Preliminary results from the FARCE 2015 campaign: multidisciplinary study of the forest–gas–aerosol–cloud system on the tropical island of La Réunion
Bibliographic record
Abstract
The Forests gAses aeRosols Clouds Exploratory (FARCE) campaign was conducted in March–April 2015 on the tropical island of La Réunion. For the first time, several scientific teams from different disciplines collaborated to provide reference measurements and characterization of La Réunion vegetation, volatile organic compounds (VOCs), biogenic VOCs (BVOCs), (bio)aerosols and composition of clouds, with a strong focus on the Maïdo mountain slope area. The main observations obtained during this 2-month intensive field campaign are summarized. They include characterizations of forest structure, concentrations of VOCs and precursors emitted by forests, aerosol loading and optical properties in the planetary boundary layer (PBL), formation of new particles by nucleation of gas-phase precursors, ice-nucleating particles concentrations, and biological loading in both cloud-free and cloudy conditions. Simulations and measurements confirm that the Maïdo Observatory lies within the PBL from late morning to late evening and that, when in the PBL, the main primary sources impacting the Maïdo Observatory are of marine origin via the Indian Ocean and of biogenic origin through the dense forest cover. They also show that (i) the marine source prevails less and less while reaching the observatory; (ii) when in the PBL, depending on the localization of a horizontal wind shear, the Maïdo Observatory can be affected by air masses coming directly from the ocean and passing over the Maïdo mountain slope, or coming from inland; (iii) bio-aerosols can be observed in both cloud-free and cloudy conditions at the Maïdo Observatory; (iv) BVOC emissions by the forest covering the Maïdo mountain slope can be transported upslope within clouds and are a potential cause of secondary organic aerosol formation in the aqueous phase at the Maïdo Observatory; and (v) the simulation of dynamics parameters, emitted BVOCs and cloud life cycle in the Meso-NH model are realistic, and more advanced Meso-NH simulations should use an increased horizontal resolution (100 m) to better take into account the orography and improve the simulation of the wind shear front zone within which lies the Maïdo Observatory. Using various observations and simulations, this work draws up an inventory of the in situ studies that could be performed in La Réunion and at the Maïdo Observatory. It also aims to develop scientific collaborations and to support future scientific projects in order to better understand the forest–gas–aerosol–cloud system in an insular tropical environment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".