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Record W4322020346 · doi:10.5194/egusphere-egu23-17156

The SWOT (Surface Water and Ocean Topography) Mission and Its Status

2023· preprint· en· W4322020346 on OpenAlexaboutno aff
Lee‐Lueng Fu, Tamlin M. Pavelsky, Rosemary Morrow, Jean-Francois Cretaux, J. Thomas Farrar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceSurface waterSWOT analysisEarth observationOcean surface topographyMeteorologyOceanographyGeologySatelliteGeographyEngineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

SWOT is a pathfinder mission using new technology to address transformative questions on energy and water of the Earth System in a warming climate.  The excess heat energy entering the Earth system as a result of the greenhouse effect is largely stored in water, and changes in the water cycle and water resources have profound effects on life on Earth.             SWOT is a next generation radar altimeter that uses synthetic aperture radar interferometry to measure the elevation of water surface over both continents and oceans in two dimensions with a radar footprint 1000 times smaller than that of a conventional altimeter. SWOT will cover the world between 78N and 78S every 21 days, leaving only small gaps comprising <5% of Earth’s surface.  More than 90% of the heat from global warming since the industrial revolution has been absorbed and stored in the ocean.  A major part of this process takes place in the ocean on scales too small to be observed from space in the past.  SWOT will improve the two-dimensional spatial resolution of sea surface height from present 200 km to 20 km to address the processes of heat uptake from the atmosphere. In a warming climate earth’s water cycle is accelerating, making it difficult to track and manage water resources as well as predicting floods and droughts.  The areal extent of surface water on land can be observed by conventional spaceborne sensors, but the volume of surface water in lakes and rivers will be surveyed by SWOT from space for the first time.  The numbers of rivers and lakes to be surveyed by SWOT are orders of magnitude more than the present observations. The high-resolution data of SWOT near the coasts will allow us to study sea level variations in unprecedented detail. Storm surge and other impacts like salt water intrusion and river diversion will be exacerbated by the continuing sea level rise.  SWOT data will help improve models to monitor and forecast these impacts. After nearly 20 years’ development, SWOT was launched on December 16, 2022 as a joint mission of NASA and the French Space Agency, CNES, with contributions from the Canadian Space Agency and the UK Space Agency. The satellite system was fully deployed within a week of launch and is in a 3-month phase of engineering checkout.  A 3-month calibration and validation phase will start afterwards in the one-day repeat initial orbit, which will transition into a 21-day repeat orbit during the science phase of the mission in mid 2023.  The release of SWOT data to the public for evaluation is expected to take place 10 months after launch.  The status of the mission at the end of April will be reported by this presentation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.556

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 head0.022
GPT teacher head0.206
Teacher spread0.184 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2023
Admission routes1
Has abstractyes

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