Perturbed physics ensemble simulations of cirrus on the cloud system‐resolving scale

Abstract

In this study, the effect of uncertainties in the parameterization of ice microphysical processes and initial conditions on the variability of cirrus microphysical and radiative properties are investigated in a series of cloud system‐resolving perturbed physics ensemble (PPE) and initial condition ensemble (ICE) simulations. Three cirrus cases representative of midlatitude, subtropical, and tropical anvil cirrus are examined. The variability in cirrus properties induced by perturbing uncertain parameters in ice microphysics parameterizations outweighs the variability induced by perturbing the initial conditions in midlatitude and subtropical cirrus. However, in tropical anvil cirrus the variability spanned by the PPE and ICE simulations is on the same order of magnitude. Uncertainties in the parameterization of ice microphysical processes affect the vertical distribution of cloud fraction, ice water content, and cloud thickness, whereas cirrus cloud cover is only marginally affected. The top three uncertainties controlling the microphysical variability and radiative impact of cirrus clouds are the mode of ice nucleation, the number concentrations of ice nuclei available for heterogeneous freezing, and the threshold size of the parameterized ice autoconversion process. Uncertainties in ice fall speeds are of minor importance. Changes in the ice deposition coefficient induce only transient effects on the microphysical properties and radiative impacts of cirrus except in cases of very low ice deposition coefficients of about 0.05. Changes in the sulfate aerosol number concentration available for homogeneous freezing have virtually no effect on the microphysical properties and radiative impact of midlatitude and subtropical cirrus but a minor effect on tropical anvil cirrus.

How microphysical choices affect simulated infrared brightness temperatures

“…It is shown that the combination of the change to the modified Phillips et al (2008) heterogeneous ice nucleation scheme with the introduction of the sedimentation of cloud ice accounts for the largest change in CIWC. This partly agrees with Muhlbauer et al (2014), who identify the number of IN available for heterogeneous freezing, which is controlled by the heterogeneous ice nucleation scheme, as one of the three major uncertainties in microphysical variability. Including cloud ice sedimentation whilst keeping the former modified Fletcher (1962) ice nucleation scheme has a far smaller impact, because the modified Fletcher (1962) scheme produces more numerous but smaller cloud ice crystals, which-due to the sizedependency of their fall speed-sediment slower than the less numerous but larger cloud ice crystals the Phillips et al (2008) scheme produces.…”

Aerosol effects on cirrus through ice nucleation in the Community Atmosphere Model CAM5 with a statistical cirrus scheme

“…Using a cloud‐system‐resolving model with two‐moment cloud microphysics scheme, Muhlbauer et al . [] also showed that sulfate aerosol number concentrations available for homogeneous freezing have virtually no effect on the microphysical properties and radiative impact of midlatitude and subtropical cirrus and have only minor effect on tropical anvil cirrus. For midlatitude and subtropical cirrus, the insensitivity of cirrus cloud properties to sulfate aerosol number concentrations is attributed to the fact that cirrus formation in these clouds is dominated by heterogeneous freezing in their simulations.…”

“…With a time step of 10 s, it is not clear how well the supersaturation is simulated for ice freezing events and further for the effects of sulfate aerosol number concentrations on simulated cirrus cloud properties in Muhlbauer et al . []. The discrepancy between this study and some other studies is now being further investigated with cloud parcel models under a variety of conditions such as sulfate aerosol size distribution, updraft velocity, numerics, etc.…”

Implementation of aerosol–cloud interactions in the regional atmosphere–aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

“…While using COSP facilitates a more consistent comparison between model output and satellite data, differences between the model simulation and the satellite can, for example, still arise due to displacements in simulated storm tracks. COSP has previously been used with COSMO by Mühlbauer et al (2014Mühlbauer et al ( , 2015. The output diagnostics include a variety of cloud properties, which facilitate consistent model-to-observation comparisons as well as consistent intermodel comparisons.…”