Impacts of Local Soil Moisture Anomalies on the Atmospheric Circulation and on Remote Surface Meteorological Fields during Boreal Summer: A Comprehensive Analysis over North America
Bibliographic record
Abstract
Abstract A series of stationary wave model (SWM) experiments are performed in which the boreal summer atmosphere is forced, over a number of locations in the continental United States, with an idealized diabatic heating anomaly that mimics the atmospheric heating associated with a dry land surface. For localized heating within a large portion of the continental interior, regardless of the specific location of this heating, the spatial pattern of the forced atmospheric circulation anomaly (in terms of 250-hPa eddy streamfunction) is largely the same: a high anomaly forms over west-central North America and a low anomaly forms to the east. In supplemental atmospheric general circulation model (AGCM) experiments, similar results are found; imposing soil moisture dryness in the AGCM in different locations within the U.S. interior tends to produce the aforementioned pattern, along with an associated near-surface warming and precipitation deficit in the center of the continent. The SWM-based and AGCM-based patterns generally agree with composites generated using reanalysis and precipitation gauge data. The AGCM experiments also suggest that dry anomalies imposed in the lower Mississippi River valley have remote surface impacts of particularly large spatial extent, and a region along the eastern half of the U.S.–Canadian border is particularly sensitive to dry anomalies in a number of remote areas. Overall, the SWM and AGCM experiments support the idea of a positive feedback loop operating over the continent: dry surface conditions in many interior locations lead to changes in atmospheric circulation that act to enhance further the overall dryness of the continental interior.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".