How does tropospheric VOC chemistry affect climate? An investigation of preindustrial control simulations using the Community Earth System Model version 2
Bibliographic record
Abstract
Because of their computational expense, models with comprehensive tropospheric chemistry have typically been run with prescribed sea surface temperatures (SSTs), which greatly limits the model's ability to generate climate responses to atmospheric forcings. In the past few years, however, several fully coupled models with comprehensive tropospheric chemistry have been developed. For example, the Community Earth System Model version 2 with the Whole Atmosphere Community Climate Model version 6 as its atmospheric component (CESM2-WACCM6) has implemented fully interactive tropospheric chemistry with 231 chemical species as well as a fully coupled ocean. Earlier versions of this model used a “SOAG scheme” that prescribes bulk emission of a single gas-phase precursor to secondary organic aerosols (SOAs). In contrast, CESM2-WACCM6 simulates the chemistry of a comprehensive range of volatile organic compounds (VOCs) responsible for tropospheric aerosol formation. Such a model offers an opportunity to examine the full climate effects of comprehensive tropospheric chemistry. To examine these effects, 211-year preindustrial control simulations were performed using the following two configurations: (1) the standard CESM2-WACCM6 configuration with interactive chemistry over the whole atmosphere (WACtl) and (2) a simplified CESM2-WACCM6 configuration using a SOAG scheme in the troposphere and interactive chemistry in the middle atmosphere (MACtl). The middle-atmospheric chemistry is the same in both configurations, and only the tropospheric chemistry differs. Differences between WACtl and MACtl were analyzed for various fields. Regional differences in annual mean surface temperature range from −4 to 4 K. In the zonal average, there is widespread tropospheric cooling in the extratropics. Longwave forcers are shown to be unlikely drivers of this cooling, and possible shortwave forcers are explored. Evidence is presented that the climate response is primarily due to increased sulfate aerosols in the extratropical stratosphere and cloud feedbacks. As found in earlier studies, enhanced internal mixing with SOAs in WACtl causes widespread reductions of black carbon (BC) and primary organic matter (POM), which are not directly influenced by VOC chemistry. These BC and POM reductions might further contribute to cooling in the Northern Hemisphere. The extratropical tropospheric cooling results in dynamical changes, such as equatorward shifts of the midlatitude jets, which in turn drive extratropical changes in clouds and precipitation. In the tropical upper troposphere, cloud-driven increases in shortwave heating appear to weaken and expand the Hadley circulation, which in turn drives changes in tropical and subtropical precipitation. Some of the climate responses are quantitatively large enough in some regions to motivate future investigations of VOC chemistry's possible influences on anthropogenic climate change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".