Observed changes in temperature extremes for the Beijing–Tianjin–Hebei region of China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT As one of the most significant threats facing the world, climate change has already been manifested everywhere in the form of frequent extreme climate events (e.g. heat waves, floods, droughts and wildfires) and has caused serious impacts on all aspects of the living environment. Due to the regional variability of global climate change, understanding the ongoing climatic changes at a local scale is very important for decision makers and resource managers to develop appropriate mitigation and adaptation strategies against the changing climate. In this study, recent changes in extreme temperature indices (including frost days, summer days, icy days, tropical nights, growing season length, cool nights and warm nights, cool days and warm days, and daily temperature range) over the Beijing–Tianjin–Hebei ( BTH ) region of China were investigated in the context of global warming. The results indicate that the historical trends of these extreme temperature indices are statistically significant in Huailai, Beijing, Leting and Shijiazhuang while no significant trends are reported in Chengde, Tianjin and Cangzhou−Potou. By comparing results between coastal and inland stations, it is found that the changes in temperature extremes in inland stations are less significant than the changes in coastal stations. The results also suggest that the indices based on minimum temperature show decreasing trends while those for maximum temperature present increasing trends. Furthermore, mutation tests were performed for all indices in order to understand when the changes were initiated. An apparent mutation point (mostly in the 1980s) is detected for most of the analysed temperature indices. This may be caused by the wide implementation of the reform and opening policy in the early 1980s to boost economic development in the BTH region.
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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 | 0.000 | 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 | 0.001 | 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 it