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Ann M. Fridlind and Andrew S. Ackerman

Abstract

A proposed objective of the planned Aerosol–Cloud–Ecosystem (ACE) satellite mission is to provide constraints on climate model representation of aerosol effects on clouds by retrieving profiles of aerosol number concentration, effective variance, and effective radius over the 0.1–1-μm radius range under humidified ambient conditions with 500-m vertical resolution and uncertainties of 100%, 50%, and 10%, respectively. Shallow, broken marine clouds provide an example of conditions where boundary layer aerosol properties would be retrieved in clear-sky gaps. To quantify the degree of constraint that proposed retrievals might provide on cloud radiative forcing (CRF) simulated by climate models under such conditions, dry aerosol size distribution parameters are independently varied here in large-eddy simulations of three well-established modeling case studies. Using the rudimentary available aerosol specifications, it is found that relative changes of total dry aerosol properties in simulations can be used as a proxy for relative changes of ambient aerosol properties targeted by ACE retrievals. The sensitivity of simulated daytime shortwave CRF to the proposed uncertainty in retrieved aerosol number concentration is −15 W m−2 in the overcast limit, roughly a factor of 2 smaller than a simple analytic estimate owing primarily to aerosol-induced reductions in simulated liquid water path across this particular set of case studies. The CRF sensitivity to proposed uncertainties in retrieved aerosol effective variance and effective radius is typically far smaller, with no corresponding analytic estimate. Generalization of the results obtained here using only three case studies would require statistical analysis of relevant meteorological and aerosol observations and quantification of observational and model uncertainties and biases.

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Ann M. Fridlind and Andrew S. Ackerman
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Kuniaki Inoue, Michela Biasutti, and Ann M. Fridlind

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The column moist static energy (MSE) budget equation approximates the processes associated with column moistening and drying in the tropics, and is therefore predictive of precipitation amplification and decay. We use ERA-Interim (ERA-I) and TRMM 3B42 data to investigate day-to-day convective variability and distinguish the roles of horizontal MSE (or moisture) advection versus vertical advection, sources, and sinks. Over tropical convergence zones, results suggest that horizontal moisture advection is a primary driver of day-to-day precipitation fluctuations; when drying via horizontal moisture advection is smaller (greater) than Chikira’s “column process,” precipitation tends to amplify (decay). In the absence of horizontal moisture advection, precipitation tends to increase spontaneously almost universally through a positive column process feedback. This bulk positive feedback is characterized by negative effective gross moist stability (GMS), which is maintained throughout the tropical convergence zones. How this positive feedback is achieved varies geographically, depending on the shape of vertical velocity (omega) profiles. In regions where omega profiles are top-heavy, the effective GMS is negative primarily owing to strong feedbacks between convection and diabatic MSE sources (radiative and surface fluxes). In these regions, vertical MSE advection stabilizes the atmosphere (positive vertical GMS). Where omega profiles are bottom-heavy, by contrast, a positive feedback is primarily driven by import of MSE through a shallow circulation (negative vertical GMS). The diabatic feedback and vertical GMS are in a seesaw balance, offsetting one another. Our results suggest that ubiquitous convective variability is amplified by the same mechanism as moisture-mode instability.

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Bastiaan van Diedenhoven, Ann M. Fridlind, and Andrew S. Ackerman

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Lidar measurements obtained during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment under a mixed-phase stratus cloud that was lightly precipitating ice show a range of surprisingly low depolarization ratios (4%–23%), despite an absence of cloud droplets there. These depolarization ratios are much lower than the range of theoretical values obtained for various ice habits. The depolarization ratios correlate well with radar reflectivity, suggesting that the variation in depolarization ratios results from variations in ice water content, rather than variation in ice habits or orientation. By calculating lidar depolarization based on (i) large-eddy simulations and (ii) in situ ice size distribution measurements, it is shown that the presence of humidified aerosol particles in addition to the ice precipitation can explain the distribution and vertical profile of the observed depolarization ratios, although uncertainties related to the aerosol size distributions are substantial. These calculations show that humidified aerosol must be taken into account when interpreting lidar depolarization measurements for cloud and precipitation phase discrimination or ice habit classification, at least under conditions similar to those observed during SHEBA.

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Hyunho Lee, Ann M. Fridlind, and Andrew S. Ackerman

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This study evaluates some available schemes designed to solve the stochastic collection equation (SCE) for collision–coalescence of hydrometeors using a size-resolved (bin) microphysics approach and documents their numerical properties within the framework of a box model. Comparing three widely used SCE schemes, we find that all converge to almost identical solutions at sufficiently fine mass grids. However, one scheme converges far slower than the other two and shows pronounced numerical diffusion at the large-drop tail of the size distribution. One of the remaining two schemes is recommended on the basis that it is well converged on a relatively coarse mass grid, stable for large time steps, strictly mass conservative, and computationally efficient. To examine the effects of SCE scheme choice on simulating clouds and precipitation, two of the three schemes are compared in large-eddy simulations of a drizzling stratocumulus field. A forward simulator that produces Doppler spectra from the large-eddy simulation results is used to compare the model output directly with radar observations. The scheme with pronounced numerical diffusion predicts excessively large mean Doppler velocities and overly broad and negatively skewed spectra compared with observations, consistent with numerical diffusion demonstrated in the box model. Statistics obtained using the recommended scheme are closer to observations, but notable differences remain, indicating that factors other than SCE scheme accuracy are limiting simulation fidelity.

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Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, and Pavlos Kollias

Abstract

This study uses eddy-permitting simulations to investigate the mechanisms that promote mesoscale variability of moisture in drizzling stratocumulus-topped marine boundary layers. Simulations show that precipitation tends to increase horizontal scales. Analysis of terms in the prognostic equation for total water mixing ratio variance indicates that moisture stratification plays a leading role in setting horizontal scales. This result is supported by simulations in which horizontal mean thermodynamic profiles are strongly nudged to their initial well-mixed state, which limits cloud scales. It is found that the spatial variability of subcloud moist cold pools surprisingly tends to respond to, rather than determine, the mesoscale variability, which may distinguish them from dry cold pools associated with deeper convection. Simulations also indicate that moisture stratification increases cloud scales specifically by increasing latent heating within updrafts, which increases updraft buoyancy and favors greater horizontal scales.

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Steven K. Krueger, Hugh Morrison, and Ann M. Fridlind
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Xiaoli Zhou, Andrew S. Ackerman, Ann M. Fridlind, and Pavlos Kollias
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Bastiaan van Diedenhoven, Ann M. Fridlind, Andrew S. Ackerman, and Brian Cairns

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Satellite measurements are used to evaluate the glaciation, particle shape, and effective radius in cloud-resolving model simulations of tropical deep convection. Multidirectional polarized reflectances constrain the ice crystal geometry and the thermodynamic phase of the cloud tops, which in turn are used to calculate near-infrared reflectances so as to constrain the simulated ice effective radius, thereby avoiding inconsistencies between retrieval algorithms and model simulations. Liquid index values derived from Polarization and Directionality of the Earth’s Reflectances (POLDER) measurements indicate only ice-topped clouds at brightness temperatures (BTs) lower than −40°C, only liquid clouds at BT > −20°C, and both phases occurring at temperatures in between. Liquid index values calculated from model simulations generally reveal too many ice-topped clouds at BT > −20°C. The model assumption of platelike ice crystals with an aspect ratio of 0.7 is found consistent with POLDER measurements for BT < −40°C when very rough ice crystals are assumed, leading to an asymmetry parameter of 0.74, whereas measurements indicate more extreme aspect ratios of ~0.15 at higher temperatures, yielding an asymmetry parameter of 0.84. MODIS-retrieved ice effective radii are found to be 18–28 μm at BT < −40°C, but biased low by about 5 μm owing primarily to the assumption of pristine crystals in the retrieval. Simulated 2.13-μm reflectances at BT < −40°C are found to be about 0.05–0.1 too large compared to measurements, suggesting that model-simulated effective radii are 7–15 μm too small. Two simulations with contrasting ice nucleation schemes showed little difference in simulated effective radii at BT < −40°C, indicating that homogeneous nucleation is dominating in the simulations. Changes around −40°C in satellite observations suggest a change in cloud-top ice shape and/or size in natural deep convection possibly related to a change in the freezing mechanism.

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Bastiaan van Diedenhoven, Andrew S. Ackerman, Brian Cairns, and Ann M. Fridlind

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A parameterization is presented that provides extinction cross section σ e, single-scattering albedo ω, and asymmetry parameter g of ice crystals for any combination of volume, projected area, aspect ratio, and crystal distortion at any wavelength in the shortwave. Similar to previous parameterizations, the scheme makes use of geometric optics approximations and the observation that optical properties of complex, aggregated ice crystals can be well approximated by those of single hexagonal crystals with varying size, aspect ratio, and distortion levels. In the standard geometric optics implementation used here, σ e is always twice the particle projected area. It is shown that ω is largely determined by the newly defined absorption size parameter and the particle aspect ratio. These dependences are parameterized using a combination of exponential, lognormal, and polynomial functions. The variation of g with aspect ratio and crystal distortion is parameterized for one reference wavelength using a combination of several polynomials. The dependences of g on refractive index and ω are investigated and factors are determined to scale the parameterized g to provide values appropriate for other wavelengths. The parameterization scheme consists of only 88 coefficients. The scheme is tested for a large variety of hexagonal crystals in several wavelength bands from 0.2 to 4 μm, revealing absolute differences with reference calculations of ω and g that are both generally below 0.015. Over a large variety of cloud conditions, the resulting root-mean-squared differences with reference calculations of cloud reflectance, transmittance, and absorptance are 1.4%, 1.1%, and 3.4%, respectively. Some practical applications of the parameterization in atmospheric models are highlighted.

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