MétaCan
Menu
← Back to cohort
Record W4221102226 · doi:10.5194/egusphere-egu22-9156

Mechanisms and drivers of the 2021 Pacific Northwest heatwave

2022· preprint· en· W4221102226 on OpenAlexaboutno aff
Dominik L. Schumacher, Mathias Hauser, Sonia I. Seneviratne

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPrecipitationAnticycloneTroposphereEnvironmental scienceClimatologyMoistureAtmospheric sciencesClimate modelTemperate climateClimate systemClimate changeMeteorologyGeographyGeologyOceanographyEcology

Abstract

fetched live from OpenAlex

The Pacific Northwest is characterized by a temperate climate with mild to warm summers, yet in late June 2021, the region was ravaged by extreme heat and ensuing wildfires. With local daily maximum temperatures 20 °C above the long term mean, the occurrence of such a brute heatwave makes it imperative to understand the underlying physical processes. Using the Community Earth System Model, we simulate this exceptional event and disentangle its thermodynamic and dynamic drivers. A factorial experimental design based on the ExtremeX framework is employed, in which the mid and upper-tropospheric circulation and soil moisture are either prescribed using reanalysis (ERA5) data, or calculated interactively. With this setup, the lower troposphere can always respond to land and ocean surface fluxes. Our results indicate that, despite widespread drought conditions in the analysis region (including the metropolitan areas of Portland, Seattle and Vancouver) and surroundings, the dynamic contribution far exceeded the effect of anomalous soil moisture. We further disentangle the soil moisture contribution into initial and event-driven, and find that precipitation in the first half of June 2021 prevented even higher near-surface temperatures by weakening the initial effect. Overall, the analysis highlights the role of the anticyclone that governed the large-scale circulation, and whose intensity during summertime and within 45°N–60 °N surpasses any other event in recent decades. As such, this heatwave presents an opportunity to investigate whether our Earth System Model of choice is capable of generating similarly extreme heat at large spatial scales on its own, i.e. with fully interactive winds. While the mean intensity of hot anticyclonic summer events over land (45°N–60 °N) is underestimated with respect to our reference simulation with prescribed circulation, the model portrays stronger variability with an interactive atmosphere and hence generates heatwaves that rival and even surpass the large-scale temperature anomalies of the Pacific Northwest 2021 event. Our investigation also points to strong temperature anomalies aloft, which we track back in time with a Lagrangian trajectory model driven by ERA5 data. By doing so, we find evidence for intense latent heating of the air that would later be part of the anticyclone, and mixed into the unusually deep atmospheric boundary layer. We further demonstrate that in the absence of anthropogenic climate change, an otherwise identical heatwave would not have reached such extreme temperatures. Altogether, this study shows that for the right atmospheric configuration and fuelled by our changing climate, unprecedented heat may be unleashed even in regions traditionally considered devoid of excessive heatwaves.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.004
GPT teacher head0.174
Teacher spread0.170 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicAtmospheric and Environmental Gas Dynamics→French-language works237,207→