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Record W4297217969 · doi:10.1175/jas-d-22-0123.1

An Analytical Solution to the Perturbation Analysis of the Interaction between Downburst Outflows and Atmospheric Boundary Layer Winds

2022· article· en· W4297217969 on OpenAlexaff
Masoud Moeini, Djordje Romanić

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsMcGill University
Fundersnot available
KeywordsOutflowPlanetary boundary layerMeteorologyPhysicsBoundary layerAtmospheric sciencesMechanicsStormPerturbation (astronomy)Geology

Abstract

fetched live from OpenAlex

Abstract Downbursts are negatively buoyant downdrafts that emerge from a storm and spread outward upon hitting the surface. The produced outflow, however, is not spreading through a calm environment, but rather through an atmosphere characterized by larger-scale atmospheric boundary layer (ABL) winds. This interaction between ABL winds and downbursts forms an outflow that is more complex than an outflow created by an isolated downdraft. Here, we propose an analytical solution of the interaction between the ABL winds and an isolated downburst outflow. The model is applicable when the ratio of centerline downdraft velocity to the horizontal ABL velocity at the cloud base is larger than the nondimensional group (H/D)(r/H)1.1, where H is the cloud-base height, D is the diameter of the downdraft, and r is the distance from the centerline of isolated downdraft. Also, the solution is derived for a specific direction in the outflow when the ABL winds and the isolated downburst outflow are aligned and the vertical profiles of radial velocity are self-similar. The model is based on the use of impinging-jet dynamics, their spreading rates, and a universal renormalization group that describes numerous laboratory measurements of velocity profiles of impinging jets issuing into both quiescent and crossflowing backgrounds. The model assumes a “known” base state corresponding to an isolated downburst, and then derives its interaction with ABL winds by way of perturbation analysis. The radial and vertical profiles of horizontal velocity from our analytical model are compared against field observations of actual downbursts and other analytical models and physical simulations of downburst-like outflows. Significance Statement Downbursts are intense downdrafts that emerge from a thunderstorm and spread outward upon hitting the surface. Near-surface wind gusts in a downburst can be similar to those observed in an EF3-rated tornado (∼75 m s−1). A downburst outflow is not spreading through a calm environment, but rather through an atmosphere characterized by larger-scale atmospheric boundary layer (ABL) winds. This interaction between ABL winds and downbursts forms an outflow that is more complex than an outflow created by an isolated downdraft. However, most of the current analytical models of downbursts do not account for this interaction. Using experimental measurements of downburst-like impinging jets and mathematical rigor, our study derives an equation that quantifies this interaction between downburst and ABL winds.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.039
GPT teacher head0.281
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2022
Admission routes1
Has abstractyes

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