Temporally and zonally varying atmospheric waveguides – climatologies and connections to quasi-stationary waves
Bibliographic record
Abstract
Abstract. Atmospheric waveguides have been linked to amplified quasi-stationary Rossby waves and thus to extreme weather events in the mid-latitudes. Here, we compare different methods of calculating temporally and spatially varying waveguides, including different ways of separating the waveguides (background flow) from waves. We compare waveguides from potential vorticity (PV) gradients (“PV waveguides”) with barotropic waveguides based on what is known as the stationary wavenumber, or KS (“KS waveguides”), which is calculated from the zonal wind. The PV waveguides use a PV rolling-zonalization method to calculate the background flow. Conversely, the background flow for the KS waveguides is calculated using time and zonal filtering. We isolate the impacts of the background flow methodology from the different waveguide definitions by calculating PV waveguides using the same background flow calculation method as the KS waveguides. There are notable differences between the waveguides identified by the two definitions. KS waveguides are more frequent in summer than in winter, whilst PV waveguides are more frequent in winter, regardless of the method of background flow calculation. Composites of days with high spatially averaged waveguide strength over particular regions show distinct differences between the two waveguide definitions. Strong KS waveguides in some regions are associated with a double-jet structure, consistent with previous research; this structure is rarely present for strong PV waveguides. The presence of high geopotential heights occurs with the double-jet anomaly, consistent with atmospheric blocking creating the KS waveguide conditions through the influence on local zonal winds, highlighting that this methodology does not sufficiently separate non-linear perturbations (i.e. blocking) from the background flow (i.e. waveguides). Significant positive correlations exist between local waveguide strength and the amplitude of quasi-stationary waves; these correlations are stronger and more widespread for PV waveguides than for KS waveguides, and they are strongest when the rolling-zonalization background flow method is used. This study further cautions against using KS waveguides on temporally and/or zonally varying scales, and we recommend rolling-zonalization PV waveguides for the study of waveguides and their connections to quasi-stationary atmospheric waves.
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".