeat Glider Observations

2017 ◽  
Vol 47 (8) ◽  
pp. 2055-2075 ◽  
Author(s):  
Martha C. Schönau ◽  
Daniel L. Rudnick
Keyword(s):  
North Pacific Ocean ◽  
Maximum Velocity ◽  
Sea Surface Salinity ◽  
North Equatorial Current ◽  
Western Boundary ◽  
Thermocline Depth ◽  
Boundary Current ◽  
Surface Salinity ◽  
The North ◽  
Mindanao Current

AbstractAutonomous underwater Spray gliders made repeat transects of the Mindanao Current (MC), a low-latitude western boundary current in the western tropical North Pacific Ocean, from September 2009 to October 2013. In the thermocline (<26 kg m−3), the MC has a maximum velocity core of −0.95 m s−1, weakening with distance offshore until it intersects with the intermittent Mindanao Eddy (ME) at 129.25°E. In the subthermocline (>26 kg m−3), a persistent Mindanao Undercurrent (MUC), with a velocity core of 0.2 m s−1 and mean net transport, flows poleward. Mean transport and standard deviation integrated from the coast to 130°E is −19 ± 3.1 Sv (1 Sv ≡ 106 m3 s−1) in the thermocline and −3 ± 12 Sv in the subthermocline. Subthermocline transport has an inverse linear relationship with the Niño-3.4 index and is the primary influence of total transport variability. Interannual anomalies during El Niño are greater than the annual cycle for sea surface salinity and thermocline depth. Water masses transported by the MC/MUC are identified by subsurface salinity extrema and are on isopycnals that have increased finescale salinity variance (spice variance) from eddy stirring. The MC/MUC spice variance is smaller in the thermocline and greater in the subthermocline when compared to the North Equatorial Current and its undercurrents.

scholarly journals Assessment of Aquarius Sea Surface Salinity

2018 ◽  
Vol 10 (9) ◽  
pp. 1341 ◽  
Author(s):  
Hsun-Ying Kao ◽  
Gary Lagerloef ◽  
Tong Lee ◽  
Oleg Melnichenko ◽  
Thomas Meissner ◽  
...  
Keyword(s):  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Global Ocean ◽  
General View ◽  
Surface Salinity ◽  
Validation Data ◽  
Accuracy Requirement ◽  
Salinity Data ◽  
Mean Square Errors

Aquarius was the first NASA satellite to observe the sea surface salinity (SSS) over the global ocean. The mission successfully collected data from 25 August 2011 to 7 June 2015. The Aquarius project released its final version (Version-5) of the SSS data product in December 2017. The purpose of this paper is to summarize the validation results from the Aquarius Validation Data System (AVDS) and other statistical methods, and to provide a general view of the Aquarius SSS quality to the users. The results demonstrate that Aquarius has met the mission target measurement accuracy requirement of 0.2 psu on monthly averages on 150 km scale. From the triple point analysis using Aquarius, in situ field and Hybrid Coordinate Ocean Model (HYCOM) products, the root mean square errors of Aquarius Level-2 and Level-3 data are estimated to be 0.17 psu and 0.13 psu, respectively. It is important that caution should be exercised when using Aquarius salinity data in areas with high radio frequency interference (RFI) and heavy rainfall, close to the coast lines where leakage of land signals may significantly affect the quality of the SSS data, and at high-latitude oceans where the L-band radiometer has poor sensitivity to SSS.

Variability of Intraseasonal Oscillations and Synoptic Signals in Sea Surface Salinity in the Bay of Bengal

2019 ◽  
Vol 32 (20) ◽  
pp. 6703-6728 ◽  
Author(s):  
Corinne B. Trott ◽  
Bulusu Subrahmanyam ◽  
Heather L. Roman-Stork ◽  
V. S. N. Murty ◽  
C. Gnanaseelan
Keyword(s):  
Soil Moisture ◽  
River Runoff ◽  
Bay Of Bengal ◽  
Southwest Monsoon ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Intraseasonal Oscillations ◽  
Salinity Data

Abstract Intraseasonal oscillations (ISOs) significantly impact southwest monsoon precipitation and Bay of Bengal (BoB) variability. The response of ISOs in sea surface salinity (SSS) to those in the atmosphere is investigated in the BoB from 2005 to 2017. The three intraseasonal processes examined in this study are the 30–90-day and 10–20-day ISOs and 3–7-day synoptic weather signals. A variety of salinity data from NASA’s Soil Moisture Active Passive (SMAP) and the European Space Agency’s (ESA’s) Soil Moisture and Ocean Salinity (SMOS) satellite missions and from reanalysis using the Hybrid Coordinate Ocean Model (HYCOM) and operational analysis of Climate Forecast System version 2 (CFSv2) were utilized for the study. It is found that the 30–90-day ISO salinity signal propagates northward following the northward propagation of convection and precipitation ISOs. The 10–20-day ISO in SSS and precipitation deviate largely in the northern BoB wherein the river runoff largely impacts the SSS. The weather systems strongly impact the 3–7-day signal in SSS prior to and after the southwest monsoon. Overall, we find that satellite salinity products captured better the SSS signal of ISO due to inherent inclusion of river runoff and mixed layer processes. CFSv2, in particular, underestimates the SSS signal due to the misrepresentation of river runoff in the model. This study highlights the need to include realistic riverine freshwater influx for better model simulations, as accurate salinity simulation is mandatory for the representation of air–sea coupling in models.

scholarly journals Inter Annual and Seasonal Cycle of Satellite Derived Sea Surface Salinity in the Bay of Bengal

2021 ◽  
Author(s):  
Kandasamy Priyanka ◽  
Ranjit Kumar Sarangi ◽  
Ramalingam Shanthi ◽  
Durairaj Poornima ◽  
Ayyappan Saravanakumar
Keyword(s):  
Coastal Water ◽  
Bay Of Bengal ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Spatial And Temporal Variation ◽  
Surface Salinity ◽  
Decadal Scale ◽  
Salinity Data ◽  
Offshore Region

Abstract A spatial and temporal variation of sea surface salinity (SSS) is vital to understand the dynamics of the seasonal and inter-annual changes in the marine environment. In the present study, Soil Moisture Active-Passive (SMAP) derived daily SSS product and Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) remote sensing reflectance (Rrs) based SSS images (Algorithm by Qing et al, 2013), applied in the coastal and offshore region of the Bay of Bengal (BoB). SMAP data validation with in situ data (offshore and coastal water, 10 and 15 points) showed good correlation at offshore water and less correlation at coastal water (R2 = 0.707/0.499, SEE = ± 0.291/±0.546, MNB = -0.0029/-0.0089 and RMSE = ± 0.092/±0.139) respectively. Similarly, MODIS-Aqua Rrs derived salinity data validated with in-situ SSS and observed the correlation as follows with R2 = 0.908/0.891, SEE = ± 2.395/±1.512, MNB = 0.0718/0.0361, RMSE = ± 0.760/±0.316 in offshore and coastal water respectively during April and August 2019. The salinity data observed in the range of 32 to 34.5psu. High SSS mean (35.6-35.8psu) observed during the spring inter-monsoon and low salinity (34.6-34.9psu) observed during winter monsoon phase as depicted from decadal scale interpretation. The present study inferred that MODIS aqua derived SSS is better than SMAP based SSS at coastal and offshore region of the western BoB, irrespective of their resolution and spectral differences. More data points based validation would provide the scope for further improvements and seasonal studies on salinity variability using ocean color sensors reflectance based datasets.

scholarly journals Matchup Characteristics of Sea Surface Salinity Using a High-Resolution Ocean Model

2021 ◽  
Vol 13 (15) ◽  
pp. 2995
Author(s):  
Frederick M. Bingham ◽  
Severine Fournier ◽  
Susannah Brodnitz ◽  
Karly Ulfsax ◽  
Hong Zhang
Keyword(s):  
High Resolution ◽  
Time Window ◽  
Single Point ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Argo Floats ◽  
Statistical Measures ◽  
Salinity Difference

Sea surface salinity (SSS) satellite measurements are validated using in situ observations usually made by surfacing Argo floats. Validation statistics are computed using matched values of SSS from satellites and floats. This study explores how the matchup process is done using a high-resolution numerical ocean model, the MITgcm. One year of model output is sampled as if the Aquarius and Soil Moisture Active Passive (SMAP) satellites flew over it and Argo floats popped up into it. Statistical measures of mismatch between satellite and float are computed, RMS difference (RMSD) and bias. The bias is small, less than 0.002 in absolute value, but negative with float values being greater than satellites. RMSD is computed using an “all salinity difference” method that averages level 2 satellite observations within a given time and space window for comparison with Argo floats. RMSD values range from 0.08 to 0.18 depending on the space–time window and the satellite. This range gives an estimate of the representation error inherent in comparing single point Argo floats to area-average satellite values. The study has implications for future SSS satellite missions and the need to specify how errors are computed to gauge the total accuracy of retrieved SSS values.

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