Validation of Methane and Carbon Monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations
Notice bibliographique
Résumé
Abstract. The Sentinel-5 Precursor (S5P) mission with the TROPOspheric Monitoring Instrument (TROPOMI) onboard has been measuring solar radiation backscattered by the Earth's atmosphere and its surface since its launch on 13 October 2017. Methane (CH4) and carbon monoxide (CO) data with a spatial resolution (initially 7 x 7 km2, upgraded to 5.5 x 7 km2 on 6th of August 2019) have been retrieved from shortwave infrared (SWIR) and near-infrared (NIR) measurements since the end of November 2017 and made available to the experts for early validation and quality checks before the official product release. In this paper, we present for the first time the S5P CH4 and CO validation results (covering a period from November 2017 to September 2020) using global Total Carbon Column Observing Network (TCCON) and Infrared Working Group of the Network for the Detection of Atmospheric Composition Change (NDACC-IRWG) network data, accounting for a priori alignment and smoothing uncertainties in the validation, and testing the sensitivity of validation results towards the application of advanced co-location criteria.We found that the required bias (systematic error) of 1.5 % and random error of 1 % for the S5P standard and bias-corrected methane data are met for measurements over land surfaces with pixels having quality assurance (QA) value > 0.5. The systematic difference between the S5P standard XCH4 and TCCON data is on average −0.69 ± 0.73 %. The systematic difference changes to a value of −0.25 ± 0.57 % for the S5P bias-corrected XCH4 data. We found a correlation of above 0.6 for most stations, which is mostly dominated by the seasonal cycle. The contributions of smoothing uncertainty at the individual stations are estimated and found to be dependent on the location. The highest contribution of the smoothing uncertainty is observed for mid-latitude TCCON stations and high latitude stations for NDACC. A seasonal dependency of the relative bias is seen. We observe a high bias during the springtime measurements at high SZA and a decreasing bias with increasing SZA for the rest of the year.We found that the required bias (systematic error) of 15 % and random error of < 10 % for the S5P carbon monoxide data are met in general for measurements over all surfaces with pixels having quality assurance value of > 0.5. There are a few stations where this is not the case, mostly due to co-location mismatches and the limited availability of co-located data. We compared the S5P XCO data with respect to standard TCCON XCO and unscaled TCCON XCO (without application of the empirical scaling factor) data sets. The systematic difference between the S5P XCO and the TCCON data is on average 9.14 ± 3.33 % (standard TCCON XCO data) and 2.36 ± 3.22 % (unscaled TCCON XCO data). We found that the systematic difference between the S5P CO column and NDACC CO column data (excluding two stations that were obvious outliers) is on average 6.44 ± 3.79 %. We found a correlation of above 0.9 for most TCCON and NDACC stations indicating that the temporal variations in CO column captured by the ground-based instruments are reproduced very similarly by the S5P CO column. The contribution of smoothing uncertainty at the individual stations is estimated and found to be significant. They are found to be dependent on the location with large changes seen for stations located in the Southern Hemisphere as compared to the Northern Hemisphere and at highly polluted stations. A cone co-location criterion, which gives a better match between the ground-based instrument's line-of-sight and satellite pixels, seems to give better results for high latitude stations and stations located close to emission sources. The validation results for the clear-sky and cloud cases of S5P pixels are comparable to the validation results including all pixels with quality assurance value of > 0.5. We observe that the relative bias increases with increasing SZA. We estimated this increase is about 10 % over the complete range of measurement SZAs.The study shows the high quality of S5P CH4 and CO data by validating the products against reference global TCCON and NDACC stations covering a wide range of latitudinal bands, atmospheric conditions, and surface conditions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».