MétaCan
Menu
Back to cohort
Record W6967176831 · doi:10.5063/aa/dpennington.63.5

IPCC Climate Change Data: CGCM1 B2a Model: 2080 Mean Temperature

2005· dataset· en· W6967176831 on OpenAlexaboutno aff

Bibliographic record

VenueUC Santa Barbara · 2005
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsForcing (mathematics)Climate modelClimate changeAlbedo (alchemy)Atmospheric modelRadiative forcingGreenhouse gasAtmosphere (unit)Flux (metallurgy)

Abstract

fetched live from OpenAlex

The first version of the Canadian Global Coupled Model, CGCM1, and its control climate are described by Flato et al. (1999). The atmospheric component of the model is essentially GCMII described by McFarlane et al. (1992). It is a spectral model with triangular truncation at wave number 32 (yielding a surface grid resolution of roughly 3.7 degrees x3.7 degrees ) and 10 vertical levels. The ocean component is based on the GFDL MOM1.1 code and has a resolution of approximately 1.8 degrees x1.8 degrees and 29 vertical levels. The model uses heat and water flux adjustments obtained from uncoupled ocean and atmosphere model runs (of 10 years and 4000 years duration respectively), followed by an `adaption' procedure in which the flux adjustment fields are modified by a 14 year integration of the coupled model. A multi-century control simulation with the coupled model has been performed using the present-day CO2 concentration to evaluate the stability of the coupled model's climate, and to compare the modelled climate and its variability to that observed. An ensemble of four transient climate change simulations has been performed and is described in Boer et al. (1999a; b). Three of these simulations use an effective greenhouse gas forcing change corresponding to that observed from 1850 to the present, and a forcing change corresponding to an increase of CO2 at a rate of 1% per year (compounded) thereafter until year 2100. The direct forcing effect of sulphate aerosols is also included by increasing the surface albedo (as in Reader and Boer, 1999) based on loadings from the sulphur cycle model of Langner and Rodhe (1991). The fourth simulation considers the effect of greenhouse gas forcing only. The change in climate predicted by a model clearly depends directly on this specification of greenhouse gas (and aerosol) forcing, and of course these are not well known. The prescription described above is similar to the IPCC "business as usual" scenario, and using a standard scenario allows the results of this model to be compared to those of other modelling groups around the world. Some initial results from these simulations are presented below. The climate sensitivity of CGCM1 is about 3.5 degrees C.From the IPCC website: The B2 world is one of increased concern for environmental and social sustainability. Education and welfare programs are widely pursued leading to reductions in mortality and, to a lesser extent, fertility. The population reaches about 10 billion people by 2100, consistent with both the United Nations and IIASA median projections. Income per capita grows at an intermediary rate to reach about US$12,000 by 2050. By 2100 the global economy might expand to reach some US$250 trillion. International income differences decrease, although not as rapidly as in scenarios of higher global convergence (A1, B1). Local inequity is reduced considerably through the development of stronger community support networks. Generally high educational levels promote both development and environmental protection. Indeed, environmental protection is one of the few remaining truly international priorities. However, strategies to address global environmental challenges are less successful than in B1, as governments have difficulty designing and implementing agreements that combine environmental protection with mutual economic benefits. The B2 storyline presents a particularly favorable climate for community initiative and social innovation, especially in view of high educational levels. Technological frontiers are pushed less than in A1 and B1 and innovations are also regionally more heterogeneous. Globally, investment in R& continues its current declining trend, and mechanisms for international diffusion of technology and know-how remain weaker than in scenarios A1 and B1 (but higher than in scenario A2). Some regions with rapid economic development and limited natural resources place particular emphasis on technology development and bilateral co-operation. Technical change is therefore uneven. The energy intensity of GDP declines at about one percent per year, in line with the average historical experience of the last two centuries. Land-use management becomes better integrated at the local level in the B2 world. Urban and transport infrastructure is a particular focus of community innovation, contributing to a low level of car dependence and less urban sprawl. An emphasis on food self-reliance contributes to a shift in dietary patterns towards local products, with reduced meat consumption in countries with high population densities. Energy systems differ from region to region, depending on the availability of natural resources. The need to use energy and other resources more efficiently spurs the development of less carbon-intensive technology in some regions. Environment policy cooperation at the regional level leads to success in the management of some transboundary environmental problems, such as acidification due to SO2, especially to sustain regional self-reliance in agricultural production. Regional cooperation also results in lower emissions of NOx and VOCs, reducing the incidence of elevated tropospheric ozone levels. Although globally the energy system remains predominantly hydrocarbon-based to 2100, there is a gradual transition away from the current share of fossil resources in world energy supply, with a corresponding reduction in carbon intensity. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099 Mean monthly and change fields.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0070.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.053

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 head0.078
GPT teacher head0.330
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueUC Santa BarbaraFrench-language works237,207