Water vapor, cloud liquid water paths, and rain rates over northern high latitude open seas
Bibliographic record
Abstract
Data from the Special Sensor Microwave Imager (SSMI; years 1987–2006), Advanced Microwave Scanning Radiometer, and a surface‐based radiometer at Barrow, Alaska are examined for insights into the behavior of water vapor, cloud liquid water and rainrates over the northern high latitude seas. We evaluated two separate sets of retrievals, and achieved the best results through combining one that contained explicit monthly mean sea ice fractions with the Wentz V6 water vapor path (WVP), cloud liquid water path (LWP), and rainrate (RR) retrievals. The water vapor path retrieval shows no sensitivity to a proxy for sub‐pixel sea ice presence, while the liquid water path retrievals are sensitive to sea ice presence during summertime but otherwise the Wentz internal sea‐ice screening appears effective. The rainrate retrieval is highly sensitive to any sea ice during all seasons. The seasonal cycle and 1987–2006 time trends are examined. The WVP annual cycle has an amplitude of ∼1 cm at all locations, approximately double a broad winter minimum, with a July maximum phasing that is consistent with a continental influence. Little change occurs between January and April in WVP and LWP. The springtime LWP increase usually occurs in tandem with the WVP increase and slightly lags the falltime WVP decrease. The maximum lag occurs over the northern Pacific, where the maximum LWP occurs in August, one month later than over the northern Atlantic, and is correlated to an August precipitation maximum. The strongest SSMI‐derived trend is an increase in wintertime moisture south of Greenland, with wintertime LWP increases in the Labrador Sea. North of the Bering Strait, where much of the recent summer and autumn sea ice loss has occurred, the autumn WVP and LWP increased from 1989 to 2001 with a subsequent LWP decrease in recent years. The recent decline appears linked to a decrease in cyclone activity. Winter and spring LWP increases from 2002 to the present are noted in the surface‐based data set from Barrow, Alaska. Over the Barents Sea, where much of the recent winter sea ice loss has occurred, winter WVP and LWP have increased over the past decade. A comparison to National Center for Atmospheric Research Community Atmospheric Model Version 3.5 values finds modeled WVPs are slightly underestimated but the amplitude of the annual cycle is similar to that observed. Modeled winter LWPs slightly exceed those measured while the modeled summer LWPs exceed by a factor of two those observed (which are more likely to be positively biased also). The modeled rainrates are similar to retrieved values in the north Pacific, and exceed retrieved values by approximately a factor of 2 in the northeast Atlantic.
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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 | 0.000 | 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) | 0.001 | 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 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".