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Record W2537682884 · doi:10.5194/gmd-10-4321-2017

Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

2017· article· en· W2537682884 on OpenAlexaff
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sébastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, G. C. Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanović, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie L. Ebi, Tyler D. Eddy, Joshua Elliott, Eric D. Galbraith, Simon N. Gosling, Fred F. Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Donald C. Pierson, Derek P. Tittensor, Robert Vautard, Michelle T. H. van Vliet, Matthias F. Biber, Richard Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris Jones, Heike K. Lotze, Hermann Lotze‐Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, Yoshiki Yamagata

Bibliographic record

VenueGeoscientific model development · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of British ColumbiaDalhousie University
FundersNational Key Research and Development Program of ChinaState Key Laboratory of Urban and Regional EcologyBundesministerium für Bildung und ForschungEuropean CommissionLeibniz-GemeinschaftDepartment for Environment, Food and Rural Affairs, UK GovernmentAgence Nationale de la RechercheMet OfficeBundesministerium für Umwelt, Naturschutz, Bau und ReaktorsicherheitNational Science Foundation
KeywordsCoupled model intercomparison projectRepresentative Concentration PathwaysGlobal warmingGreenhouse gasEnvironmental scienceClimate changeComputable general equilibriumUnited Nations Framework Convention on Climate ChangeClimatologyClimate modelGlobal temperatureGlobal-warming potentialKyoto ProtocolEnvironmental resource managementNatural resource economicsEconomics

Abstract

fetched live from OpenAlex

Abstract. In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a special report in 2018 on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 °C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).

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)0.017
metaresearch head score (Gemma)0.015
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: Protocol · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0060.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0160.003

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 head0.094
GPT teacher head0.399
Teacher spread0.305 · 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
GenreProtocol

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

Citations675
Published2017
Admission routes1
Has abstractyes

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