Recent changes in tropospheric water vapor over the Arctic as assessed from radiosondes and atmospheric reanalyses
Bibliographic record
Abstract
Changes in tropospheric water vapor over the Arctic are examined for the period 1979 to 2010 using humidity and temperature data from nine high latitude radiosonde stations north of 70°N with nearly complete records, and from six atmospheric reanalyses, emphasizing the three most modern efforts, MERRA, CFSR and ERA‐Interim. Based on comparisons with the radiosonde profiles, the reanalyses as a group have positive cold‐season humidity and temperature biases below the 850 hPa level and consequently do not capture observed low‐level humidity and temperature inversions. MERRA has the smallest biases. Trends in column‐integrated (surface to 500 hPa) water vapor (precipitable water) computed using data from the radiosondes and from the three modern reanalyses at the radiosonde locations are mostly positive, but magnitudes and statistical significance vary widely between sites and seasons. Positive trends in precipitable water from MERRA, CFSR and ERA‐Interim, largest in summer and early autumn, dominate the northern North Atlantic, including the Greenland, Norwegian and Barents seas, the Canadian Arctic Archipelago and (on the Pacific side) the Beaufort and Chukchi seas. This pattern is linked to positive anomalies in air and sea surface temperature and negative anomalies in end‐of‐summer sea ice extent. Trends from ERA‐Interim are weaker than those from either MERRA or CFSR. As assessed for polar cap averages (the region north of 70°N), MERRA, CFSR and ERA‐Interim all show increasing surface‐500 hPa precipitable over the analysis period encompassing most months, consistent with increases in 850 hPa air temperature and 850 hPa specific humidity. Data from all of the reanalyses point to strong interannual and decadal variability. The MERRA record in particular shows evidence of artifacts likely introduced by changes in assimilation data streams. A focus on the most recent decade (2001–2010) reveals large differences between the three reanalyses in the vertical structure of specific humidity and temperature anomalies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".