Assimilation of SMAP brightness temperatures in environment and climate change Canada's new land surface parameterization scheme
Bibliographic record
Abstract
The NASA Soil Moisture Active Passive (SMAP) mission was launched in January 2015 and has been providing near global coverage of soil moisture every 3 days. At Environment and Climate Change Canada (ECCC) considerable effort has been focused upon the assimilation of SMAP brightness temperatures for a better analysis of the soil moisture state and resulting Numerical Weather Prediction (NWP) forecasts. A new land-surface parameterization, Soil, Vegetation, and Snow (SVS) was recently developed at ECCC which includes more sophisticated hydrology incorporating multiple soil layers where soil moisture evolves according to Darcian flow, and includes separate energy budgets for different land-surface components. The objectives of this study are to perform a set of assimilation experiments to quantify improvements in soil moisture and added NWP skill from the inclusion of SMAP data within SVS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".