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Subtropical Stratocumulus and its Effect on Climate

Subtropical Stratocumulus and its Effect on Climate. Ph.D. Defense Peter Caldwell 7/24/07. ~250km. (true-color MODIS image of SE Pacific, 10/16/01). Motivation:. Stratus clouds cover over 1/4 of the globe!. Annual ISCCP Low Cloud Amount. Annual ERBE Net Rad. Forcing.

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Subtropical Stratocumulus and its Effect on Climate

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  1. Subtropical Stratocumulus and its Effect on Climate Ph.D. Defense Peter Caldwell 7/24/07 ~250km (true-color MODIS image of SE Pacific, 10/16/01)

  2. Motivation: Stratus clouds cover over 1/4 of the globe! Annual ISCCP Low Cloud Amount Annual ERBE Net Rad. Forcing Graphics Courtesy of Dennis Hartmann 40 40 -90 0 80 -40 0 No Data Percent W m-2 and, of all cloud types, have the strongest cloud forcing (cloud forcing = clear-sky TOA rad. flux – observed TOA rad. flux) Graphics courtesy Dennis Hartmann

  3. “A mere 4% increase in the area of the globe covered by low level stratus clouds would be sufficient to offset the 2-3K predicted rise in global temperature due to a doubling of CO2.” -Randall et al (1984)

  4. Are Low Clouds Increasing or Decreasing? Surface Observer Network Norris (1999) finds a global increase, but cautions that finding is uncertain Satellites ISCCP shows global decrease (Norris, 2005) Corrupted by temporal evolution of viewing-angle bias (Evan et al, 2007) GCMs No consistent picture Currently GFDL shows less, CAM shows more (e.g. Medeiros et al, 2007)

  5. Condensation/ evaporation warm/cool BL How Does Sc Work? qt=qv+ql sl=cpT+gz-Lql Free Troposphere Subsiding warm air + cold SST = strong inversion zi Strong LW cooling at cloud top destabilizes BL Entrainment warms, dries BL Boundary Layer (BL) Entrainment drying → large LHF sl(0) ≈ cpSST →SHF small Ocean

  6. Goals • Use boundary-layer (BL) budgets to deduce diurnal cycle of entrainment • Compare these results with output from a Large-Eddy Simulation (LES) • Use the LES to extend the observations

  7. East Pacific Investigation of Climate (EPIC) Overview • During this time, radiosonde, cloud remote sensing, and surface measurements were taken aboard the NOAA vessel Ronald H. Brown • The EPIC campaign included 6 • days (Oct. 16-22nd, 2001) at 85oW, • 20oS

  8. Data Synthesis

  9. EPIC Radiosonde Results • Surprisingly well-mixed! • Noticable diurnal cycle of well-mixedness • Large zidiurnal cycle

  10. The Mass Budget Subsidence pushes the BL down balance between subsidence and entrainment Entrainment forces the BL up Ocean zi/t + u•zi= we - ws Subsidence rate Cloud-top height tendency Horizontal advection of cloud-top height Entrainment rate

  11. zi Total Water Mixing Ratio (qt) Budget qt=qv+ql Free trop. Entrainment Dqt Advective Drying Mixed layer Latent Heating Precip Ocean Typical qT profile

  12. Liquid Static Energy (sl) Budget Net radiative flux divergence Free trop. Entrainment LW SW Dsl zi sl Mixed layer Advective Cooling Sensible Heating Precip sl = cpT+gz-Lql Ocean

  13. Budget Tables qtBudget: • Surface evaporation (LHF) balances we and advective drying slBudget: • LW radiative cooling balances we warming and SW heating. * Drizzle unimportant in budgets, but strongly impacts turbulence *

  14. Entrainment Estimates • All methods show strong entrainment (~5mm s-1) at night, dropping to near 0 during the day. • Disagreement between methods is the an indicator of uncertainty.

  15. Limitations of Budget Studies • Accurate observations of important variables may not be available (e.g. entrainment) • Difficult to isolate effect of individual forcing from observations (where everything varies at once)

  16. LES to the Rescue? • Resolves larger-scale turbulent motions, parameterizes the smaller scales • Large eddies generally transport most of the BL energy, momentum, and mass • Small eddies are easier to parameterize • “Realistic” representation of physics, “free” of arbitrary tunings BUT IS LES TRUSTWORTHY?

  17. LES Methodology Dimensions: • dz varies, dx= 25 m • Top 1/3 of domain=sponge • 128 pts horiz x 272 in vert Plan: Perform 6-day runs forced with EPIC-Sc Integrated Dataset Model Basics: • System for Atmospheric Modeling (SAM) (Khairoutdinov + Randall, 2003) • Khairoutdinov + Kogan (2000) (KK) drizzle with fixed droplet concentration • Bulk surface fluxes w/ wind near surface nudged towards observations (tau=3hrs) • CAM3 radiation called every 20 steps A 128x128x272 run takes ~105 hrs on 64 cores

  18. Albedo at 32 hrs into 3D run 0.5 y (m) 0.3 0.1 x (m) LES Methodology (cont’d) Dealing with a Long Simulation: • Computational expense: • Use large dx, large dz where appropriate • Perform sensitivity studies in 2D (2D vs 3D comparison suggests ok) • Small domain (3.2 km x 2.3 km) • Free-tropospheric drift: • Nudge free-troposphere to observations following Wyant et al. (1997)

  19. LES Methodology (cont’d) “If for a given forcing a simulation can be made to predict the correct entrainment rate, other aspects of the simulation are likely to be in better accord with the data.” –Stevens et al. (2005) Getting Entrainment Right: • Using small dz near the inversion • NOT using a subgrid-scale parameterization for scalars • Including cloud droplet sedimentation with artificially-increased geometric standard deviation σg of the (lognormal) droplet spectrum Why sed decreases we 1. less cloud-top LW cooling 2. less evap cooling of entrained parcels

  20. What is LES doing? Look for: • Entrainment events • Turbulent mixing Virtual Potential Temperature (K) (From a 2D simulation with Nd=100 cm-3, BL mean wind removed)

  21. What is LES doing? Look for: • Entrainment events • Turbulent mixing Virtual Potential Temperature (K) (From a 2D simulation with Nd=100 cm-3, BL mean wind removed)

  22. Analysis of 3D Base Simulation

  23. Model-Obs Agreement in Mean qtBudget: • Agreement generally quite good! • Radiative cooling underestimated because LWP too low • Entrainment fluxes too strong slBudget:

  24. LWP Comparison • Model captures diurnal cycle, but a bit too small • some of agreement due to compensating zi, zb errors Obs Model

  25. Timeseries of ql, zi, zb, and LCL zi • Model captures diurnal cycle of zi but underestimates amplitude. • Overentrainment during day results in model zb rise • Difference between zband LCL is similar between LES and obs, suggesting model captures BL stratification zb ql(g kg-1) LCL white=obs black=obs red=LES

  26. Timeseries of ql, zi, zb, and LCL zi Cloud die-off on days 292-293 due to dry + warm advection zb ql(g kg-1) LCL white=obs black=obs red=LES 2 2 0 0 θl advect (K day-1) qt advect (g kg-1 day-1) -2 -2 290 291 292 293 294 Julian Date

  27. Entrainment in LES • Entrainment highly correlated with vertical velocity variance near zi • Suggests model entrainment by eddies, not numerical diffusion • Height dependence of correlation suggests typical entrainment eddy lengthscale < 0.3 zi Night Day 0.9 zi

  28. LES night EPIC LES day DY w*3/(ziΔb) (mm s-1) ASTEX NT ACE CCR Parameterizing Entrainment A Conceptual Framework: • Entrainment more efficient in other obs (except DY) • no reason for universal A • Model matches EPIC obs! • because of σg tuning? • how can this be?!! inversion strength empirical constant . / average generation of BL turbulence

  29. Obs = black LES = gray we = Diurnal Cycle of Entrainment Diurnal cycle, repeated 2x for clarity Observations match w*scaling except at 1100LT Possibilities: • Midday physics different • Obs incorrect at this time • must be somewhat true since negative we impossible • Obs more uncertain during day (not well-mixed, cloud top≠zi…)

  30. LES drizzle • Correct magnitude • initiates prematurely zb drizzle (mm hr-1) Surf drizzle (mm day-1) Comstock et al. (2004) • Drizzle too sensitive to forcing

  31. 2D Sensitivity Studies

  32. 3D 2D Does Dimensionality Matter? • Until cloud disappears, runs are quite similar • Particularly in zi • Unclear why cloud reforms in 3D • Perhaps better TKE storage?

  33. Is Subgrid Model important? • No, turbulent diffusion of scalars makes no difference. • Suggests mixing due to resolved scale motions • Differs from the UCLA LES simulating DYCOMS RF01 No SGS Smagorinsky

  34. Diurnal Cycle of ws ECMWF 24 hr mean Effect of Subsidence Diurnal Cycle Forcing: • Dry heating off Andes causes large ws diurnal cycle in the EPIC region (Garreaud + Munoz, 2004) • Explains ½ of the zi diurnal cycle in the mass budget. Model Response: • Most of model zi variation due to ws • sympathetic zb response means no LWP change ziand zb LWP

  35. less droplets average drop larger falls faster more precip obs Nd=100 Nd=25 surf zb Effect of Drizzle and Sedimentation Droplet concentration (Nd) often used as a lever to adjust precipitation since • Nd ↑  drizzle ↓ (as expected) • Smaller Fp(zb) and larger Fp(0) in model suggests under-evaporation

  36. obs Nd=100 Nd=25 driz no driz Effect of Drizzle/Sedimentation on LWP • Minimum LWP insensitive • at low such LWP, model can’t drizzle at any Nd • implies drizzle has no permanent impact • Peak LWP does depend strongly on precipitation • precip decreases LWP by removing ql, but also increases LWP by damping turbulence and hence we • ql removal seems to be dominating

  37. Remember same in all runs  Δzi reflects Δwe Effect of Drizzle/Sedimentation on BL Depth • Changes in entrainment due entirely to sedimentation! • sedimentation effect enhanced by artificial increase of σg. Is this effect real? no driz no driz/sed driz obs Nd=100 Nd=25

  38. Nd=100 Nd=25 driz no driz obs Effect of Nd when σg=1.2 • Drizzle makes a bigger difference in Nd=25 cm-3 case • Little precip for leverage in Nd=100 cm-3 case • Δzi still more affected by sedimentation than drizzle zi LWP zbDriz * Cloud dies after day 291

  39. Conclusions • Low cloud response to warming is still totally unclear • Observational budgets suggest nighttime entrainment of ~5 mm s-1, dipping to 0 around midday • LES is able to reproduce the mean BL properties and the diurnal cycle of LWP observed during EPIC • The diurnal cycle of model ziis too weak and that of zbtoo strong • results in compensating errors that yield correct LWP • due to underprediction of midday entrainment • Midday physics different or obs wrong?

  40. Conclusions • Model drizzle is too sensitive to LWP and evaporation is too weak • Diurnal cycle of ws unimportant in model • Changing Nd affects entrainment more through sedimentation than drizzle

  41. _ Entrainment Warming LW Cooling Entrainment, Drizzle Drying Cloud Top Downdraft Cloudbase Updraft Cloudbase Buoyancy Flux From Bretherton (1997) Buoyancy Flux Drives Turbulence • Buoyancy Flux = w’b’ is main source of BL TKE Idealized Parcel Trajectory

  42. obs Nd=100 Nd=25 driz no driz How is Sedimentation affecting we? Sedimentation affects entrainment by: • decreasing cloud-top radiative cooling (affects entire BL) • decreasing evaporation of entrained air (local effect) • Changing Nd significantly impacts w*, even without drizzle • suggests radiative cooling is important

  43. qt tendency entrainment flux sl tendency SW absorption entrainment flux qtBudget Diurnal cycle of qt budget sl Budget Diurnal cycle of sl budget *excluded terms have diurnal amplitude < 20 W m-2

  44. Model Turbulence • Turbulence weaker during day • Always a mid-BL minimum (suggests imperfect mixing) • Subcloud peak is often larger than in-cloud

  45. Model TKE Budget • Convective pulses cause subcloud peaks • Buoyancy flux is dominant • Dissipation doesn’t occur where TKE is generated (strange) TKE generation (m2 s-3)

  46. Mixed-Layer Buoyancy Flux • In typical subtropical STBLs, the main source of TKE (which drives entrainment) is buoyancy flux, • where and . • Expressing svas a linear combination of sl and qt, • accounting for condensation effects by changing co- • efficients above cloud base, for

  47. Diurnal Cycle of Buoyancy Flux • Buoyancy flux becomes negative below cloud base early in the morning and remains that way throughout the day. • If precipitation is omitted: • Buoyancy flux never < 0 • Time of minimum shifts to 11am *** Suggests precipitation is important to diurnal cycle of BL turbulence ***

  48. What About Grid Anisotropy? • Again, this change has little effect • Increasing horizontal grid spacing increases entrainment. • Not a robust response • Opposite of Stevens + Bretherton (1999) Δx=25 m Δx=6.25 m

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