The Numerical Simulation of Marine Boundary Layer Clouds

Abstract. Ground-based radar observations show that, over the eastern North Atlantic, 50 % of warm marine boundary layer (WMBL) hydrometeors occur below 1.2 km and have reflectivities of < −17 dBZ, thus making their detection from space susceptible to the extent of surface clutter and radar sensitivity. Surface clutter limits the ability of the CloudSat cloud profiling radar (CPR) to observe the true cloud base in ∼52 % of the cloudy columns it detects and true virga base in ∼80 %, meaning the CloudSat CPR often provides an incomplete view of even the clouds it does detect. Using forward simulations, we determine that a 250 m resolution radar would most accurately capture the boundaries of WMBL clouds and precipitation; that being said, because of sensitivity limitations, such a radar would suffer from cloud cover biases similar to those of the CloudSat CPR. Observations and forward simulations indicate that the CloudSat CPR fails to detect 29 %–43 % of the cloudy columns detected by ground-based sensors. Out of all configurations tested, the 7 dB more sensitive EarthCARE CPR performs best (only missing 9.0 % of cloudy columns) indicating that improving radar sensitivity is more important than decreasing the vertical extent of surface clutter for measuring cloud cover. However, because 50 % of WMBL systems are thinner than 400 m, they tend to be artificially stretched by long sensitive radar pulses, hence the EarthCARE CPR overestimation of cloud top height and hydrometeor fraction. Thus, it is recommended that the next generation of space-borne radars targeting WMBL science should operate interlaced pulse modes including both a highly sensitive long-pulse mode and a less sensitive but clutter-limiting short-pulse mode.

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Dynamical and thermodynamical coupling between the North Atlantic subtropical high and the marine boundary layer clouds in boreal summer

Climate Dynamics ◽

10.1007/s00382-017-3750-6 ◽

2017 ◽

Vol 50 (7-8) ◽

pp. 2457-2469 ◽

Cited By ~ 2

Author(s):

Wei Wei ◽

Wenhong Li ◽

Yi Deng ◽

Song Yang ◽

Jonathan H. Jiang ◽

...

Keyword(s):

Boundary Layer ◽

North Atlantic ◽

Marine Boundary Layer ◽

Subtropical High ◽

Boreal Summer ◽

Boundary Layer Clouds ◽

North Atlantic Subtropical High ◽

The North ◽

The North Atlantic

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Reply to Comments on “Seasonal Variation of the Physical Properties of Marine Boundary Layer Clouds off the California Coast”

Journal of Climate ◽

10.1175/2010jcli3483.1 ◽

2010 ◽

Vol 23 (12) ◽

pp. 3421-3423 ◽

Cited By ~ 1

Author(s):

Wuyin Lin ◽

Minghua Zhang ◽

Norman G. Loeb

Keyword(s):

Boundary Layer ◽

Seasonal Variation ◽

Physical Properties ◽

Marine Boundary Layer ◽

California Coast ◽

Boundary Layer Clouds

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Exploring microphysical properties of marine boundary layer clouds through network analysis

10.5194/egusphere-egu21-13307 ◽

2021 ◽

Author(s):

Lucile Ricard ◽

Athanasios Nenes ◽

Jakob Runge ◽

Paraskevi Georgakaki

Keyword(s):

Boundary Layer ◽

High Resolution ◽

Network Analysis ◽

Marine Boundary Layer ◽

Large Eddy Simulations ◽

Dynamical Structure ◽

Boundary Layer Clouds ◽

Microphysical Properties ◽

Spatial Coverage ◽

Large Eddy

<p>Aerosol-cloud interactions remain the largest uncertainty in assessments of anthropogenic climate forcing, while the complexity of these interactions require methods that enable abstractions and simplifications that allow their improved treatment in climate models. Marine boundary layer clouds are an important component of the climate system as their large albedo and spatial coverage strongly affect the planetary radiative balance. High resolution simulations of clouds provide an unprecedented understanding of the structure and behavior of these clouds in the marine atmosphere, but the amount of data is often too large and complex to be useful in climate simulations. Data reduction and inference methods provide a way that to reduce the complexity and dimensionality of datasets generated from high-resolution Large Eddy Simulations.</p><p>In this study we use network analysis, (the &#948;-Maps method) to study the complex interaction between liquid water, droplet number and vertical velocity in Large Eddy Simulations of Marine Boundary Layer clouds. &#948;-Maps identifies domains that are spatially contiguous and possibly overlapping and characterizes their connections and temporal interactions. The objective is to better understand microphysical properties of marine boundary layer clouds, and how they are impacted by the variability in aerosols. Here we will capture the dynamical structure of the cloud fields predicted by the MIMICA Large Eddy Simulation (LES) model. The networks inferred from the different simulation fields are compared between them (intra-comparisons) using perturbations in initial conditions and aerosol, using a set of four metrics. The networks are then evaluated for their differences, quantifying how much variability is inherent in the LES simulations versus the robust changes induced by the aerosol fields.&#160;</p>

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Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

Atmospheric Measurement Techniques ◽

10.5194/amt-8-2663-2015 ◽

2015 ◽

Vol 8 (7) ◽

pp. 2663-2683 ◽

Cited By ~ 21

Author(s):

M. D. Fielding ◽

J. C. Chiu ◽

R. J. Hogan ◽

G. Feingold ◽

E. Eloranta ◽

...

Keyword(s):

Boundary Layer ◽

Marine Boundary Layer ◽

Microwave Radiometer ◽

Cloud Water ◽

Radar Reflectivity ◽

New Method ◽

Error Statistics ◽

Water Path ◽

Boundary Layer Clouds ◽

Cloud Water Path

Abstract. Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.

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Cloud Processing of Aerosol Particles in Marine Stratocumulus Clouds

Atmosphere ◽

10.3390/atmos10090520 ◽

2019 ◽

Vol 10 (9) ◽

pp. 520 ◽

Cited By ~ 1

Author(s):

Andrea I. Flossmann ◽

Wolfram Wobrock

Keyword(s):

Boundary Layer ◽

Marine Boundary Layer ◽

Numerical Study ◽

Spatial Scales ◽

Aerosol Particles ◽

Cloud Microphysics ◽

Marine Stratocumulus ◽

Boundary Layer Clouds ◽

Cloud Processing ◽

Stratocumulus Clouds

Cloud processing of aerosol particles is an important process and is, for example, thought to be responsible for the so-called “Hoppel-minimum” in the marine aerosol particle distribution or contribute to the cell organization of marine boundary layer clouds. A numerical study of the temporal and spatial scales of the processing of aerosol particles by typical marine stratocumulus clouds is presented. The dynamical framework is inspired by observations during the VOCALS (Variability of the American Monsoon System Ocean-Cloud-Atmosphere-Land Study) Regional Experiment in the Southeast Pacific. The 3-D mesoscale model version of DESCAM (Detailed Scavenging Model) follows cloud microphysics of the stratocumulus deck in a bin-resolved manner and has been extended to keep track of cloud-processed particles in addition to non-processed aerosol particles in the air and inside the cloud drops. The simulation follows the evolution of the processing of aerosol particles by the cloud. It is found that within one hour almost all boundary layer aerosol particles have passed through at least one cloud cycle. However, as the in-cloud residence times of the particles in the considered case are only on the order of minutes, the aerosol particles remain essentially unchanged. Our findings suggest that in order to produce noticeable microphysical and dynamical effects in the marine boundary layer clouds, cloud processing needs to continue for extended periods of time, exceeding largely the time period considered in the present study. A second model study is dedicated to the interaction of ship track particles with marine boundary layer clouds. The model simulates quite satisfactorily the incorporation of the ship plume particles into the cloud. The observed time and spatial scales and a possible Twomey effect were reproduced.

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