ALBERT

Description: Forecasts of southeast Pacific stratocumulus at 20°S and 85°W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 are examined with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3–5 days to determine the differences with the EPIC field observations. Observations during the EPIC cruise show a well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the models is that the planetary boundary layer (PBL) depth is too shallow when compared to EPIC observations. However, it is suggested that improved PBL depths are achieved with more physically realistic PBL schemes: at one end, CAM uses a dry and surface-driven PBL scheme and produces a very shallow PBL, while the ECWMF model uses an eddy-diffusivity/mass-flux approach and produces a deeper and better-mixed PBL. All the models produce a strong diurnal cycle in the liquid water path (LWP), but there are large differences in the amplitude and phase when compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface and the surface energy budget. This is particularly relevant for coupled simulations as this can lead to a large SST bias.

Description: High-resolution time–height data over warm tropical oceans are examined, from three global atmosphere models [GFDL’s Atmosphere Model 2 (AM2), NCAR’s Community Atmosphere Model, version 3 (CAM3), and a NASA Global Modeling and Assimilation Office (GMAO) model], field campaign observations, and observation-driven cloud model outputs. The character of rain events is shown in data samples and summarized in lagged regressions versus surface rain rate. The CAM3 humidity and cloud exhibit little vertical coherence among three distinct layers, and its rain events have a short characteristic time, reflecting the convection scheme’s penetrative nature and its closure’s concentrated sensitivity to a thin boundary layer source level. In contrast, AM2 rain variations have much longer time scales as convection scheme plumes whose entrainment gives them tops below 500 hPa interact with humidity variations in that layer. Plumes detraining at model levels above 500 hPa are restricted by cloud work function thresholds, and upper-tropospheric humidity and cloud layers fed by these are detached from the lower levels and are somewhat sporadic. With these discrete entrainment rates and instability thresholds, AM2 also produces some synthetic-looking noise (sharp features in height and time) on top of its slow rain variations. A distinctive feature of the NASA model is a separate anvil scheme, distinct from the main large-scale cloud scheme, fed by relaxed Arakawa–Schubert (RAS) plume ensemble convection (a different implementation than in AM2). Its variability is rich and vertically coherent, and involves a very strong vertical dipole component to its tropospheric heating variations, of both signs (limited-depth convective heating and top-heavy heating in strong deep events with significant nonconvective rain). Grid-scale saturation events occur in all three models, often without nonconvective surface rain, causing relatively rare episodes of large negative top-of-atmosphere cloud forcing. Overall, cloud forcing regressions show a mild net positive forcing by rain-correlated clouds in CAM3 and mild net cooling in the other models, as the residual of large canceling shortwave and longwave contributions.

Description: Three-dimensional radiative transfer calculations are accurate, though computationally expensive, if the spatial distribution of cloud properties is known. The difference between these calculations and those using the much less expensive independent column approximation is called the 3D radiative transfer effect. Assessing the magnitude of this effect in the real atmosphere requires that many realistic cloud fields be obtained, and profiling instruments such as ground-based radars may provide the best long-term observations of cloud structure. Cloud morphology can be inferred from a time series of vertical profiles obtained from profilers by converting time to horizontal distance with an advection velocity, although this restricts variability to two dimensions. This paper assesses the accuracy of estimates of the 3D effect in shallow cumulus clouds when cloud structure is inferred in this way. Large-eddy simulations provide full three-dimensional, time-evolving cloud fields, which are sampled every 10 s to provide a “radar’s eye view” of the same cloud fields. The 3D effect for shortwave surface fluxes is computed for both sets of fields using a broadband Monte Carlo radiative transfer model, and intermediate calculations are made to identify reasons why estimates of the 3D effect differ in these fields. The magnitude of the 3D effect is systematically underestimated in the two-dimensional cloud fields because there are fewer cloud edges that cause the effect, while the random error in hourly estimates is driven by the limited sample observed by the profiling instrument.