Assimilated ozone from EOS‐Aura: Evaluation of the tropopause region and tropospheric columns
Bibliographic record
Abstract
Retrievals from the Microwave Limb Sounder (MLS) and the Ozone Monitoring Instrument (OMI) on EOS‐Aura were included in the Goddard Earth Observing System version 4 (GEOS‐4) ozone data assimilation system. The distribution and daily to seasonal evolution of ozone in the stratosphere and troposphere during 2005 are investigated. In the lower stratosphere, where dynamical processes dominate, comparisons with independent ozonesonde and Measurement of Ozone and Water Vapour by Airbus In‐Service Aircraft (MOZAIC) data indicate mean agreement within 10%. In the troposphere, OMI and MLS provide constraints on the ozone column, but the ozone profile shape results from the parameterized ozone chemistry and the resolved and parameterized transport. Assimilation of OMI and MLS data improves tropospheric column estimates in the Atlantic region but leads to an overestimation in the tropical Pacific and an underestimation in the northern high and middle latitudes in winter and spring. Transport and data biases are considered in order to understand these discrepancies. Comparisons of assimilated tropospheric ozone columns with ozonesonde data reveal root‐mean‐square (RMS) differences of 2.9–7.2 Dobson units (DU), which are smaller than the model‐sonde RMS differences of 3.2–8.7 DU. Four different definitions of the tropopause using temperature lapse rate, potential vorticity (PV), and isentropic surfaces or ozone isosurfaces are compared with respect to their global impact on the estimated tropospheric ozone column. The largest sensitivity in the tropospheric ozone column is found near the subtropical jet, where the ozone‐ or PV‐determined tropopause typically lies below the lapse rate tropopause.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".