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Record W6948375031 · doi:10.5063/aa/dpennington.34.7

IPCC Climate Change Data: CGCM1 A2a Model: 2020 Radiation

2005· dataset· en· W6948375031 on OpenAlexaboutno aff

Bibliographic record

VenueUC Santa Barbara · 2005
Typedataset
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsForcing (mathematics)Climate modelAlbedo (alchemy)Radiative forcingClimate changeAtmosphere (unit)Atmospheric modelGreenhouse gasTransient climate simulation

Abstract

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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. For the A2 emissions scenario the main emphasis is on a strengthening of regional and local culture, with a return to family values in many regions. The A2 world consolidates into a series of roughly continental economic regions, emphasizing local cultural roots. In some regions, increased religious participation leads many to reject a materialist path and to focus attention on contributing to the local community. Elsewhere, the trend is towards ncreased investment in education and science and growth in economic productivity. Social and political structures diversify with some regions moving towards stronger welfare systems and reduced income inequality, while others move towards "lean" government. Environmental concerns are relatively weak, although some attention is paid to bringing local pollution under control and maintaining local environmental amenities. The A2 world sees more international tensions and less cooperation than in A1 or B1. People, ideas and capital are less mobile so that technology diffuses slowly. International disparities in productivity, and hence income per capita, are maintained or increased. With the emphasis on family and community life, fertility rates decline only slowly, although they vary among regions. Hence, this scenario family has high population growth (to 15 billion by 2100) with comparatively low incomes per capita relative to the A1 andB1 worlds, at US$7,200 in 2050 and US$16,000 in 2100.Technological change is rapid in some regions and slow in others as industry adjusts to local resource endowments, culture, and education levels. Regions with abundant energy and mineral resources evolve more resource intensive economies, while those poor in resources place very high priority on minimizing import dependence through technological innovation to improve resource efficiency and make use of substitute inputs. The fuel mix in different regions is determined primarily by resource availability. And divisions among regions persist in terms of their mix of technologies, with high-income but resource-poor regions shifting toward advanced post fossil technologies (renewables in regions of large land availability, nuclear in densely populated, resource poor regions) and low-income resource-rich regions generally relying on older fossil technologies.With substantial food requirements, agricultural productivity is one of the main focus areas for innovation and RD efforts in this future. Initially high levels of soil erosion and water pollution are eventually eased through the local development of more sustainable high-yield agriculture.Although attention is given to potential local and regional environmental damage, it is not uniform across regions. For example, sulfur and particulate emissions are reduced in Asia due to impacts on human health and agricultural production but increase in Africa as a result of the intensified exploitation of coal and other mineral resources. The A2 world sees high energy and carbon intensity, and correspondingly high GHG emissions. Its CO2 emissions are the highest of all four scenario families. Data are available for the following periods:1961-1990, 2010-2039; 2040-2069; and 2090-2099, mean and monthly 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), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.164
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0050.055
Open science0.0160.012
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.163
GPT teacher head0.394
Teacher spread0.231 · 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".

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Citations0
Published2005
Admission routes1
Has abstractyes

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