Comparing GEM Regional, GEM-LAM 2.5 and RUC Model Simulations of Mesoscale Features over Southern Ontario 2009 CMOS Congress 31 May – 4 June, Halifax,

Slides:



Advertisements
Similar presentations
Trends in Estimated Mixing Depth Daily Maximums R. L. Buckley, A. Dupont, R. J. Kurzeja, and M. J. Parker Atmospheric Technologies Group Savannah River.
Advertisements

JMA Takayuki MATSUMURA (Forecast Department, JMA) C Asia Air Survey co., ltd New Forecast Technologies for Disaster Prevention and Mitigation 1.
What’s quasi-equilibrium all about?
The University of Reading Helen Dacre AMS 2010 Air Quality Forecasting using a Numerical Weather Prediction Model ETEX Surface Measurement Sites.
The University of Reading Helen Dacre UM user 2009 Forecasting the transport of pollution using a NWP model ETEX Surface Measurement Sites.
1 00/XXXX © Crown copyright Carol Roadnight, Peter Clark Met Office, JCMM Halliwell Representing convection in convective scale NWP models : An idealised.
Chapter 13 – Weather Analysis and Forecasting
Climate and Weather Section 2.3, p.33.
The MSC Forecasters Forums and the Future Role of the Human Forecaster David Sills Cloud Physics and Severe Weather Research Section, Environment Canada,
Weather diary 31ST March-6 April hungary,Marcali.
Page 1 NAE 4DVAR Oct 2006 © Crown copyright 2006 Mark Naylor Data Assimilation, NWP NAE 4D-Var – Testing and Issues EWGLAM/SRNWP meeting Zurich 9 th -12.
LOWER YUBA RIVER ACCORD Monitoring and Evaluation Program Redd Surveys Casey Campos PSMFC.
The Effect of the Complex Coastline in the Houston Area John Nielsen-Gammon Texas A&M University.
Multi-Year Examination of Dense Fog at Burlington International Airport John M. Goff NOAA/NWS Burlington, VT.
GSA Northeastern Meeting March , 2013 Bretton Woods, NH A Comparison between Runoff Trends in a Headwater Basin and More Developed Watersheds: A.
EC Regional Air Quality Deterministic Prediction System (RAQDPS) Mike Moran Air Quality Research Division Environment Canada, Toronto, Ontario Mtg on AQ.
Development of Data Assimilation Systems for Short-Term Numerical Weather Prediction at JMA Tadashi Fujita (NPD JMA) Y. Honda, Y. Ikuta, J. Fukuda, Y.
Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
Slide: 1 Version 0.3, 20 January 2004 METEOSAT SECOND GENERATION (MSG) METEOROLOGICAL USE OF THE SEVIRI HIGH-RESOLUTION VISIBLE (HRV) CHANNEL Contact:Jochen.
Weekly Attendance by Class w/e 6 th September 2013.
Jess Charba Fred Samplatsky Phil Shafer Meteorological Development Laboratory National Weather Service, NOAA Updated September 06, 2013 LAMP Convection.
The Effects of Lake Michigan on Mature Mesoscale Convective Systems Nicholas D. Metz and Lance F. Bosart Department of Atmospheric and Environmental Sciences.
Jordan Bell NASA SPoRT Summer Intern  Background  Goals of Project  Methodology  Analysis of Land Surface Model Results  Severe weather case.
UNSTABLE The UNderstanding Severe Thunderstorms and Alberta Boundary Layers Experiment Neil Taylor 1, Dave Sills 2, John Hanesiak 3, Jason Milbrandt 4.
Recent performance statistics for AMPS real-time forecasts Kevin W. Manning – National Center for Atmospheric Research NCAR Earth System Laboratory Mesoscale.
METEOROLOGIST KISHAN SRIPADA TEMPERATE DECIDUOUS FOREST.
Mesonet Observations during the UNSTABLE 2008 Pilot David Sills 1, Neil Taylor 2, Craig Smith 3, Geoff Strong 4 and John Hanesiak 5 1 Cloud Physics and.
Surface parameters forecast in Vancouver and Whistler area - Verification of MC2v498 parallel runs Yan Shen University of British Columbia.
Rapid Update Cycle Model William Sachman and Steven Earle ESC452 - Spring 2006.
Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land.
SNOWIN’ TO BEAT THE BAND Using Satellite and Local Analysis and Prediction System Output to Diagnose the Rapid Development of a Mesoscale Snow Band Eleanor.
FORECASTING EASTERN US WINTER STORMS Are We Getting Better and Why? Jeff S. Waldstreicher NOAA/NWS Eastern Region Scientific Services Division – Bohemia,
1 st UNSTABLE Science Workshop April 2007 Science Question 3: Science Question 3: Numerical Weather Prediction Aspects of Forecasting Alberta Thunderstorms.
How might climate change affect heavy lake-effect snowstorms Kenneth Kunkel, Nancy Westcott, and David Kristovich Illinois State Water Survey Champaign,
Warm Season Thunderstorm Patterns Over the New Jersey Area Al Cope Paul Croft National Weather Service Kean University Mount Holly, NJ Union, NJ.
Mesoscale & Microscale Meteorological Division / ESSL / NCAR WRF (near) Real-Time High-Resolution Forecast Using Bluesky Wei Wang May 19, 2005 CISL User.
Jamie Wolff Jeff Beck, Laurie Carson, Michelle Harrold, Tracy Hertneky 15 April 2015 Assessment of two microphysics schemes in the NOAA Environmental Modeling.
Photo by Dave Fratello. Focus To evaluate CAM5/CARMA at 1x1 degree resolution with aircraft observations. - Improve cirrus cloud representation in the.
SAAWSO HIGH IMPACT WEATHER EVENTS Ismail Gultepe EC, Cloud Physics and Severe Weather Research Section Toronto, Ontario M3H 5T4, Canada.
The climate and climate variability of the wind power resource in the Great Lakes region of the United States Sharon Zhong 1 *, Xiuping Li 1, Xindi Bian.
Performance of the Experimental 4.5 km WRF-NMM Model During Recent Severe Weather Outbreaks Steven Weiss, John Kain, David Bright, Matthew Pyle, Zavisa.
2006(-07)TAMDAR aircraft impact experiments for RUC humidity, temperature and wind forecasts Stan Benjamin, Bill Moninger, Tracy Lorraine Smith, Brian.
Application of Numerical Weather Prediction Prognoses to Operational Weather Forecasting in Hong Kong Pre-CAS Technical Conference on "Environmental Prediction.
Comparing GEM 15 km, GEM-LAM 2.5 km and RUC 13 km Model Simulations of Mesoscale Features over Southern Ontario 2010 Great Lakes Op Met Workshop Toronto,
How Much Sunshine? Investigation 3 part 1
The Effect of Coastline Curvature and Sea Breeze Development on the Maximum Convergence Zone at Cape Canaveral, Florida By: Takashi Kida Meteorology Department.
AMS 22 nd Conference on Weather Analysis and Forecasting/18 th Conference on Numerical Weather Prediction – Park City, Utah 1 June 26, 2007 IMPACT.
Post processing on NWP output and nowcasting on the grid for feeding the forecast system in Canada Donald Talbot Chief of Meteorological System Section,
Update on the Northwest Regional Modeling System 2015 Cliff Mass and David Ovens University of Washington.
Oct. 28 th th SRNWP, Bad Orb H.-S. Bauer, V. Wulfmeyer and F. Vandenberghe Comparison of different data assimilation techniques for a convective.
Trials of a 1km Version of the Unified Model for Short Range Forecasting of Convective Events Humphrey Lean, Susan Ballard, Peter Clark, Mark Dixon, Zhihong.
10th COSMO General Meeting, Cracow, Poland Verification of COSMOGR Over Greece 10 th COSMO General Meeting Cracow, Poland.
National Weather Service Houston/Galveston Lance Wood Science and Operations Officer Assessing the Impact of MODIS SST Utilizing a local WRF.
Applied Meteorology Unit 1 Observation Denial and Performance of a Local Mesoscale Model Leela R. Watson William H. Bauman.
Implementation of Terrain Resolving Capability for The Variational Doppler Radar Analysis System (VDRAS) Tai, Sheng-Lun 1, Yu-Chieng Liou 1,3, Juanzhen.
Update on the Northwest Regional Modeling System 2013
Alan F. Srock and Lance F. Bosart
Overview of Deterministic Computer Models
Diurnal cycle of warm season precipitation in Hainan Island
Better Forecasting Bureau
Juanzhen Sun (RAL/MMM)
FORECASTING EASTERN US WINTER STORMS Are We Getting Better and Why?
Aviation Forecast Guidance from the RUC
Junhua Zhang and Wanmin Gong
New Developments in Aviation Forecast Guidance from the RUC
Neil Taylor Hydrometeorology and Arctic Lab
Rita Roberts and Jim Wilson National Center for Atmospheric Research
NWP Strategy of DWD after 2006 GF XY DWD Feb-19.
COAMPS Coupled Ocean Atmosphere Prediction System Developed by FNMOC and NRL (1996) Operational - MEL/FNMOC Experimental - NRL-MRY 27 km Spatial.
Presentation transcript:

Comparing GEM Regional, GEM-LAM 2.5 and RUC Model Simulations of Mesoscale Features over Southern Ontario 2009 CMOS Congress 31 May – 4 June, Halifax, NS David Sills, Norbert Driedger and Emma Hung Cloud Physics and Severe Weather Research Section, Environment Canada, Toronto, Canada

Introduction and Motivation Variety of NWP models used at the OSPC RSD for mesoscale analysis and nowcasting guidance: REG - regional version of ECs Global Environmental Multiscale (GEM) model with 15 km horizontal grid spacing, LAM - limited-area version of the GEM model with 2.5 km horizontal grid spacing, and RUC - the US Rapid Update Cycle (RUC) model with 13 km horizontal grid spacing LAMs higher resolution should provide more accurate solutions in regions of complex topography RUCs 1-hr data assimilation cycle should effectively nudge the model solution closer to reality

Methodology Focused on features with mesoscale detail over southern Ontario and surrounding areas: Early-season, late-season and summer lake breezes Winter land breezes with snow squalls Warm / cold fronts Low positions Others: prefrontal convergence, trofs, lake funnelling, etc. used 18 UTC data from June 2008 to May 2009 Model performance ranked (1 st, 2 nd, 3 rd ) based on subjective comparison of mesoscale features against observations (sfc winds, radar reflectivity, vis sat) Ties were always ranked as 2 (1-2-2, 2-2-3, 2-2-2)

232 mesoscale features were compared from 217 days Overall averaged rankings: LAM – 1.78 RUC – 1.94 REG – 2.19 LAM ranked higher than REG: 115 events or 49.5% RUC ranked higher than REG: 103 events or 44.4% 1s2s3s1s + 2s LAM RUC REG Results - Overall

Model rankings have clear monthly differences LAM model superior Aug-Oct and Feb-Mar, worse than REG Nov and Jan RUC model superior Nov-Jan and Apr-May, worse than REG Oct and Mar No month has REG the highest ranked model Results – By Month

Model ranking also has clear differences based on feature type LAM superior with early and late season lake breezes, worse than REG for winter land breezes RUC superior with low positions, worse than REG for early- and late- season lake breezes REG does well with winter land breezes Results – By Feature Type (N=25) (N=19) (N=32) (N=105) (N=21) (N=23)

Results – By Convection Is there a difference for summer convective environments? Very little change for convection vs. no convection Model rankings consistent as well Summer – All Events Summer - Convection Summer – No Convection LAM RUC REG

Case Study – Low on 6 Apr 09

Late Season Lake Breezes - 15 Oct 09

Winter Land Breezes - 16 Jan 09

Conclusions Overall, the mesoscale features generated by the LAM and the RUC were closer to observations than the REG, with LAM having the highest averaged ranking There were clear monthly differences in model rankings, as well in differences due to feature type

Conclusions Contd The LAM and RUC ranked about the same for summer lake breezes and warm/cold fronts The LAM ranked first for early- and late- season lake breezes, while RUC ranked first for low positions LAM ranked last for winter land breezes, while RUC ranked last for early- and late- season lake breezes

There appeared to be little difference between events with convection and events without convection This is a preliminary investigation – a more objective approach and larger sample sizes are needed Would a high-resolution LAM with an hourly data assimilation cycle produce even better results? Conclusions Contd

Thank you!