{"id":557,"date":"2021-03-09T15:58:17","date_gmt":"2021-03-09T15:58:17","guid":{"rendered":"https:\/\/www.iamas.org\/iccp\/?page_id=557"},"modified":"2021-03-10T13:08:08","modified_gmt":"2021-03-10T13:08:08","slug":"session-16-measurement-techniques-cloud-and-precipitation-properties-and-uncertainties","status":"publish","type":"page","link":"https:\/\/www.iamas.org\/iccp\/session-16-measurement-techniques-cloud-and-precipitation-properties-and-uncertainties\/","title":{"rendered":"Session 16 – Measurement techniques (cloud and precipitation properties) and uncertainties"},"content":{"rendered":"\n

Oral session:<\/p>\n\n\n\n

S16.1 Development of Stochastic Parameterizations of Cloud Microphysics for Models and Retrievals: Use of Uncertainty in In-Situ Observations
Greg McFarquhar*1,2, Wei Wu1, Joe Finlon1, Shichu Zhu1, Dan Stechman1, Robert Jackson1,3, Robert Rauber1, Brian Jewett1, Alfons Schwarzenboeck4, Alexei Korolev5, Delphine Leroy5, J Walter Strapp6, Michael Poellot7
1University of Illinois, USA, 2National Center for Atmospheric Research, USA, 3University of Wyoming, USA, 4Laboratoire de M\u00e9t\u00e9orologie Physique, CNRS\/Universit\u00e9 Blaise Pascal, France, 5Meteorological Service of Canada,<\/em> Canada, 6Met Analytics, Inc., Canada, 7University of North Dakota, USA<\/em> (video; position 0:00)<\/a><\/td><\/tr>
S16.2 Toward the future of cloud particle characterization with large sample volume ensemble particle probes
Matthew Hayman
NCAR, USA<\/em> (video; position 16:00)<\/a><\/td><\/tr>
S16.3 How biased is the sampling of clouds by aircraft? Paul Field1,2, Kalli Furtado*1
1Met Office, UK, 2University of Leeds, UK<\/em> (video; position 29:50)<\/a><\/td><\/tr>
S16.4 Quantification of Mixed Phase Cloud Properties with Single Particle Light Scattering Polarimetry
Darrel Baumgardner*1, Martina Kraemer2, Martin Gallagher3, James Dorsey3, Jonathan Croiser3
1Droplet Measurement Technologies, USA, 2Forschung Juelich, Germany,<\/em>
3University of Manchester, UK<\/em> (video; position 43:35)<\/a><\/td><\/tr>
S16.5 A Submicron Cloud Particle Imager (CPI) for Small UAV and Manned Aircraft Paul Lawson*, Akira Kyle, Colin Gurganus
SPEC Inc., USA<\/em> (video; position 0:00)<\/a><\/td><\/tr>
S16.6 Measurements of mixed-phase and ice cloud microphysical properties with spectrum-resolved water Raman lidar and their use in evaluating cloud radar\/lidar retrieval methods
Jens Reichardt*, Christine Knist
Deutscher Wetterdienst, Germany<\/em> (video; position 15:00)<\/a><\/td><\/tr>
S16.7 Improved synergy retrievals of precipitation rates and ice cloud properties using cloud radar with Doppler capability
Shannon Mason*1, Christine Chiu1, Robin Hogan2,1
1University of Reading, UK, 2ECMWF, UK<\/em> (video; position 27:00)<\/a><\/td><\/tr>
S16.8 Diagnosing Raindrop Breakup and Coalescence from Vertically Pointing Radar Observations
Christopher Williams
University of Colorado Boulder, USA<\/em> (video; position 42:00)<\/a><\/td><\/tr>
S16.9 Using a Ground Based Integrated Sensor System to Remotely Detect Supercooled Cloud Layers in Cold Climates
Faisal Boudala*1, George Isaac2, David Hudak1, Robert Crawford1, Martha Anderson3, Paul Yang4, Marie-France Turcotte5, Ismail Gultepe1, Di Wu1
1Cloud Physics and Severe Weather Research Section, Environment and Climate Change Canada, Canada, 2Weather Impacts Consulting Incorporated, Canada, 3Department of National Defence, Government of Canada, Canada, 4Meteorological Service of Canada, Environment and Climate Change Canada, Canada, 5Meteorological Service of Canada, Environment and Climate Change<\/em>
Canada, Canada<\/em> (video; position 0:00)<\/a><\/td><\/tr>
S16.10 Statistical Assessment of Rainfall Properties Over Varying Scales Joshua Teves*, Michael Larsen
College of Charleston, USA<\/em> (video; position 15:00)<\/a><\/td><\/tr>
S16.11 Examination of the catch efficiency of precipitation gauges based on the type of snow
Julie M. Th\u00e9riault*1, Roy Rasmussen2, Matteo Colli3, Luca G. Lanza3
1University of Quebec at Montreal, Canada, 2National Center for Atmospheric<\/em>
Research, USA, 3University of Genova, Italy<\/em> (video; position 30:00)<\/a><\/td><\/tr>
S16.12 Development of a New Theoretical Framework for the Analysis of Disdrometer Data
Michael Larsen*1, Robert Lemasters2, Katelyn O’Dell1, Joshua Teves1
1College of Charleston, USA, 2Emory University, USA<\/em> (video; position 0:00)<\/a><\/td><\/tr>
S16.13 Exploring the Microphysical Properties of Exoplanet Clouds (or Bringing Exoplanet Clouds Down to Earth)
Alexandria Johnson*1,2, Sara Lance1,3, Sara Seager1, David Charbonneau4, Amy Bauer5, Daniel Cziczo1
1Massachusetts Institute of Technology, USA, 2Brown University, USA, 3SUNY Albany, USA, 4Harvard-Smithsonian Center for Astrophysics, USA, 5TSI<\/em>
Incorporated, USA<\/em> (video; position 15:00)<\/a><\/td><\/tr>
S16.14 Quantitative evaluation of seven optical sensors for cloud microphysical measurements at the Puy-de-D\u00f4me Observatory, France
Guyot Gwennol\u00e9*1, Gourbeyre Christophe1, Febvre Guy1, Shcherbakov Valery1, Burnet Fred\u00e9ric2, Dupont Jean Charles3, Sellegri Karine1, Jourdan Olivier1 1LaMP, France, 2M\u00e9t\u00e9o-France\/CNRS, France, 3Institut Pierre-Simon Laplace,<\/em> France<\/em> (video; position 46:00)<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Poster session:<\/p>\n\n\n\n

P16.1 Improving the retrieval of particle size spectra and liquid water content from optical spectrometer measurements using a Monte Carlo inversion method
Guy Febvre, Delphine Leroy*, Valery Shcherbakov, Alfons Schwarzenboeck
LaMP -CNRS\/UBP-, France<\/em><\/td><\/tr>
P16.2 Mass retrieval for ice crystals from particle images and ice water content measurements: a numerical optimization approach
Pierre Coutris*1, Delphine Leroy1, Emmanuel Fontaine1, Alfons Schwarzenboeck1, J. Walter Strapp2
1Laboratoire de M\u00e9t\u00e9orologie Physique (LaMP), CNRS\/Universit\u00e9 Blaise Pascal, France, 2Met Analytics, Inc., Canada<\/em><\/td><\/tr>
P16.3 Characterization of response time behavior on the Fast-2D optical array probe detector board Matthew Hayman*, Katie McMenamin, Jorgen Jensen
NCAR, USA<\/em><\/td><\/tr>
P16.4 Study of droplet activation in thin liquid clouds using ground-based Raman lidar and ancillary remote sensors
Marco Rosoldi*, Fabio Madonna, Gelsomina Pappalardo
Consiglio Nazionale delle Ricerche Istituto di Metodologie per l’Analisi Ambientale, Italy<\/em><\/td><\/tr>
P16.5 Cloud cover estimation based on ceilometer measurements: a comparison with visual observations Montse Costa-Sur\u00f3s*2, Josep Calb\u00f31, Josep-Abel Gonz\u00e1lez1, Arturo Sanchez-Lorenzo3
1Universitat de Girona, Spain, 2University of Warsaw, Poland, 3Instituto Pirenaico de Ecolog\u00eda, Consejo Superior de Investigaciones Cient\u00edficas, Spain<\/em><\/td><\/tr>
P16.6 Finnish Meteorological Institute – Aerosol Cloud Interaction Tube (FMI – ACIT), parameters for proper operation and first results.
Konstantinos Doulgeris*, David Brus
Finnish Meteorological Institute, Finland<\/em><\/td><\/tr>
P16.7 Calculation of polarimetric radar fields using the output of a bin microphysics scheme No\u00e9mi Sarkadi*1, Istv\u00e1n Geresdi1, Mikl\u00f3s Szak\u00e1ll2
1University of P\u00e9cs, Hungary, 2Johannes Gutenberg University of Mainz, Germany<\/em><\/td><\/tr>
P16.8 A droplet generator system for calibrating and evaluating the performance of airborne cloud particle probes.
Robert Jackson*, Spencer Faber, William Kuestner, Jeffrey French
University of Wyoming, USA<\/em><\/td><\/tr>
P16.9 Interpretation of airborne CASPOL measurements using methods developed in the CLOUD chamber
Leonid Nichman*1, Emma J\u00e4rvinen2, James Dorsey1,3, Sebastian O’Shea1, Paul Connolly1, Jonathan Crosier1,3, Martin Gallagher1
1University of Manchester, UK, 2Karlsruhe Institute of Technology, Germany, 3National Centre for Atmospheric Science, UK<\/em><\/td><\/tr>
P16.10 The complexity of variational retrieval of liquid cloud properties
Kerstin Ebell*, Ulrich Loehnert, Emiliano Orlandi, Susanne Crewell University of Cologne, Institute for Geophysics and Meteorology, Germany<\/em><\/td><\/tr>
P16.11 Investigating a New Disdrometer Sampling Method to Reduce Measurement Variability Katelyn O’Dell*, Michael Larsen
College of Charleston, USA<\/em><\/td><\/tr>
P16.12 An observation system for detection of local severe snowstorm causing snow-related disaster Katsuya Yamashita*, Sento Nakai, Hiroki Motoyoshi
National Research Institute for Earth Science and Disaster Prevention, Japan<\/em><\/td><\/tr>
P16.13 Quantitative Estimation of Contribution of Raindrop flux to total precipitation intensity in Mixed Phase Precipitation from Optical Disdrometer Data
Hiroki Motoyoshi*1, Ryohei Misumi2, Masaaki Ishizaka1, Sento Nakai1, Katsuya Yamashita1
1Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Prevention, Japan, 2Storm, Flood and Landslide Research Unit, National Research Institute for Earth Science and Disaster Prevension, Japan<\/em><\/td><\/tr>
P16.14 Fast open path IR hygrometer for airborne application \u2013 feasibility study
Jakub Nowak*1, Pawe\u0142 Magryta2, Micha\u0142 Kustosz2, Tadeusz Stacewicz2, Wojciech Kumala1, Szymon Malinowski1
1University of Warsaw, Faculty of Physics, Institute of Geophysics, Poland, 2University of Warsaw, Faculty of Physics, Institute of Experimental Physics, Poland<\/em><\/td><\/tr>
P16.15 Rainfall characteristics in central London: a cross sensor, high temporal resolution analysis Andrew Gabey*, Sue Grimmond, Simone Kotthaus, William Morrison
University of Reading, UK<\/em><\/td><\/tr>
P16.16 Compararison Study between Ultrasonic and Laser Snow Depth Meter over Daegwallyeong Site during 2011-2014
JiWon Choi*, Ki-Ho Chang, Ha-Young Yang, Jin-Yim Jeong, Dong-Oh Park, Baek-Jo Kim National Institute of Meteorological Sciences, Republic of Korea<\/em><\/td><\/tr>
P16.17 Documenting variability of ice mass-dimensional properties during winter storms in Finland
Annakaisa von Lerber*1,2, Dmitri Moisseev3,1, Walter Petersen4, Ari-Matti Harri1
1Finnish Meteorological Institute, Finland, 2Aalto University, Finland, 3University of Helsinki, Finland, 4NASA Marshall Space Flight Center, USA<\/em><\/td><\/tr>
P16.18 Discriminating between liquid and ice particles measured in mixed phase cloud during the INUPIAQ campaign
Robert Farrington*1, Paul Connolly1, Thomas Choularton1, Keith Bower1, Gary Lloyd1, Michael Flynn1, Christopher Hoyle2, Paul Field3,4, Erik Herrmann2
1University of Manchester, UK, 2Paul Scherrer Institute, Switzerland, 3University of Leeds, UK, 4Met Office, UK<\/em><\/td><\/tr>
P16.19 Providing the better methods to estimate snowfall rate by using laser disdrometers Hiroyuki Konishi*1, Naohiko Hirasawa2
1Osaka Kyoiku Univ., Japan, 2National Institute of Polar Research, Japan<\/em><\/td><\/tr>
P16.20 Variability of Local Droplet Size Distributions in Marine and Arctic Stratocumulus Clouds Observed with Airborne Digital Holography
S. Glienke*1,2, O. Schlenczek1,3, J. Fugal1,3, R. Shaw2, S. Borrmann1,3
1Johannes Gutenberg University Mainz, Germany, 2Michigan Technological University, USA, 3Max Planck Institute for Chemistry, Germany<\/em><\/td><\/tr>
P16.21 Improvements in Optical Array Probe Characterization: Laboratory and Simulation Results Colin Gurganus*, Paul Lawson
SPEC, USA<\/em><\/td><\/tr>
P16.22 Uncertainties in historical precipitation and wind time series over Russia and their influence on reanalysis data
Pavel Shabanov
P.P. Shirshov Institute of Oceanology of the Russian Academy of Sciences (IO RAS), Russia<\/em><\/td><\/tr>
P16.23 Improved Algorithms for Radar Remote Sensing of Snowfall Rate Using Dual Polarization C Band Radar Faisal Boudala*1, David Hudak1, Sudesh Boodoo1, Norman Donaldson1, Rodica Nitu2, Kai Wong2
1Cloud Physics and Severe Weather Research Section, Environment and Climate Change Canada, Canada, 22Meteorological Service of Canada, Environment Canada, Environment and Climate Change Canada, Canada<\/em><\/td><\/tr>
P16.24 ADVANCED OPTICAL PACKAGE FOR ESTIMATING OF CLOUD COVER AND STRUCTURE Mikhail Krinitskiy
P.P.Shirshov Institute of Oceanology of the Russian Academy of Sciences, Russia<\/em><\/td><\/tr>
P16.25 Vertical profile of fog microphysics measurements : a case study.
Fr\u00e9d\u00e9ric BURNET*, Pierre-Etienne BRILOUET, Marie MAZOYER, Thierry BOURRIANNE, Jean-Michel ETCHEBERRY, Dominique LEGAIN
Meteo-France\/CNRS, CNRM\/GAME, France<\/em><\/td><\/tr>
P16.26 Comparative analysis of lab-grown ice crystals by Cryo-Scanning Electron Microscopy Lucas Bancroft*, Katie Boaggio, Kevin Hurler, Manisha Bandamede, Nathan Magee The College of New Jersey, USA<\/em><\/td><\/tr>
P16.27 Potential of Higher Moments of the Radar Doppler Spectrum for Studying Ice Clouds Maximilian Maahn*1, Ulrich L\u00f6hnert2
1University of Colorado, USA, 2University of Cologne, Germany<\/em><\/td><\/tr>
P16.28 Quantifying uncertainty in forward scattering probes due to non-sphericity of atmospheric ice crystals Junshik Um*, Greg M McFarquhar
University of Illinois at Urbana-Champaign, USA<\/em><\/td><\/tr>
P16.29 Recalibration of CAS probe during time periods with large droplet concentrations: Results from RACORO Siddhant Gupta*1, Greg M McFarquhar1, Haf Jonsson2
1University of Illinois at Urbana-Champaign, USA, 2Center for Interdisciplinary Remotely Piloted Aircraft Studies, Canada<\/em><\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

Oral session: S16.1 Development of Stochastic Parameterizations of Cloud Microphysics for Models and Retrievals: Use of Uncertainty in In-Situ ObservationsGreg McFarquhar*1,2, Wei Wu1, Joe Finlon1, Shichu Zhu1, Dan Stechman1, Robert Jackson1,3, Robert Rauber1, Brian Jewett1, Alfons Schwarzenboeck4, Alexei Korolev5, Delphine Leroy5, J Walter Strapp6, Michael Poellot71University of Illinois, USA, 2National Center for Atmospheric Research, USA, […]<\/p>\n","protected":false},"author":9,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"ngg_post_thumbnail":0,"cybocfi_hide_featured_image":"","footnotes":""},"class_list":["post-557","page","type-page","status-publish","hentry"],"post_mailing_queue_ids":[],"_links":{"self":[{"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/pages\/557","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/comments?post=557"}],"version-history":[{"count":3,"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/pages\/557\/revisions"}],"predecessor-version":[{"id":576,"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/pages\/557\/revisions\/576"}],"wp:attachment":[{"href":"https:\/\/www.iamas.org\/iccp\/wp-json\/wp\/v2\/media?parent=557"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}