SHEBA model intercomparison of weakly-forced Arctic mixed-phase stratus Hugh Morrison National Center for Atmospheric Research Thanks to Paquita Zuidema.

Slides:



Advertisements
Similar presentations
Ewan OConnor, Robin Hogan, Anthony Illingworth Drizzle comparisons.
Advertisements

Robin Hogan Julien Delanoe University of Reading Remote sensing of ice clouds from space.
Studying the Arctic Stratiform Clouds Using Four Different Microphysics Schemes Ping Du, Prof. Eric Girard.
Impacts of Large-scale Controls and Internal Processes on Low Clouds
Stratus Cloud parameters retrieval from Doppler radar Virendra P. Ghate.
Allison Parker Remote Sensing of the Oceans and Atmosphere.
Lidar-Based Microphysical Retrievals During M-PACE Gijs de Boer Edwin Eloranta The University of Wisconsin - Madison ARM CPMWG Meeting, October 31, 2006.
Steven Siems 1 and Greg McFarquhar 2 1 Monash University, Melbourne, VIC, Australia 2 University of Illinois, Urbana, IL, USA Steven Siems 1 and Greg McFarquhar.
1 A First Look at Mid-Level Clouds Using CloudSat, CALIPSO, and MODIS Data Stanley Q. Kidder, J. Adam Kankiewicz, Thomas H. Vonder Haar Cooperative Institute.
By : Kerwyn Texeira. Outline Definitions Introduction Model Description Model Evaluation The effect of dust nuclei on cloud coverage Conclusion Questions.
Matthew Shupe Ola Persson Paul Johnston Cassie Wheeler Michael Tjernstrom Surface-Based Remote-Sensing of Clouds during ASCOS Univ of Colorado, NOAA and.
1. The problem of mixed-phase clouds All models except DWD underestimate mid-level cloud –Some have separate “radiatively inactive” snow (ECMWF, DWD) –Met.
Chapter 6: Global Fluxes and The Deep Circulation Heat Budget Conservation of Salt Oceanic Water Masses Oceanic Mixing Temperature - Salinity Diagrams.
Chapter 7 Water and Atmospheric Moisture
Aerosol effects on rain and hail formation and their representation using polarimetric radar signatures Eyal Ilotovich, Nir Benmoshe and Alexander Khain.
Matthew Shupe Von Walden David Turner U. Colorado/NOAA-ESRL U. Idaho NOAA - NSSL New Cloud Observations at Summit, Greenland: Expanding the IASOA Network.
The Arctic Climate Paquita Zuidema, RSMAS/MPO, MSC 118, Feb, 29, 2008.
Bastiaan van Diedenhoven (Columbia University, NASA GISS) Ann Fridlind, Andrew Ackerman & Brian Cairns (NASA GISS) An investigation of ice crystal sizes.
Acknowledgments This research was supported by the DOE Atmospheric Radiation Measurements Program (ARM) and by the PNNL Directed Research and Development.
Reading Quizzes Chapter 23. Reading quiz What is the term used to describe the heat energy that is absorbed or released by a substance during.
Horizontal Distribution of Ice and Water in Arctic Stratus Clouds During MPACE Michael Poellot, David Brown – University of North Dakota Greg McFarquhar,
Characterization of Arctic Mixed-Phase Cloudy Boundary Layers with the Adiabatic Assumption Paquita Zuidema*, Janet Intrieri, Sergey Matrosov, Matthew.
Radiative Properties of Eastern Pacific Stratocumulus Clouds Zack Pecenak Evan Greer Changfu Li.
Case Study Example 29 August 2008 From the Cloud Radar Perspective 1)Low-level mixed- phase stratocumulus (ice falling from liquid cloud layer) 2)Brief.
Stephan de Roode (KNMI) Entrainment in stratocumulus clouds.
Matthew Shupe, Ola Persson, Amy Solomon CIRES – Univ. of Colorado & NOAA/ESRL David Turner NOAA/NSSL Dynamical and Microphysical Characteristics and Interactions.
Hyperspectral Data Applications: Convection & Turbulence Overview: Application Research for MURI Atmospheric Boundary Layer Turbulence Convective Initiation.
Introduction to Cloud Dynamics We are now going to concentrate on clouds that form as a result of air flows that are tied to the clouds themselves, i.e.
Unit 4-2: Clouds. Fog – A cloud on the ground When the air at the surface becomes cooled below the dew point, water vapor condenses. When the air at the.
The ASTEX Lagrangian model intercomparison case Stephan de Roode and Johan van der Dussen TU Delft, Netherlands.
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
Aerosol-Cloud Interactions and Radiative Forcing: Modeling and Observations Graham Feingold 1, K. S. Schmidt 2, H. Jiang 3, P. Zuidema 4, H. Xue 5, P.
High-Resolution Simulation of Hurricane Bonnie (1998). Part II: Water Budget Braun, S. A., 2006: High-Resolution Simulation of Hurricane Bonnie (1998).
LIDAR OBSERVATIONS CONSTRAINT FOR CIRRUS MODELISATION IN Large Eddy Simulations O. Thouron, V. Giraud (LOA - Lille) H. Chepfer, V. Noël(LMD - Palaiseau)
RICO Modeling Studies Group interests RICO data in support of studies.
Matthew Shupe Ola Persson Paul Johnston Duane Hazen Clouds during ASCOS U. of Colorado and NOAA.
1 Atmospheric profiling to better understand fog and low level cloud life cycle ARM/EU workshop on algorithms, May 2013 J. Delanoe (LATMOS), JC.
New observations of clouds, atmosphere, and precipitation at Summit, Greenland Matthew Shupe, Von Walden, David Turner Ryan Neely, Ben Castellani, Chris.
WMO Cloud Modeling workshop, Warsaw, July 2012 WMO Cloud Modeling workshop, Warsaw, July 2012 Idealized Oklahoma squall Line 20 june 2007, reflectivity.
Boundary-layer turbulence, surface processes, and orographic precipitation growth in cold clouds or: The importance of the lower boundary Qun Miao Ningbo.
Distribution of Liquid Water in Orographic Mixed-Phase Clouds Diana Thatcher Mentor: Linnea Avallone LASP REU 2011.
A study of ice formation by primary nucleation and ice multiplication in shallow precipitating embedded convection T. Choularton 1, I. Crawford 1, C. Dearden.
Observed & Simulated Profiles of Cloud Occurrence by Atmospheric State A Comparison of Observed Profiles of Cloud Occurrence with Multiscale Modeling Framework.
Towards a Characterization of Arctic Mixed-Phase Clouds Matthew D. Shupe a, Pavlos Kollias b, Ed Luke b a Cooperative Institute for Research in Environmental.
High-Resolution Simulation of Hurricane Bonnie (1998). Part II: Water Budget SCOTT A. BRAUN J. Atmos. Sci., 63,
Retrieval of Cloud Phase and Ice Crystal Habit From Satellite Data Sally McFarlane, Roger Marchand*, and Thomas Ackerman Pacific Northwest National Laboratory.
APR CRM simulations of the development of convection – some sensitivities Jon Petch Richard Forbes Met Office Andy Brown ECMWF October 29 th 2003.
Radiative Influences on Glaciation Time-Scales in Mixed-Phase Clouds Zachary Lebo, Nathanial Johnson, and Jerry Harrington Penn State University Acknowledgements:
Multidisciplinary drifting Observatory for the Study of Arctic Climate
The Multidisciplinary drifting Observatory
Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment, Part II: Multi-layered cloud GCSS.
Earth Observing Satellites Update John Murray, NASA Langley Research Center NASA Aviation Weather Satellites Last Year NASA’s AURA satellite, the chemistry.
A new look at – Tropical Mid-Troposphere Clouds P. Zuidema, B. Mapes, J. Lin, C. Fairall P. Zuidema, B. Mapes, J. Lin, C. Fairall CIRES/CDC NOAA/ETL Boulder,
Horizontal Variability In Microphysical Properties of Mixed-Phase Arctic Clouds David Brown, Michael Poellot – University of North Dakota Clouds are strong.
Investigation of Microphysical Parameterizations of Snow and Ice in Arctic Clouds During M-PACE through Model- Observation Comparisons Amy Solomon 12 In.
Particle Size, Water Path, and Photon Tunneling in Water and Ice Clouds ARM STM Albuquerque Mar Sensitivity of the CAM to Small Ice Crystals.
An Evaluation of Cloud Microphysics and Radiation Calculations at the NSA Matthew D. Shupe a, David D. Turner b, Eli Mlawer c, Timothy Shippert d a CIRES.
FOG. Fog is a cloud (usually stratus) that is in contact with the ground. –Relatively stable air ie. Shallow lapse rate needed –Temperature to dew point.
Update on progress with the implementation of a new two-moment microphysics scheme: Model description and single-column tests Hugh Morrison, Andrew Gettelman,
Remote sensing and modeling of cloud contents and precipitation efficiency Chung-Hsiung Sui Institute of Hydrological Sciences National Central University.
The Lifecyle of a Springtime Arctic Mixed-Phase Cloudy Boundary Layer observed during SHEBA Paquita Zuidema University of Colorado/ NOAA Environmental.
Properties of Tropical Ice Clouds: Analyses Based on Terra/Aqua Measurements P. Yang, G. Hong, K. Meyer, G. North, A. Dessler Texas A&M University B.-C.
Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments Yali Luo State.
Simulation of the Arctic Mixed-Phase Clouds
Group interests RICO data required
+ = Climate Responses to Biomass Burning Aerosols over South Africa
Stephen Klein and Renata McCoy Lawrence Livermore National Laboratory
Schematic diagram showing the various radiative mechanisms associated with cloud effects that have been identified as significant in relation to aerosols.
Group interests RICO data in support of studies
Unit 5 Earth’s Energy Budget.
Presentation transcript:

SHEBA model intercomparison of weakly-forced Arctic mixed-phase stratus Hugh Morrison National Center for Atmospheric Research Thanks to Paquita Zuidema (Univ. Miami)

Overview Case study is derived from measurements during Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment ( over the central Arctic Ocean) Long-lived low-level mixed-phase stratus were observed during early May, focus is on May 7, 1998 Several key differences from MPACE cases: o Colder temperatures (~ -22 C vs. -15 C) o Much smaller surface turbulent heat fluxes (ice-covered vs. open ocean) o More polluted aerosol o Much smaller amounts of cloud liquid water

Goals Document ability of models to simulate thin mixed- phase clouds for conditions much different than MPACE Specifically, we want to focus on: o Longevity of mixed-phase clouds in simulations o Sensitivity to concentration of ice nuclei or ice crystals, and how this differs between LES, CRM, and SCM

LWP (black), IWP (red) Radar reflectivity

Radar reflectivity, aircraft track Sonde T LWP

Aircraft LWC

Aircraft particle concentrations

Large-scale horizontal and vertical advection from constrained ECMWF analyses (Morrison and Pinto 2004), modified above BL so that T and qv profiles are approximately constant in time. Initial profiles:

Intercomparison is being conducted jointly with 2008 WMO Cloud Modeling Workshop in Cozumel, Mexico, July 2008 Details of the model specification and protocol and model forcing dataset are given in the case study documentation, available at: (Scroll down to “Arctic mixed-phase stratiform clouds (case #2)”)

Example of results using ARCSCM

Timeline Discussion of results in breakout session at WMO Cloud Modeling Workshop in July 2008 Submission of results by fall 2008 (no deadline set yet) If interested, send an to