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

2010 ◽  
Vol 23 (12) ◽  
pp. 3421-3423 ◽  
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

scholarly journals Statistical Analyses of Satellite Cloud Object Data from CERES. Part V: Relationships between Physical Properties of Marine Boundary Layer Clouds

2008 ◽  
Vol 21 (24) ◽  
pp. 6668-6688 ◽  
Author(s):  
Zachary A. Eitzen ◽  
Kuan-Man Xu ◽  
Takmeng Wong
Keyword(s):  
Boundary Layer ◽  
Cluster Analysis ◽  
Physical Properties ◽  
Radiative Forcing ◽  
Marine Boundary Layer ◽  
Radiant Energy ◽  
Cloud Fraction ◽  
Cloud Radiative Forcing ◽  
Boundary Layer Clouds ◽  
Shallow Cumulus

Abstract Relationships between physical properties are studied for three types of marine boundary layer cloud objects identified with the Clouds and the Earth’s Radiant Energy System (CERES) footprint data from the Tropical Rainfall Measuring Mission satellite between 30°S and 30°N. Each cloud object is a contiguous region of CERES footprints that have cloud-top heights below 3 km, and cloud fractions of 99%–100% (overcast type), 40%–99% (stratocumulus type), or 10%–40% (shallow cumulus type). These cloud fractions represent the fraction of ∼2 km × 2 km Visible/Infrared Scanner pixels that are cloudy within each ∼10 km × 10 km footprint. The cloud objects have effective diameters that are greater than 300 km for the overcast and stratocumulus types, and greater than 150 km for the shallow cumulus type. The Spearman rank correlation coefficient is calculated between many microphysical/optical [effective radius (re), cloud optical depth (τ), albedo, liquid water path, and shortwave cloud radiative forcing (SW CRF)] and macrophysical [outgoing longwave radiation (OLR), cloud fraction, cloud-top temperature, longwave cloud radiative forcing (LW CRF), and sea surface temperature (SST)] properties for each of the three cloud object types. When both physical properties are of the same category (microphysical/optical or macrophysical), the magnitude of the correlation tends to be higher than when they are from different categories. The magnitudes of the correlations also change with cloud object type, with the correlations for overcast and stratocumulus cloud objects tending to be higher than those for shallow cumulus cloud objects. Three pairs of physical properties are studied in detail, using a k-means cluster analysis: re and τ, OLR and SST, and LW CRF and SW CRF. The cluster analysis of re and τ reveals that for each of the cloud types, there is a cluster of cloud objects with negative slopes, a cluster with slopes near zero, and two clusters with positive slopes. The joint OLR and SST probability plots show that the OLR tends to decrease with SST in regions with boundary layer clouds for SSTs above approximately 298 K. When the cloud objects are split into “dry” and “moist” clusters based on the amount of precipitable water above 700 hPa, the associated OLRs increase with SST throughout the SST range for the dry clusters, but the OLRs are roughly constant with SST for the moist cluster. An analysis of the joint PDFs of LW CRF and SW CRF reveals that while the magnitudes of both LW and SW CRFs generally increase with cloud fraction, there is a cluster of overcast cloud objects that has low values of LW and SW CRF. These objects are generally located near the Sahara Desert, and may be contaminated with dust. Many of these overcast objects also appear in the re and τ cluster with negative slopes.

Seasonal Variation of the Physical Properties of Marine Boundary Layer Clouds off the California Coast

2009 ◽  
Vol 22 (10) ◽  
pp. 2624-2638 ◽  
Author(s):  
Wuyin Lin ◽  
Minghua Zhang ◽  
Norman G. Loeb
Keyword(s):  
Boundary Layer ◽  
Seasonal Variation ◽  
Air Temperature ◽  
Seasonal Variations ◽  
Marine Boundary Layer ◽  
Sea Surface ◽  
Cloud Base ◽  
California Coast ◽  
Low Clouds ◽  
Inversion Strength

Abstract Marine boundary layer (MBL) clouds can significantly regulate the sensitivity of climate models, yet they are currently poorly simulated. This study aims to characterize the seasonal variations of physical properties of these clouds and their associated processes by using multisatellite data. Measurements from several independent satellite datasets [International Satellite Cloud Climatology Project (ISCCP), Clouds and the Earth’s Radiant Energy System–Moderate Resolution Imaging Spectroradiometer (CERES–MODIS), Geoscience Laser Altimeter System (GLAS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)], in conjunction with balloon soundings from the mobile facility of the Atmospheric Radiation Measurement (ARM) program at Point Reyes and reanalysis products, are used to characterize the seasonal variations of MBL cloud-top and cloud-base heights, cloud thickness, the degree of decoupling between clouds and MBL, and inversion strength off the California coast. The main results from this study are as follows: (i) MBL clouds over the northeast subtropical Pacific in the summer are more prevalent and associated with a larger in-cloud water path than in winter. The cloud-top and cloud-base heights are lower in the summer than in the winter. (ii) Although the lower-tropospheric stability of the atmosphere is higher in the summer, the MBL inversion strength is only weakly stronger in the summer because of a negative feedback from the cloud-top altitude. Summertime MBL clouds are more homogeneous and are associated with lower surface latent heat flux than those in the winter. (iii) Seasonal variations of low-cloud properties from summer to winter resemble the downstream stratocumulus-to-cumulus transition of MBL clouds in terms of MBL depth, cloud-top and cloud-base heights, inversion strength, and spatial homogeneity. The “deepening–warming” mechanism of Bretherton and Wyant for the stratocumulus-to-trade-cumulus transition downstream of the cold eastern ocean can also explain the seasonal variation of low clouds from the summer to the winter, except that warming of the sea surface temperature needs to be taken as relative to the free-tropospheric air temperature, which occurs in the winter. The observed variation of low clouds from summer to winter is attributed to the much larger seasonal cooling of the free-tropospheric air temperature than that of the sea surface temperature.

scholarly journals Stratocumulus Cloud Clearings and Notable Thermodynamic and Aerosol Contrasts across the Clear–Cloudy Interface

2016 ◽  
Vol 73 (3) ◽  
pp. 1083-1099 ◽  
Author(s):  
Ewan Crosbie ◽  
Zhen Wang ◽  
Armin Sorooshian ◽  
Patrick Y. Chuang ◽  
Jill S. Craven ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Observational Studies ◽  
Marine Boundary Layer ◽  
California Coast ◽  
Boundary Layer Clouds ◽  
Primary Driver ◽  
Scale Characteristics ◽  
Dynamic Forcing ◽  
Multiple Levels ◽  
Aerosol Cloud Interactions

Abstract Data from three research flights, conducted over water near the California coast, are used to investigate the boundary between stratocumulus cloud decks and clearings of different sizes. Large clearings exhibit a diurnal cycle with growth during the day and contraction overnight and a multiday life cycle that can include oscillations between growth and decay, whereas a small coastal clearing was observed to be locally confined with a subdiurnal lifetime. Subcloud aerosol characteristics are similar on both sides of the clear–cloudy boundary in the three cases, while meteorological properties exhibit subtle, yet important, gradients, implying that dynamics, and not microphysics, is the primary driver for the clearing characteristics. Transects, made at multiple levels across the cloud boundary during one flight, highlight the importance of microscale (~1 km) structure in thermodynamic properties near the cloud edge, suggesting that dynamic forcing at length scales comparable to the convective eddy scale may be influential to the larger-scale characteristics of the clearing. These results have implications for modeling and observational studies of marine boundary layer clouds, especially in relation to aerosol–cloud interactions and scales of variability responsible for the evolution of stratocumulus clearings.

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.

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