TOLNet validation of satellite ozone profiles in the troposphere: impact of retrieval wavelengths
Notice bibliographique
Résumé
Abstract. The Tropospheric Ozone Lidar Network (TOLNet) was applied to validate retrievals of ozone (O3) profiles in the troposphere from the TROPOspheric Monitoring Instrument (TROPOMI) ultraviolet (UV), Cross-track Infrared Sounder (CrIS) infrared (IR), and a combined UV+IR wavelength retrieval from TROPOMI/CrIS. Observations from six separate ground-based lidar systems and various locations of ozonesondes distributed throughout North America and Europe were applied to quantify systematic bias and random errors for each satellite retrieval. Furthermore, TOLNet data were used to intercompare idealized UV, IR, and UV+IR convolved profiles of O3 in the troposphere during case studies representative of high O3 events. This study shows that the combination of wavelengths in satellite retrievals (i.e., UV+IR) increases the sensitivity and vertical resolution of the retrievals of O3 in the troposphere compared to single-wavelength products. The improved sensitivity and vertical resolution in UV+IR retrievals in the middle- and upper-troposphere resulted in tropospheric degree of freedom (DOF) values ~33 % higher compared to UV- and IR-only retrievals. The increased DOFs in the UV+IR retrievals allowed for improved reproduction of mid- and upper-tropospheric O3 enhancements, and to a lesser degree near-surface pollution enhancements, compared to single wavelength satellite products. The validation of O3 profiles in the troposphere retrieved with the UV-only, IR-only, and UV+IR Tikhonov regularised Ozone Profile retrievAl with SCIATRAN (TOPAS) algorithm developed at the Institute for Environmental Physics, University of Bremen demonstrated the utility of using TOLNet as a satellite evaluation data set. TOPAS UV-only, IR-only, and UV+IR wavelength retrievals had systematic biases throughout the troposphere of 11.2 ppb (22.1 %), -1.7 ppb (-0.3 %), and 3.5 ppb (7.8 %), respectively, which meet the tropospheric systematic bias requirements of TROPOMI and CrIS. The primary drivers of systematic bias were determined to be the a priori vertical profile shape, solar zenith angle, and surface albedo. Random errors, representative of uncertainty in the retrievals, were large for all three retrievals with UV-only, IR-only, and UV+IR wavelength retrievals having root mean squared errors (RMSE) throughout the troposphere of 17.4 ppb (19.8 % of mean tropospheric column values), 10.5 ppb (12.6 % of mean tropospheric column values), and 14.0 ppb (14.6 % of mean tropospheric column values), respectively. TOPAS UV-only profiles did not meet the uncertainty requirements defined for TROPOMI for the troposphere; however, CrIS IR-only retrievals did meet the uncertainty requirements defined by this mission. The larger random biases reflect the challenge of retrieving daily O3 profiles due to the limited sensitivity and vertical resolution of these retrievals in the troposphere. Tropospheric systematic biases and random error were lower in IR-only and combined UV+IR retrievals compared to UV-only products due to the increased sensitivity in the troposphere allowing the retrievals to deviate further from the a priori profiles. Consistent daily observations from TOLNet demonstrated that the performance of the three satellite products varied by season and altitude in the troposphere. TOLNet was shown in this study to be a sufficient source of satellite O3 profile validation data in the troposphere which is critical as this data source is the primary product identified for the tropospheric O3 validation of the recently-launched Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission.
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 | 0,003 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».