Mesoscale wind climate modelling in steep mountains
Bibliographic record
Abstract
Abstract Although the Mesoscale Community Compressible (MC2) model successfully reproduces the wind climate (for wind energy development purposes) of the Gaspé region, equivalent simulations for the steep mountainous southern Yukon have been unsatisfactory. An important part of the problem lies in the provision of suitable boundary conditions in the lower troposphere. This paper will describe an alternative provision of boundary conditions to the MC2 model based partly on standard National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis statistics, however, with modified lower tropospheric conditions based on local radiosonde measurements. The MC2 model is part of the AnemoScope wind energy simulation toolkit which applies statistical‐dynamical downscaling of basic large‐scale weather situations (i.e., the NCEP/NCAR Reanalysis) to simulate the steadystate wind climate of a complex region. A case study summarized here imposes a typical mean winter temperature inversion on the boundary conditions to reduce downward momentum transfer in the MC2 model over the Whitehorse region. In conjunction with this step, the geostrophic wind at the boundaries is held constant (with height) in speed and direction, based on the (observed) dominant southwesterly winds above the mountaintops. The resulting simulation produces wind directions within the modelled domain that are in much better agreement with the available measurements. However, despite the imposed atmospheric stability, downward transfer of horizontal momentum from aloft still appears to exceed that occurring in nature. It is recommended that (in future studies of this type regarding mountain wind climate) the input statistics processed from the NCEP/NCAR Reanalysis be modified by referencing the geostrophic winds to a level above the mountaintops. It is also suggested that converting to a height (z) coordinate system may reduce the erroneous downward momentum transfer found in the present terrain‐following grid.
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 | 0.000 | 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".