Numerical Model Generated Hawaii Test Scenes for EarthCARE Pre-launch Studies - Part 1: Atmospheric and Surface Properties
Bibliographic record
Abstract
This first part of the dataset contains the atmospheric and surface conditions of Hawaii test scene (39320E) used for pre-launch studies of EarthCARE’s retrieval algorithms and data management system. The data are produced by Environment and Climate Change Canada's Global Environmental Multi-scale (GEM) NWP model (Côté et al., 1998, Girard et al., 2014). The surface albedo climatology is based MODIS’s MCD43GF 1 km resolution bidirectional reflectance distribution function (BRDF) product for the period 2002 to 2013 (Schaaf et al. 2002). Please refer to the second part of Hawaii scene dataset for the mass content and effective radius of hydrometeors and aerosols, and the third part of the dataset for the number concentration of hydrometeors and aerosols, as well as the data of vertical wind speed. The Hawaii test frame is 6200 km long and 200 km wide with horizontal grid-spacing of 250 km and 57 vertical layers. The simulation is initialized at 12:00 UTC 23-Jun-2015 and saved at 00h00 UTC on 24-Jun-2015. This frame crosses the central Pacific Ocean, near Hawaii, with a mesoscale convective system (MCS) in its center, clear skies in the north and south part of the frame, and a weak frontal system at its southern extremity.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".