Data · dataset · 2026
Causes and implications of persistent atmospheric carbon dioxide biases in Earth System Models
Listed in National Center for Atmospheric Research
The strength of feedbacks between a changing climate and future COâ concentrations is uncertain and difficult to predict using Earth System Models (ESMs).
Description
We analyzed emission-driven simulationsâin which atmospheric COâ levels were computed prognosticallyâfor historical (1850-2005) and future periods (Representative Concentration Pathway (RCP)â8.5 for 2006â2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5).
Comparison of ESM prognostic atmospheric COâ over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric COâ. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric COâ biases and future COâ levels for the multimodel ensemble.
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We used this relationship to create a contemporary COâ tuned model (CCTM) estimate of the atmospheric COâ trajectory for the 21st century. The CCTM yielded COâ estimates of 600±14âppm at 2060 and 947±35âppm at 2100, which were 21âppm and 32âppm below the multimodel mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric COâ, COâ-induced radiative forcing, and COâ-induced temperature increases for the RCPâ8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble.
Our analysis provided evidence that much of the model-to-model variation in projected COâ during the 21st century was tied to biases that existed during the observational era and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of COâ from Mauna Loa, our analysis suggests that uncertainties in future climate projections can be reduced.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7hh6m14 ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/causes-and-implications-of-persistent-atmospheric-carb… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=b4ef0af5-6a78-4ead-a66c-701a6719d… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | b4ef0af5-6a78-4ead-a66c-701a6719dd64 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |