Possible impacts of climate change on fog in the Arctic and subpolar North Atlantic
Bibliographic record
Abstract
Abstract. A conventional parameterization of midlatitude warm fog occurrence, based on in situ observations, is employed to estimate marine surface visibility in the Arctic and North Atlantic from three datasets: an ensemble member of the Hadley Earth System (HadGEM2) model and a nested regional WRF simulation that follow historical and future emissions scenarios for 1979–2100, and the ERA-Interim reanalysis for 1979–2004. Over large scales (of an entire year and region), all three gridded datasets agree well in terms of variables like surface air temperature, whose systematic differences seem small by comparison with its predicted change over the course of this century. On the other hand, systematic differences are more apparent in large-scale estimates of relative humidity and visibility. Large differences are attributed to a sensitivity to representation bias that is inherent in the formulation of each individual model and analysis. Two simple linear calibrations are examined, both of which assume that an in situ based parameterization is broadly consistent with the use of marine (ICOADS) observations of air and dew point temperature as an error-free reference. A single-step calibration is considered that takes the mean and variance of ICOADS frequency distributions as a reference. A two-step calibration is also performed in which ICOADS collocations are taken as a reference for the ERA reanalysis, which in turn is taken as a large-scale reference for the 1979–2004 HadGEM2 and WRF simulations. Both linear calibrations are applied (locally in time and space to air and dew point temperature) to the future climate scenarios of HadGEM2 and WRF. Although ICOADS observations are not error-free and parameterized visibility estimates are unlikely to capture much more than half the variance found in observations, attempts are made to present consistent regional changes in the frequency of high relative humidity, as a proxy for warm fog occurrence. The large-scale decrease in visibility over the 21st century is in the range of 8 %–12 % in the Arctic and 0 %–5 % in the North Atlantic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".