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Record W2810075903 · doi:10.1109/aero.2018.8396504

The surface water and ocean topography mission

2018· article· en· W2810075903 on OpenAlexaboutno aff
Parag Vaze, Said Kaki, D. Limonadi, Daniel Esteban-Fernández, Guy Zohar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersCalifornia State University, SacramentoJet Propulsion LaboratoryAzusa Pacific UniversityUniversity of Pittsburgh
KeywordsOcean surface topographyAltimeterMesoscale meteorologyRemote sensingGeologySWOT analysisSea-surface heightOcean currentSea surface temperatureRadarBathymetryEnvironmental scienceMeteorologyGeodesyClimatologyGeographyOceanographyComputer science

Abstract

fetched live from OpenAlex

The Surface Water and Ocean Topography SWOT mission is a partnership between two communities, physical oceanography and hydrology, to share high vertical accuracy and high spatial resolution topography data produced by the science payload, whose principal instrument is a Ka-band radar Interferometer. The SWOT mission will provide large-scale data sets of ocean sea-surface height resolving scales of 15km (in ocean wavelength) and larger, allowing the characterization of ocean mesoscale and submesoscale circulation. Present altimeter constellations can only resolve the ocean circulation at ocean wavelengths larger than 200km. SWOT will address fundamental questions on the dynamics of ocean variability at wavelengths shorter than 200km, which encompasses mesoscale and submesoscale processes such as the formation, evolution, and dissipation of eddy variability (including narrow currents, fronts, and quasi-geostrophic turbulence) and their role in air-sea interaction. The SWOT mission will also provide measurements of water storage changes in terrestrial surface water bodies and will provide estimates of discharge in large (wider than 100m) rivers, globally. The SWOT measurements will directly measure the surface water (lakes, reservoirs, rivers, and wetlands) component of the water cycle. The core of the SWOT payload consists of a Ka-band Radar Interferometer (KaRIn) - a dual-antenna synthetic aperture radar specifically designed to make high precision height and backscatter measurements enabling the key oceanographic and hydrology data sets. The SWOT payload also includes: a Nadir Altimeter (NA) system, a radiometer for tropospheric path delay corrections, and a precision orbit determination instrument suite consisting of Global Positioning System-Payload (GPSP), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) receivers, and a Laser Retroreflector Array (LRA). SWOT is a partnership mission between NASA, the French Space Agency (CNES), The United Kingdom Space Agency (UKSA), and The Canadian Space Agency (CSA). The spacecraft bus and command & data ground stations are provided by CNES, while the launch vehicle and payload module are provided by NASA/JPL. The SWOT payload module instrument suite consists of the NASA/JPL provided KaRIn instrument, cross-track radiometer, GPS, and laser retroreflector, as well as the CNES provided DORIS and nadir pointing radar altimeter. CNES also provides the Radio Frequency Unit (RFU) sub-system for which the UKSA contributes the Duplexer assembly. The RFU is a key subsystem of the KaRIn instrument. CSA contributes the Extended Interaction Klystron (EIK) which is one of the KaRIn subsystem. This paper describes the mission design, implementation of the Payload, and some of the interface and design challenges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.193
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2018
Admission routes1
Has abstractyes

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