Biases of Global Tropopause Altitude Products in Reanalyses and Implications for Estimates of Tropospheric Column Ozone
Bibliographic record
Abstract
Accuracy of global tropopause altitude products from reanalyses is important to applications of the products, including the derivation of tropospheric column ozone (TCO). Here, monthly biases in lapse-rate tropopause pressure (PLRT) in two reanalyses, NCEP/NCAR and MERRA-2, and associated implications for estimating TCO are examined, based on global radiosonde observations over 1980–2017 at 689 stations. Our analysis suggests that the global mean PLRT is underestimated by −2.3 hPa in NCEP/NCAR and by −0.9 hPa in MERRA-2, mainly attributable to large negative biases around the subtropics (~20°–50°) in both hemispheres, with generally positive biases at other latitudes. Overall, NCEP/NCAR outperforms MERRA-2 in the Northern Hemisphere but underperforms MERRA-2 in the Southern Hemisphere. PLRT biases in the two reanalyses vary more evidently with latitude than with longitude. From winter to summer, the peaks of negative PLRT biases around the subtropics shift poleward by ~10°. Approximately, 70% of the reanalysis PLRT biases are within −10–10 hPa. Consequently, a negative (positive) PLRT bias induces a positive (negative) TCO bias. In absolute magnitude, the mean ozonesonde TCO bias attributable to PLRT biases is ~0.2, ~0.8 and ~1.2 Dobson Units (DU) if a PLRT bias is within 0–5, 10–15, and 10–15 hPa. Using a global ozone climatology, we estimate that the global mean bias in TCO induced by the PLRT biases in both reanalyses is positive, being 0.64 DU (or 2.2%) for NCEP/NCAR and 0.28 DU (or 1.1%) for MERRA-2.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".