Solar radiation in the Mackenzie River Basin : retrieval from satellite measurements and evaluation of atmospheric models
Bibliographic record
Abstract
Accurate determination of solar flux at the top of the atmosphere (TOA), which can only be made from satellite observations, is essential for climate studies. In the present study, we developed a new technique to derive the solar fluxes at the TOA and at the surface from operational meteorological satellites. Two key steps in the technique are the narrowband to broadband (NTB) conversion and deriving the net solar flux at the surface from TOA observations. We developed a new NTB conversion algorithm from ScaRaB observations and radiation transfer model simulations. In deriving the net solar fluxes at the surface from TOA measurements, the effects of absorbing aerosols have been investigated. The technique described above has been applied to AVHRR data to derive a dataset of solar flux in the Mackenzie River Basin (MRB) for the Canadian GEWEX Enhanced Study (CAGES) period from June 1998 to September 1999. The derived net solar fluxes at the surface were evaluated with the surface measurements in the basin and good agreement was achieved. Radiation fields from two atmospheric models used in the Mackenzie GEWEX Study (MAGS) project, the Canadian Regional Climate Model (CRCM) and the Global Environmental Multiscale (GEM) model, were evaluated against satellite retrievals of radiation fluxes in the present study. It was found that the CRCM simulated the TOA reflected flux well in the MRB for the summer of 1994, but large biases were found in the partition of absorbed solar radiation between the atmosphere and the earth's surface. The net surface solar radiation was found to be overestimated by about 15% in the CRCM. Evaluation of the preliminary output from the new version of CRCM shows substantial improvement. Evaluation of radiation fields from the GEM model shows good agreement under clear skies, but under cloudy skies, the TOA albedo simulated by the GEM model in the MRB was about 30% lower than observations for the summer of 1999.
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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 | 0.004 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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 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".