Time series of mesospheric species measured using ground-based microwave spectrometry: Retrieval and Error estimation
Bibliographic record
Abstract
As the human emission of greenhouse gases continue to increase, the atmosphere is changing. The mesosphere region is particularly interesting as the magnitude of\ntemperature change in this region is expected to be larger, than in the lower layers of the atmosphere. However, there is still much uncertainty related to the long-term\neffects of these changes. It is therefore important to have instruments that can provide long-term monitoring of the dynamics and chemistry of the middle atmosphere.\n\nSpecies with long photochemical lifetime can be used to study the dynamics of the mesosphere. At the Onsala Space Observatory two such species, CO and H2O,\nhave been measured over a number of years with microwave spectrometers. These instruments can provide us with continuous measurements of the mesosphere over long\ntime periods. This thesis concerns characterising and improving the measurements and retrievals from the two microwave spectrometers.\n\nThis thesis puts forth a possible improvement in the inversion algorithm used for retrieving time-series from ground-based microwave spectrometers. By using a\ntwo dimensional retrieval method, the inversions can take into account the temporal correlation of the atmospheric state. The new method was tested on the 22 GHz spec-\ntrometer measuring mesospheric water vapour at OSO. The result is a more flexible retrieval that removes the problem of ad-hoc selecting data averaging times before\nperforming an inversion. An additional improvement offered by the new method is the ability to consistently interpolate the retrieved data in order to close measurement\ngaps or re-grid the data.\n\nThe thesis also compares a six year long time series of mesospheric CO from the 115 GHz spectrometer at OSO to measurements from contemporary satellite instruments.\nThe systematic errors of the instrument are estimated to ±40 % from 2002-2004 and ±20 % from 2004-2008. Compared to the satellite measurements, the measurements\nfrom the OSO radiometer have a mean difference of less than or equal to 25 %. This is consistent with the combined systematic errors of both the ground-based and satellite\ninstruments.\n\nThe thorough error characterisation, and the improved retrieval method, presented in this thesis ensure that the data produced by the microwave spectrometers at OSO remain relevant and important for the future study of the middle atmosphere.\n
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".