Observational and Modeling Studies of High Ice Water Content Clouds: Implications for Process–Oriented Understanding
Notice bibliographique
Résumé
High ice water content (HIWC) regions with small ice crystals, where ice water contents (IWCs) are greater than 1.5 g m-3 and median mass diameters (MMDs) less than about 300 micrometers, occur above tropical mesoscale convective systems (MCSs) and can have detrimental impacts on aircraft engines. Data collected by the French Falcon aircraft and the National Research Council of Canada Convair-580 during the 2014 and 2015 High Altitude Ice Crystals and High Ice Water Content (HAIC/HIWC) projects are revisited here along with coordinated modeling studies to investigate processes that can produce such HIWCs. In particular, data collected from 2014 in the vicinity of Darwin Australia and from 2015 in the vicinity of Cayenne French Guyana are used to determine how bulk microphysical properties (e.g., number concentration, IWC, median volume diameter) and characteristics of ice crystal size distributions (i.e., multimodal nature, parameters fit to gamma distributions for each mode) vary with environmental conditions such as temperature, vertical velocity, MCS age, distance from MCS core, and surface characteristics. It is determined that temperature and vertical velocity are the biggest controls of small ice crystals, but younger cells, stronger convective strengths and closer proximity to convective cores also increase the relative importance of small crystals.Numerical simulations conducted using the Weather Research and Forecasting model with four different bulk microphysics schemes generally reproduce the observed temperature, dew-point, and wind structure. However, comparison of regime-specific observations against properties simulated over Cayenne using a variety of existing parameterization schemes show that although the coverage and evolution of convection is well predicted, simulations overestimate the intensity and spatial extent of observed airborne X-band radar reflectivity and do not well depict the peak of observed size distributions with maximum dimensions between 0.1 and 1 mm. To explore formation mechanisms for large numbers of small ice crystals, a series of simulations varying the representation of secondary ice production (SIP) processes were conducted. Simulations including one of three SIP mechanisms separately (i.e., the Hallett&#8211;Mossop mechanism, fragmentation during ice&#8211;ice collisions, and shattering of freezing droplets) did not replicate the observed ratio of number concentration divided by IWC. However, the simulation including all three SIP processes produced HIWC regions consistent with observations in terms of number concentration and radar reflectivity, which was not replicated using the original P3 two-ice category configuration that only included the Hallett-Mossop mechanism. In summary, observations and simulations show primary ice production plays a key role in generating HIWC regions at temperatures < -40 Celsius, shattering of freezing droplets dominates ice particle production in HIWC regions between -15 and 0 Celsius during the early stage of convection, and fragmentation during ice&#8211;ice collisions dominates between -15 and 0 Celsius during the later stage of convection and between -40 and -20 Celsius over the whole convection period. This study thus shows the dominant role of SIP processes in the formation of numerous small crystals in HIWC regions. Implications for future measurement and modeling needs are discussed.
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».