Abstract.The relationship between precipitation rate and accumulation mode aerosol concentration in marine stratocumulus-topped boundary layers is investigated by applying the precipitation susceptibility metric to aircraft data obtained during the VOCALS Regional Experiment. A new method to calculate the precipitation susceptibility that incorporates non-precipitating clouds is introduced. The mean precipitation rate R over a segment of the data is expressed as the product of a drizzle fraction f and a drizzle intensity I (mean rate for drizzling columns). The susceptibility S x is then defined as the fractional decrease in precipitation variable x={R,f ,I } per fractional increase in the concentration of aerosols with dry diameter >0.1 µm, with cloud thickness h held fixed. The precipitation susceptibility S R is calculated using data from both precipitating and nonprecipitating cloudy columns to quantify how aerosol concentrations affect the mean precipitation rate of all clouds of a given h range and not just the mean precipitation of clouds that are precipitating. S R systematically decreases with increasing h, and this is largely because S f decreases with h while S I is approximately independent of h. In a general sense, S f can be thought of as the effect of aerosols on the probability of precipitation, while S I can be thought of as the effect of aerosols on the intensity of precipitation. Since thicker clouds are likely to precipitate regardless of ambient aerosol concentration, we expect S f to decrease with increasing h. The results are broadly insensitive to the choice of horizontal averaging scale. Similar susceptibilities are found for both cloud base and near-surface drizzle rates. The analysis is repeated with cloud liquid water path held fixed instead of cloud thickness. Simple power law relationships relating precipitation rate to aerosol concentration or cloud droplet concentration do not capture this observed behavior.

Abstract. Cloud microphysical process rates control the amount of condensed water in clouds and impact the susceptibility of precipitation to cloud-drop number and aerosols. The relative importance of different microphysical processes in a climate model is analyzed, and the autoconversion and accretion processes are found to be critical to the condensate budget in most regions. A simple steady-state model of warm rain formation is used to illustrate that the diagnostic rain formulations typical of climate models may result in excessive contributions from autoconversion, compared to observations and large eddy simulation models with explicit bin-resolved microphysics and rain formation processes. The behavior does not appear to be caused by the bulk process rate formulations themselves, because the steady-state model with the same bulk accretion and autoconversion has reduced contributions from autoconversion. Sensitivity tests are conducted to analyze how perturbations to the precipitation microphysics for stratiform clouds impact process rates, precipitation susceptibility and aerosol-cloud interactions (ACI). With similar liquid water path, corrections for the diagnostic rain assumptions in the GCM based on the steady-state model to boost accretion indicate that the radiative effects of ACI may decrease by 20 % in the GCM. Links between process rates, susceptibility and ACI are not always clear in the GCM. Better representation of the precipitation process, for example by prognosticating precipitation mass and number, may help better constrain these effects in global models with bulk microphysics schemes.

The increase in cloud optical depth with warming at middle and high latitudes is a robust cloud feedback response found across all climate models. This study builds on results that suggest the optical depth response to temperature is timescale invariant for low‐level clouds. The timescale invariance allows one to use satellite observations to constrain the models' optical depth feedbacks. Three passive‐sensor satellite retrievals are compared against simulations from eight models from the Atmosphere Model Intercomparison Project (AMIP) of the 5th Coupled Model Intercomparison Project (CMIP5). This study confirms that the low‐cloud optical depth response is timescale invariant in the AMIP simulations, generally at latitudes higher than 40°. Compared to satellite estimates, most models overestimate the increase in optical depth with warming at the monthly and interannual timescales. Many models also do not capture the increase in optical depth with estimated inversion strength that is found in all three satellite observations and in previous studies. The discrepancy between models and satellites exists in both hemispheres and in most months of the year. A simple replacement of the models' optical depth sensitivities with the satellites' sensitivities reduces the negative shortwave cloud feedback by at least 50% in the 40°–70°S latitude band and by at least 65% in the 40°–70°N latitude band. Based on this analysis of satellite observations, we conclude that the low‐cloud optical depth feedback at middle and high latitudes is likely too negative in climate models.

Abstract.Five pockets of open cells (POCs) are studied using aircraft flights from the VOCALS Regional Experiment (VOCALS-REx), conducted in October and November 2008 over the southeast Pacific Ocean. Satellite imagery from the geostationary satellite GOES-10 is used to distinguish POC areas, and measurements from the aircraft flights are used to compare aerosol, cloud, precipitation, and boundary layer conditions inside and outside of POCs. Conditions observed across individual POC cases are also compared.POCs are observed in boundary layers with a wide range of inversion heights (1250 to 1600 m) and surface wind speeds (5 to 11 m s −1 ) and show no remarkable difference from the observed surface and free-tropospheric conditions during the two months of the field campaign. In all cases, compared to the surrounding overcast region the POC boundary layer is more decoupled, supporting both thin stratiform and deeper cumulus clouds. Although cloud-base precipitation rates are higher in the POC than the overcast region in each case, a threshold precipitation rate that differentiates POC precipitation from overcast precipitation does not exist. Mean cloud-base precipitation rates in POCs can range from 1.7 to 5.8 mm d −1 across different POC cases. The occurrence of heavy drizzle (> 0 dBZ) lower in the boundary layer better differentiates POC precipitation from overcast precipitation, likely leading to the more active cold pool formation in POCs. Cloud droplet number concentration is at least a factor of 8 smaller in the POC clouds, and the ratio of drizzle water to cloud water in POC clouds is over an order of magnitude larger than that in overcast clouds, indicating an enhancement of collision-coalescence processes in POC clouds.Despite large variations in the accumulation-mode aerosol concentrations observed in the surrounding overcast region (65 to 324 cm −3 ), the accumulation-mode aerosol concentrations observed in the subcloud layer of all five POCs exhibit a much narrower range (24 to 40 cm −3 ), and cloud droplet concentrations within the cumulus updrafts originating in this layer reflect this limited variability. Above the POC subcloud layer exists an ultraclean layer with accumulationmode aerosol concentrations < 5 cm −3 , demonstrating that in-cloud collision-coalescence processes efficiently remove aerosols. The existence of the ultraclean layer also suggests that the major source of accumulation-mode aerosols, and hence of cloud condensation nuclei in POCs, is the ocean surface, while entrainment of free-tropospheric aerosols is weak. The measurements also suggest that at approximately 30 cm −3 a balance of surface source and coalescence scavenging sinks of accumulation-mode aerosols maintain the narrow range of observed subcloud aerosol concentrations.

No abstract

This paper describes the first implementation of the Δx = 3.25 km version of the Energy Exascale Earth System Model (E3SM) global atmosphere model and its behavior in a 40‐day prescribed‐sea‐surface‐temperature simulation (January 20 through February 28, 2020). This simulation was performed as part of the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) Phase 2 model intercomparison. Effective resolution is found to be the horizontal dynamics grid resolution despite using a coarser grid for physical parameterizations. Despite this new model being in an immature and untuned state, moving to 3.25 km grid spacing solves several long‐standing problems with the E3SM model. In particular, Amazon precipitation is much more realistic, the frequency of light and heavy precipitation is improved, agreement between the simulated and observed diurnal cycle of tropical precipitation is excellent, and the vertical structure of tropical convection and coastal stratocumulus look good. In addition, the new model is able to capture the frequency and structure of important weather events (e.g., tropical cyclones, extratropical cyclones including atmospheric rivers, and cold air outbreaks). Interestingly, this model does not get rid of the erroneous southern branch of the intertropical convergence zone nor the tendency for strongest convection to occur over the Maritime Continent rather than the West Pacific, both of which are classic climate model biases. Several other problems with the simulation are identified, underscoring the fact that this model is a work in progress.

Abstract. Although typically associated with precipitating cumuli, cold pools also form under shallower stratocumulus. This study presents cold-pool observations as sampled by the NSF/NCAR C-130, which made cloud and boundarylayer measurements over the southeast Pacific stratocumulus region at an altitude of approximately 150 m during the VO-CALS Regional Experiment. Ninety edges of cold pools are found in the C-130 measurements by identifying step-like changes in the potential temperature. Examination of their mesoscale environment shows that the observed cold pools tend to form under heavier precipitation, thicker clouds, and in cleaner environments. Cold pools are also found to form under clouds with high LWP values over the night of or before sampling. When they form, cold pools often form in clusters or on top of each other, rather than as separate, individual entities. Their sizes range from 2 km to 16 km (middle 50th percentile), where the largest of cold pools are associated with the greatest drops in temperature. Composites of various observed thermodynamic and chemical variables along the cold-pool edges indicate increased humidity, equivalent potential temperature, coarse-mode aerosol, and dimethyl sulfide concentration inside cold pools. The enhancements inside cold pools are consistent with increased static stability that traps fluxes from the ocean surface in the lowest levels of the boundary layer. By using pressure perturbations, the average cold pool is estimated to be approximately 300 m deep. The temperature depression in cold pools also leads to density-driven flows that drive convergence of horizontal winds and measurable, mechanically driven vertical wind velocity at the edges of cold pools.

Cloud microphysical process rates control the amount of condensed water in clouds and impact the susceptibility of precipitation to drop number and aerosols. The relative importance of different microphysical processes in a climate model is analyzed, and the autoconversion and accretion processes are found to be critical to the condensate budget in most regions. A simple steady-state model of warm rain formation is used to illustrate that the diagnostic rain formulations typical of climate models may result in excessive contributions from autoconversion, compared to observations and large eddy simulation models with explicit bin-resolved microphysics and rain formation processes. The behavior does not appear to be caused by the bulk process rate formulations themselves, because the steady state model with bulk accretion and autoconversion has reduced contributions from autoconversion. Sensitivity tests are conducted to analyze how perturbations to the precipitation microphysics for stratiform clouds impact process rates, precipitation susceptibility and aerosol-cloud interactions (ACI). With similar liquid water path, corrections for the diagnostic rain assumptions in the GCM based on the steady state model to boost accretion over autoconversion indicate that the radiative effects of ACI may decrease by 20% in the GCM for the same mean liquid water path. Links between process rates, susceptibility and ACI are not always clear in the GCM. Better representation of the precipitation process, for example by prognosing precipitation mass and number, may help better constrain these effects in global models with bulk microphysics schemes