MétaCan
Menu
Back to cohort
Record W4321481615 · doi:10.5194/egusphere-egu23-6167

The northern hight latitude dust belt

2023· preprint· en· W4321481615 on OpenAlexaboutno aff
Outi Meinander, Pavla Dagsson‐Waldhauserová, Ana Vucovic Vimic

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsnot available
Fundersnot available
KeywordsLatitudeEnvironmental scienceHigh latitudeAtmospheric sciencesGeology

Abstract

fetched live from OpenAlex

Identifying the locations of local dust sources and their emission, transport, and deposition processes is important for understanding the multiple impacts of dust on the Earth's systems. We have recently provided a significant update to the scientific understanding on the climatically and environmentally significant high-latitude dust (HLD) sources. Based on the presented evidence (Meinander et al. 2022), we have suggested a “northern high latitude dust belt” (Meinander et al. 2022), defined as the area north of 50∘ N, with a “transitional HLD-source area” extending at latitudes 50–58∘ N in Eurasia and 50–55∘ N in Canada and a “cold HLD-source area” including areas north of 60∘ N in Eurasia and north of 58∘ N in Canada, with currently “no dust source” area between the HLD and low-latitude dust (LLD) dust belt, except for British Columbia. We estimate the high-latitude land area with potential dust activity to cover over 560 000 km2 with very high potential for dust emission, and over 240 000 km2 with the highest potential for dust emission.We have identified, described, and quantified the source intensity (SI) values, which show the potential of soil surfaces for dust emission scaled to values 0 to 1 concerning globally best productive sources, using the Global Sand and Dust Storms Source Base Map (G-SDS-SBM). This includes 64 HLD sources in our collection for the northern (Alaska, Canada, Denmark, Greenland, Iceland, Svalbard, Sweden, and Russia) and southern (Antarctica and Patagonia) high latitudes. Our work also included model results on HLD emission, long-range transport, and deposition at various scales of time and space, and we have specified key climatic and environmental impacts of HLD and related research questions, which could improve our understanding of HLD sources, on clouds and climate feedback, atmospheric chemistry, marine environment, cryosphere, and cryosphere–atmosphere feedbacks. For example, we estimated that about 57% of the dust deposition in snow- and ice-covered Arctic regions was from high latitude dust sources.We gratefully acknowledge Douglas Hamilton.Citation: Meinander, O. et al. Newly identified climatically and environmentally significant high-latitude dust sources, Atmos. Chem. Phys., 22, 11889–11930, https://doi.org/10.5194/acp-22-11889-2022, 2022.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.004

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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicAeolian processes and effectsFrench-language works237,207