Forecast simulations of Southeast Pacific Stratocumulus with CAM3 and CAM3-UW. Cécile Hannay (1), Jeffrey Kiehl (1), Dave Williamson (1), Jerry Olson (1),

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Forecast simulations of Southeast Pacific Stratocumulus with CAM3 and CAM3-UW. Cécile Hannay (1), Jeffrey Kiehl (1), Dave Williamson (1), Jerry Olson (1), Jim Hack (1) and Chris Bretherton (2). (1) : National Center for Atmospheric Research, Boulder, Colorado (2) : Department of Atmospheric Science, University of Washington, Seattle, Washington. 2. Evolution of the 5-day forecasts We initialize CAM every 6 hours with the ECMWF analyses for the period October 11-22, For each initialization, we run the model for 5 days obtaining an ensemble of forecasts with various features. However, individual forecasts can be grouped into 2 typical behaviors: either CAM maintains the PBL or the PBL collapses. To illustrate this, we examine 2 typical forecasts starting on October 16 at 0UT (PBL maintained) and October 20 at 0UT (PBL collapses). Forecast of the PBL and cloud layer The 2 versions of the model CAM3 and CAM3-UW show similarities. In both models, the PBL collapses (maintains) for the Oct 16 (Oct 20) initialization. When the PBL collapses, the model becomes very moist near the surface. There are differences between the 2 versions of the model: - CAM3 produces an unrealistically thick layer of clouds that sometimes extends to the surface. CAM3 produces some ‘empty’ clouds (clouds with very low or no liquid water content). - CAM3-UW clouds are more realistic and lay on a single level. CAM3-UW better represents the diurnal cycle of the PBL, due to the entrainment of dry air at the top of the PBL. When the PBL collapses, the cloud fraction and cloud water in CAM3-UW go to zero. CAM3 CAM3-UW Oct 16 initializationOct 20 initializationOct 16 initialization Oct 20 initialization Figure 4: 5-day evolution of Q, CLOUD and CLDLIQ in CAM3 and CAM3-UW for forecasts initialized on Oct 16 and Oct 20. Correlation with surface fluxes, TKE and omega We illustrate the relationship between PBL height in CAM3 and some variables in CAM3 and CAM3-UW. Figure 5: Turbulent Kinetic Energy (TKE) and vertical velocity in CAM3-UW for forecasts initialized on Oct 16 and Oct 20 Oct 16Oct 20 Figure 6: PBL height and latent heat flux in observations and in CAM3. October 20 initialization (PBL collapses) When the PBL collapses, the shallow scheme turns off in CAM3 and the PBL scheme weakens in CAM3-UW. 3. Moisture budgets We have made a detailed analysis of the budget terms of temperature, moisture and cloud water. As an illustration, we consider the terms of the moisture budget. The moisture equation can be written: where TOT is the total tendency, ADV represent the tendency to the advection (sum of the horizontal and vertical advection) and PAR represents the subgrid scale parameterization term. We separate the parameterization term into its components: - PBL is the moisture tendency due to the PBL scheme, - SHALLOW is the tendency coming from the shallow convection including the evaporation of shallow convective precipitation. - CLDWAT is the tendency coming from the prognostic cloud water scheme, which includes the conversion between vapor and condensate in the stratiform cloud and the evaporation of falling precipitation and cloud water sedimentation. - DEEP is the deep convection tendency (not active for the EPIC column). October 16 initialization (PBL maintained) In CAM3 and CAM3-UW, the advection term dries the upper part of the PBL while the parameterization term moistens it. The 2 models show similar patterns for these 2 terms. However, splitting the parameterization term into its components reveals that the mechanism for moistening the PBL is different between the 2 models. - CAM3 unphysically maintains the PBL by a mixture of dry convection and shallow convection. The PBL scheme moves the moisture up and creates a moist layer around 950mb. This moist layer triggers the shallow scheme which ventilates the moisture higher in the atmosphere. - CAM3-UW behaves more physically. It is the PBL scheme that moves the moisture up in the boundary layer without any significant contribution from the shallow scheme. PAR = PBL + SHALLOW + CLDWAT (+ DEEP) TOT = ADV + PAR or CAM3 Parameterization terms The tendencies are from: - PBL = PBL scheme - SHALLOW = shallow convection scheme - CLDWAT = prognostic cloud water CAM3-UW Parameterization terms The tendencies are from: - PBL = PBL scheme - SHALLOW = shallow convection scheme - CLDWAT = prognostic cloud water CAM3 Parameterization terms The tendencies are from: - PBL = PBL scheme - SHALLOW = shallow convection scheme - CLDWAT = prognostic cloud water CAM3-UW Parameterization terms The tendencies are from: - PBL = PBL scheme - SHALLOW = shallow convection scheme - CLDWAT = prognostic cloud water CAM3 TOT = ADV + PAR The tendencies are from: - TOT= total tendency - ADV = advection tendency - PAR = parameterization tendency Models We use 2 versions of CAM with different parameterizations of PBL and shallow cumulus. the standard CAM3 which uses Holtslag-Boville (1993) for the boundary layer and Hack (1994) for the shallow convection. the CAM3-UW uses the turbulence scheme of Grenier-Bretherton (2001) which includes explicit entrainment at the top of the PBL coupled with a shallow cumulus scheme which includes the determination of cloud-base mass flux based on surface layer turbulent kinetic energy (TKE) and convective inhibition near the cloud base. We use 3 vertical resolutions (26, 30 and 60 levels). Here we present the 30-level results. 1. Overview We illustrate the way CAM and CAM3-UW represent regions of persistent stratocumulus with forecast simulations of a column in the South Eastern Pacific (20S-85W). Motivation Stratocumulus clouds play an important role in the seasonal cycle of the Eastern Pacific and the global climate by exerting a strong cooling effect on the surface. These clouds are very complex to parameterize in GCMs because : - they are only a few hundred meters thick. Therefore, they are difficult to represent with the current climate model vertical resolution. - they are maintained by a complex set of interactions between the cloud layer and its environment, which are not always well understood. Figure 1: Some processes controlling stratocumulus. Stratocumulus Buoyancy flux subsidence Potential temperature Inversion jump BL height sfc Entrainement of dry air LW cooling The Eastern Pacific Investigation of Climate (EPIC) column This location has been chosen because of the availability of observational datasets and accurate analyses. the WHOI buoy provides a long-term time-series of surface meteorological variables. the 2001 EPIC cruise provides a comprehensive dataset of remote sensing and surface measurements for Oct 16-21, the MK ECMWF analyses provide a realistic state of the EPIC column. EPIC Figure 2: The EPIC column (20S-85W). Time-height cross-section of potential temperature (THETA) and moisture (q) from radiosondes and ECMWF analysis. Observations shows a very stable PBL under a sharp inversion. ECMWF analyses provide a realistic state for the EPIC column even if the height of the PBL and the strength of the inversion are underestimated. Forecast framework In the CAPT protocol, we realistically initialize CAM with analyses and we then run the model in forecast mode to determine the drift from the analyses and/or available field data. This method allows us to diagnose model parameterization deficiencies. Figure 3: Forecast runs framework Strategy If the model is initialized realistically, we assume the error comes from the parameterizations deficiencies. Advantages Full feedback SCM Limitations Accuracy of the atmospheric state ? Initialize realistically Operational ECMWF analysis (Martin Koehler PBL) CAM 5-day forecast Starting daily at 00 UT (also forecasts at 6,12,18 UT) EPIC 2001 cruise WHOI buoy