Use of EarthCARE products within the EUMETSAT validation facility for Level 2 Cloud products  
Notice bibliographique
Résumé
The EUMETSAT central facility generates and disseminates several cloud products from both geostationary and low-Earth orbit passive sensors, which serve a variety of applications, spanning from nowcasting, to numerical weather prediction to climate monitoring. The retrieved cloud parameters include cloud/dust/ash detection, cloud top height and microphysics (particle effective radius and optical thickness). All EUMETSAT products are validated and continuously quality monitored against independent reference data to ensure state-of-the-art algorithm performance, product quality/accuracy compliant with user and operational service requirements, and stability and continuity/consistency over time (i.e., coping with instrument degradation, algorithm evolutions, updated calibration, etc.).This contribution provides an overview of the tools developed at EUMETSAT to perform the monitoring and validation of cloud products against lidar/radar measurements, which have established themselves as a trustworthy source for the detection of cloud layers and superior to any other validation data source when it comes to estimate the cloud height, particle microphysical and optical properties. We focus on the status of these tools and the plans for their further development and release to users. The tools are fully automated and handle the validation of products from both geostationary and polar-orbiting satellites, including data download and organisation, instrument co-location and the development of comparison metrics. The toolkit includes:A tool performing the validation of EUMETSAT against space-based radar and lidar measurements. For almost two decades (since 2006), the CloudSat and CALIPSO observations have been the prime reference source for this validation. EarthCARE will provide the natural continuation to the observations provided by these two instruments, which reached their end of life in autumn 2023. We discuss the use of EarthCARE products as envisaged in the validation activities with a particular focus on the retrieval of cloud properties based on the synergistic use of lidar, radar and multi-spectral imager data. Furthermore, the higher sensitivity measurements expected from HSRL and CPR on board EarthCARE with respect to CALIPSO and CloudSat will require careful investigations in order to transfer the current experience in the use of A-Train products as a validation reference to the new EarthCARE products. A tool performing the validation of EUMETSAT cloud products against ground-based radar and lidar measurements from ACTRIS (the European Research Infrastructure for the observation of Aerosol, Cloud and Trace Gases), specifically using the cloud products generated by the ACTRIS-Cloudnet processing facility maintained by the Finnish Meteorological Institute (FMI). This validation activity fills in the gap between CloudSat/CALIPSO end of life and EarthCARE launch. METIS-Clouds (Monitoring and Evaluation of Thematic Information from Space), a web application tool providing access to the collection of monitoring and validation results of EUMETSAT cloud products, on a global and regional level. This collection is exploited by both the in-house algorithm developers (to identify and fix issues, bugs, etc.) and the users (to assess the product accuracy).
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».