COMBINED TEMPERATURE-PRECIPITATION MODES AND THEIR RELATIONSHIP WITH LARGE-SCALE CLIMATE INDICES IN PARANÁ, SOUTHERN BRAZIL (1980-2014)
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
In recent decades the Northeast of Brazil experienced several episodes of intense droughts while other regions were affected by heavy rainfall events that caused severe flooding. The variability of temperature and precipitation in Brazil are associated with large-scale climatic indices, such as the El Niño Southern Oscillation (ENSO), the Multidecadal Atlantic Oscillation (AMO) and the Tropical North Atlantic (TNA). In this study, quantiles 25 and 75 of temperature and precipitation were used to determine the climatic trends in terms of number of days for the different modes (warm and dry, warm and humid, cold and dry or cold and wet). Subsequently, correlation analyzes were carried out with nine different climatic indices that influence the regional climate of southern Brazil. Our results highlighted the absence of a dominant mode throughout the seasons and over the years. We also found spatio-temporal trends in this region. In addition, except for the warm-dry mode where 8 out of 10 stations were correlated with the Niño1 + 2 index, there were few correlations between the modes and the different climate indices used in this research. Despite the increasing temperature trends, and a complex and heterogeneous variations in precipitation regime, our results did not indicate any significant changes in the modes nor their relationship with the climate indices.
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.
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 | 0.001 | 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) | 0.000 | 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