Using CloudSat data to look at the cloud and precipitation structure in the Arctic
Bibliographic record
Abstract
Clouds and precipitation are fundamental determinates of the Arctic climate. Despite the presence of clouds and storm systems, very few precipitations reach the ground. In fact, polar precipitation patterns are characterized by frequent sublimation of the water particles during their descent. This discrepancy between cloud coverage and storm systems and the amount of precipitation on the ground is not explained because relatively little is known about these features due partly to the lack of available data. Recently, CloudSat, a polar-orbiting satellite, was launched in order to provide unique information about the cloud and precipitation structure of the Arctic, which cannot be measured using current weather instruments. The data is used in the context of the Storm Studies in the Arctic, a field experiment that started in Fall 2007 in the Canadian Arctic, aims at describing the extreme weather occurring over Baffin Island and Iqaluit. The present study focuses on the Southern Baffin Island using data from CloudSat for the area covered by the Storm Studies in the Arctic field experiment. We analyzed 37 passes of CloudSat over Iqaluit and examined cloud altitude and type, environmental conditions like temperature and relative humidity, as well as the precipitation type, size, and rate. Our analysis shows that the cloud structure is characterized by formations that are mostly stratiform, composed of one to two cloud-layers at low- and mid-level, and mostly thin individual clouds. A low cloud base and a large cloud thickness seem to be requirements for precipitation over the region. Although these results do not give satisfying answers regarding what triggers sublimation , they provide general information about the macrostructure of the clouds. This is a first step in understanding why in the Arctic very little precipitation reaches the ground. We believe further information about cloud microstructure can be garnered using data from CloudSat. Our data therefore provides recommendation for the Storm Studies in the Arctic experiment that started after this study was conducted.
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 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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".