The Sydney 2000 World Weather Research Programme Forecast Demonstration Project: Overview and Current Status
Bibliographic record
Abstract
The first World Weather Research Programme (WWRP) Forecast Demonstration Project (FDP), with a focus on nowcasting, was conducted in Sydney, Australia, from 4 September to 21 November 2000 during a period associated with the Sydney 2000 Olympic Games. Through international collaboration, nine nowcasting systems from the United States, United Kingdom, Canada, and Australia were deployed at the Sydney Office of the Bureau of Meteorology (BOM) to demonstrate the capability of modern forecast systems and to quantify the associated benefits in the delivery of a real-time nowcast service. On-going verification and impact studies supported by international committees assisted by the WWRP formed an integral part of this project. A description is given of the project, including component systems, the weather, and initial outcomes. Initial results show that the nowcasting systems tested were transferable and able to provide valuable information enhancing BOM nowcasts. The project provided for unprecedented interchange of concepts and ideas between forecasters, researchers, and end users in an operational framework where they all faced common issues relevant to real time nowcast decision making. A training workshop sponsored by the World Meteorological Organization (WMO) was also held in conjunction with the project so that other member nations could benefit from the FDP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".