Keith A. Brewster1 Jerry Brotzge1, Kevin W

Slides:



Advertisements
Similar presentations
Chapter 13 – Weather Analysis and Forecasting
Advertisements

Keith Brewster Radar Assimilation Workshop National Weather Center 18-Oct-2011.
Object Based Cluster-Analysis and Verification of a Convection-Allowing Ensemble during the 2009 NOAA Hazardous Weather Testbed Spring Experiment Aaron.
WRF Modeling System V2.0 Overview
WP2 : Fine-scale rainfall data acquisition and prediction : Objective: develop and implement a system for estimation and forecasting of fine-scale (100m,
Calibration of GOES-R ABI cloud products and TRMM/GPM observations to ground-based radar rainfall estimates for the MRMS system – Status and future plans.
Toward Improving Representation of Model Microphysics Errors in a Convection-Allowing Ensemble: Evaluation and Diagnosis of mixed- Microphysics and Perturbed.
A short term rainfall prediction algorithm Nazario D. Ramirez and Joan Manuel Castro University of Puerto Rico NOAA Collaborator: Robert J. Kuligowski.
Colorado State University
An Efficient Ensemble Data Assimilation Approach and Tests with Doppler Radar Data Jidong Gao Ming Xue Center for Analysis and Prediction of Storms, University.
ASSIMILATION of RADAR DATA at CONVECTIVE SCALES with the EnKF: PERFECT-MODEL EXPERIMENTS USING WRF / DART Altuğ Aksoy National Center for Atmospheric Research.
Weather Model Background ● The WRF (Weather Research and Forecasting) model had been developed by various research and governmental agencies became the.
Roll or Arcus Cloud Squall Lines.
Chapter 13 – Weather Analysis and Forecasting. The National Weather Service The National Weather Service (NWS) is responsible for forecasts several times.
CASA – Collaborative Adaptive Sensing of the Atmosphere NWRT/PAR – National Weather Radar Testbed / Phased Array Radar Kurt D. Hondl DOC/NOAA/OAR National.
Linked Environments for Atmospheric Discovery (LEAD): Web Services for Meteorological Research and Education.
Mesoscale & Microscale Meteorological Division / ESSL / NCAR WRF (near) Real-Time High-Resolution Forecast Using Bluesky Wei Wang May 19, 2005 CISL User.
Roll or Arcus Cloud Supercell Thunderstorms.
The National Severe Storms Laboratory Jeff Kimpel, Director NSSL NOAA Science Advisory Board Norman, Oklahoma November 5, 2002.
March 14, 2006Intl FFF Workshop, Costa Rica Weather Decision Technologies, Inc. Hydro-Meteorological Decision Support System Bill Conway, Vice President.
Warn-on-Forecast Capabilities and Possible Contributions by CAPS By Ming Xue Center for Analysis and Prediction of Storms and School of Meteorology University.
Applied Meteorology Unit 1 An Operational Configuration of the ARPS Data Analysis System to Initialize WRF in the NWS Environmental Modeling System 31.
Toward a 4D Cube of the Atmosphere via Data Assimilation Kelvin Droegemeier University of Oklahoma 13 August 2009.
L inked E nvironments for A tmospheric D iscovery leadproject.org Using the LEAD Portal for Customized Weather Forecasts on the TeraGrid Keith Brewster.
LAPS __________________________________________ Analysis and nowcasting system for Finland/Scandinavia Finnish Meteorological Institute Erik Gregow.
OUTLINE Current state of Ensemble MOS
Numerical Prediction of High-Impact Local Weather: How Good Can It Get? Kelvin K. Droegemeier Regents’ Professor of Meteorology Vice President for Research.
Kelvin K. Droegemeier and Yunheng Wang Center for Analysis and Prediction of Storms and School of Meteorology University of Oklahoma 19 th Conference on.
Outline Background Highlights of NCAR’s R&D efforts A proposed 5-year plan for CWB Final remarks.
WSN05 6 Sep 2005 Toulouse, France Efficient Assimilation of Radar Data at High Resolution for Short-Range Numerical Weather Prediction Keith Brewster,
Precipitation Verification of CAPS Real- time Forecasts During IHOP 2002 Ming Xue 1,2 and Jinzhong Min 1 Other contributors: Keith Brewster 1 Dan Weber.
NOAA Hazardous Weather Test Bed (SPC, OUN, NSSL) Objectives – Advance the science of weather forecasting and prediction of severe convective weather –
TWO-YEAR ASSESSMENT OF NOWCASTING PERFORMANCE IN THE CASA SYSTEM Evan Ruzanski 1, V. Chandrasekar 2, and Delbert Willie 2 1 Vaisala, Inc., Louisville,
MMET Team Michelle Harrold Tracy Hertneky Jamie Wolff Demonstrating the utility of the Mesoscale Model Evaluation Testbed (MMET)
Travis Smith Hazardous Weather Forecasts & Warnings Nowcasting Applications.
Norman Weather Forecast Office Gabe Garfield 2/23/11.
Applied Meteorology Unit 1 High Resolution Analysis Products to Support Severe Weather and Cloud-to-Ground Lightning Threat Assessments over Florida 31.
Numerical Simulation and Prediction of Supercell Tornadoes Ming Xue School of Meteorology and Center for Analysis and Prediction of Storms University of.
Prediction Thrust Activities in CASA Briefing for WNI Dr. Ming Xue Director of CAPS Center for Analysis and Prediction of Storms August 2, 2006.
Challenges in PBL and Innovative Sensing Techniques Walter Bach Army Research Office
The Performance of a Weather-Adaptive 3DVAR System for Convective-scale RUA and some suggestions for future GSI-based RUA Jidong Gao NOAA/National Severe.
Eye-tracking during the Forecaster Warning Decision Process: A Pilot Experiment Katie Bowden OU CIMMS/School of Meteorology, Ph.D. Student Pam Heinselman.
11 Short-Range QPF for Flash Flood Prediction and Small Basin Forecasts Prediction Forecasts David Kitzmiller, Yu Zhang, Wanru Wu, Shaorong Wu, Feng Ding.
High Resolution Assimilation of Radar Data for Thunderstorm Forecasting on OSCER Keith A. Brewster, Kevin W. Thomas, Jerry Brotzge, Yunheng Wang, Dan Weber.
Travis Smith U. Of Oklahoma & National Severe Storms Laboratory Severe Convection and Climate Workshop 14 Mar 2013 The Multi-Year Reanalysis of Remotely.
Multi-scale Analysis and Prediction of the 8 May 2003 Oklahoma City Tornadic Supercell Storm Assimilating Radar and Surface Network Data using EnKF Ting.
Encast Global forecasting.
60 min Nowcasts 60 min Verification Cold Front Regime
CAPS Radar QC and Remapping
Progress in development of HARMONIE 3D-Var and 4D-Var Contributions from Magnus Lindskog, Roger Randriamampianina, Ulf Andrae, Ole Vignes, Carlos Geijo,
Tuning an Analysis and Incremental Analysis Updating (IAU) Assimilation for an Efficient High Resolution Forecast System Keith A. Brewster1
A few examples of heavy precipitation forecast Ming Xue Director
Tuning an Analysis and Incremental Analysis Updating (IAU) Assimilation for an Efficient High Resolution Forecast System Keith A. Brewster1
Rapid Update Cycle-RUC
Tadashi Fujita (NPD JMA)
CAPS is one of the first 11 NSF Science and Technology (S&T) Centers
Radar Observation of Severe Weather
Center for Analysis and Prediction of Storms (CAPS) Briefing by Ming Xue, Director CAPS is one of the 1st NSF Science and Technology Centers established.
Analysis and Prediction Thrust - IP1 Report
Juanzhen Sun (RAL/MMM)
Be The Weather Guy Presented to UCALL on October 14, 2009
CAPS Mission Statement
Winter storm forecast at 1-12 h range
Update on the Northwest Regional Modeling System 2017
CAPS Real-time Storm-Scale EnKF Data Assimilation and Forecasts for the NOAA Hazardous Weather Testbed Spring Forecasting Experiments: Towards the Goal.
A Real-Time Learning Technique to Predict Cloud-To-Ground Lightning
WMO NWP Wokshop: Blending Breakout
Collaborative Adaptive Sensing of the Atmosphere (CASA WX)
Science of Rainstorms with applications to Flood Forecasting
MOGREPS developments and TIGGE
Presentation transcript:

Nowcasting and Short-term Forecasting of Thunderstorms and Severe Weather Using OSCER Keith A. Brewster1 Jerry Brotzge1, Kevin W. Thomas1, Jidong Gao1, Ming Xue1,2 and Yunheng Wang1 1Center for Analysis and Prediction of Storms 2School of Meteorology University of Oklahoma Oklahoma Supercomputing Symposium October 12, 2011

CASA & NEXRAD Radars CASA NetRad NSF ERC: Collaborative Adaptive Sensing of the Atmosphere X-Band Dual-Pol Radars 40 km nominal range Collaborative, Adaptive Scanning Fill-in below coverage of NEXRAD Toward phased-array panels – low-cost! NEXRAD S-Band Radars 14 covering domain Data used out to 230 km

CASA NetRad Network Southwest Oklahoma

Spring 2007-2009 Near-Real Time Forecast Domain Dx = 1 km 53 Levels 600x540 Radars Used: 4 CASA 14 NEXRAD Plus Satellite & Surface Data 540 km 600 km

CASA Forecasting Workflow Observations CAPS Ingest Cluster Linux Server Observation Pre-Processing Radar Data File Selection Mesonet & Sfc Obs Processing Input File Generation Operational Forecast Model Data CAPS Ingest Cluster OSCER Sooner Supercomputer Analysis & Data Assimilation Graphics on WW Web Radar Data QC and Remapping 3DVAR Analysis ARPS Forecast Model Model Interpolation CYCLE OSCER Sooner Supercomputer Run Forecast Model PSC Mass Store & CAPS Linux Cluster 3D Data File Archive ARPS Forecast Model Graphics Generation

Improving the MPI Efficiency of Radar Remapper Radar data are converted from 3-D polar to 3-D Cartesian coordinates. Original Strategy: Horizontal Domain Decomposition Each processor finds solution on columns within its domain nproc_y=5 nproc_x=5 Potentially uneven workload

Improving the MPI Efficiency of Radar Remapper Radar data are converted from polar to Cartesian coordinates of model grid. Improved Algorithm For each radar Within domain decomposition, determine columns having valid data Collect columns with valid data in 1-D array Distribute work for these columns uniformly among processors Execute remapping algorithm MPI Distribute results to original home processor for output. nproc_y=5 nproc_x=5

Real-Time NWP Runs 2009 9 Weeks in Spring Season 6-hour 1-km resolution forecasts Use Radar Reflectivity & Radial Velocity 3DVAR wind with ADAS cloud analysis ARPS Model Runs posted to Web in real-time http://www.caps.ou.edu/wx/casa/ Run on Parallel Linux Boxes OU OSCER 600 processors/2 runs at a time Total Run Time 1.5 hours Two Runs in Near Real-time CASA & NEXRAD No CASA Data

2007-2009 Assimilation Strategy 40-min Assimilation 5.5-hour Forecast IAU IAU IAU IAU 0150 0200 0210 0220 0230 03 04 05 06 07 08 Manual on-demand model start-up for storms in the network.

Assimilation vs. Analysis Wind Speed/Vectors 500m AGL 0220 UTC Chickasha Radar Analysis Only Forecast/Assimilation

Forecast temperature perturbation + Vort. at z =500m AGL End of Data Assimilation Period 0220 UTC 0230 UTC Movie 0240 UTC 0250 UTC

2010 Nowcast Strategy 2125 2130 2200 IAU 2230 2300 2-hour Forecast 5-min Assim 2330 Domain size: 350 x 320 x 53. Total Run Time < 10 min 800 cores (100 dual-quad-core servers) Forecast model run every 10-min whenever the radars were operating (during precipitation).

Sample: 10 May 2010 21:40 From NWS Norman

T=05 min (assimilated state) 2140 2140 UTC Nowcast/Forecast T=05 min (assimilated state) 2140

2140 UTC Nowcast/Forecast T=15 min 2150

2140 UTC Nowcast/Forecast T=25 min 2200

2140 UTC Nowcast/Forecast T=35 min 2210

2140 UTC Nowcast/Forecast T=45 min 2220

2140 UTC Nowcast/Forecast T=55 min 2230

Data Assimilation Accomplishments Developed a very efficient real-time data assimilation, nowcasting and forecasting system Demonstrated initial impacts of CASA data on cloud-scale analysis and forecasting Advanced real-time storm-scale assimilation to where we can directly compare forecasted small-scale vorticity features to radar signatures Major step towards “warn on forecast”

Ongoing Work Using CASA Data Objective Verification of recent forecasts, to also include object-based methods. Rainfall (using QPE field from NSSL) Vorticity Centers Methods to improve data assimilation Improvements to current algorithms More sophisticated, but expensive, algorithms Acknowledgments: NSF Sponsors CASA ERC Computing: OU OSCER

In 2012 moving the radars to the Dallas/Ft Worth Metro Metro Area - This is the recommend placement of the first four sites. Late winter 2012 – First 4 radars Summer 2012 – next 2 radars Fall 2012 – Next radar Winter – 2013 CSU The sites include UNT and UTA buildings, which have the best connectivity so far from all proposed sites and the FAA building, which is presumed to have good network access too. Covers the metroplex with very high resolution data, Covers the gap above the NEXRAD radar in Fort Worth. The north south orientation will capture storms coming from the northwest and into the metroplex, while the existing NEXRAD can give warning for storms coming from the southwest. Provides unprecdented low level coverage of the trinity river for flooding, and accurate precipitation estimates. Also provide coverage of rivers, lakes to the north which impacts precipitation estimates. Very fast updates (1 Min) for rapidly evolving severe weather in the Metroplex. Disadvantages: CASA will provide very low coverage, but some coverage provided by NEXRAD. This system will focus more on real time data vs. forecasts. Which airports are we covering in addition to DFW and Love Field. In 2012 moving the radars to the Dallas/Ft Worth Metro

More radars will be added during the year. Northeast Expansion - This configuration continues coverage over highly populated areas and gets into areas where there is more of a radar gap. More radars will be added during the year.