Performance of the Canadian Arctic Prediction System during the YOPP Special Observing Periods
Bibliographic record
Abstract
As a contribution to the Year of Polar Prediction (YOPP), Environment and Climate Change Canada (ECCC) developed the Canadian Arctic Prediction System (CAPS), a high-resolution (3-km horizontal grid-spacing) deterministic Numerical Weather Prediction (NWP) system that ran in real-time from February 2018 to November 2021. During YOPP, ECCC was also running two other operational systems that cover the Arctic: the 10-km Regional Deterministic Prediction System (RDPS) and the 25-km Global Deterministic Prediction System (GDPS). The performance of these three systems over the Arctic was monitored and routinely compared during 2018, both subjectively and with objective verification scores. This work provides a description of CAPS and compares the surface variable objective verification for the Canadian deterministic NWP systems operational during YOPP, focusing on the Arctic winter and summer Special Observing Periods (Feb-March and July-Aug-Sept, 2018). CAPS outperforms RDPS and GDPS in predicting near-surface temperature, dew-point temperature, wind and precipitation, in both seasons and domains. All three systems exhibit a diurnal cycle in the near-surface temperature biases, with maxima at night and minima in day-time. In order to mitigate representativeness issues associated with complex topography, model tile temperatures are adjusted to the station elevation by applying a standard atmosphere lapse-rate: especially for the coarse-resolution models, the lapse-rate adjustment reduces the temperature cold biases characterising mountain terrains. Verification of winter precipitation is performed by adjusting solid precipitation measurement errors from the undercatch in windy conditions: the Canadian models’ systematic positive bias, which was artificially inflated by the undercatch, is reduced by the adjustment, to attain neutral bias. These YOPP dedicated intense verification activities have identified some strengths, weaknesses and systematic behaviours of the Canadian deterministic prediction systems at high latitudes: these results can serve as a benchmark, for comparison and further development. Moreover, this YOPP verification exercise has revealed some issues related to the verification of surface variables and has led to the development of better verification practices for the polar regions (and beyond).
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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 | 0.001 |
| Science and technology studies | 0.002 | 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".