Observing the Ocean Surface Topography at High Resolution by the Surface Water and Ocean Topography (SWOT) Mission
Bibliographic record
Abstract
This paper presents the oceanographic objectives and plans of calibration and validation, science investigations and applications for the Surface Water and Ocean Topography (SWOT) Mission. This international mission, planned for launch in 2021, will make high-resolution observations of the ocean surface topography as a next-generation altimetry mission utilizing the technique of radar interferometry. With measurement over a swath of 120 km (20 km nadir gap), SWOT will map the entire earth within +/- 77.6 degree latitudes every 21 days. Over the ocean, this new measurement will extend the two-dimensional resolution of ocean surface topography estimated from conventional radar altimetry from 150 km wavelength to possibly 15 km, offering opportunities to study the oceanic dynamic processes at these scales that act as one of the main gateways connecting the interior of the ocean to the upper layer. SWOT has a non-sun-synchronous orbit, specifically designed to observe and improve our understanding of the barotropic and baroclinic tides. As such, it will provide a unique opportunity to observe both low-frequency geostrophically balanced motions and high-frequency internal tides and gravity waves, and their non-linear interactions. We will present an overview of the SWOT Science Team’s work in understanding these dynamical surface topography signals, from high-resolution and high-frequency modeling, and from in-situ and satellite observations. The first 90 days of the mission (after the commissioning phase for engineering check-out and adjustment) will be flown in a 1-day repeat fast-sampling phase for calibration and validation. This unique, rapid temporal sampling will allow enhanced understanding of the SSH measurement at 15-150 km wavelengths in terms of signals and measurement errors. In particular, there will be two measurements a day at the crossover diamond-shaped regions, where the two-dimensional measurement at twice daily interval will provide the maximum amount of information on rapidly changing signals and errors. We are engaging the international community to participate in in-situ observations under the 1-day orbit swaths, to evaluate and link the SWOT sea surface height measurements to the observed internal oceanic processes in different regions and seasons. The mission’s science team will be renewed in 2020. The topics of oceanographic investigations cover mesoscale and submesoscale processes; modeling and data assimilation; tides, waves, and high-frequency processes; calibration and validation; coastal and estuarine processes. We will present some of the innovative techniques being developed to reduce the effects of measurement errors in the 2D SSH fields, and to address the challenges posed by the coarse temporal sampling and presence of internal tides in the construction of high-level gridded products and assimilated ocean state estimation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".