1 / 15

GCSS BLCWG update

GCSS BLCWG update. Chris Bretherton, BLCWG Chair Thanks to Andy Ackerman (LES case leader) Margreet vanZanten/Bjorn Stevens SCM and LES case participants Other BLCWG attendees. RF01 case: LES (Stevens et al. 2005 MWR). 10 groups submitted 16 LES runs.

seasonc
Download Presentation

GCSS BLCWG update

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GCSS BLCWG update Chris Bretherton, BLCWG Chair Thanks to Andy Ackerman (LES case leader) Margreet vanZanten/Bjorn Stevens SCM and LES case participants Other BLCWG attendees

  2. RF01 case: LES (Stevens et al. 2005 MWR) • 10 groups submitted 16 LES runs. • Observed cloud deepens and thickens very slightly in 8 hrs with well-constrained we = 0.35 cm s-1. Almost all LES models predict we to within 30% (good) but most considerably underestimate LWP.

  3. LES mean UCLA-0 (no SGS) UCLA-1 (Smagorinsky SGS) Red obs Green LES full range Blue LES interquartile range • A subset (4 of 16 LESs) predicted LWP better. These models used subgrid schemes which strongly inhibited SGS vertical mixing within the inversion layer. Their we and turbulent velocity variance profiles were also most consistent with observations.

  4. RF01 SCM LWP and entrainment evolution • Within an hour, 10 SCMs diverge toward a wide range of LWP bracketing obs. • After this time, in most SCMs, LWP quasisteady with we within 50% of observed. • Most SCMs similar at high vs. normal resolution, correctly predict no drizzle.

  5. DYCOMS RF02 nocturnal drizzling stratocumulus Nd ~ 45-70 cm-3

  6. Participating SCMs

  7. Surface drizzle vs. LWP • Diverse sensitivities. • Microphysical parameterizations or droplet size assumptions?

  8. Cloud-base drizzle vs. LWP

  9. Precip vs. no-precip sensitivity studies In drizzly models (except JMA), LWP increased substantially by drizzle suppression.

  10. Discussion • Small revisions to case (Nd, u, fixed fluxes); revised submissions due Aug. 1 (must include real drizzle). • WG preferred not to initiate new case or meeting yet; better to digest results we have and try to improve model performance on these two cases. Provides an opportunity for simplified microphysics-only intercomparison in a specified flow field. • Lots of interest in a RICO case when obs. are mature, and in some global GCM sensitivity studies (perhaps in intercomparison mode, perhaps using Pacific x-sect) to drizzle and sedimentation in boundary layer cloud.

More Related