Spatial and seasonal variations in evapotranspiration over Canada's landmass
Bibliographic record
Abstract
Abstract. A 30 yr (1979–2008) dataset of actual evapotranspiration (ET) at 1 km resolution was generated over Canada's landmass by integrating remote sensing land surface data and gridded climate data using the EALCO model run at a 30 min time step. This long-term high-resolution dataset was used to characterize the spatiotemporal variations in ET across Canada. The results show that annual ET varied from 600 mm yr−1 over several regions in the south to less than 100 mm yr−1 in the northern Arctic. Nationally, ET in summer (i.e., June to August) comprised 65% of the annual total amount. ET in the cold season remained mostly below 10 mm month−1 over the country. Negative monthly ET was obtained over the Arctic region in winter, indicating EALCO simulated a larger amount of condensation than ET. Overall, the mean ET over the entire Canadian landmass for the 30 yr was 239 mm yr−1, or 44% of its corresponding precipitation. Comparisons of available ET studies in Canada revealed large uncertainties in ET estimates associated with using different approaches. The scarcity of ET measurements for the diverse ecosystems in Canada remains a significant challenge for reducing the uncertainties; this gap needs to be addressed in future studies to improve capabilities in climate/weather modeling and water resource management.
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.
How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".