SlideServe
Menu
Préférences
© SlideServe · v2026

A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO

sricharson avatar
16 diapositives · 192 Views · Jan 02, 2020

A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO. Wim de Rooy & Pier Siebesma Royal Netherlands Meteorological Institute (KNMI). Hirlam 1D. Hirlam but with: Statistical cloud scheme Tiedtke mass flux convection scheme with updates:

A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO - slide 1
01 / 16A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO
1 / 17

Télécharger la présentation

A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation
  1. A simple parameterization for detrainment in shallow cumulusHirlam results for RICO Wim de Rooy & Pier Siebesma Royal Netherlands Meteorological Institute (KNMI)

  2. Hirlam 1D Hirlam but with: • Statistical cloud scheme • Tiedtke mass flux convection scheme with updates: • Mass flux closure at cloud base (Neggers et al. 2002) • Triggering (Jacob & Siebesma 2003) • versions with a conventional or a new lateral mixing concept

  3. Fixed  and : • No dependence on environmental • humidity conditions Mass flux concept • Buoyancy sorting concept • Complex, fundamental problems M M M Courtesy: Stephan de Roode Fraction of environmental air

  4. Conventional fixed =z-1 and =0.00275 m-1 okay for BOMEX but for RICO? What’s going on?

  5. LES results for BOMEX, ARM and RICO show: • Not much variation in . For a correct simulation of the Mass flux profile, =z-1 is good enough. • Much more variation in . The value of  mainly depends on: - Cloud Layer Height - Environmental conditions

  6. Cloud Layer Height dependence Cloud ensembles Mass flux profiles with =z-1 and =0.00275 ztop Cloud layer depth=1000m z (e.g. BOMEX) zbot M ztop Cloud layer depth=200m zbot M ztop Cloud layer depth=2000m e.g. RICO z zbot M

  7. Dependence on environmental conditions Eliminate cloud height dependence by looking at a non-dimensionalized mass flux profile LES Non-dimensionalized mass flux profiles ARM case LES z*

  8. Suppose we would know the non-dimensionless mass flux m* halfway the cloud layer at height z* Ztop Z* Zbot

  9. From LES, the non-dimensionalized mass flux half way the cloud layer as a function of c

  10. Good results with the new parameterization for ARM, BOMEX and:

  11. Conclusions • The proposed detrainment parameterization is simple but includes two important dependencies: • Cloud layer height dependence • Current mass flux schemes ignore this dependence which evidently can lead to large discrepancies with observed mass flux profiles. • Environmental conditions • With the c dependence the new scheme can be seen as an alternative for more complex buoyancy sorting schemes (without some of the disadvantages)

  12. Conclusions • Good results for a wide range of shallow convection cases (BOMEX, ARM, RICO) • Easy to incorporate in existing mass flux schemes (and will be incorporated in an EDMF dual mass flux environment)

  13. LES: The non-dimensionalized mass flux half way the cloud layer as a function of RH

  14. Dependence on environmental conditions Eliminate cloud height dependence by looking at a non-dimensionalized mass flux profile LES Non-dimensionalized mass flux profiles ARM case Non-dimensionalized mass flux profiles with fixed  and 