Mixed‐phase cloud phase partitioning using millimeter wavelength cloud radar Doppler velocity spectra

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Journal of Geophysical Research: Atmospheres

• Publication date

  2014-06-27

• Fields of study

  Geology, Physics, Environmental Science

• Identifiers
  DOI 10.1002/2013JD021182
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• The Indirect and Semi-Direct Aerosol Campaign

  2014cited by this paper
• Use of radar Doppler spectra in Arctic mixed-phase cloud studies

  2013cited by this paper
• Separating Cloud and Drizzle Radar Moments during Precipitation Onset Using Doppler Spectra

  2013cited by this paper
• Clouds at Arctic Atmospheric Observatories. Part II: Thermodynamic Phase Characteristics

  2011cited by this paper
• Toward ice formation closure in Arctic mixed‐phase boundary layer clouds during ISDAC

  2011cited by this paper
• Ice aspect ratio influences on mixed-phase clouds: Impacts on phase partitioning in parcel models

  2011cited by this paper
• Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing applications

  2011cited by this paper
• Indirect and semi-direct aerosol campaign: The impact of Arctic aerosols on clouds

  2011cited by this paper
• Millimeter wave scattering from ice crystals and their aggregates: Comparing cloud model simulations with X- and Ka-band radar measurements

  2011cited by this paper
• Merged Sounding Value-Added Product

  2010influential reference
• Using Doppler Spectra to Separate Hydrometeor Populations and Analyze Ice Precipitation in Multilayered Mixed-Phase Clouds

  2010cited by this paper
• Detection of supercooled liquid in mixed‐phase clouds using radar Doppler spectra

  2010cited by this paper
• Cloud influence on and response to seasonal Arctic sea ice loss

  2009cited by this paper
• On Deriving Vertical Air Motions from Cloud Radar Doppler Spectra

  2008cited by this paper
• A Focus on Mixed-Phase Clouds: The Status of Ground-Based Observational Methods

  2008cited by this paper
• Vertical Motions in Arctic Mixed-Phase Stratiform Clouds

  2008cited by this paper
• A new algorithm for the extraction of cloud parameters using multipeak analysis of cloud radar data First application and preliminary results

  2008cited by this paper
• The contribution of cloud and radiation anomalies to the 2007 Arctic sea ice extent minimum

  2008cited by this paper
• A FOCUS ON MIXED-PHASE CLOUDS

  2008cited by this paper
• The Atmospheric Radiation Measurement Program Cloud Profiling Radars: Second-Generation Sampling Strategies, Processing, and Cloud Data Products

  2007cited by this paper
• Retrieving Liquid Wat0er Path and Precipitable Water Vapor From the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

  2007cited by this paper
• Ice properties of single-layer stratocumulus during the Mixed-Phase Arctic Cloud Experiment: 2. Model results

  2007cited by this paper
• Limitations of the Wegener–Bergeron–Findeisen Mechanism in the Evolution of Mixed-Phase Clouds

  2007cited by this paper
• Arctic Mixed-Phase Cloud Properties Derived from Surface-Based Sensors at SHEBA

  2006cited by this paper
• Intercomparison of bulk cloud microphysics schemes in mesoscale simulations of springtime Arctic mixed-phase stratiform clouds

  2006cited by this paper
• Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA

  2005cited by this paper
• An Arctic Springtime Mixed-Phase Cloudy Boundary Layer Observed during SHEBA.

  2005cited by this paper
• Cloud Radiative Forcing of the Arctic Surface: The Influence of Cloud Properties, Surface Albedo, and Solar Zenith Angle

  2004cited by this paper
• Evaluation of Radar Reflectivity-Based Estimates of Water Content in Stratiform Marine Clouds

  2004cited by this paper
• The Illustrated Wavelet Transform Handbook Introductory Theory And Applications In Science

  2002cited by this paper
• Retrieval of Cloud Microphysical Parameters from 94-GHz Radar Doppler Power Spectra

  1999cited by this paper
• A Fuzzy Logic Method for Improved Moment Estimation from Doppler Spectra

  1998cited by this paper
• On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles

  1998influential reference
• Arctic Cloud–Radiation–Temperature Associations in Observational Data and Atmospheric Reanalyses

  1998cited by this paper
• The Potential of 8-mm Radars for Remotely Sensing Cloud Drop Size Distributions

  1997cited by this paper
• The Retrieval of Stratocumulus Cloud Properties by Ground-Based Cloud Radar

  1997cited by this paper
• Measurement of Stratus Cloud and Drizzle Parameters in ASTEX with a K

  1995influential reference
• A model for particle microphysics, turbulent mixing, and radiative transfer in the stratocumulus-topped marine boundary layer and comparisons with measurements

  1995cited by this paper
• Measurement of Cloud Droplet Size Spectra by Doppler Radar

  1994cited by this paper
• Studies of the radiative properties of ice and mixed-phase clouds

  1994cited by this paper
• Annual Cycle of Radiation Fluxes over the Arctic Ocean: Sensitivity to Cloud Optical Properties

  1992cited by this paper
• Wavelets and signal processing

  1991cited by this paper
• Radar Reflectivity of Cumulus Clouds

  1987cited by this paper
• Doppler radar characteristics of precipitation at vertical incidence

  1973cited by this paper
• Some Observations of Vertical Velocities and Precipitation Sizes in a Thunderstorm

  1964cited by this paper
• THE ESTIMATION OF CLOUD PARAMETERS BY RADAR

  1954cited by this paper

• Research on the inversion method of vertical airflow motion in complex phase layered clouds

  2026cites this paper
• Classifying thermodynamic cloud phase using machine learning models

  2025cites this paper
• 基于模糊逻辑识别云粒子相态的优化算法

  2024cites this paper
• The characteristics of cloud macro-parameters caused by the seeder–feeder process inside clouds measured by millimeter-wave cloud radar in Xi'an, China

  2024cites this paper
• Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks

  2022cites this paper
• Cloud Seeding Evidenced by Coherent Doppler Wind Lidar

  2021cites this paper
• The ARM Radar Network: At the Leading Edge of Cloud and Precipitation Observations

  2020cites this paper
• Can Embedded Liquid Cloud Layer Volumes Be Classified in Polar Clouds Using a Single- Frequency Zenith-Pointing Radar?

  2020cites this paper
• Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors

  2020cites this paper
• peakTree: a framework for structure-preserving radar Doppler spectra analysis

  2019cites this paper
• A molecular understanding of the interaction of typical aromatic acids with common aerosol nucleation precursors and their atmospheric implications

  2019cites this paper
• Toward Exploring the Synergy Between Cloud Radar Polarimetry and Doppler Spectral Analysis in Deep Cold Precipitating Systems in the Arctic

  2018cites this paper
• Mixed-Phase Clouds: Progress and Challenges

  2017cites this paper
• Vertical structure of boundary layer convection during cold‐air outbreaks at Barrow, Alaska

  2016cites this paper
• Understanding Rapid Changes in Phase Partitioning between Cloud Liquid and Ice in Stratiform Mixed-Phase Clouds: An Arctic Case Study

  2016cites this paper
• A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

  2016cites this paper
• Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling

  2015cites this paper
• The characteristics of cloud macro parameters caused by seeder-feeder 1 inside clouds measured by millimeter-wave cloud radar in Xi'an 2

  year unknowncites this paper
• Classifying Thermodynamic Cloud Phase Using Machine Learning

  year unknowncites this paper