Subtropical Low Cloud Feedback in a Superparameterized GCM - A Mechanism and a CRM Column Analogue

1. Subtropical low cloud feedback in a superparameterized GCM - a mechanism and a CRM column analogue Peter N. Blossey Matthew C. Wyant Christopher S. Bretherton Department of Atmospheric Sciences University of Washington (thanks also to Marat Khairoutdinov and CMMAP)

2. Clouds in a superparameterized GCM • Superparameterization - a climate model with a small cloud-resolving model (CRM) running in place of the normal physical parameterizations in every grid column. • Computationally expensive, but may simulate turbulent clouds (especially deep convection) more realistically. • SP-CAM (Khairoutdinov and Randall 2005) uses 2D CRMs with 32x30 gridpoints,x = 4 km - under-resolves boundary-layer Cu, Sc. • Wyant et al. (2006) examined SPCAM cloud response to an idealized climate warming by comparing 3.5-year simulations with control SSTs vs. SST+2K. • Is the cloud response: • physically understandable? • sensitive to grid resolution?

3. SPCAM has reasonable net CRF and low clouds • Patterns good; not enough offshore stratocumulus; ‘bright’ trades/ITCZ. • LTS = 700 - 1000 • correlated to net CRF over subtropical oceans. • - Natural separator between subtropical cloud regimes. Use LTS for Bony-type cloud regime sorting’ to analyze subtropical (30S-30N) oceanic low cloud response

4. +2K cloud/CRF changes • SWCF trends dominate net Þ low cloud response. • Low cloud increases in subtropics, summer high-latitude. • LTS increases over all ocean regions.

5. Typical vertical structure in trades (SE Pac) • Cloud fraction and inversion strength increase together. • Net CRF (not shown) proportional to cloud fraction. Inversion strengthens and LTS increases Subsidence changes are location-dependent.

6. LTS-sorted low-latitude ocean cloud response warm SST cold SST high LTS subsidence low LTS high LTS subsidence low LTS • 10-20% relative increase in low cld fraction/condensate across all high-LTS (cool-SST, subsiding) regimes.

7. Other LTS-ordered fields high SST low SST low SST high SST diverse changes 1-2% moister PBL more PBL rad cool low LTS high LTS low LTS high LTS

8. Conceptual model of SP-CAM trade ‘Cu’ feedbacks Radiative Mechanism Higher SST More absolute humidity More radiative cooling More convection More clouds Possible issues: • SP-CAM under-resolution • Sensitive to GHG & warming scenario since radiatively-driven.

9. Column Analogue for SP-CAM low-cld feedbacks • Calculate MMF composite for LTS decile (e.g. 80-90%). • Use composite , horizontal advective T/q tendencies and SST. Nudge to composite winds. A realistic wind direction profile is also needed (RICO). • Allow mean subsidence to adjust to local diabatic cooling to keep SCM T profile close to SP-CAM sounding. (More on next slide.) • Nudge moisture above surface layer to counteract effects of sporadic deep convection and detraining high cloud in SP-CAM composite forcings. • Run to a statistically-steady state. Key assumption 1: (like Zhang&Breth 2008, Caldwell&Breth 2008) - Regime-mean +2K cloud response can be recovered from regime-mean profile/advective tendency changes.

10. Key assumption 2:Vertical Velocity Feedbacks • In low latitudes, the free-tropospheric temperature profile is remotely forced by deep convection over the warm parts of the tropics. • Weak temperature gradient approximation (WTG): Stratified adjustment (compensating vertical motions) prevents build-up of local temperature anomalies. • Our new WTG formulation for column modeling builds on Caldwell & Bretherton (2008); related to approaches used by Mapes (2004), Raymond & Zeng (2005),Kuang (2008). • Compared to existing approaches, it has the advantage of a clear derivation from a relevant physical model applicable to quasi-steady dynamics.

11. Vertical Velocity Feedbacks (Derivation) • Assume small perturbation to a reference state. • The linear, damped, hydrostatic, quasi-steady momentum and mass conservation equations in pressure coordinates give: • These equations can be combined to relate * to Tv*: • Assuming sinusoidal pertubations in x of wavenumber k: A horizontal length scale , where k=(2), and momentum-damping rate am are needed. We choose =650km and am=1/(2 days) w/ am vertically uniform.

12. LTS80-90 forcings and profiles ,q profiles; SST Hor. advection ctrl +2K + q nudging winds averaging period

13. Results • CRM has deeper moist layer, but similar +2K cloud response. • Mean and +2K cld response depend a bit on setup details, wind shear. CRM SP-CAM

14. Cu-layer radiative forcing/nudging SP-CAM • Radiative heating change in the same sense in CRM as in SP-CAM, though not as strong. • Vertical velocity feedback  is small compared to SP-CAM 0, has little change in +2K run. • Q nudging small compared to vadv. Q nudge CRM CRM Vertical Advection

15. LES resolution (x=100 m, z=40 m, Nx=512) • Large reduction in mean low cloud and SW cloud forcing. • +2K low cloud change similar in magnitude but different in structure. LES CRM

16. Interpretation 4 km makes Cu clouds too weak and broad • Excessive Cu needed to flux water up to inversion. LES CRM

17. Conclusions • Subtropical boundary-layer cloud increases dramatically in SP-CAM simulations with 2 K warmer SST. • Tropospheric warming increases the clear-sky radiative cooling of the moist Cu layer, driving more Cu cloud. • A column CRM analogue suggests that SP-CAM mean cloud are greatly overestimated due to coarse CRM resolution. The structure of the +2K cloud changes depends on resolution. • LES column analogues show promise for studying greenhouse+aerosol effects on boundary-layer clouds; further research needed into the optimal formulation of large-scale dynamical feedbacks on the column. • See poster later today for a static version of this talk.