Mass Changes in a High‐Latitude River Basin From Two Decades of GRACE/GRACE‐FO
Bibliographic record
Abstract
Abstract The rise in global temperatures is amplified in high‐latitude regions, where snow and ice play a vital role in the hydrological cycle. Understanding the impacts of climate change on ecosystems and communities in Northern regions requires accurate hydrological data. Within Northern Canada, in situ data sparsity (in both spatial and temporal resolution) poses a challenge to robust characterization of hydrological trends. The increasing availability of satellite‐derived data can provide an independent measure of terrestrial water storage. This study compares terrestrial water storage anomalies (TWSA) from Gravity Recovery and Climate Experiment (GRACE) and GRACE‐FO to in situ and satellite‐derived precipitation and evaporation products within the Mackenzie River Basin (MRB), Canada, a high‐latitude basin characterized by low population density and significant contribution of freshwater to the Arctic Ocean. Declining trends in TWSA from GRACE/GRACE‐FO in the MRB are not fully explained by corresponding trends in hydrological parameters. Water budget analysis reveals inconsistencies between GRACE/GRACE‐FO derived TWSA and TWSA derived using precipitation, evaporation, and runoff data, which may be attributed to physical processes represented in the GRACE/GRACE‐FO observations. Three models of glacial isostatic adjustment (GIA), namely the ICE6G_D (VM5a), Caron‐18, and LM‐17.3 models, were compared to examine the sensitivity of the GRACE/GRACE‐FO‐derived TWSA to the GIA model (correction) employed, revealing approximately ±1 cm of equivalent water height per year variability in the TWSA linear trend. The results suggest that robust characterization of regional mass processes (e.g., subsidence, residual GIA) within the MRB is necessary to isolate hydrological mass changes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".