Research Objective 4: Develop improved parameterizations of boundary-layer clouds and turbulence for use in MMFs and GCRMs
|
|
|
- Alyson McCoy
- 8 years ago
- Views:
Transcription
1 Research Objective 4: Develop improved parameterizations of boundary-layer clouds and turbulence for use in MMFs and GCRMs Steve Krueger and Chin-Hoh Moeng CMMAP Site Review 31 May 2007
2 Scales of Atmospheric Motion 10,000 km Planetary waves 1000 km 100 km 10 km 1 km 100 m Cumulonimbus Extratropical Mesoscale Cumulus Turbulence => clouds clouds Cyclones Convective Systems Global Climate Model (GCM) Cloud System Resolving Model (CSRM) Multiscale Modeling Framework Large Eddy Simulation (LES) Model 10 m
3 Boundary layer cloud systems Marine stratocumulus Trade cumulus Shallow convection over land (with diurnal cycle) Transition from shallow to deep convection Deep precipitating convective Cold-air outbreaks over mid-latitude oceans Convective plumes from leads during winter Boundary layers over inhomogenous surfaces or terrain
4 Boundary layer clouds in cloud system resolving models (CSRMs) CSRMs used in MMFs have horizontal grid sizes of 4 km or more. Such CSRMs are expected to represent all types of cloud systems. However, many boundary layer clouds are not resolved by such CSRMs. Our objective is to improve the representation of boundary layer clouds and turbulence in CSRMs used in MMFs.
5 Shallow cumulus clouds and mesoscale organization Typical CSRMs grid sizes are too large to resolve shallow cumulus. A CSRM with a suitable SGS parameterization should be able to represent SGS shallow cumulus and resolve their mesoscale organization. Evaluate parameterization with LES and observations.
6 Meeting the Objectives Develop and test improved representations of SGS convection and turbulence in CSRMs. Parameterizations under consideration PDF/HOC (probability density function/high-order closure): Predicts statistics of turbulence to infer SGS cloud properties Two-scale MMF: 2D LES model predicts a sample of cloud properties. Additional physics to be included Effects of surface inhomogeniety (elevation, land surface properties) Evaluation methods Use 3D LES benchmark simulations Compare to observational datasets
7 Cloud fraction evolution for BOMEX shallow cumulus CSU System for Atmospheric Modeling (SAM) CRM with LOC and IP-HOC, and LES version LOC LES IP-HOC (%)
8 Figure R5: Low-cloud fraction results obtained in tests of a mini-les parameterization of turbule coupled with the MMF. The top panel shows results from a control run with the standard MMF, the Low-cloud fraction results obtained in tests of a mini-les parameterization of turbulence, coupled with the MMF. The top panel shows results from a control run with the standard MMF, the middle panel shows results from the mini-les version of the MMF, and the bottom panel shows observations from ISCCP. SP-CAM SP-MLES-CAM
9 Evaluation Methods Benchmark simulations Large-domain LES (e.g., 100 km x 100 km domain, 100-m grid size) Compare to CSRM results using various SGS parameterizations. Analyze results to gain insight into scale interactions, etc.
10 llarge domain LES of trade wind cumulus 40 km x 40 km domain, 100-m grid size
11 Evaluation Methods Observational datasets High-resolution cloud properties from satellite measurements Vertical structure of clouds from ground and satellitebased cloud radars Aircraft-based measurements during field experiments
12 Shallow cumulus clouds and mesoscale organization Typical CSRMs grid sizes are too large to resolve shallow cumulus. A CSRM with a suitable SGS parameterization should be able to represent SGS shallow cumulus and resolve its mesoscale organization. LES is used to provide benchmark simulations.
13 High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land (Khairoutdinov and Randall 2006) Figure 8. PDF of cloud size as a function of height shown for three different simulation times. Mean and standard deviations are shown by the white and yellow lines, respectively. 150 km x 150 km, 100 m grid size, 6 h
14 Time-height cross section of cloud fraction simulated by SAM CRM with the Cheng-Xu PDF/HOC for BOMEX. The horizontal grid sizes range from 4 km (a) to 250 m (e). Results from the SAM LES are also shown in (f).
An economical scale-aware parameterization for representing subgrid-scale clouds and turbulence in cloud-resolving models and global models
An economical scale-aware parameterization for representing subgrid-scale clouds and turbulence in cloud-resolving models and global models Steven Krueger1 and Peter Bogenschutz2 1University of Utah, 2National
What the Heck are Low-Cloud Feedbacks? Takanobu Yamaguchi Rachel R. McCrary Anna B. Harper
What the Heck are Low-Cloud Feedbacks? Takanobu Yamaguchi Rachel R. McCrary Anna B. Harper IPCC Cloud feedbacks remain the largest source of uncertainty. Roadmap 1. Low cloud primer 2. Radiation and low
Improving Representation of Turbulence and Clouds In Coarse-Grid CRMs
Improving Representation of Turbulence and Clouds In CoarseGrid CRMs Peter A. Bogenschutz and Steven K. Krueger University of Utah, Salt Lake City, UT Motivation Embedded CRMs in MMF typically have horizontal
Large Eddy Simulation (LES) & Cloud Resolving Model (CRM) Françoise Guichard and Fleur Couvreux
Large Eddy Simulation (LES) & Cloud Resolving Model (CRM) Françoise Guichard and Fleur Couvreux Cloud-resolving modelling : perspectives Improvement of models, new ways of using them, renewed views And
Improving Low-Cloud Simulation with an Upgraded Multiscale Modeling Framework
Improving Low-Cloud Simulation with an Upgraded Multiscale Modeling Framework Kuan-Man Xu and Anning Cheng NASA Langley Research Center Hampton, Virginia Motivation and outline of this talk From Teixeira
Parameterization of Cumulus Convective Cloud Systems in Mesoscale Forecast Models
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Parameterization of Cumulus Convective Cloud Systems in Mesoscale Forecast Models Yefim L. Kogan Cooperative Institute
1D shallow convective case studies and comparisons with LES
1D shallow convective case studies and comparisons with CNRM/GMME/Méso-NH 24 novembre 2005 1 / 17 Contents 1 5h-6h time average vertical profils 2 2 / 17 Case description 5h-6h time average vertical profils
Evalua&ng Downdra/ Parameteriza&ons with High Resolu&on CRM Data
Evalua&ng Downdra/ Parameteriza&ons with High Resolu&on CRM Data Kate Thayer-Calder and Dave Randall Colorado State University October 24, 2012 NOAA's 37th Climate Diagnostics and Prediction Workshop Convective
How To Model An Ac Cloud
Development of an Elevated Mixed Layer Model for Parameterizing Altocumulus Cloud Layers S. Liu and S. K. Krueger Department of Meteorology University of Utah, Salt Lake City, Utah Introduction Altocumulus
Evaluation of precipitation simulated over mid-latitude land by CPTEC AGCM single-column model
Evaluation of precipitation simulated over mid-latitude land by CPTEC AGCM single-column model Enver Ramírez Gutiérrez 1, Silvio Nilo Figueroa 2, Paulo Kubota 2 1 CCST, 2 CPTEC INPE Cachoeira Paulista,
Long-term Observations of the Convective Boundary Layer (CBL) and Shallow cumulus Clouds using Cloud Radar at the SGP ARM Climate Research Facility
Long-term Observations of the Convective Boundary Layer (CBL) and Shallow cumulus Clouds using Cloud Radar at the SGP ARM Climate Research Facility Arunchandra S. Chandra Pavlos Kollias Department of Atmospheric
A Review on the Uses of Cloud-(System-)Resolving Models
A Review on the Uses of Cloud-(System-)Resolving Models Jeffrey D. Duda Since their advent into the meteorological modeling world, cloud-(system)-resolving models (CRMs or CSRMs) have become very important
Convective Vertical Velocities in GFDL AM3, Cloud Resolving Models, and Radar Retrievals
Convective Vertical Velocities in GFDL AM3, Cloud Resolving Models, and Radar Retrievals Leo Donner and Will Cooke GFDL/NOAA, Princeton University DOE ASR Meeting, Potomac, MD, 10-13 March 2013 Motivation
Using Cloud-Resolving Model Simulations of Deep Convection to Inform Cloud Parameterizations in Large-Scale Models
Using Cloud-Resolving Model Simulations of Deep Convection to Inform Cloud Parameterizations in Large-Scale Models S. A. Klein National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics
Clouds and Convection
Max-Planck-Institut Clouds and Convection Cathy Hohenegger, Axel Seifert, Bjorn Stevens, Verena Grützun, Thijs Heus, Linda Schlemmer, Malte Rieck Max-Planck-Institut Shallow convection Deep convection
Unified Cloud and Mixing Parameterizations of the Marine Boundary Layer: EDMF and PDF-based cloud approaches
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Unified Cloud and Mixing Parameterizations of the Marine Boundary Layer: EDMF and PDF-based cloud approaches Joao Teixeira
GCMs with Implicit and Explicit cloudrain processes for simulation of extreme precipitation frequency
GCMs with Implicit and Explicit cloudrain processes for simulation of extreme precipitation frequency In Sik Kang Seoul National University Young Min Yang (UH) and Wei Kuo Tao (GSFC) Content 1. Conventional
STRATEGY & Parametrized Convection
for WP4.1.3 // meeting, 22 Sept 2005 morning, Francoise Guichard some inferences from the EUROCS project EUROCS: european project on cloud systems in NWP/climate models European Component of GCSS (GEWEX
Impact of microphysics on cloud-system resolving model simulations of deep convection and SpCAM
Impact of microphysics on cloud-system resolving model simulations of deep convection and SpCAM Hugh Morrison and Wojciech Grabowski NCAR* (MMM Division, NESL) Marat Khairoutdinov Stony Brook University
Potential Climate Impact of Large-Scale Deployment of Renewable Energy Technologies. Chien Wang (MIT)
Potential Climate Impact of Large-Scale Deployment of Renewable Energy Technologies Chien Wang (MIT) 1. A large-scale installation of windmills Desired Energy Output: supply 10% of the estimated world
Continental and Marine Low-level Cloud Processes and Properties (ARM SGP and AZORES) Xiquan Dong University of North Dakota
Continental and Marine Low-level Cloud Processes and Properties (ARM SGP and AZORES) Xiquan Dong University of North Dakota Outline 1) Statistical results from SGP and AZORES 2) Challenge and Difficult
Boundary-Layer Cloud Feedbacks on Climate An MMF Perspective
Boundary-Layer Cloud Feedbacks on Climate An MMF Perspective Matthew E. Wyant Peter N. Blossey Christopher S. Bretherton University of Washington Marat Khairoutdinov Minghua Zhang Stony Brook University
CFMIP-2 : Cloud Feedback Model Intercomparison Project Phase 2
CFMIP-2 : Cloud Feedback Model Intercomparison Project Phase 2 Sandrine Bony on behalf of the CFMIP coordination committee From Victoria to Hamburg WGCM meetings : 2006 WGCM meeting: necessity to develop
Chapter 7 Stability and Cloud Development. Atmospheric Stability
Chapter 7 Stability and Cloud Development Atmospheric Stability 1 Cloud Development - stable environment Stable air (parcel) - vertical motion is inhibited if clouds form, they will be shallow, layered
Improving Mesoscale Prediction of Cloud Regime Transitions in LES and NRL COAMPS
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Improving Mesoscale Prediction of Cloud Regime Transitions in LES and NRL COAMPS David B. Mechem Atmospheric Science Program,
Comparison of the Vertical Velocity used to Calculate the Cloud Droplet Number Concentration in a Cloud-Resolving and a Global Climate Model
Comparison of the Vertical Velocity used to Calculate the Cloud Droplet Number Concentration in a Cloud-Resolving and a Global Climate Model H. Guo, J. E. Penner, M. Herzog, and X. Liu Department of Atmospheric,
Simulation of low clouds from the CAM and the regional WRF with multiple nested resolutions
Click Here for Full Article GEOPHYSICAL RESEARCH LETTERS, VOL. 36, L08813, doi:10.1029/2008gl037088, 2009 Simulation of low clouds from the CAM and the regional WRF with multiple nested resolutions Wuyin
The formation of wider and deeper clouds through cold-pool dynamics
The formation of wider and deeper clouds through cold-pool dynamics Linda Schlemmer, Cathy Hohenegger e for Meteorology, Hamburg 2013-09-03 Bergen COST Meeting Linda Schlemmer 1 / 27 1 Motivation 2 Simulations
Sensitivity studies of developing convection in a cloud-resolving model
Q. J. R. Meteorol. Soc. (26), 32, pp. 345 358 doi:.256/qj.5.7 Sensitivity studies of developing convection in a cloud-resolving model By J. C. PETCH Atmospheric Processes and Parametrizations, Met Office,
Cloud-Resolving Simulations of Convection during DYNAMO
Cloud-Resolving Simulations of Convection during DYNAMO Matthew A. Janiga and Chidong Zhang University of Miami, RSMAS 2013 Fall ASR Workshop Outline Overview of observations. Methodology. Simulation results.
The effects of organization on convective and large-scale interactions using cloud resolving simulations with parameterized large-scale dynamics
The effects of organization on convective and large-scale interactions using cloud resolving simulations with parameterized large-scale dynamics Emily M. Riley, Brian Mapes, Stefan Tulich, Zhiming Kuang
Since launch in April of 2006, CloudSat has provided
A Multipurpose Radar Simulation Package: QuickBeam BY J. M. HAYNES, R. T. MARCHAND, Z. LUO, A. BODAS-SALCEDO, AND G. L. STEPHENS Since launch in April of 2006, CloudSat has provided the first near-global
Can latent heat release have a negative effect on polar low intensity?
Can latent heat release have a negative effect on polar low intensity? Ivan Føre, Jon Egill Kristjansson, Erik W. Kolstad, Thomas J. Bracegirdle and Øyvind Sætra Polar lows: are intense mesoscale cyclones
Various Implementations of a Statistical Cloud Scheme in COSMO model
2 Working Group on Physical Aspects 61 Various Implementations of a Statistical Cloud Scheme in COSMO model Euripides Avgoustoglou Hellenic National Meteorological Service, El. Venizelou 14, Hellinikon,
Simulations of Clouds and Sensitivity Study by Wearther Research and Forecast Model for Atmospheric Radiation Measurement Case 4
Simulations of Clouds and Sensitivity Study by Wearther Research and Forecast Model for Atmospheric Radiation Measurement Case 4 Jingbo Wu and Minghua Zhang Institute for Terrestrial and Planetary Atmospheres
Turbulence-microphysics interactions in boundary layer clouds
Turbulence-microphysics interactions in boundary layer clouds Wojciech W. Grabowski 1 with contributions from D. Jarecka 2, H. Morrison 1, H. Pawlowska 2, J.Slawinska 3, L.-P. Wang 4 A. A. Wyszogrodzki
CHARACTERISTICS OF CLOUDS AND THE NEAR CLOUD ENVIRONMENT IN A SIMULATION OF TROPICAL CONVECTION
CHARACTERISTICS OF CLOUDS AND THE NEAR CLOUD ENVIRONMENT IN A SIMULATION OF TROPICAL CONVECTION by Ian Bruce Glenn A thesis submitted to the faculty of The University of Utah in partial fulfillment of
Titelmasterformat durch Klicken. bearbeiten
Evaluation of a Fully Coupled Atmospheric Hydrological Modeling System for the Sissili Watershed in the West African Sudanian Savannah Titelmasterformat durch Klicken June, 11, 2014 1 st European Fully
A comparison of simulated cloud radar output from the multiscale modeling framework global climate model with CloudSat cloud radar observations
Click Here for Full Article JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 114,, doi:10.1029/2008jd009790, 2009 A comparison of simulated cloud radar output from the multiscale modeling framework global climate
Atmospheric Processes
Atmospheric Processes Steven Sherwood Climate Change Research Centre, UNSW Yann Arthus-Bertrand / Altitude Where do atmospheric processes come into AR5 WGI? 1. The main feedbacks that control equilibrium
Description of zero-buoyancy entraining plume model
Influence of entrainment on the thermal stratification in simulations of radiative-convective equilibrium Supplementary information Martin S. Singh & Paul A. O Gorman S1 CRM simulations Here we give more
Evaluation of clouds in GCMs using ARM-data: A time-step approach
Evaluation of clouds in GCMs using ARM-data: A time-step approach K. Van Weverberg 1, C. Morcrette 1, H.-Y. Ma 2, S. Klein 2, M. Ahlgrimm 3, R. Forbes 3 and J. Petch 1 MACCBET Symposium, Royal Meteorological
Limitations of Equilibrium Or: What if τ LS τ adj?
Limitations of Equilibrium Or: What if τ LS τ adj? Bob Plant, Laura Davies Department of Meteorology, University of Reading, UK With thanks to: Steve Derbyshire, Alan Grant, Steve Woolnough and Jeff Chagnon
Cumulus Convection, Climate Sensitivity, and Heightened Imperatives for Physically Robust Cumulus Parameterizations in Climate Models
Cumulus Convection, Climate Sensitivity, and Heightened Imperatives for Physically Robust Cumulus Parameterizations in Climate Models Leo Donner GFDL/NOAA, Princeton University NCAR, 11 February 2014 Key
An A-Train Water Vapor Thematic Climate Data Record Using Cloud Classification
An A-Train Water Vapor Thematic Climate Data Record Using Cloud Classification Eric J. Fetzer, Qing Yue, Alexandre Guillaume, Van T. Dang, Calvin Liang, Brian H. Kahn, Brian D. Wilson, Bjorn H. Lambrigtsen
Month-Long 2D Cloud-Resolving Model Simulation and Resultant Statistics of Cloud Systems Over the ARM SGP
Month-Long 2D Cloud-Resolving Model Simulation and Resultant Statistics of Cloud Systems Over the ARM SGP X. Wu Department of Geological and Atmospheric Sciences Iowa State University Ames, Iowa X.-Z.
MOGREPS status and activities
MOGREPS status and activities by Warren Tennant with contributions from Rob Neal, Sarah Beare, Neill Bowler & Richard Swinbank Crown copyright Met Office 32 nd EWGLAM and 17 th SRNWP meetings 1 Contents
Trimodal cloudiness and tropical stable layers in simulations of radiative convective equilibrium
GEOPHYSICAL RESEARCH LETTERS, VOL. 35, L08802, doi:10.1029/2007gl033029, 2008 Trimodal cloudiness and tropical stable layers in simulations of radiative convective equilibrium D. J. Posselt, 1 S. C. van
The ARM-GCSS Intercomparison Study of Single-Column Models and Cloud System Models
The ARM-GCSS Intercomparison Study of Single-Column Models and Cloud System Models R. T. Cederwall and D. J. Rodriguez Atmospheric Science Division Lawrence Livermore National Laboratory Livermore, California
Cloud Thickness Estimation from GOES-8 Satellite Data Over the ARM-SGP Site
Cloud Thickness Estimation from GOES-8 Satellite Data Over the ARM-SGP Site V. Chakrapani, D. R. Doelling, and A. D. Rapp Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis National Aeronautics
Chapter 6: Cloud Development and Forms
Chapter 6: Cloud Development and Forms (from The Blue Planet ) Why Clouds Form Static Stability Cloud Types Why Clouds Form? Clouds form when air rises and becomes saturated in response to adiabatic cooling.
High Resolution Modeling, Clouds, Precipitation and Climate
High Resolution Modeling, Clouds, Precipitation and Climate Pier Siebesma, Ramon Mendez Gomez, Jerome Schalkwijk, Stephan de Roode Jisk Attema, Jessica Loreaux, Geert Lenderink, Harm Jonker 1. Precipitation
Frank and Charles Cohen Department of Meteorology The Pennsylvania State University University Park, PA, 16801 -U.S.A.
376 THE SIMULATION OF TROPICAL CONVECTIVE SYSTEMS William M. Frank and Charles Cohen Department of Meteorology The Pennsylvania State University University Park, PA, 16801 -U.S.A. ABSTRACT IN NUMERICAL
IMPACT OF SAINT LOUIS UNIVERSITY-AMERENUE QUANTUM WEATHER PROJECT MESONET DATA ON WRF-ARW FORECASTS
IMPACT OF SAINT LOUIS UNIVERSITY-AMERENUE QUANTUM WEATHER PROJECT MESONET DATA ON WRF-ARW FORECASTS M. J. Mueller, R. W. Pasken, W. Dannevik, T. P. Eichler Saint Louis University Department of Earth and
A glance at compensating errors between low-level cloud fraction and cloud optical properties using satellite retrievals
A glance at compensating errors between low-level cloud fraction and cloud optical properties using satellite retrievals Christine Nam & Sandrine Bony Laboratoire de Météorologie Dynamique Structure Overview
A limited area model (LAM) intercomparison study of a TWP-ICE active monsoon mesoscale convective event
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117,, doi:10.1029/2011jd016447, 2012 A limited area model (LAM) intercomparison study of a TWP-ICE active monsoon mesoscale convective event Ping Zhu, 1 Jim Dudhia,
Project Title: Quantifying Uncertainties of High-Resolution WRF Modeling on Downslope Wind Forecasts in the Las Vegas Valley
University: Florida Institute of Technology Name of University Researcher Preparing Report: Sen Chiao NWS Office: Las Vegas Name of NWS Researcher Preparing Report: Stanley Czyzyk Type of Project (Partners
A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection
JULY 2006 K U A N G A N D BRETHERTON 1895 A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection ZHIMING KUANG* Division of Geological and Planetary
High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land
High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land Marat Khairoutdinov 1 and David Randall Department of Atmospheric Science Colorado State University Accepted for publication
Sub-grid cloud parametrization issues in Met Office Unified Model
Sub-grid cloud parametrization issues in Met Office Unified Model Cyril Morcrette Workshop on Parametrization of clouds and precipitation across model resolutions, ECMWF, Reading, November 2012 Table of
Dutch Atmospheric Large-Eddy Simulation Model (DALES v3.2) CGILS-S11 results
Dutch Atmospheric Large-Eddy Simulation Model (DALES v3.2) CGILS-S11 results Stephan de Roode Delft University of Technology (TUD), Delft, Netherlands Mixed-layer model analysis: Melchior van Wessem (student,
Comment on "Observational and model evidence for positive low-level cloud feedback"
LLNL-JRNL-422752 Comment on "Observational and model evidence for positive low-level cloud feedback" A. J. Broccoli, S. A. Klein January 22, 2010 Science Disclaimer This document was prepared as an account
Stability and Cloud Development. Stability in the atmosphere AT350. Why did this cloud form, whereas the sky was clear 4 hours ago?
Stability and Cloud Development AT350 Why did this cloud form, whereas the sky was clear 4 hours ago? Stability in the atmosphere An Initial Perturbation Stable Unstable Neutral If an air parcel is displaced
Evaluating the Impact of Cloud-Aerosol- Precipitation Interaction (CAPI) Schemes on Rainfall Forecast in the NGGPS
Introduction Evaluating the Impact of Cloud-Aerosol- Precipitation Interaction (CAPI) Schemes on Rainfall Forecast in the NGGPS Zhanqing Li and Seoung-Soo Lee University of Maryland NOAA/NCEP/EMC Collaborators
Observed Cloud Cover Trends and Global Climate Change. Joel Norris Scripps Institution of Oceanography
Observed Cloud Cover Trends and Global Climate Change Joel Norris Scripps Institution of Oceanography Increasing Global Temperature from www.giss.nasa.gov Increasing Greenhouse Gases from ess.geology.ufl.edu
Cloud Development and Forms. LIFTING MECHANISMS 1. Orographic 2. Frontal 3. Convergence 4. Convection. Orographic Cloud. The Orographic Cloud
Introduction to Climatology GEOGRAPHY 300 Cloud Development and Forms Tom Giambelluca University of Hawai i at Mānoa LIFTING MECHANISMS 1. Orographic 2. Frontal 3. Convergence 4. Convection Cloud Development
Lecture 3. Turbulent fluxes and TKE budgets (Garratt, Ch 2)
Lecture 3. Turbulent fluxes and TKE budgets (Garratt, Ch 2) In this lecture How does turbulence affect the ensemble-mean equations of fluid motion/transport? Force balance in a quasi-steady turbulent boundary
Evolution of convective cloud top height: entrainment and humidifying processes. EUROCS Workshop, Madrid, 16-19/12/2002
Jean-Marcel Piriou Centre National de Recherches Météorologiques Groupe de Modélisation pour l Assimilation et la Prévision Evolution of convective cloud top height: entrainment and humidifying processes
Convective Clouds. Convective clouds 1
Convective clouds 1 Convective Clouds Introduction Convective clouds are formed in vertical motions that result from the instability of the atmosphere. This instability can be caused by: a. heating at
Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations
Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations S. C. Xie, R. T. Cederwall, and J. J. Yio Lawrence Livermore National Laboratory Livermore, California M. H. Zhang
Atmospheric kinetic energy spectra from high-resolution GEM models
Atmospheric kinetic energy spectra from high-resolution GEM models Bertrand Denis NWP Section Canadian Meteorological Centre Environment Canada SRNWP 2009 Bad Orb, Germany Outline Introduction What we
Application of Numerical Weather Prediction Models for Drought Monitoring. Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia
Application of Numerical Weather Prediction Models for Drought Monitoring Gregor Gregorič Jožef Roškar Environmental Agency of Slovenia Contents 1. Introduction 2. Numerical Weather Prediction Models -
Guy Carpenter Asia-Pacific Climate Impact Centre, School of energy and Environment, City University of Hong Kong
Diurnal and Semi-diurnal Variations of Rainfall in Southeast China Judy Huang and Johnny Chan Guy Carpenter Asia-Pacific Climate Impact Centre School of Energy and Environment City University of Hong Kong
The horizontal diffusion issue in CRM simulations of moist convection
The horizontal diffusion issue in CRM simulations of moist convection Wolfgang Langhans Institute for Atmospheric and Climate Science, ETH Zurich June 9, 2009 Wolfgang Langhans Group retreat/bergell June
Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP ICE
Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. 138: 734 754, April 2012 A Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model
Chapter 6 - Cloud Development and Forms. Interesting Cloud
Chapter 6 - Cloud Development and Forms Understanding Weather and Climate Aguado and Burt Interesting Cloud 1 Mechanisms that Lift Air Orographic lifting Frontal Lifting Convergence Localized convective
Towards Multiscale Simulations of Cloud Turbulence
Towards Multiscale Simulations of Cloud Turbulence Ryo Onishi *1,2 and Keiko Takahashi *1 *1 Earth Simulator Center/JAMSTEC *2 visiting scientist at Imperial College, London (Prof. Christos Vassilicos)
Wind resources map of Spain at mesoscale. Methodology and validation
Wind resources map of Spain at mesoscale. Methodology and validation Martín Gastón Edurne Pascal Laura Frías Ignacio Martí Uxue Irigoyen Elena Cantero Sergio Lozano Yolanda Loureiro e-mail:mgaston@cener.com
4.2 OBSERVATIONS OF THE WIDTH OF CLOUD DROPLET SPECTRA IN STRATOCUMULUS
4.2 OBSERVATIONS OF THE WIDTH OF CLOUD DROPLET SPECTRA IN STRATOCUMULUS Hanna Pawlowska 1 and Wojciech W. Grabowski 2 1 Institute of Geophysics, Warsaw University, Poland 2 NCAR, Boulder, Colorado, USA
Clouds. A simple scientific explanation for the weather-curious. By Kira R. Erickson
Clouds A simple scientific explanation for the weather-curious By Kira R. Erickson Table of Contents 1 3 4 INTRO 2 Page 3 How Clouds Are Formed Types of Clouds Clouds and Weather More Information Page
Financing Community Wind
Financing Community Wind Wind Data and Due Diligence What is the Project's Capacity Factor? Community Wind Energy 2006 March 8, 2006 Mark Ahlstrom mark@windlogics.com Slide 1 The Need for Wind Assessment
Including thermal effects in CFD simulations
Including thermal effects in CFD simulations Catherine Meissner, Arne Reidar Gravdahl, Birthe Steensen catherine@windsim.com, arne@windsim.com Fjordgaten 15, N-125 Tonsberg hone: +47 8 1800 Norway Fax:
How To Calculate Turbulent Collision
Impact of turbulent collisions on cloud development Ryo Onishi and Keiko Takahashi Earth Simulator Center (ESC), Japan Agency of Marine-Earth Science and Technology (JAMSTEC) Turbulent collision kernel
O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM. Darmstadt, 27.06.2012
O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM Darmstadt, 27.06.2012 Michael Ehlen IB Fischer CFD+engineering GmbH Lipowskystr. 12 81373 München Tel. 089/74118743 Fax 089/74118749
Theory of moist convection in statistical equilibrium
Theory of moist convection in statistical equilibrium By analogy with Maxwell-Boltzmann statistics Bob Plant Department of Meteorology, University of Reading, UK With thanks to: George Craig, Brenda Cohen,
2.8 ENTRAINMENT AND THE FINE STRUCTURE OF THE STRATOCUMULUS TOPPED BOUNDARY LAYERS
2.8 ENTRAINMENT AND THE FINE STRUCTURE OF THE STRATOCUMULUS TOPPED BOUNDARY LAYERS Q. Wang 1, M. S. Horner 1, S. Wang 2, and J.A. Kalogiros 3 1 Naval Postgraduate School, Monterey, CA 2 Naval Research
A new positive cloud feedback?
A new positive cloud feedback? Bjorn Stevens Max-Planck-Institut für Meteorologie KlimaCampus, Hamburg (Based on joint work with Louise Nuijens and Malte Rieck) Slide 1/31 Prehistory [W]ater vapor, confessedly
California Standards Grades 9 12 Boardworks 2009 Science Contents Standards Mapping
California Standards Grades 912 Boardworks 2009 Science Contents Standards Mapping Earth Sciences Earth s Place in the Universe 1. Astronomy and planetary exploration reveal the solar system s structure,
Super-parametrization in climate and what do we learn from high-resolution
Super-parametrization in climate and what do we learn from high-resolution Marat Khairoutdinov Stony Brook University USA ECMWF Annual Seminar, 1-4 September 2015 scales-separation parameterized convection
Cloud feedback. Chris Bretherton University of Washington. Rob Wood, Peter Blossey, Matt Wyant, Dennis Hartmann, Mark Zelinka
Cloud feedback Chris Bretherton University of Washington with Rob Wood, Peter Blossey, Matt Wyant, Dennis Hartmann, Mark Zelinka What is cloud feedback? The effect on an externally-forced climate perturbation
RADIATION IN THE TROPICAL ATMOSPHERE and the SAHEL SURFACE HEAT BALANCE. Peter J. Lamb. Cooperative Institute for Mesoscale Meteorological Studies
RADIATION IN THE TROPICAL ATMOSPHERE and the SAHEL SURFACE HEAT BALANCE by Peter J. Lamb Cooperative Institute for Mesoscale Meteorological Studies and School of Meteorology The University of Oklahoma
TOPIC: CLOUD CLASSIFICATION
INDIAN INSTITUTE OF TECHNOLOGY, DELHI DEPARTMENT OF ATMOSPHERIC SCIENCE ASL720: Satellite Meteorology and Remote Sensing TERM PAPER TOPIC: CLOUD CLASSIFICATION Group Members: Anil Kumar (2010ME10649) Mayank
Impacts of a future city master plan on on thermal and wind environments in Vinh city, Vietnam
Impacts of a future city master plan on on thermal and wind environments in Vinh city, Vietnam Satoru Iizuka, Nagoya University, Japan Tatsunori Ito, Nagoya University, Japan Masato Miyata, Mitsubishi
Diurnal Cycle of Convection at the ARM SGP Site: Role of Large-Scale Forcing, Surface Fluxes, and Convective Inhibition
Thirteenth ARM Science Team Meeting Proceedings, Broomfield, Colorado, March 31-April 4, 23 Diurnal Cycle of Convection at the ARM SGP Site: Role of Large-Scale Forcing, Surface Fluxes, and Convective
Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data
VOLUME 64 J O U R N A L O F T H E A T M O S P H E R I C S C I E N C E S DECEMBER 2007 Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data XIPING ZENG,*, WEI-KUO TAO,
Evaluating climate model simulations of tropical cloud
Tellus (2004), 56A, 308 327 Copyright C Blackwell Munksgaard, 2004 Printed in UK. All rights reserved TELLUS Evaluating climate model simulations of tropical cloud By MARK A. RINGER and RICHARD P. ALLAN,
Long-Term Cloud-Resolving Model Simulations of Cloud Properties and Radiative Effects of Cloud Distributions
Long-Term Cloud-Resolving Model Simulations of Cloud Properties and Radiative Effects of Cloud Distributions Xiaoqing Wu and Sunwook Park Department of Geological and Atmospheric Sciences Iowa State University,
Not all clouds are easily classified! Cloud Classification schemes. Clouds by level 9/23/15
Cloud Classification schemes 1) classified by where they occur (for example: high, middle, low) 2) classified by amount of water content and vertical extent (thick, thin, shallow, deep) 3) classified by
Towards an NWP-testbed
Towards an NWP-testbed Ewan O Connor and Robin Hogan University of Reading, UK Overview Cloud schemes in NWP models are basically the same as in climate models, but easier to evaluate using ARM because:
Science Goals for the ARM Recovery Act Radars
DOE/SC-ARM-12-010 Science Goals for the ARM Recovery Act Radars JH Mather May 2012 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States