Evaluating the Snow Crystal Size Distribution and Density Assumptions within a Single-Moment Microphysics Scheme
Bibliographic record
Abstract
Abstract The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was a field campaign designed to obtain aircraft, surface, and radar observations of clouds and precipitation in support of improving the simulation of snowfall and cold season precipitation, their microphysical processes represented within forecast models, and radiative properties relevant to remotely sensed retrievals. During the campaign, a midlatitude cyclone tracked along the U.S.–Canadian border on 22 January 2007, producing an extensive area of snowfall. Observations of ice crystals from this event are used to evaluate the assumptions and physical relationships for the snow category within the Goddard six-class, single-moment microphysics scheme, as implemented within the Weather Research and Forecasting (WRF) model. The WRF model forecast generally reproduced the precipitation and cloud structures sampled by radars and aircraft, permitting a comparison between C3VP observations and model snowfall characteristics. Key snowfall assumptions in the Goddard scheme are an exponential size distribution with fixed intercept and effective bulk density, and the relationship between crystal diameter and terminal velocity. Fixed values for the size distribution intercept and density did not represent the vertical variability of naturally occurring populations of aggregates, and the current diameter and fall speed relationship underestimated terminal velocities for all sizes of crystals.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".