SCIENCE · INVESTIGATE AND EXPLAIN

Match attribution intervals to their meaning

Distinguish ensemble spread, assessed ranges and compatible periods before comparing evidence.

Learning outcome: Audit uncertainty and scope without inventing joint distributions from marginal endpoints.

Starting recap

Observed assessed warming has a very likely range; panel-b driver contributions have likely ranges, following the official report.

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Try

Adding component low and high endpoints does not reconstruct the published total-human likely range.

Open the experiment

Predict

Can differently labeled uncertainty endpoints be subtracted to obtain a new attribution interval?

Your prediction and reason

Experiment

Compare observed and human assessed intervals, then audit the baseline and time scope of annual, decadal and earlier NASA quantities.

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

Identify the quantity before interpreting its interval

An interval is incomplete without the quantity, period, reference and meaning of its endpoints. The timeline’s simulation bands and the assessed-contributions panel are different kinds of summaries. They must not be treated as interchangeable error bars simply because both appear as shaded or bracketed ranges.

The timeline supplies ensemble means and 5th–95th percentile bounds for each simulation comparison. Its observed annual series has no accompanying uncertainty band in this particular file. Missing observational uncertainty is not evidence of perfect accuracy; it means the selected archive does not provide that field.

The contributions panel assesses 2010–2019 relative to 1850–1900. Observed warming is 1.06°C with a very likely range of 0.88–1.21°C. Total human influence is 1.07°C with a likely range of 0.80–1.30°C. Preserve these distinct labels when comparing their overlap.

Resolve a source-metadata discrepancy explicitly

The CEDA SPM.2 catalogue contains a generic file description calling panel-b ranges “very likely.” The official figure caption and IPCC SPM section A.1.3 identify those attribution ranges as likely. This investigation follows the report’s semantics and records the discrepancy rather than quietly treating every interval alike.

Likely and very likely are calibrated assessment terms, not permission to invent a Gaussian distribution around each center. The stored lower and upper values do not provide a complete probability distribution or dependence structure between categories. You cannot derive arbitrary percentiles or a combined confidence level from these endpoints alone.

For a paper audit, copy the observed interval and the human-influence interval with their labels. Note their overlapping values, but do not claim that the amount of overlap is a p-value or the probability that the estimates agree.

Do not add uncertain endpoints as though they were a joint result

The greenhouse-gas likely range is +1.0 to +2.0°C; the other-human likely range is −0.8 to 0.0°C. Adding low endpoints gives +0.2°C and adding high endpoints gives +2.0°C. That arithmetic does not produce an assessed likely range for total human influence.

The separate ranges do not tell you how their uncertainties vary together. Taking extremes jointly also changes the interpretation of the interval. Use the published total-human range, +0.80 to +1.30°C, rather than manufacturing a replacement from component endpoints.

Likewise, do not add the total-human interval to its component intervals. Overlap of categories is a different problem from dependence of uncertainties, and both can invalidate a seemingly tidy calculation. Label each problem separately in your audit.

Match time and baseline before comparing

The highlighted 2019 annual observation, 1.226°C, is not the same quantity as the assessed 2010–2019 warming of 1.06°C. Their baseline matches, but their averaging periods differ. Subtracting them would describe an annual-versus-decade difference, not an attribution residual.

The earlier NASA lesson used a 1951–1980 reference and a different source product. Its stored 2024 anomaly cannot be compared directly with this historical assessment as though only the driver changed. The frozen NASA series also lacks the full 1850–1900 interval needed to reconstruct that baseline from its own values.

Make a compatibility checklist on paper with quantity, spatial scope, period, baseline and interval meaning. Apply it to one valid same-year timeline comparison and one invalid cross-panel attribution claim. The aim is to explain the mismatch, not merely reject the numbers.

Transfer to an unfamiliar interval claim

A learner says: “The observed range is very likely and the human range is likely, so subtracting their endpoints gives a very likely range for natural warming.” What information is missing, and which source result should be used for the natural contribution?

Check the attribution-uncertainty transfer

The endpoints do not specify a joint distribution or compatible probability calculation, and the two assessment labels differ. Use the published solar/volcanic and internal-variability assessments with their own meanings. Do not manufacture a new natural-attribution interval by subtracting the observed and human ranges.

Apply

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

Explain the source metadata discrepancy and distinguish category overlap from unknown dependence between uncertainties.

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.

Previous: Interpret assessed human and natural contributions Next: Write a supported historical attribution claim

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