Radiative feedback of dust aerosols on the East Asian dust storms
Bibliographic record
Abstract
A new radiative parameterization scheme of dust aerosol has been developed within a mesoscale dust storm (DS) forecasting model to study the direct radiation of dust aerosol by incorporating both online forecasted dust concentrations and the updated dust reflective index. The radiation‐induced temperature variations are fed back online to the model dynamics, resulting in two‐way interactions between meteorology and dust aerosols. For a typical DS of 16–18 April 2006 in East Asia, the study shows that the strong extinction by dust leads to significant changes in the radiation flux from surface to the top of atmosphere, which tends to decrease the air temperature in the lower dust aerosol layers but to increase the air temperature in the upper dust aerosol layers. Consequently, variations of 3‐D temperature fields reduce the cold air in the upper atmosphere, increase the sea level air pressure, decrease surface wind velocity, and eventually weaken the Mongolian cyclones owing to the blocking effects. These changes, in return, have impacts on the emission, transport, and deposition processes of DS. The interactively simulated total dust emission from the ground is reduced by over 50%, and the 72‐hour averaged optical depth of dust aerosols declines by about 33% compared to the one‐way model without dust direct radiative feedback, which indicates strong negative feedback effects. The findings of this study also suggest that online calculation of dust direct radiative effects in a mesoscale dust prediction model may lead to an improvement in the prediction of meteorological elements such as temperature, wind, and pressure during the dust events owing to its improved calculation accuracy of regional radiation budgets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".