Spatial coherence of meteorological droughts in the <scp>UK</scp> since 1914
Why this work is in the frame
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Bibliographic record
Abstract
We apply the drought severity index ( DSI ) on a multi‐temporal basis to a monthly precipitation dataset to study the spatial coherence of meteorological droughts in the UK since 1914. Analyses are undertaken for the wet ( O ctober– M arch) and dry ( A pril– S eptember) seasons and for moderate and extreme drought severities. We develop a drought covariance index that allows us to quantify the spatial coherence of droughts based on the fraction of years with extreme (or moderate) droughts that each pair of grid points has in common. Results show greater coherence in (and more widespread) moderate, short duration and wet season droughts. Results are discussed in terms of the relationship between the N orth A tlantic Oscillation and precipitation, the spatial variability of precipitation and the detectability of droughts. Finally, we examine the implications of our study for drought management with a focus on water transfers.
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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 | 0.001 | 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) | 0.001 | 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 it