Adaptation of the SMOS soil moisture retrieval algorithm for organic-rich soils and its validation over various Northern sites
Bibliographic record
Abstract
From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones and the included dielectric mixing model relating soil moisture to permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher northern latitudes is crucial since these regions are especially sensitive to climate change and a considerable feedback is expected due to carbon liberated from thawing ground of these extremely organic soils. Due to differing structural characteristics and thus varying bound water fractions, the permittivity of organic material is lower than the one of most mineral soils at a given water content. This assumption was verified by means of measurements in organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia. For this purpose, conventional soil moisture sensors were used as well as weak perturbation and waveguide techniques in order to infer effective soil permittivity at the microwave L-band (1-2 GHz). Based on these data, a generic L-band soil moisture – permittivity relation for organic soils was derived and validated with dielectric mixing model runs as well as literature data. Furthermore, the derived function was tested in the L-MEB model. Results showed that modeled data agreed with measurements from a tower-based passive L-band microwave radiometer observing organic-rich soil over a 2 months period in a highly controlled set-up. The generic «organic» empirical model was then implemented in the SMOS Prototype Algorithm to retrieve soil moisture over a site in Northern Finland. The validation with in situ soil moisture observations calibrated for organic soils showed a distinct improvement in the agreement between the satellite and ground datasets when using the «organic» instead of the operational SMOS processor version. This analysis is to be continued in more detail and the validation effort needs to be expanded over as many regions with abundant soil organic matter content as possible. Appropriate in situ observations are currently available from various sites in Alaska, Canada, and the Netherlands. In this communication, first the derivation of the generic L-band «organic» soil moisture-permittivity model will be presented. Focus will then be on the comparison of «organic» SMOS soil moisture retrievals with corresponding operational SMOS products as well as in situ observations over all available sites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".