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

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Presentation on theme: "GCSS BLCWG update Chris Bretherton, BLCWG Chair Thanks to Andy Ackerman (LES case leader) Margreet vanZanten/Bjorn Stevens SCM and LES case participants."— 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 w e = 0.35 cm s -1. Almost all LES models predict w e to within 30% (good) but most considerably underestimate LWP.

3 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 w e and turbulent velocity variance profiles were also most consistent with observations. Red obs GreenLES full range BlueLES interquartile range LES mean UCLA-0 (no SGS) UCLA-1 (Smagorinsky SGS)

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 w e within 50% of observed. Most SCMs similar at high vs. normal resolution, correctly predict no drizzle.

5 DYCOMS RF02 nocturnal drizzling stratocumulus N d ~ 45-70 cm -3

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11 Participating SCMs NameSCMTurbulenceCld. Frac. Microphys. AustinCCCMa4? ChlondECHAM4-5 moist TKE + w e pdfSundquist KitagawaJMA 1 st -order KRH-pdfSundquist LappenCAM3 [CAM3+UW] Nonlocal, sfc-based. K-profile, explicit-w e RH/stab RH Autoconv./coll., N = 65 cm -3 Larson2GPDF-HOC From pdfKhair.-Kogan w. joint pdf LockUKMO Nonlocal, explicit-w e RH-pdfAutoconv./coll., N = 100 cm -3 MenonGISS SCM Dry adjustmentRH/stabAutoconv./coll. (del Genio) Roode RACMO [EC CY23R4] K-profile, explicit-w e Tiedtke Sundquist, P  LWC

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

13 Cloud-base drizzle vs. LWP

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

15 Discussion Small revisions to case (N d, 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.


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