Macrophysical properties of continental shallow cumuli: diurnal evolution

2019 ◽  
Author(s):  
Evgueni I. Kassianov ◽  
Erin A. Riley ◽  
Jessica M. Kleiss ◽  
Laura D. Riihimaki ◽  
Larry K. Berg
Keyword(s):  
Macrophysical Properties

scholarly journals Cirrus clouds properties derived from polarized micro pulse lidar (p-mpl) observations at the atmospheric observatory ‘el arenosillo’ (sw iberian peninsula): a case study for radiative implications

2018 ◽  
Vol 176 ◽  
pp. 05042
Author(s):  
Ana del Águila ◽  
Laura Gómez ◽  
José Manuel Vilaplana ◽  
Mar Sorribas ◽  
Carmen Córdoba-Jabonero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Surface Radiation ◽  
Radiative Balance ◽  
Macrophysical Properties ◽  
Micro Pulse Lidar ◽  
First Time ◽  
Change Concerns

Cirrus (Ci) clouds are involved in Climate Change concerns since they affect the radiative balance of the atmosphere. Recently, a polarized Micro Pulse Lidar (P-MPL), standard system within NASA/MPLNET has been deployed at the INTA/Atmospheric Observatory ‘El Arenosillo’ (ARN), located in the SW Iberian Peninsula. Hence, the INTA/P-MPL system is used for Ci detection over that station for the first time. Radiative effects of a Ci case observed over ARN are examined, as reference for future long-term Ci observations. Optical and macrophysical properties are retrieved, and used for radiative transfer simulations. Data are compared to the measured surface radiation levels and all-sky images simultaneously performed at the ARN station.

Observed and Modeled Warm Rainfall Occurrence and Its Relationships with Cloud Macrophysical Properties

2015 ◽  
Vol 72 (11) ◽  
pp. 4075-4090 ◽  
Author(s):  
Joshua M. King ◽  
Christian D. Kummerow ◽  
Susan C. van den Heever ◽  
Matthew R. Igel
Keyword(s):  
Atmospheric Modeling ◽  
Rainfall Occurrence ◽  
Analysis Technique ◽  
Lower Cloud ◽  
Statistical Relationships ◽  
Macrophysical Properties ◽  
Fine Resolution ◽  
Regional Atmospheric Modeling ◽  
Negatively Buoyant ◽  
Equilibrium Experiment

Abstract Observed and modeled rainfall occurrence from shallow (warm) maritime clouds and their composite statistical relationships with cloud macrophysical properties are analyzed and directly compared. Rain falls from ~25% of warm, single-layered, maritime clouds observed by CloudSat and from ~27% of the analogous warm clouds simulated within a large-domain, fine-resolution radiative–convective equilibrium experiment performed using the Regional Atmospheric Modeling System (RAMS), with its sophisticated bin-emulating bulk microphysical scheme. While the fractional occurrence of observed and simulated warm rainfall is found to increase with both increasing column-integrated liquid water and cloud depth, calculations of rainfall occurrence as a joint function of these two macrophysical quantities suggest that the modeled bulk cloud-to-rainwater conversion process is more efficient than observations indicate—in agreement with previous research. Unexpectedly and in opposition to the model-derived relationship, deeper CloudSat-observed warm clouds with little column water mass are more likely to rain than their corresponding shallow counterparts, despite having lower cloud-mean water contents. Given that these composite relationships were derived from statically identified warm clouds, an attempt is made to quantitatively explore rainfall occurrence within the context of the warm cloud life cycle. Extending a previously established cloud-top buoyancy analysis technique, it is shown that rainfall likelihoods from positively buoyant RAMS-simulated clouds more closely resemble the surprising observed relationships than do those derived from negatively buoyant simulated clouds. This suggests that relative to the depiction of warm clouds within the RAMS output, CloudSat observes higher proportions of positively buoyant, developing warm clouds.

Cloud macrophysical properties from airborne observations during EUREC4A

2020 ◽  
Author(s):  
Heike Konow ◽  
Marcus Klingebiel ◽  
Felix Ament
Keyword(s):  
Deep Convection ◽  
Dry Season ◽  
Trade Wind ◽  
Special Focus ◽  
Wet Season ◽  
Diurnal Cycles ◽  
Cloud Radar ◽  
Wide Range ◽  
Macrophysical Properties ◽  
Different Response

<p><span>Trade wind cumulus clouds are the predominant cloud type over the tropical Atlantic east of the island of Barbados. Parameters describing their macroscopic shape can help characterizing and comparing general features of clouds. This characterizing will indirectly help to constrain estimates of climate sensitivity, because models with different structures of trade wind cumuli feature different response to increased CO2 contents.</span></p><p><span>Two aircraft campaigns with the HALO (High Altitude LOng range) aircraft took place in the recent past in this region: NARVAL-South (Next-generation Aircraft Remote-Sensing for VALidation studies) in December 2013, during the dry season, and NARVAL2 in August 2016, during the wet season. During these two campaigns, a wide range of cloud regimes from shallow to deep convection were sampled. This past observations are now extended with observations from this year’s measurement campaign EUREC<sup>4</sup>A, again during the dry season. EUREC<sup>4</sup>A is endorsed as WCRP capstone experiment and the synergy of four research aircraft, four research vessels and numerous additional observations will provide comprehensive characterizations of trade wind clouds and their environment.</span></p><p><span>Part of the NARVAL payload on HALO is a 35 GHz cloud radar, which has been deployed on HALO on several missions since 2013. These cloud radar measurements are used to segment individual clouds entities by applying connected component analysis to the radar cloud mask. From these segmented individual clouds, macrophysical parameters are derived to characterize each individual cloud. </span></p><p><span>This presentation will give an overview of the cloud macrophysics observed from HALO during EUREC<sup>4</sup>A. Typical macrophysical parameters, i.e. cloud depth, cloud length, cloud fraction, are analyzed. We will relate these to observations from past campaigns and assess the representativeness of EUREC<sup>4</sup>A. As special focus of the EUREC<sup>4</sup>A campaign, measurements will be performed during different times of the day to detect diurnal cycles. Macrophysical parameters can be used to characterize changes over the day and cloud scenes of similar clouds types can be identified.</span></p>

Cloud macrophysical properties from KAZR at the SACOL

2017 ◽  
Vol 62 (8) ◽  
pp. 824-835 ◽  
Author(s):  
ZeEn ZHU ◽  
Chuang ZHENG ◽  
JinMing GE ◽  
JianPing HUANG ◽  
Qiang FU
Keyword(s):  
Macrophysical Properties

scholarly journals Subseasonal variability of low cloud radiative properties over the southeast Pacific Ocean

2010 ◽  
Vol 10 (8) ◽  
pp. 4047-4063 ◽  
Author(s):  
R. C. George ◽  
R. Wood
Keyword(s):  
Large Scale ◽  
Cloud Fraction ◽  
Radiative Properties ◽  
Pressure System ◽  
Cloud Albedo ◽  
Cloud Properties ◽  
Droplet Concentration ◽  
Subseasonal Variability ◽  
Low Cloud ◽  
Macrophysical Properties

Abstract. Subseasonal variability of cloud radiative properties in the persistent southeast Pacific stratocumulus deck is investigated using MODIS satellite observations and NCEP reanalysis data. A once-daily albedo proxy is derived based on the fractional coverage of low cloud (a macrophysical field) and the cloud albedo, with the latter broken down into contributions from microphysics (cloud droplet concentration) and macrophysics (liquid water path). Subseasonal albedo variability is dominated by the contribution of low cloud fraction variability, except within 10–15° of the South American coast, where cloud albedo variability contributes significantly. Covariance between cloud fraction and cloud albedo also contributes significantly and positively to the variance in albedo, which highlights how complex and inseparable the factors controlling albedo are. Droplet concentration variability contributes only weakly to the subseasonal variability of albedo, which emphasizes that attributing albedo variability to the indirect effects of aerosols against the backdrop of natural meteorological variability is extremely challenging. The dominant large scale meteorological variability is associated with the subtropical high pressure system. Two indices representing changes in the subtropical high strength and extent explain 80–90% of this variability, and significantly modulate the cloud microphysical, macrophysical, and radiative cloud properties. Variations in droplet concentration of up to 50% of the mean are associated with the meteorological driving. We hypothesize that these fluctuations in droplet concentration are a result of the large scale meteorology and their correlation with cloud macrophysical properties should not be used as evidence of aerosol effects. Mechanisms by which large scale meteorology affects cloud properties are explored. Our results support existing hypotheses linking cloud cover variability to changes in cold advection, subsidence, and lower tropospheric stability. Within 10° of the coast interactions between variability in the surface high pressure system and the orography appear to modulate both cloud macrophysical properties and aerosol transport through suppression of the marine boundary layer depth near the coast. This suggests one possible way in which cloud macrophysical properties and droplet concentration may be correlated independently of the second aerosol indirect effect. The results provide variability constraints for models that strive to represent both meteorological and aerosol impacts on stratocumulus clouds.

scholarly journals Effect of Aerosol on the Susceptibility and Efficiency of Precipitation in Warm Trade Cumulus Clouds

2010 ◽  
Vol 67 (11) ◽  
pp. 3525-3540 ◽  
Author(s):  
Hongli Jiang ◽  
Graham Feingold ◽  
Armin Sorooshian
Keyword(s):  
Power Law ◽  
Precipitation Rate ◽  
Trade Wind ◽  
Liquid Water Path ◽  
Cumulus Clouds ◽  
Scale Models ◽  
Stratocumulus Clouds ◽  
Power Law Function ◽  
Macrophysical Properties ◽  
Precipitating Clouds

Abstract Large-eddy simulations of warm, trade wind cumulus clouds are conducted for a range of aerosol conditions with a focus on precipitating clouds. Individual clouds are tracked over the course of their lifetimes. Precipitation rate decreases progressively as aerosol increases. For larger, precipitating clouds, the polluted clouds have longer lifetimes because of precipitation suppression. For clean aerosol conditions, there is good agreement between the average model precipitation rate and that calculated based on observed radar reflectivity Z and precipitation rate R relationships. Precipitation rate can be expressed as a power-law function of liquid water path (LWP) and Nd, to reasonable accuracy. The respective powers for LWP and Nd are of similar magnitude compared to those based on observational studies of stratocumulus clouds. The time-integrated precipitation rate represented by a power-law function of LWP, Nd, and cloud lifetime is much more reliably predicted than is R expressed in terms of LWP and Nd alone. The precipitation susceptibility (So = −dlnR/dlnNd) that quantifies the sensitivity of precipitation to changes in Nd depends strongly on LWP and exhibits nonmonotonic behavior with a maximum at intermediate LWP values. The relationship between So and precipitation efficiency is explored and the importance of including dependence on Nd in the latter is highlighted. The results provide trade cumulus cloud population statistics, as well as relationships between microphysical/macrophysical properties and precipitation, that are amenable for use in larger-scale models.

scholarly journals Statistical Analyses of Satellite Cloud Object Data from CERES. Part II: Tropical Convective Cloud Objects during 1998 El Niño and Evidence for Supporting the Fixed Anvil Temperature Hypothesis

2007 ◽  
Vol 20 (5) ◽  
pp. 819-842 ◽  
Author(s):  
Kuan-Man Xu ◽  
Takmeng Wong ◽  
Bruce A. Wielicki ◽  
Lindsay Parker ◽  
Bing Lin ◽  
...  
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Convective Cloud ◽  
Tropical Pacific ◽  
Statistical Distributions ◽  
Size Category ◽  
High Cloud ◽  
Large Size ◽  
Precession Cycle ◽  
Macrophysical Properties

Abstract Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January–August 1998 are examined using the Tropical Rainfall Measuring Mission/Clouds and the Earth’s Radiant Energy System Single Scanner Footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud object size, sea surface temperature (SST), and satellite precession cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100–150 (small), 150–300 (medium), and >300 km (large), except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed toward high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precession cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This evidence supports the fixed anvil temperature hypothesis of Hartmann and Larson for the large-size category. Combined with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SST ranges, statistical characteristics of cloud microphysical properties, optical depth, and albedo are not sensitive to the SST, but those of cloud macrophysical properties are dependent upon the SST. This result is related to larger differences in large-scale dynamics among the SST ranges than among the satellite precession cycles. Frequency distributions of vertical velocity from the European Centre for Medium-Range Weather Forecasts model that is matched to each cloud object are used to further understand some of the findings in this study.

Sign in / Sign up

Export Citation Format

Share Document