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Record W2911082519 · doi:10.5194/acp-19-9927-2019

Investigation of Arctic middle-atmospheric dynamics using 3 years of H <sub>2</sub> O and O <sub>3</sub> measurements from microwave radiometers at Ny-Ålesund

2019· article· en· W2911082519 on OpenAlexfundno aff
Franziska Schranz, B. Tschanz, Rolf Rüfenacht, Klemens Hocke, Mathias Palm, Niklaus Kämpfer

Bibliographic record

VenueAtmospheric chemistry and physics · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftCanadian Space AgencySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsAtmospheric sciencesStratosphereOzoneEnvironmental scienceWater vaporMicrowave radiometerAtmosphere (unit)ArcticOzone depletionClimatologyRadiometerMeteorologyPhysicsGeographyOceanographyRemote sensingGeology

Abstract

fetched live from OpenAlex

We used 3 years of water vapour and ozone measurements to study the dynamics in the Arctic middle atmosphere. We investigated the descent of water vapour within the polar vortex, major and minor sudden stratospheric warmings and periodicities at Ny-Ålesund. The measurements were performed with the two ground-based microwave radiometers MIAWARA-C and GROMOS-C, which have been co-located at the AWIPEV research base at Ny-Ålesund, Svalbard (79 ∘ N, 12 ∘ E), since September 2015. Both instruments belong to the Network for the Detection of Atmospheric Composition Change (NDACC). The almost continuous datasets of water vapour and ozone are characterized by a high time resolution of the order of hours. A thorough intercomparison of these datasets with models and measurements from satellite, ground-based and in situ instruments was performed. In the upper stratosphere and lower mesosphere the MIAWARA-C water vapour profiles agree within 5 % with SD-WACCM simulations and ACE-FTS measurements on average, whereas AuraMLS measurements show an average offset of 10 %–15 % depending on altitude but constant in time. Stratospheric GROMOS-C ozone profiles are on average within 6 % of the SD-WACCM model, the AuraMLS and ACE-FTS satellite instruments and the OZORAM ground-based microwave radiometer which is also located at Ny-Ålesund. During these first 3 years of the measurement campaign typical phenomena of the Arctic middle atmosphere took place, and we analysed their signatures in the water vapour and ozone measurements. Two major sudden stratospheric warmings (SSWs) took place in March 2016 and February 2018 and three minor warmings were observed in early 2017. Ozone-rich air was brought to the pole and during the major warmings ozone enhancements of up to 4 ppm were observed. The reversals of the zonal wind accompanying a major SSW were captured in the GROMOS-C wind profiles which are retrieved from the ozone spectra. After the SSW in February 2018 the polar vortex re-established and the water vapour descent rate in the mesosphere was 355 m d −1 . Inside of the polar vortex in autumn we found the descent rate of mesospheric water vapour from MIAWARA-C to be 435 m d −1 on average. We find that the water vapour descent rate from SD-WACCM and the vertical velocity w‾* of the residual mean meridional circulation from SD-WACCM are substantially higher than the descent rates of MIAWARA-C. w‾* and the zonal mean water vapour descent rate from SD-WACCM agree within 10 % after the SSW, whereas in autumn w‾* is up to 40 % higher. We further present an overview of the periodicities in the water vapour and ozone measurements and analysed seasonal and interannual differences.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.187
Teacher spread0.168 · 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 designObservational
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

Citations13
Published2019
Admission routes1
Has abstractyes

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