Spatial Variation in the Synoptic Structure of Convective Systems over the Great Plains
Bibliographic record
Abstract
Abstract During the summer, rainfall over the Rocky Mountains peaks in the afternoon. The diurnal time of maximum rain becomes progressively delayed in going eastward from the Rocky Mountains, such that over much of the Great Plains, maximum rain occurs near 0300 local time. We use Rapid Refresh (RAP) reanalysis data from July and August of 2009–19 to show that there is continuous spatial variation in the mean structure of the high-rain events that occur along this anomalous diurnally propagating rainfall feature. High-rain events that occur farther from the Rockies are more likely to be associated with a larger warm anomaly to the south of the rain event center, a smaller cold anomaly, a larger negative surface pressure anomaly, and increased low-level southerly meridional wind. We also use the Integrated Multi-Satellite Retrievals for GPM (IMERG) rainfall dataset to show that, on hourly time scales, afternoon rainfall that occurs over the Rocky Mountains propagates eastward onto the Great Plains but is rapidly attenuated and becomes negligible east of 100°W. This eastward rainfall propagation appears to be mediated in part by the formation of a low-level cold anomaly and increased surface pressure over the Rocky Mountains, a reversal of the upslope wind, and increased low-level zonal mass convergence over the adjacent near plains. Significance Statement Models have difficulty in simulating the diurnal time of nocturnal rainfall over the Great Plains. Deep convection in this region is often associated with severe weather. Rainfall variability over the Great Plains has a significant impact on soil moisture and agricultural productivity. This paper explores how the structure of deep convective rain events over the Great Plains varies with longitude. The results improve our understanding of deep convection development in the Great Plains and have the potential to contribute to improved forecasts of convective rainfall.
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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 | 0.001 | 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) | 0.001 | 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 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".