61 research outputs found

    Interdecadal Variations in the Alaska Gyre

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    Climatic dynamic topography variations in the Alaska gyre during the period 1968-1990 are described with an objective analysis of more than 12000 STD and XBT stations, and COADS wind stress data Interannual the dynamic height and SST variations were correlated and were consistent with recently described large-scale climatic shifts in the North Pacific. The gyre was centered more to the east, circulation appeared stronger, and SST was lower during the early to mid-1970s than during the 1980s. The Aleutian low (NP and PNA indices) intensified during the interim, but the response did not appear as a gyre spinup. Instead, the associated wind stress anomalies forced a slowly varying dynamic height anomaly across the eastern and northern part of the gyre through Ekman convergence, which had the effect of displacing the gyre's low somewhat to the WSW in the 1980s. The wind curl spectrum was white, and the slow oceanic response was modeled as stochastic-forced climate variability with a simple first-order Markov autoregression process. Forcing was assumed to be Ekman pumping of the pycnocline, and the damping coefficient was estimated from the data to be approx. 1 yr. A hindcast with observed winds gave estimated dynamic height patterns similar to those observed, with a canonical correlation of 0.79 at 99% confidence. This response was weak in the western half of the gyre, where slow baroclinic variability may have been influenced by long Rossby wave propagation. A simple autoregression simulation using artificial white noise forcing shows the evolution of decadal variations similar in nature to those observed. This result, along with the low frequency correlation between dynamic height and SST, suggests that the upper-ocean climatic variability in this region is primarily wind forced

    The Aquarius Salinity Retrieval Algorithm: Early Results

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    The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. 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. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to O2, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind. This is based on the radar backscatter measurements by the scatterometer. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation (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

    Sea Surface Salinity: The Next Remote Sensing Challenge

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    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

    The Aquarius Salinity Retrieval Algorithm

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    The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step

    The Determination of Surface Salinity with the European SMOS Space Mission

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    The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission aims at obtaining global maps of soil moisture and sea surface salinity from space for large-scale and climatic studies. It uses an L-band (1400–1427 MHz) Microwave Interferometric Radiometer by Aperture Synthesis to measure brightness temperature of the earth’s surface at horizontal and vertical polarizations ( h and v). These two parameters will be used together to retrieve the geophysical parameters. The retrieval of salinity is a complex process that requires the knowledge of other environmental information and an accurate processing of the radiometer measurements. Here, we present recent results obtained from several studies and field experiments that were part of the SMOS mission, and highlight the issues still to be solved

    NASA Tropical Rainfall Measurement Mission (TRMM): Effects of tropical rainfall on upper ocean dynamics, air-sea coupling and hydrologic cycle

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    This was a Tropical Rainfall Measurement Mission (TRMM) modeling, analysis and applications research project. Our broad scientific goals addressed three of the seven TRMM Priority Science Questions, specifically: What is the monthly average rainfall over the tropical ocean areas of about 10(exp 5) sq km, and how does this rain and its variability affect the structure and circulation of the tropical oceans? What is the relationship between precipitation and changes in the boundary conditions at the Earth's surface (e.g., sea surface temperature, soil properties, vegetation)? How can improved documentation of rainfall improve understanding of the hydrological cycle in the tropics

    Ocean Measurements from Space in 2025

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    Seasat, launched by the US National Aeronautics and Space Administration (NASA) in 1977, was the first dedicated ocean-viewing satellite. Since then, in addition to NASA, the space agencies of Europe, France, Canada, Germany, India, Japan, and China have all launched ocean-viewing sensors or dedicated ocean-viewing satellites. Properties currently measured from space are sea surface temperature; topography (height); salinity; significant wave height and wave spectra; surface wind speed and vectors; ocean color; continental and sea ice extent, "flow, deformation, thickness; ocean mass; and to a lesser extent, surface currents. By 2025, one additional measurement may become available—total surface currents—but the largest foreseen improvements are increased spatial and temporal resolution and increased accuracy for all the currently measured properties

    Highlights of the First 15 Months of Aquarius Salinity Measurements

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

    Resolving the global surface salinity field and variations by blending satellite and in situ observations

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    Lagerloef, Gary ...et al.-- Proceedings of OceanObs’09: Sustained Ocean Observations and Information for Society, 21-25 September 2009, Venice, Italy.-- 11 pages, 5 figures, 2 tablesThis Community White Paper (CWP) examines the present Sea Surface Salinity (SSS) observing system, satellite systems to measure SSS and the requirements for satellite calibration and data validation. We provide recommendations for augmenting the in situ observing network to improve the synergism between in situ and remote sensing measurements. The goal is have an integrated (in situ-satellite) salinity observing system to provide necessary the global salinity analyses to open new frontiers of ocean and climate research. It is now well established that SSS is one of the fundamental variables for which sustained global observations are required to improve our knowledge and prediction of the ocean circulation, global water cycle and climate. With the advent of two new satellites, the ocean observing system will begin a new era for measuring and understanding the SSS field. The SMOS (Soil Moisture and Ocean Salinity) and Aquarius/SAC-D (Scientific Application Satellite-D) missions planned to be launched between late 2009 and late 2010, are intended to provide ~150-200 km spatial resolution globally, and accuracy ~0.2 psu, or better, on monthly average. The challenge for the next decade is to combine these satellite and in situ systems to generate the optimal global SSS analysis for climate and ocean research. The in situ data provide surface calibration and validation for the satellite data, while the satellites provide more complete spatial and temporal coverage. The first priority is the maintenance of the existing in situ SSS observing network. In addition, we propose specific enhancements, ideally to include (1) deploying ~ 200 SSS sensors on surface velocity drifters and moorings in key regions, and (2) adding higher vertical resolution near-surface profiles to ~100 Argo buoys to address surface stratification, mixing and skin effects. Plans during the next few years to deploy a significant fraction of these enhanced measurements are identifiedPeer Reviewe

    SMOS and Aquarius/SAC-D Missions: The Era of Spaceborne Salinity Measurements is About to Begin

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    24 pages, 5 figures, 2 tablesThe SMOS and Aquarius/SAC-D are explorer missions that aim to measure ocean salinity for the first time from space, and usher in the new era of ocean remote sensing. Here we provide a brief description of the evolution and development of the missions since the last Oceans from Space a decade ago. Salinity remote sensing is done in the microwave frequency band centered at 1.413 GHz (L-band). The two missions apply very different technical approaches. SMOS sensor is phased array synthetic aperture radiometer, whereas the Aquarius sensor is a real aperture 3-beam push broom design with both radiometer and radar measurements to better correct for the surface roughness effects. Both will require data averaging to map surface salinity at 150–200 km resolution and monthly time scales needed to understand the links between ocean circulation, changes in the water cycle, and climate. These pathfinder missions will likely provide a decade of salinity data to evaluate at the 2020 Oceans from Space meeting, and will guide the future technology development to improve resolution and accuracyThis chapter is partly a contribution to the SMOS Barcelona Expert Centre on Radiometric Calibration and Ocean Salinity (SMOS-BEC) funded through grant ESP2007-05667-C04 from the Spanish Ministry of Science and InnovationPeer Reviewe
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