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Andreas Muhlbauer and Ulrike Lohmann

Abstract

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentration is assumed to retard the cloud droplet coalescence and the riming process in mixed-phase orographic clouds, thereby decreasing orographic precipitation.

In this study, idealized 3D simulations are conducted to investigate aerosol–cloud interactions in mixed-phase orographic clouds and the possible impact of anthropogenic and natural aerosols on orographic precipitation. Two different types of aerosol anomalies are considered: naturally occurring mineral dust and anthropogenic black carbon.

In the simulations with a dust aerosol anomaly, the dust aerosols serve as efficient ice nuclei in the contact mode, leading to an early initiation of the ice phase in the orographic cloud. As a consequence, the riming rates in the cloud are increased, leading to increased precipitation efficiency and enhancement of orographic precipitation.

The simulations with an anthropogenic aerosol anomaly suggest that the mixing state of the aerosols plays a crucial role because coating and mixing may cause the aerosols to initiate freezing in the less efficient immersion mode rather than by contact nucleation. It is found that externally mixed black carbon aerosols increase riming in orographic clouds and enhance orographic precipitation. In contrast, internally mixed black carbon aerosols decrease the riming rates, leading in turn to a decrease in orographic precipitation.

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Andreas Muhlbauer and Ulrike Lohmann

Abstract

Aerosols serve as a source of cloud condensation nuclei (CCN) and influence the microphysical properties of clouds. In the case of orographic clouds, it is suspected that aerosol–cloud interactions reduce the amount of precipitation on the upslope side of the mountain and enhance the precipitation on the downslope side when the number of aerosols is increased. The net effect may lead to a shift of the precipitation distribution toward the leeward side of mountain ranges, which affects the hydrological cycle on the local scale.

In this study aerosol–cloud interactions in warm-phase clouds and the possible impact on the orographic precipitation distribution are investigated. Herein, simulations of moist orographic flow over topography are conducted and the influence of anthropogenic aerosols on the orographic precipitation formation is analyzed. The degree of aerosol pollution is prescribed by different aerosol spectra that are representative for central Switzerland. The simulations are performed with the Consortium for Small-Scale Modeling’s mesoscale nonhydrostatic limited-area weather prediction model (COSMO) with a horizontal grid spacing of 2 km and a fully coupled aerosol–cloud parameterization.

It is found that an increase in the aerosol load leads to a downstream shift of the orographic precipitation distribution and to an increase in the spillover factor. A reduction of warm-phase orographic precipitation is observed at the upslope side of the mountain. The downslope precipitation enhancement depends critically on the width of the mountain and on the flow dynamics. In the case of orographic precipitation induced by stably stratified unblocked flow, the loss in upslope precipitation is not compensated by leeward precipitation enhancement. In contrast, flow blocking may lead to leeward precipitation enhancement and eventually to a compensation of the upslope precipitation loss. The simulations also indicate that latent heat effects induced by aerosol–cloud–precipitation interactions may considerably affect the orographic flow dynamics and consequently feed back on the orographic precipitation development.

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Andreas Muhlbauer, Peter Spichtinger, and Ulrike Lohmann

Abstract

In this study, robust parametric regression methods are applied to temperature and precipitation time series in Switzerland and the trend results are compared with trends from classical least squares (LS) regression and nonparametric approaches. It is found that in individual time series statistically outlying observations are present that influence the LS trend estimate severely. In some cases, these outlying observations lead to an over-/underestimation of the trends or even to a trend masking. In comparison with the classical LS method and standard nonparametric techniques, the use of robust methods yields more reliable trend estimations and outlier detection.

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Hugh Morrison, Greg Thompson, Matthew Gilmore, Wanmin Gong, Richard Leaitch, and Andreas Muhlbauer
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Elias M. Zubler, Ulrike Lohmann, Daniel Lüthi, Christoph Schär, and Andreas Muhlbauer

Abstract

Increasing the aerosol number in warm-phase clouds is thought to decrease the rain formation rate, whereas the physical processes taking place in mixed-phase clouds are more uncertain. Increasing number concentrations of soluble aerosols may reduce the riming efficiency and therefore also decrease precipitation. On the other hand, the glaciation of a cloud by heterogeneous freezing of cloud droplets may enhance the formation of graupel and snow. Using a numerical weather prediction model with coupled aerosol microphysics, it is found, in a statistical framework with 270 clean and polluted 2D simulations of mixed-phase precipitation over an Alpine transect, that the presence of the ice phase determines the magnitude and the sign of the effect of an increasing aerosol number concentration on orographic precipitation. Immersion/condensation freezing is the only ice-nucleating process considered here. It is shown that this indirect aerosol effect is much less pronounced in cold simulations compared to a warmer subset and that cloud glaciation tends to compensate the loss of rain in polluted situations. Comparing the clean and polluted cases, a reduction of rain by 52%, on average (std dev = 25%), over the transect in the polluted cases is found. For frozen precipitation a much broader range of differences is found (mean = +4%, std dev = 60%). Furthermore, this study shows that in comparison with the clean cases more precipitation spills over to the leeward side of the major ridge in the polluted cases (median = +14.6%).

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Douglas Lowenthal, A. Gannet Hallar, Ian McCubbin, Robert David, Randolph Borys, Peter Blossey, Andreas Muhlbauer, Zhiming Kuang, and Mary Moore

Abstract

The Isotopic Fractionation in Snow (IFRACS) study was conducted at Storm Peak Laboratory (SPL) in northwestern Colorado during the winter of 2014 to elucidate snow growth processes in mixed-phase clouds. The isotopic composition (δ 18O and δD) of water vapor, cloud water, and snow in mixed-phase orographic clouds were measured simultaneously for the first time. The depletion of heavy isotopes [18O and deuterium (D)] was greatest for vapor, followed by snow, then cloud. The vapor, cloud, and snow compositions were highly correlated, suggesting similar cloud processes throughout the experiment. The isotopic composition of the water vapor was directly related to its concentration. Isotopic fractionation during condensation of vapor to cloud drops was accurately reproduced assuming equilibrium fractionation. This was not the case for snow, which grows by riming and vapor deposition. This implies stratification of vapor with altitude. The relationship between temperature at SPL and δ 18O was used to show that the snow gained most of its mass within 922 m above SPL. Relatively invariant deuterium excess (d) in vapor, cloud water, and snow from day to day suggests a constant vapor source and Rayleigh fractionation during transport. The diurnal variation of vapor d reflected the differences between surface and free-tropospheric air during the afternoon and early morning hours, respectively. These observations will be used to validate simulations of snow growth using an isotope-enabled mesoscale model with explicit microphysics.

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Andreas Muhlbauer, Wojciech W. Grabowski, Szymon P. Malinowski, Thomas P. Ackerman, George H. Bryan, Zachary J. Lebo, Jason A. Milbrandt, Hugh Morrison, Mikhail Ovchinnikov, Sarah Tessendorf, Julie M. Thériault, and Greg Thompson
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