The Drought Research Initiative: A Comprehensive Examination of Drought over the Canadian Prairies
Bibliographic record
Abstract
The Canadian Prairies are often subjected to drought, and it is sometimes catastrophic. The most recent event occurred over the period 1999–2005, and it produced some of the driest conditions in the historical record. To address such droughts, the Drought Research Initiative (DRI) network was established. The particular focus of DRI was to understand better the factors that led to, sustained and ended this recent drought, including its internal structure, and to contribute to the better prediction of such events. To accomplish this objective, the drought was considered from several perspectives involving the atmosphere, the land surface and sub-surface; the role of vegetation was also considered. This drought was unusual in that its large-scale forcing was quite variable over its duration; regions of record high precipitation sometimes occurred simultaneously across the Prairies, and cloud fields were common. It, nonetheless, produced some of the greatest reduction in sub-surface moisture on record and led to major declines in river flows. The DRI research community from across the country, furthermore, worked closely with many partners affected by the drought so that they are better able to cope with such events in the future. This article provides a brief overview of this drought's characteristics as well as DRI's objectives and key scientific issues. It also summarizes key results from each of the articles in this special issue and ends with comments on DRI's overall contributions. R ésumé [Traduit par la rédaction] Les Prairies canadiennes sont souvent touchées par des sécheresses et celles-ci sont parfois catastrophiques. L’événement le plus récent est survenu durant la période 1999–2005 et a produit certaines des conditions les plus sèches jamais enregistrées. Afin d’étudier ces sécheresses, le Réseau de recherche sur la sécheresse (DRI) a été créé. L'objectif premier du DRI était de mieux comprendre les facteurs qui ont donné naissance à cette sécheresse, qui l'ont entretenu et qui y ont mis fin, y compris sa structure interne, et de contribuer à mieux prévoir ces événements. Pour atteindre cet objectif, la sécheresse a été examinée de différents points de vue prenant en considération l'atmosphère, la surface de la terre et la subsurface tout en tenant compte du rôle de la végétation. Cette sécheresse était inhabituelle en ce que son forçage à grande échelle a été assez variable au cours de sa durée; certaines régions des prairies ont en même temps reçu des précipitations record et les champs de nuages étaient fréquents. Elle a néanmoins produit certaines des plus importantes réductions de l'humidité souterraine jamais enregistrées et a occasionné des diminutions marquées du débit des cours d'eau. Les chercheurs du DRI d'un bout à l'autre du pays ont en outre travaillé étroitement avec plusieurs partenaires touchés par la sécheresse afin que ceux-ci soient mieux en mesure d'affronter de tels événements dans le futur. Le présent article donne un bref aperçu des caractéristiques de cette sécheresse ainsi que des objectifs du DRI et des principales questions scientifiques auxquelles il s'intéresse. Il résume aussi les résultats clés de chacun des articles publiés dans ce numéro spécial et se termine par des commentaires sur les contributions générales du DRI.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.018 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".