scholarly journals Spectral dependence of MODIS cloud droplet effective radius retrievals for marine boundary layer clouds

2014 ◽  
pp. 135-165 ◽  
Author(s):  
Zhibo Zhang ◽  
Steven Platnick ◽  
Andrew S. Ackerman ◽  
Hyoun-Myoung Cho
Keyword(s):  
Boundary Layer ◽  
Spectral Dependence ◽  
Marine Boundary Layer ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Boundary Layer Clouds

Quantification of aerosol effects on marine boundary layer clouds with machine learning

2021 ◽  
Author(s):  
Lukas Zipfel ◽  
Hendrik Andersen ◽  
Jan Cermak
Keyword(s):  
Machine Learning ◽  
Boundary Layer ◽  
Marine Boundary Layer ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Satellite Observations ◽  
Radiative Properties ◽  
Cloud Base ◽  
Boundary Layer Clouds ◽  
Cloud Droplet Number Concentration

<p>Satellite observations are used in regional machine learning models to quantify sensitivities of marine boundary-layer clouds (MBLC) to aerosol changes.</p><p>MBLCs make up a large part of the global cloud coverage as they are persistently present over more than 20% of the Earth’s oceans in the annual mean.They play an important role in Earth’s energy budget by reflecting solar radiation and interacting with thermal radiation from the surface, leading to a net cooling effect. Cloud properties and their radiative characteristics such as cloud albedo, horizontal and vertical extent, lifetime and precipitation susceptibility are dependent on environmental conditions. Aerosols in their role as condensation nuclei affect these cloud radiative properties through changes in the cloud droplet number concentration and subsequent cloud adjustments to this perturbation. However, the magnitude and sign of these effects remain among the largest uncertainties in future climate predictions.</p><p>In an effort to help improve these predictions a machine learning approach in combination with observational data is pursued:</p><p>Satellite observations from the collocated A-Train dataset (C3M) for 2006-2011 are used in combination with ECMWF atmospheric reanalysis data (ERA5) to train regional Gradient Boosting Regression Tree (GBRT) models to predict changes in key physical and radiative properties of MBLCs. The cloud droplet number concentration (N<sub>d</sub>) and the liquid water path (LWP) are simulated for the eastern subtropical oceans, which are characterised by a high annual coverage of MBLC due to the occurrence of semi-permanent stratocumulus sheets. Relative humidity above cloud, cloud top height and temperature below the cloud base and at the surface are identified as important predictors for both N<sub>d</sub> and LWP.  The impact of each predictor variable on the GBRT model's output is analysed using Shapley values as a method of explainable machine learning, providing novel sensitivity estimates that will improve process understanding and help constrain the parameterization of MBLC processes in Global Climate Models.</p>

scholarly journals Modeling microphysical effects of entrainment in clouds observed during EUCAARI-IMPACT field campaign

2013 ◽  
Vol 13 (16) ◽  
pp. 8489-8503 ◽  
Author(s):  
D. Jarecka ◽  
H. Pawlowska ◽  
W. W. Grabowski ◽  
A. A. Wyszogrodzki
Keyword(s):  
Boundary Layer ◽  
Turbulent Mixing ◽  
Marine Boundary Layer ◽  
Cloud Droplet ◽  
Droplet Radius ◽  
Subgrid Scale ◽  
Microphysics Scheme ◽  
Local Conditions ◽  
Field Campaign ◽  
Les Model

Abstract. This paper discusses aircraft observations and large-eddy simulation (LES) modeling of 15 May 2008, North Sea boundary-layer clouds from the EUCAARI-IMPACT field campaign. These clouds are advected from the northeast by the prevailing lower-tropospheric winds and featured stratocumulus-over-cumulus cloud formations. An almost-solid stratocumulus deck in the upper part of the relatively deep, weakly decoupled marine boundary layer overlays a field of small cumuli. The two cloud formations have distinct microphysical characteristics that are in general agreement with numerous past observations of strongly diluted shallow cumuli on one hand and solid marine stratocumulus on the other. Based on the available observations, a LES model setup is developed and applied in simulations using a novel LES model. The model features a double-moment warm-rain bulk microphysics scheme combined with a sophisticated subgrid-scale scheme allowing local prediction of the homogeneity of the subgrid-scale turbulent mixing. The homogeneity depends on the characteristic time scales for the droplet evaporation and for the turbulent homogenization. In the model, these scales are derived locally based on the subgrid-scale turbulent kinetic energy, spatial scale of cloudy filaments, mean cloud droplet radius, and humidity of the cloud-free air entrained into a cloud, all predicted by the LES model. The model reproduces contrasting macrophysical and microphysical characteristics of the cumulus and stratocumulus cloud layers. Simulated subgrid-scale turbulent mixing within the cumulus layer and near the stratocumulus top is on average quite inhomogeneous, but varies significantly depending on the local conditions.

scholarly journals Mind the gap – Part 1: Accurately locating warm marine boundary layer clouds and precipitation using spaceborne radars

2020 ◽  
Vol 13 (5) ◽  
pp. 2363-2379 ◽  
Author(s):  
Katia Lamer ◽  
Pavlos Kollias ◽  
Alessandro Battaglia ◽  
Simon Preval
Keyword(s):  
Boundary Layer ◽  
Cloud Cover ◽  
Marine Boundary Layer ◽  
Short Pulse ◽  
Pulse Mode ◽  
Cloud Base ◽  
Boundary Layer Clouds ◽  
Highly Sensitive ◽  
Eastern North Atlantic ◽  
Long Pulse

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.

Exploring microphysical properties of marine boundary layer clouds through network analysis

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

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;In this study we use network analysis, (the &amp;#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. &amp;#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.&amp;#160;&lt;/p&gt;

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

2015 ◽  
Vol 8 (7) ◽  
pp. 2663-2683 ◽  
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.

scholarly journals Cloud Processing of Aerosol Particles in Marine Stratocumulus Clouds

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 520 ◽  
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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