Quality Assurance in Atmospheric Modeling

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Quality Assurance in Atmospheric Modeling"

Transcription

1 Quality Assurance in Atmospheric Modeling To Appear in the Bulletin of the American Meteorological Society Thomas T. Warner

2 An Explosion in Mesoscale Model Usage

3 Rapid Increase in Model Users Due to: Easy access to and use of models Availability of compucng resources Value of model- generated atmospheric informacon (observing capabilices develop slowly, model resolucon scales with computer development) Expected use of modeling in most research New applicacons (regional climate)

4 So, you want to run a mesoscale model? 14 Steps toward improving the outcome

5 1. Clearly Define the ScienCfic or PracCcal ObjecCve Hypothesis to be tested? How will you know whether you are successful? Is this a fishing trip? Do you really need a mesoscale model? uclafacultyassociation.blogspot.com

6 2. IdenCfy and Develop a Physical Understanding of the Atmospheric Processes that must be Accurately Simulated. Necessary to design simulacon(s) what processes are important? (conveccon, radiacon, cloud physics, snowcover, etc.) Necessary to judge efficacy of simulacon Not complete understanding a[er all this may be the reason for the study but enough to guide choices in methodology

7 3. Perform a Thorough Analysis of all Available ObservaCons Increase familiarity with phenomena or processes under invescgacon Know how and where model results may be helpful Be be_er able to judge adequacy of simulacons sriks6711.wordpress.com

8 4. Prepare an Experimental Design Case study? Which case? Is a real- case simulacon the best strategy or should it be idealized? Do we need a model at all? Ensemble of cases? Process study? How will verificacon be done?

9 5. Define the model configuracon Domain ResoluCon (horizontal and verccal)? eo.ucar.edu

10 What do Mesoscale Models Resolve? 7 x

11 6. Don t run the model just yet. Running the model before steps 1-5 are complete could simply waste Cme. (the sooner the model is run, the longer the study will take) Re- evaluate goals and design of study as necessary.

12 7. Choose Cme and method of inicalizacon InterpolaCon from other model? VariaConal data assimilacon? Ensemble data assimilacon? What spinup is allowed? Knowledge of techniques? abarnyard.com

13 8. Evaluate sensicvity to lateral boundary locacons and specificacon (if limited area) Tradeoff between large domain (computaconal cost) and small domain (determinacon of solucon by boundaries Open or periodic (idealized) Quality of model/data on lateral boundaries sonatinassong.blogspot.com

14 Influence of Lateral Boundaries Figure. Twelve-hour simulations of 250-hPa winds (m s-1) from the 40-km grid increment Eta Model initialized at 1200 UTC 3 August 1992, based on experiments that used a large (a) and small (b) computational domain. The isotach interval is 5 m s-1. From Treadon and Peterson (1993).

15 9. Define the most appropriate physical parameterizacons. Braham, 1974, BAMS

16 Different Schemes, Different Results Figure 4. Average rainfall rate, for a spring-season convective event (a), based on observations (OBS) and for five simulations that used different treatments for the convection - four different parameterizations, and no parameterization (EX). Also depicted is the rainfallrate bias score averaged for three warm-season convective events (b), again for each of the four parameterizations and for the use of no parameterization. The four convective parameterizations were the Grell (GR), Kain-Fritsch (KF), Betts-Miller (BM), and Anthes- Kuo (AK) schemes. Adapted from Wang and Seaman (1997).

17 10. Understand the limits to predictability of the phenomenon being studied It's tough to make predictions, especially about the future. Yogi Berra Errors affect progressively larger scales with time Zhang, Fuqing, Naifang Bei, Richard Rotunno, Chris Snyder, Craig C. Epifanio, 2007: Mesoscale Predictability of Moist Baroclinic Waves: Convection-Permitting Experiments and Multistage Error Growth Dynamics. J. Atmos. Sci., 64, nndb.com

18 11. Establish a verificacon plan before the model is run and perform a thorough verificacon, using appropriate metrics, of the model solucon using all available observacons. Why before? Because model output may vary with verificacon method? Importance? Confidence in model use (process study or forecast) QuanCfy strengths and weaknesses Assure right answer for right reason. Choose appropriate verificacon metrics

19 Beware of VerificaCon Metrics

20 12. Be organized Maintain an experimental log Be systemacc about what is archived Note: Tom s office NEVER looked like this

21 13. Use good coding praccces and well- documented so[ware Will new code be developed? Black- box vs. white- box tescng Be able to repeat your results (because you will probably have to) Upgrades to community codes use newest version? Latest version could have major bugs Does upgrade affect reproducibility?

22 14. Use open- source so[ware tools to improve the efficiency of the modeling process Use version- control so[ware to keep track of model versions Use well- documented packages Open- source packages are available to facilitate interpretacon of model output Calc.f Calc.f_old Calc.f_new Calc.f_new_a Calc.f_new_b Calc.f_older Calc.f_somewhat_newer Calc.f_i-cant-remember Calc.f_err Calc.f_err1

23 Conclusions Research models are tools, and like any tool, must be used properly Modeler should be as familiar with observacons as the model More planning and preparacon of simulacons leads to shorter (and be_er) duracon of studies It is encrely possible to set out to do a modeling study and never run the model.

24 Tom s Legacy Understand how nature works, using whatever tools are needed Know the observacons first Run models last, not first Confront model results with observacons and meteorological insight Model to teach and teach to model

Aformal definition of quality assurance that is

Aformal definition of quality assurance that is QUALITY ASSURANCE IN ATMOSPHERIC MODELING by Thomas T. Warner The rapid growth in the number of atmospheric model users is motivation for reviewing best practices in atmospheric modeling and emphasizing

More information

Operational Mesoscale NWP at the Japan Meteorological Agency. Tabito HARA Numerical Prediction Division Japan Meteorological Agency

Operational Mesoscale NWP at the Japan Meteorological Agency. Tabito HARA Numerical Prediction Division Japan Meteorological Agency Operational Mesoscale NWP at the Japan Meteorological Agency Tabito HARA Numerical Prediction Division Japan Meteorological Agency NWP at JMA JMA has been operating two NWP models. GSM (Global Spectral

More information

Cloud-Resolving Simulations of Convection during DYNAMO

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.

More information

Can latent heat release have a negative effect on polar low intensity?

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

More information

Convection permitting models setting the scene

Convection permitting models setting the scene Convection permitting models setting the scene Nigel Roberts MetOffice@Reading The elephant in the corner convective storms Hand et al 2004 examined UK 20 th century extreme flood events and found that

More information

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 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

More information

Wind resources map of Spain at mesoscale. Methodology and validation

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

More information

Developing Continuous SCM/CRM Forcing Using NWP Products Constrained by ARM Observations

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

More information

Parameterization of Cumulus Convective Cloud Systems in Mesoscale Forecast Models

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

More information

Clouds and Convection

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

More information

Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF

Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF 3 Working Group on Verification and Case Studies 56 Comparative Evaluation of High Resolution Numerical Weather Prediction Models COSMO-WRF Bogdan Alexandru MACO, Mihaela BOGDAN, Amalia IRIZA, Cosmin Dănuţ

More information

Research Objective 4: Develop improved parameterizations of boundary-layer clouds and turbulence for use in MMFs and GCRMs

Research Objective 4: Develop improved parameterizations of boundary-layer clouds and turbulence for use in MMFs and GCRMs 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 Scales of Atmospheric

More information

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 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

More information

Description of zero-buoyancy entraining plume model

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

More information

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 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 -

More information

Atmospheric kinetic energy spectra from high-resolution GEM models

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

More information

Evalua&ng Downdra/ Parameteriza&ons with High Resolu&on CRM Data

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

More information

Various Implementations of a Statistical Cloud Scheme in COSMO model

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,

More information

Frank and Charles Cohen Department of Meteorology The Pennsylvania State University University Park, PA, 16801 -U.S.A.

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

More information

Uncertainties in using the hodograph method to retrieve gravity wave characteristics from individual soundings

Uncertainties in using the hodograph method to retrieve gravity wave characteristics from individual soundings GEOPHYSICAL RESEARCH LETTERS, VOL. 31, L11110, doi:10.1029/2004gl019841, 2004 Uncertainties in using the hodograph method to retrieve gravity wave characteristics from individual soundings Fuqing Zhang

More information

Project Title: Quantifying Uncertainties of High-Resolution WRF Modeling on Downslope Wind Forecasts in the Las Vegas Valley

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

More information

Clarity. Helping you understand the facts about weather forecasting

Clarity. Helping you understand the facts about weather forecasting Clarity Helping you understand the facts about weather forecasting Forecasting the weather is essential to help you prepare for the best and the worst of our climate. Met Office forecasters work 24/7,

More information

Convective Vertical Velocities in GFDL AM3, Cloud Resolving Models, and Radar Retrievals

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

More information

An Integrated Ensemble/Variational Hybrid Data Assimilation System

An Integrated Ensemble/Variational Hybrid Data Assimilation System An Integrated Ensemble/Variational Hybrid Data Assimilation System DAOS Working Group Meeting September 2012 Tom Auligné, National Center for Atmospheric Research Acknowledgements: Contributors: Luke Peffers

More information

Very High Resolution Arctic System Reanalysis for 2000-2011

Very High Resolution Arctic System Reanalysis for 2000-2011 Very High Resolution Arctic System Reanalysis for 2000-2011 David H. Bromwich, Lesheng Bai,, Keith Hines, and Sheng-Hung Wang Polar Meteorology Group, Byrd Polar Research Center The Ohio State University

More information

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 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

More information

MICROPHYSICS COMPLEXITY EFFECTS ON STORM EVOLUTION AND ELECTRIFICATION

MICROPHYSICS COMPLEXITY EFFECTS ON STORM EVOLUTION AND ELECTRIFICATION MICROPHYSICS COMPLEXITY EFFECTS ON STORM EVOLUTION AND ELECTRIFICATION Blake J. Allen National Weather Center Research Experience For Undergraduates, Norman, Oklahoma and Pittsburg State University, Pittsburg,

More information

Towards an NWP-testbed

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:

More information

Development of an Elevated Mixed Layer Model for Parameterizing Altocumulus Cloud Layers

Development of an Elevated Mixed Layer Model for Parameterizing Altocumulus Cloud Layers 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

More information

118358 SUPERENSEMBLE FORECASTS WITH A SUITE OF MESOSCALE MODELS OVER THE CONTINENTAL UNITED STATES

118358 SUPERENSEMBLE FORECASTS WITH A SUITE OF MESOSCALE MODELS OVER THE CONTINENTAL UNITED STATES 118358 SUPERENSEMBLE FORECASTS WITH A SUITE OF MESOSCALE MODELS OVER THE CONTINENTAL UNITED STATES Donald F. Van Dyke III * Florida State University, Tallahassee, Florida T. N. Krishnamurti Florida State

More information

REDUCING UNCERTAINTY IN SOLAR ENERGY ESTIMATES

REDUCING UNCERTAINTY IN SOLAR ENERGY ESTIMATES REDUCING UNCERTAINTY IN SOLAR ENERGY ESTIMATES Mitigating Energy Risk through On-Site Monitoring Marie Schnitzer, Vice President of Consulting Services Christopher Thuman, Senior Meteorologist Peter Johnson,

More information

Titelmasterformat durch Klicken. bearbeiten

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

More information

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 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,

More information

MOGREPS status and activities

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

More information

7B.2 MODELING THE EFFECT OF VERTICAL WIND SHEAR ON TROPICAL CYCLONE SIZE AND STRUCTURE

7B.2 MODELING THE EFFECT OF VERTICAL WIND SHEAR ON TROPICAL CYCLONE SIZE AND STRUCTURE 7B.2 MODELING THE EFFECT OF VERTICAL WIND SHEAR ON TROPICAL CYCLONE SIZE AND STRUCTURE Diana R. Stovern* and Elizabeth A. Ritchie University of Arizona, Tucson, Arizona 1. Introduction An ongoing problem

More information

Sub-grid cloud parametrization issues in Met Office Unified Model

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

More information

Triple eyewall experiment of the 2012 typhoon Bolaven using cloud resolving ensemble forecast

Triple eyewall experiment of the 2012 typhoon Bolaven using cloud resolving ensemble forecast The 3 rd Research meeting of Ultrahigh Precision Meso Scale Weather Prediction Thu. 21 Mar. 2013 Triple eyewall experiment of the 2012 typhoon Bolaven using cloud resolving ensemble forecast Seiji ORIGUCHI,

More information

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 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

More information

Thor Erik Nordeng (P.O. Box 43, N-0313 OSLO, NORWAY)

Thor Erik Nordeng (P.O. Box 43, N-0313 OSLO, NORWAY) (Picture: http://www.dagbladet.no/nyheter/2007/02/24/493138.html) A study of model performance for the February 2007 snowstorm on Sørlandet. Part I: Evaluation against observations Thor Erik Nordeng (P.O.

More information

Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders

Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders Physical properties of mesoscale high-level cloud systems in relation to their atmospheric environment deduced from Sounders Claudia Stubenrauch, Sofia Protopapadaki, Artem Feofilov, Theodore Nicolas &

More information

Stochastic variability of mass flux in a cloud resolving simulation

Stochastic variability of mass flux in a cloud resolving simulation Stochastic variability of mass flux in a cloud resolving simulation Jahanshah Davoudi Thomas Birner, orm McFarlane and Ted Shepherd Physics department, University of Toronto Stochastic variability of mass

More information

Limitations of Equilibrium Or: What if τ LS τ adj?

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

More information

Simulation of low clouds from the CAM and the regional WRF with multiple nested resolutions

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

More information

Next generation models at MeteoSwiss: communication challenges

Next generation models at MeteoSwiss: communication challenges Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Next generation models at MeteoSwiss: communication challenges Tanja Weusthoff, MeteoSwiss Material from

More information

An exploratory study of the possibilities of analog postprocessing

An exploratory study of the possibilities of analog postprocessing Intern rapport ; IR 2009-02 An exploratory study of the possibilities of analog postprocessing Dirk Wolters De Bilt, 2009 KNMI internal report = intern rapport; IR 2009-02 De Bilt, 2009 PO Box 201 3730

More information

Guy Carpenter Asia-Pacific Climate Impact Centre, School of energy and Environment, City University of Hong Kong

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

More information

HUNGARIAN METEOROLOGICAL SERVICE, BUDAPEST

HUNGARIAN METEOROLOGICAL SERVICE, BUDAPEST WWW TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA- PROCESSING AND FORECASTING SYSTEM (GDPFS), AND THE ANNUAL NUMERICAL WEATHER PREDICTION (NWP) PROGRESS REPORT FOR THE YEAR 2005 HUNGARIAN METEOROLOGICAL

More information

Introduction to parametrization development

Introduction to parametrization development Introduction to parametrization development Anton Beljaars (ECMWF) Thanks to: The ECMWF Physics Team and many others Outline Introduction Physics related applications Does a sub-grid scheme have the correct

More information

Convection Resolving Model (CRM) MOLOCH. 1-Breve descrizione del CRM sviluppato all ISAC-CNR

Convection Resolving Model (CRM) MOLOCH. 1-Breve descrizione del CRM sviluppato all ISAC-CNR Convection Resolving Model (CRM) MOLOCH 1-Breve descrizione del CRM sviluppato all ISAC-CNR 2-Ipotesi alla base della parametrizzazione dei processi microfisici Objectives Develop a tool for very high

More information

Climate Extremes Research: Recent Findings and New Direc8ons

Climate Extremes Research: Recent Findings and New Direc8ons Climate Extremes Research: Recent Findings and New Direc8ons Kenneth Kunkel NOAA Cooperative Institute for Climate and Satellites North Carolina State University and National Climatic Data Center h#p://assessment.globalchange.gov

More information

A Review on the Uses of Cloud-(System-)Resolving Models

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

More information

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 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

More information

Theory of moist convection in statistical equilibrium

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,

More information

Breeding and predictability in coupled Lorenz models. E. Kalnay, M. Peña, S.-C. Yang and M. Cai

Breeding and predictability in coupled Lorenz models. E. Kalnay, M. Peña, S.-C. Yang and M. Cai Breeding and predictability in coupled Lorenz models E. Kalnay, M. Peña, S.-C. Yang and M. Cai Department of Meteorology University of Maryland, College Park 20742 USA Abstract Bred vectors are the difference

More information

CRM simula+ons with parameterized large- scale dynamics using +me- dependent forcings from observa+ons

CRM simula+ons with parameterized large- scale dynamics using +me- dependent forcings from observa+ons CRM simula+ons with parameterized large- scale dynamics using +me- dependent forcings from observa+ons Shuguang Wang, Adam Sobel, Zhiming Kuang Zhiming & Kerry s workshop Harvard, March 2012 In tropical

More information

Mass flux fluctuation in a cloud resolving simulation with diurnal forcing

Mass flux fluctuation in a cloud resolving simulation with diurnal forcing Mass flux fluctuation in a cloud resolving simulation with diurnal forcing Jahanshah Davoudi Norman McFarlane, Thomas Birner Physics department, University of Toronto Mass flux fluctuation in a cloud resolving

More information

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 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

More information

A Real Case Study of Using Cloud Analysis in Grid-point Statistical Interpolation Analysis and Advanced Research WRF Forecast System

A Real Case Study of Using Cloud Analysis in Grid-point Statistical Interpolation Analysis and Advanced Research WRF Forecast System A Real Case Study of Using Cloud Analysis in Grid-point Statistical Interpolation Analysis and Advanced Research WRF Forecast System Ming Hu 1 and Ming Xue 1, 1 Center for Analysis and Prediction of Storms,

More information

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 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,

More information

Cloud Model Verification at the Air Force Weather Agency

Cloud Model Verification at the Air Force Weather Agency 2d Weather Group Cloud Model Verification at the Air Force Weather Agency Matthew Sittel UCAR Visiting Scientist Air Force Weather Agency Offutt AFB, NE Template: 28 Feb 06 Overview Cloud Models Ground

More information

Cloud/Radiation parameterization issues in high resolution NWP

Cloud/Radiation parameterization issues in high resolution NWP Cloud/Radiation parameterization issues in high resolution NWP Bent H Sass Danish Meteorological Institute 10 June 2009 As the horizontal grid size in atmospheric models is reduced the assumptions made

More information

ASSESSMENT OF THE CAPABILITY OF WRF MODEL TO ESTIMATE CLOUDS AT DIFFERENT TEMPORAL AND SPATIAL SCALES

ASSESSMENT OF THE CAPABILITY OF WRF MODEL TO ESTIMATE CLOUDS AT DIFFERENT TEMPORAL AND SPATIAL SCALES 16TH WRF USER WORKSHOP, BOULDER, JUNE 2015 ASSESSMENT OF THE CAPABILITY OF WRF MODEL TO ESTIMATE CLOUDS AT DIFFERENT TEMPORAL AND SPATIAL SCALES Clara Arbizu-Barrena, David Pozo-Vázquez, José A. Ruiz-Arias,

More information

The State of the Climate And Extreme Weather. Deke Arndt NOAA s National Climatic Data Center

The State of the Climate And Extreme Weather. Deke Arndt NOAA s National Climatic Data Center The State of the Climate And Extreme Weather Deke Arndt June Feb 2013 2011 1 The world s largest archive of weather and climate data NCDC is located in Asheville, North Carolina A place of active retirement

More information

Improving Cloud Impacts on Photolysis Rates in Off-Line AQMs

Improving Cloud Impacts on Photolysis Rates in Off-Line AQMs Improving Cloud Impacts on Photolysis Rates in Off-Line AQMs Chris Emery ENVIRON Corporation June 24, 2009 Acknowledgements: K. Baker, B. Timin, EPA/OAQPS Introduction Photochemistry is strongly influenced

More information

Big Data Assimilation Revolutionizing Weather Prediction

Big Data Assimilation Revolutionizing Weather Prediction February 23, 2015, ISDA2015, Kobe Big Data Assimilation Revolutionizing Weather Prediction M. Kunii, J. Ruiz, G.-Y. Lien, K. Kondo, S. Otsuka, Y. Maejima, and Takemasa Miyoshi* RIKEN Advanced Institute

More information

CAUSES. (Clouds Above the United States and Errors at the Surface)

CAUSES. (Clouds Above the United States and Errors at the Surface) CAUSES (Clouds Above the United States and Errors at the Surface) Cloud-regime analysis to find the causes of surface temperature errors in weather and climate models Cyril Morcrette and Kwinten Van Weverberg

More information

for WP4.1.3 // meeting, 22 Sept 2005 morning, Francoise Guichard EUROCS: european project on cloud systems in NWP/climate models

for WP4.1.3 // meeting, 22 Sept 2005 morning, Francoise Guichard EUROCS: european project on cloud systems in NWP/climate models 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

More information

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 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

More information

Cloud/Hydrometeor Initialization in the 20-km RUC Using GOES Data

Cloud/Hydrometeor Initialization in the 20-km RUC Using GOES Data WORLD METEOROLOGICAL ORGANIZATION COMMISSION FOR BASIC SYSTEMS OPEN PROGRAMMME AREA GROUP ON INTEGRATED OBSERVING SYSTEMS EXPERT TEAM ON OBSERVATIONAL DATA REQUIREMENTS AND REDESIGN OF THE GLOBAL OBSERVING

More information

Turbulence-microphysics interactions in boundary layer clouds

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

More information

Development of a. Solar Generation Forecast System

Development of a. Solar Generation Forecast System ALBANY BARCELONA BANGALORE 16 December 2011 Development of a Multiple Look ahead Time Scale Solar Generation Forecast System John Zack Glenn Van Knowe Marie Schnitzer Jeff Freedman AWS Truepower, LLC Albany,

More information

Turbulent mixing in clouds latent heat and cloud microphysics effects

Turbulent mixing in clouds latent heat and cloud microphysics effects Turbulent mixing in clouds latent heat and cloud microphysics effects Szymon P. Malinowski1*, Mirosław Andrejczuk2, Wojciech W. Grabowski3, Piotr Korczyk4, Tomasz A. Kowalewski4 and Piotr K. Smolarkiewicz3

More information

Characterizing Task Usage Shapes in Google s Compute Clusters

Characterizing Task Usage Shapes in Google s Compute Clusters Characterizing Task Usage Shapes in Google s Compute Clusters Qi Zhang 1, Joseph L. Hellerstein 2, Raouf Boutaba 1 1 University of Waterloo, 2 Google Inc. Introduction Cloud computing is becoming a key

More information

CFMIP-2 : Cloud Feedback Model Intercomparison Project Phase 2

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

More information

Estimation of satellite observations bias correction for limited area model

Estimation of satellite observations bias correction for limited area model Estimation of satellite observations bias correction for limited area model Roger Randriamampianina Hungarian Meteorological Service, Budapest, Hungary roger@met.hu Abstract Assimilation of satellite radiances

More information

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 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

More information

Software Testing. Knowledge Base. Rajat Kumar Bal. Introduction

Software Testing. Knowledge Base. Rajat Kumar Bal. Introduction Software Testing Rajat Kumar Bal Introduction In India itself, Software industry growth has been phenomenal. IT field has enormously grown in the past 50 years. IT industry in India is expected to touch

More information

Why aren t climate models getting better? Bjorn Stevens, UCLA

Why aren t climate models getting better? Bjorn Stevens, UCLA Why aren t climate models getting better? Bjorn Stevens, UCLA Four Hypotheses 1. Our premise is false, models are getting better. 2. We don t know what better means. 3. It is difficult, models have rough

More information

Mesoscale re-analysis of historical meteorological data over Europe Anna Jansson and Christer Persson, SMHI ERAMESAN A first attempt at SMHI for re-analyses of temperature, precipitation and wind over

More information

Evaluating the Impact of Cloud-Aerosol- Precipitation Interaction (CAPI) Schemes on Rainfall Forecast in the NGGPS

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

More information

Unified Cloud and Mixing Parameterizations of the Marine Boundary Layer: EDMF and PDF-based cloud approaches

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

More information

The horizontal diffusion issue in CRM simulations of moist convection

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

More information

Team Members. Lei Wen, Slavko Vasi, Barry Turner, Olivier Bousquet. Isztar Zawadzki. McGill University

Team Members. Lei Wen, Slavko Vasi, Barry Turner, Olivier Bousquet. Isztar Zawadzki. McGill University Quantitative Precipitation Forecast (QPF) from Weather Prediction Models and Radar Nowcasts, and Atmospheric Hydrological Modelling for Flood Simulation Charles Lin Professor, Department of Atmospheric

More information

AOSN II System Goals and Performance Metrics R. Davis, J. Bellingham, P. Chandler, F. Chavez, N. Leoanard, A. Robinson (revised 11 May 2003)

AOSN II System Goals and Performance Metrics R. Davis, J. Bellingham, P. Chandler, F. Chavez, N. Leoanard, A. Robinson (revised 11 May 2003) AOSN II System Goals and Performance Metrics R. Davis, J. Bellingham, P. Chandler, F. Chavez, N. Leoanard, A. Robinson (revised 11 May 2003) The 2003 AOSN II field program depends on coordinated activities

More information

Integrated Stochastic Weather and Production Simulation Modeling

Integrated Stochastic Weather and Production Simulation Modeling Integrated Stochastic Weather and Production Simulation Modeling Thomas Edmunds, Vera Bulaevskaya, Alan Lamont, Matthew Simpson, and Philip Top Lawrence Livermore National Laboratory Livermore, CA USA

More information

DRI Workshop-2007. R. L. Raddatz U of Winnipeg

DRI Workshop-2007. R. L. Raddatz U of Winnipeg DRI Workshop-2007 R. L. Raddatz U of Winnipeg Raddatz,R.L, 2005. Moisture recycling on the Canadian Prairies for summer droughts and pluvials from 1997 to 2003. Agricultural and Forest Meteorology, 131,

More information

A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning.

A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning. A system of direct radiation forecasting based on numerical weather predictions, satellite image and machine learning. 31st Annual International Symposium on Forecasting Lourdes Ramírez Santigosa Martín

More information

Climate modelling. Dr. Heike Huebener Hessian Agency for Environment and Geology Hessian Centre on Climate Change

Climate modelling. Dr. Heike Huebener Hessian Agency for Environment and Geology Hessian Centre on Climate Change Hessisches Landesamt für Umwelt und Geologie Climate modelling Dr. Heike Huebener Hessian Agency for Environment and Geology Hessian Centre on Climate Change Climate: Definition Weather: momentary state

More information

Release Management Report

Release Management Report ALMA Integrated Compu2ng Team Coordina2on & Planning Mee2ng #4 San2ago, 19-21 November 2014 Release Management Report Ruben Soto ICT Release Manager Releases (since June 2014) 4 incremental releases have

More information

Climatology and Monitoring of Dust and Sand Storms in the Arabian Peninsula

Climatology and Monitoring of Dust and Sand Storms in the Arabian Peninsula Climatology and Monitoring of Dust and Sand Storms in the Arabian Peninsula Mansour Almazroui Center of Excellence for Climate Change Research (CECCR) King Abdulaziz University, Jeddah, Saudi Arabia E-mail:

More information

High Performance Computing for Numerical Weather Prediction

High Performance Computing for Numerical Weather Prediction High Performance Computing for Numerical Weather Prediction Isabella Weger European Centre for Medium-Range Weather Forecasts Slide 1 ECMWF ECMWF A European organisation with headquarters in the UK Established

More information

Project Title: Improving Anticipation of the Influence of Upstream Convection on QPF

Project Title: Improving Anticipation of the Influence of Upstream Convection on QPF University: North Carolina State University Name of University Researcher Preparing Report: Gary Lackmann NWS Office: Raleigh, NC Name of NWS Researcher Preparing Report: Jonathan Blaes Partners or Cooperative

More information

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) 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

More information

Application Value Assessment

Application Value Assessment Value Assessment Journey to Realising the Value of an Organisation s Portfolio Fujitsu UK & Ireland - Business & Services By Chris Waite, Fujitsu Businesses today operate in highly competitive environments

More information

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 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

More information

Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma KEITH BREWSTER

Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma KEITH BREWSTER FEBRUARY 2006 H U E T A L. 675 3DVAR and Cloud Analysis with WSR-88D Level-II Data for the Prediction of the Fort Worth, Texas, Tornadic Thunderstorms. Part I: Cloud Analysis and Its Impact MING HU AND

More information

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands Supplementary Material to A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands G. Lenderink and J. Attema Extreme precipitation during 26/27 th August

More information

Cloud-Resolving Model Simulation and Mosaic Treatment of Subgrid Cloud-Radiation Interaction

Cloud-Resolving Model Simulation and Mosaic Treatment of Subgrid Cloud-Radiation Interaction Cloud-Resolving Model Simulation and Mosaic Treatment of Subgrid Cloud-Radiation Interaction X. Wu Department of Geological and Atmospheric Sciences Iowa State University Ames, Iowa X.-Z. Liang Illinois

More information

Usama Anber 1, Shuguang Wang 2, and Adam Sobel 1,2,3

Usama Anber 1, Shuguang Wang 2, and Adam Sobel 1,2,3 Response of Atmospheric Convection to Vertical Wind Shear: Cloud Resolving Simulations with Parameterized Large-Scale Circulation. Part I: Specified Radiative Cooling. Usama Anber 1, Shuguang Wang 2, and

More information

Proposals of Summer Placement Programme 2015

Proposals of Summer Placement Programme 2015 Proposals of Summer Placement Programme 2015 Division Project Title Job description Subject and year of study required A2 Impact of dual-polarization Doppler radar data on Mathematics or short-term related

More information