Characterization of Shallow Oceanic Precipitation using Profiling and Scanning Radar Observations at the Eastern North Atlantic ARM Observatory

Lamer, Katia; Treserras, Bernat Puigdomènech; Zhu, Zeen; Isom, Bradley; Bharadwaj, Nitin; Kollias, Pavlos

doi:10.5194/amt-2019-160

Cited by 4 publications

(6 citation statements)

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“…Determination of drizzle sizes from vertically pointing remote sensing instruments inherently assumes the center of the drizzle cell to pass directly over the site and limit the number of cells sampled within the cloud field. Observations from scanning precipitation radars operating in surveillance mode together with data from geostationary satellites could be used to derive the drizzle cell sizes, their temporal and spatial evolution, and changes in intensity (Lamer et al, 2019). Out of the 251 drizzle shafts observed by the vertically pointing instruments, only 76 (28%) were sampled for more than 15 min by the radar.…”

Section: Summary and Discussionmentioning

confidence: 99%

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

2020

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Nine cases of postcold frontal marine stratocumulus clouds exhibiting open cellular mesoscale organization are analyzed to characterize the drizzle, turbulence, and density currents below them. Data collected by the vertically pointing Doppler cloud radar and multiple lidars part of the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site are used in these analyses. A total of 251 drizzle shafts passed over the site with 76 shafts sampled for more than 15 min by the vertically pointing instruments. On average the drizzle shafts were~18 km wide with below-cloud drizzle water path of 40 g m −2 , cloud base rain rate of 7.78 mm day −1 , and cloud base drizzle modal diameter of 393 μm. The widths of the drizzle shafts did not exhibit any relationship with the cloud base rain rate, below-cloud drizzle water path, and the total water removed from the cloud. The downdrafts in the lowest 500 m within the drizzle cells strengthened with increasing cloud base rain rates, while the updrafts within drizzle cells did not exhibit this behavior. On average, the surface air density, pressure, water vapor mixing ratio, and wind speed along the background wind during the drizzle shaft were higher by 1.88 g m −3 , 8.60 Pa, 0.24 g kg −1 , and 1.22 m s −1 , respectively, from their background values. On the other hand, the surface air temperature was lower by 0.43 K during the drizzle shaft than its background value. The coincident measurements highlight the drizzle-turbulence-surface coupling in these cloud systems. In this study, the data collected at the Atmospheric Radiation Measurement (ARM)'s Eastern North Atlantic (ENA) site are used along with those from instruments on board geostationary and polar-orbiting satellites.

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Section: Summary and Discussionmentioning

confidence: 99%

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

2020

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“…In 2013, the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) user facility established the Eastern North Atlantic (ENA) observatory aimed to provide long-term MBL clouds observations (Kollias et al, 2020;Lamer et al, 2019). The comprehensive, long-term dataset collected at the ENA site along with the advanced cloud retrieval algorithms being developed (Zhu et al, 2019(Zhu et al, , 2021 provide a unique opportunity for investigating the role of turbulence on precipitation for MBL clouds.…”

Section: Supporting Informationmentioning

confidence: 99%

“…The analysis is based on a combination of existing products and two new DSD parameters retrieved from the KAZR Doppler spectrum. Best estimates of turbulence eddy dissipation rate (EDR) (Borque et al, 2016), precipitation rate (Lamer et al, 2019), and cloud adiabaticity (Zhu et al, 2019) are calculated using well-established techniques. In addition, a novel algorithm is developed to retrieve two key microphysical variables related to the DSD properties: the DSD-contributed Doppler spectrum width ( 𝐴𝐴 𝐴𝐴DSD ) and the size of the maximum droplet observed in radar volume ( 𝐴𝐴 𝐴𝐴max ).…”

Section: Microphysical and Dynamical Productsmentioning

confidence: 99%

Observational Investigation of the Effect of Turbulence on Microphysics and Precipitation in Warm Marine Boundary Layer Clouds

Zhu

Yang

Kollias

et al. 2023

Geophysical Research Letters

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Marine boundary layer (MBL) clouds cover 30% of the Earth's surface and strongly influence the Earth's radiative budget by reflecting significant amount of solar radiation back to space (Wood, 2012). It is estimated that only 4% change of the low-level clouds amount can offset the warming effect caused by doubling CO 2 concentration (Randall et al., 1984). Thus, an accurate estimation of the MBL clouds feedbacks is essential for the future climate prediction (Bony & Dufresne, 2005;Cess et al., 1990;Stephens, 2005). However, MBL clouds are a delicate, complex system with dynamics and microphysics closely interacts with each other across a wide range of scales from millimeter to thousands of kilometers (Khain & Pinsky, 2018). Several processes that act at small-scales and affect MBL clouds are poorly observed and poorly parameterized in climate models, which leads to large uncertainties in the MBL clouds representation and feedbacks (Glassmeier & Feingold, 2017;Randall, 1989).Turbulence is ubiquitous in MBL clouds and can be generated by surface forcing, cloud top radiative cooling, and wind shear (Mellado, 2017). Turbulence at various scales closely interact with the cloud microphysics and plays an important role on rain formation, cloud dissipation, and Stratocumulus (Sc)-Cumulus (Cu) transition process (Bodenschatz et al., 2010;Grabowski & Wang, 2013). For example, turbulence at small scales is known to enhance the collision-coalescence (C-C) mechanism, broaden the drop size distribution (DSD) and trigger precipitation (Chen et al., 2018;Pinsky et al., 2008;Shaw, 2003). Specifically, it is estimated that in shallow cumulus clouds with eddy dissipation rate (EDR) on the order of 10 −2 m 2 s −3 , the presence of turbulence can enhance the collision efficiency and shorten the drizzle formation time by 40%

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“…In the subcloud layer, drizzle microphysical retrievals are estimated using the radar-lidar technique developed by O'Connor et al (2005). A detailed description of the drizzle retrievals used in this study can be found in Lamer and Kollias (2019). Finally, the V air in the subcloud layer is estimated from the difference between the observed Doppler velocity and the reflectivity-weighted drizzle sedimentation velocity.…”

Section: Instruments and Datamentioning

confidence: 99%

On the Estimation of In‐Cloud Vertical Air Motion Using Radar Doppler Spectra

Zhu

Kollias

Yang

et al. 2021

Geophysical Research Letters

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Characterization of Shallow Oceanic Precipitation using Profiling and Scanning Radar Observations at the Eastern North Atlantic ARM Observatory

Cited by 4 publications

References 50 publications

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

Observational Investigation of the Effect of Turbulence on Microphysics and Precipitation in Warm Marine Boundary Layer Clouds

On the Estimation of In‐Cloud Vertical Air Motion Using Radar Doppler Spectra

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