SCIENCE · INVESTIGATE AND EXPLAIN

Write a supported historical attribution claim

Connect archived comparisons with the IPCC synthesis while preserving causal and observational scope.

Learning outcome: Produce a reproducible brief that states the supported human-influence conclusion and identifies limits on extrapolation.

Starting recap

The interface interprets published evidence; it does not rerun attribution studies. Its panels have overlapping scientific inputs.

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Try

The assessed human contribution accounts for observed warming in 2010–2019 relative to 1850–1900; this is not an attribution of every local event.

Open the experiment

Predict

Does one annual band comparison establish the cause of an individual weather disaster?

Your prediction and reason

Experiment

Write a brief with a timeline comparison, assessed contributions, uncertainty labels and an explicit boundary on the conclusion.

Compare archived attribution evidence

Published attribution evidence · archived model comparisons and assessments · Frozen attribution-v1: IPCC AR6 SPM.1 annual observations and archived CMIP6 comparisons, plus SPM.2 assessed 2010–2019 contributions. All use 1850–1900 as reference, but annual values and a decade are distinct. Simulation bands are ensemble 5th–95th percentiles; assessment ranges retain their own likely/very-likely labels. No models are trained, fitted or rerun here.

Highlighted annual year: 2019 Assessed driver to inspect: Total human influence

Reset keeps your prediction, captures and practice history.

This investigation interprets published evidence for human influence on warming. The archived natural-only comparison differs from simulations including human and natural influences. The IPCC assessment attributes the observed warming over its assessed period to human influence; the viewer helps inspect that evidence but does not perform a new attribution study.

Annual comparison at 2019 (°C relative to 1850–1900)
Evidence	Value / ensemble mean	5th percentile	95th percentile	Observed − mean
Observed annual change	1.226	Not supplied here	Not supplied here	Not a model comparison
Human + natural simulations	1.190	0.738	1.871	0.036
Natural-only simulations	0.049	-0.136	0.307	1.177

The residual subtracts the archived ensemble mean from the observed annual estimate. It is not an attributed human contribution, a forecast error score or a significance test. Individual years can depart from ensemble means because variability is not synchronized. Inside or outside a model band is not, by itself, a complete causal test. The observational series has no uncertainty column in this file; that does not mean it is perfectly known.

Total human influence: Total human influence is an aggregate assessed contribution. Do not add it again to its greenhouse-gas and other-human component categories.

Published centers and ranges for the assessed 2010–2019 decade
Quantity	Center °C	Lower °C	Upper °C	Range label
Observed warming (observations)	1.06	0.88	1.21	Very likely
Total human influence	1.07	0.80	1.30	Likely
Well-mixed greenhouse gases	1.50	1.00	2.00	Likely
Other human drivers	-0.40	-0.80	0.00	Likely
Solar and volcanic drivers	0.00	-0.10	0.10	Likely
Internal variability	0.00	-0.20	0.20	Likely

Total human influence is an aggregate, so adding it to its component categories double-counts. Rounded component centers need not reproduce the independently assessed total exactly; adding lower and upper endpoints does not produce a valid combined uncertainty range. The source does not supply a joint distribution for that operation. A zero center for natural influences or internal variability does not imply zero effects in every year.

The annual panel and decade panel address different time averages. Neither should be subtracted directly from the earlier NASA series, which uses a 1951–1980 reference. That frozen NASA record starts in 1880 and cannot reconstruct the entire 1850–1900 reference. This historical assessment is not a latest-year estimate. These two IPCC panels draw on overlapping scientific evidence, not two statistically independent replications.

Inspect source versions and range definitions

Snapshot attribution-v1 preserves SPM.1 version 20221116 and SPM.2 version 20210809. The SPM.1 file marks missing model values with 1.00E+20; they are normalized to unavailable and never plotted as real temperatures. Its model fields contain archived historical-ssp245 and natural-only comparisons, not forecasts run in this browser. CEDA's generic SPM.2 panel-b description says “very likely,” but the official figure caption and SPM A.1.3 say “likely.” This viewer follows the official caption and report, retaining the discrepancy in provenance. No Gaussian distributions or new probability levels are inferred.

Data adapted under CC BY 4.0: Gillett, Malinina, Kaufman and Neukom (2023), SPM.1 data; Szopa and colleagues (2021), SPM.2 data; and IPCC (2021), Summary for Policymakers, pp. 3–32, doi:10.1017/9781009157896.001. This site normalizes missing values, selects records and redraws the numerical evidence; it does not reproduce the published figure artwork.

2019 observed change 1.226 °C. Observed minus human-plus-natural mean 0.036 °C; observed minus natural-only mean 1.177 °C.

Total human influence: assessed center 1.07 °C, likely range 0.80 to 1.30 °C for 2010–2019 relative to 1850–1900. Annual residuals are descriptive comparisons, not significance tests or independently estimated causal contributions.

Observation to attach to a capture

Captures preserve year and driver selections in attribution-v1. They replay comparisons of archived observations, simulation summaries and assessed contributions, not a new attribution analysis or causal experiment.

Understand

State the supported conclusion clearly

For 2010–2019 relative to 1850–1900, the assessed human contribution accounts for the observed global warming. This is the conclusion supported by the IPCC attribution synthesis, not simply a claim that two plotted series correlate. The human central estimate is 1.07°C and the observed estimate is 1.06°C, with their respective assessed ranges.

The IPCC AR6 Summary for Policymakers synthesizes observations, physically based models and attribution studies. This investigation makes selected evidence inspectable. It does not rerun the studies, calculate a new attribution probability or provide an independent replication of the whole assessment.

An appropriately bounded conclusion can be firm. Saying that the browser does not perform the original analysis is not a reason to imply that the source assessment leaves human influence and a natural-only explanation equally supported.

Connect the comparison to the conclusion

Highlight 2019 in the timeline. The observed anomaly is 1.226°C. It is close to the human-plus-natural ensemble mean of about 1.18995°C and far above the natural-only mean of about 0.04939°C. The full curves show how that comparison develops over time rather than hiding the context behind one selected year.

Then inspect the contributions panel. Solar/volcanic and internal-variability assessments are centered near zero over the assessed decade, with much smaller ranges than the observed warming. Human greenhouse-gas warming is partly offset by other human cooling influences. Together, these summaries support a coherent account of the observed net change.

The SPM.1 dataset and SPM.2 dataset are complementary views of assessed evidence. Their underlying scientific inputs overlap. Do not call the two panels statistically independent replications merely because they are stored in different files.

Build a reproducible evidence brief

On paper, write a four-part brief. First name the historical claim, period and baseline. Second provide one numerical timeline comparison with units and the simulation-band meaning. Third provide the observed and total-human assessed estimates with their distinct uncertainty labels. Fourth explain a limit that prevents extending the conclusion to another question without more evidence.

Choose the highlighted year before reading its detailed residuals. Keep the full timeline visible and explain whether that year is representative of the long-term comparison. A single small residual is not the complete attribution argument; a single larger residual does not automatically overturn it.

Include the frozen dataset version and source citations. The underlying CEDA files are available under CC BY 4.0 and require attribution to their data creators and the IPCC report. The displayed chart is an interpretation of archived data, not a newly acquired climate observation.

Reject extensions the evidence does not support

Global historical attribution does not identify the cause of an individual local storm or determine a country’s contribution from these files alone. The assessed intervals concern a historical decade, not a forecast for the next decade. Nor do they establish a direct conversion from atmospheric ppm to the emissivity slider in the earlier greenhouse lab.

The 2020 timeline provides an especially concrete boundary: observation is present but the two simulation summaries are missing. An evidence brief must report that gap rather than fill it silently. The browser cannot claim a selected-year residual where its source supplies no model mean.

Other limits require different evidence rather than different arithmetic. A regional impact question needs regional data and relevant mechanisms. A policy choice needs consequences and values beyond temperature contributions. Preserve the supported global attribution conclusion while identifying those separate questions.

Transfer by repairing a misleading summary

A summary says: “The browser proves every recent weather disaster was human-caused, because its 2019 observed value lies inside one simulation band.” Rewrite it as a supported historical conclusion and identify the missing evidence for its event claim.

Check the attribution-evidence transfer

The archived comparison and IPCC synthesis support that human influence accounts for observed global warming over the assessed 2010–2019 period relative to 1850–1900. A single annual band comparison is not the whole attribution analysis. Attributing an individual event requires event-specific observations, definitions and counterfactual analysis, which these files do not supply.

Apply

Public practice checks a specific claim. It does not establish independent mastery.

Distinguish a firm supported global attribution conclusion from unsupported event, regional or future claims.

Your explanation and limitations

Continue

Completion requires a saved prediction, at least one capture and a reflection. Presence checks do not grade your reasoning.

Skipping retains experiments and awards no mastery.

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