Introduction

1. Zonal Profiles MISR Observed/Simulated Clouds (by three height and three OD categories) Low-Level (< 3 km) Mid-Level (3 to 7 km) High (> 7 km) ISCCP+MISR optically-thin HM Cloud Single / Multilayer / Total Introduction • We evaluate cloud biases in five climate models participating in the Coupled Model Inter-comparison Project, Phase 5 (CMIP5) using simulated and observed MISR and ISCCP histograms of cloud-top-height and optical-depth. • Because top-of-atmosphere outgoing longwave fluxes are related to cloud-top-height and outgoing shortwave fluxes are related to cloud-optical-depth, this framework provides a way to evaluate the distribution of model clouds in a way that is closely related to their radiative impact. • Globally averaged cloud radiative effects (see table in lower right) are well represented in all of the models, but with compensating biases at regional scales due to local biases in the cloud properties. • Here we concentrate on zonal profiles over ocean, which have been averaged into three cloud-top-height categories and three optical-depth categories. • While similar to ISCCP, the cloud-top-height in the MISR dataset is obtained using a stereo-imaging technique that is purely geometric and insensitive to the calibration of the MISR cameras(see figure below). • This technique provides more accurate retrievals of cloud-top-height for low-level and mid-level clouds, and more reliable discrimination of mid-level clouds from other clouds, while ISCCP provides greater sensitivity to optically-thin high-level clouds. • ISCCP and MISR histograms can be combined to separate optically-thin upper-level clouds (OD < ~ 1) into multi-layer and single-layer categories (Marchand et al. 2010). s 1 4 Cloud Biases in CMIP5 using MISRand ISCCP simulatorsB. Hillman*, R. Marchand*, A. Bodas-Salcedo, J. Cole, J.-C. Golaz, and J. E. Kay*University of Washington, Department of Atmospheric Sciences 2 2 3a 3a 2 3a CTH-OD in the Tropical Warm Pool TOA Cloud-Radiative Effect Key Points / Discussion 3b Polewardof about 50o S, there is a large increase in optically-thin low-cloud and a decrease in optically-thick and optically-intermediate low-cloud, while total cloud cover compares relatively well with observations, in all the models except CAM4. This suggests problems in phase partitioning in these models, producing too little liquid water. This has a large impact on SW CRE with all the models (except arguably AM3) having far too little SW CRE poleward of 50o S. All of the models produce roughly the same total amount of mid-level cloud in both the southern and northern hemisphere extratropics. Observations, however, show greater amounts of mid-level cloud, due principally to optically-intermediate cloud, in the southern hemisphere. The situation is somewhat reversed with respect to high-level clouds where the observations show more optically-thick and optically-intermediate cloud at high-levels in the northern hemisphere. This is partially captured by the models. The reasons for this asymmetry are not immediately clear, but we speculate that this is related to the greater quantities of supercooled liquid water that have been identified based on CALIPSO measurements over SH oceans relative to NH oceans poleward of about 40 N/S (e.g., Hu et al. 2010, Yi et al. 2014). On a zonal basis models tend to underestimate the amount of optically-thin high-level cloud where the optical depths of the high-level cloud are between about 0.3 and 1. (The primary exception to this is for AM3 and CanAM4 in the tropics). It is likely that a variety of physical mechanisms (parameterizations) are involved in this problem. In the extratropics, all of the models, with the exception of CAM5 tend to produce too much optically thick high-topped cloud. Thus the lack of high-cloud in the optical depth range between 0.3 and 1.0 may suggests that models do not maintain condensate in the upper-troposphere sufficiently long. This may reflect problems in the parameterization of particle falls speeds and more broadly the representation of microphysical processes related to particle size and precipitation, but other factors such as the role of mesoscale (subgrid) variability may be a factor (e.g. Gettlemen et al 2010). In the tropics there is a great diversity of predicted cloud CTH-OD distributions between the models, as shown for the tropical warm pool (to the right), as well as in cloud-radiative-effects. It is tempting to interpret these differences as being driven primarily by differences in the convective parameterizations. The AM3 in particular shows unrealistically large quantities of clouds with optical depth below 3.6 that were not present in AM2 and it is likely that this is due to a new anvil parameterization added to AM3 (Leo Donner, personal communication). On the other hand, the CAM4 and CAM5 models use identical deep convective parameterizations (Zhang-MacFarlane scheme) and yet have notably different distributions, showing that changes in the microphysical parameterization (the new two-moment scheme) or perhaps interactions with other parameterizations (e.g., the new shallow convection scheme) also play a large role and more detailed studies will be needed to untangle these differences. There is an underestimate of optically-thin multilayer cloud that is consistent with both an underestimate in optically thin high and mid-level cloud plus an underestimate of low-level cloud coverage. MISR CTH Retrieval 1 Occurrence of Supercooledliquid water (Hu et al. 2010) Tables shows global mean (ocean-only) cloud radiative effect (CRE) values from CERES-EBAF (in W/m2) and cloud amounts (%) from MISR and ISCCP in the first column. The remainder of the table gives model biases relative to observations. Results are provided for both total (τ>0.3) and optically thick (τ>23.0) cloud amounts.