MétaCan
Menu
Back to cohort
Record W2268046997 · doi:10.5194/acp-16-305-2016

Radiative and climate impacts of a large volcanic eruption during stratospheric sulfur geoengineering

2016· article· en· W2268046997 on OpenAlexaff
Anton Laakso, Harri Kokkola, Antti‐Ilari Partanen, Ulrike Niemeier, Claudia Timmreck, K. E. J. Lehtinen, H. Hakkarainen, Hannele Korhonen

Bibliographic record

VenueAtmospheric chemistry and physics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsConcordia University
FundersLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaMaj ja Tor Nesslingin SäätiöForschungszentrum JülichUniversity of OxfordAcademy of FinlandBranco Weiss Fellowship – Society in Science
KeywordsRadiative forcingAtmospheric sciencesStratosphereSulfate aerosolVulcanian eruptionRadiative transferAtmosphere (unit)Environmental scienceClimate modelVolcanoClimatologyAerosolClimate changeMeteorologyGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. Both explosive volcanic eruptions, which emit sulfur dioxide into the stratosphere, and stratospheric geoengineering via sulfur injections can potentially cool the climate by increasing the amount of scattering particles in the atmosphere. Here we employ a global aerosol-climate model and an Earth system model to study the radiative and climate changes occurring after an erupting volcano during solar radiation management (SRM). According to our simulations the radiative impacts of the eruption and SRM are not additive and the radiative effects and climate changes occurring after the eruption depend strongly on whether SRM is continued or suspended after the eruption. In the former case, the peak burden of the additional stratospheric sulfate as well as changes in global mean precipitation are fairly similar regardless of whether the eruption takes place in a SRM or non-SRM world. However, the maximum increase in the global mean radiative forcing caused by the eruption is approximately 21 % lower compared to a case when the eruption occurs in an unperturbed atmosphere. In addition, the recovery of the stratospheric sulfur burden and radiative forcing is significantly faster after the eruption, because the eruption during the SRM leads to a smaller number and larger sulfate particles compared to the eruption in a non-SRM world. On the other hand, if SRM is suspended immediately after the eruption, the peak increase in global forcing caused by the eruption is about 32 % lower compared to a corresponding eruption into a clean background atmosphere. In this simulation, only about one-third of the global ensemble-mean cooling occurs after the eruption, compared to that occurring after an eruption under unperturbed atmospheric conditions. Furthermore, the global cooling signal is seen only for the 12 months after the eruption in the former scenario compared to over 40 months in the latter. In terms of global precipitation rate, we obtain a 36 % smaller decrease in the first year after the eruption and again a clearly faster recovery in the concurrent eruption and SRM scenario, which is suspended after the eruption. We also found that an explosive eruption could lead to significantly different regional climate responses depending on whether it takes place during geoengineering or into an unperturbed background atmosphere. Our results imply that observations from previous large eruptions, such as Mount Pinatubo in 1991, are not directly applicable when estimating the potential consequences of a volcanic eruption during stratospheric geoengineering.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.196
Teacher spread0.192 · 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

Citations59
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAtmospheric chemistry and physicsSame topicClimate Change and GeoengineeringFrench-language works237,207