using wrf output in the integrated data viewer (idv)•uses gempak to select roi •wrf-nmm run over...

1010thth Annual WRF User Annual WRF User’’s Workshops Workshop

Using WRF output in theUsing WRF output in theIntegrated Data Viewer (IDV)Integrated Data Viewer (IDV)

Don Murray and Jeff McWhirterDon Murray and Jeff McWhirterUnidata Program Center/UCARUnidata Program Center/UCAR

Boulder, COBoulder, CO

10th Annual WRF User10th Annual WRF User’’s Workshops Workshop

OutlineOutline

• What is the IDV?– IDV features

• WRF data to IDV• IDV, Unidata, WRF• Case study

– December 20, 2006 Denver Snowstorm


What is the IDV?What is the IDV?• Visualization and analysis tool

for geoscience data developedand supported by Unidata

• Freely available Java™framework and application

• Integrated 2D/3D displays of awide range of data

• Built on VisAD library


IDV StrengthsIDV Strengths• Easy to download and install

on any platform• Remote and local access to

datasets• 2D/3D visualization• Bundle mechanism• Support for multi-disciplinary

datasets integrated from avariety of sources

• Flexible framework supportscustomization (GEON-IDV,field projects, McIDAS-V)

• Extensive documentation– User’s Guide– Tutorial

• Community drivendevelopment

Model simulation of wind, isentropicModel simulation of wind, isentropicpotential vorticity and low level moisturepotential vorticity and low level moistureflow over the Great Salt Lake basinflow over the Great Salt Lake basin


• Sample of Supported Formats:– netCDF– GRIB– Vis5D– KML– CSV– GEMPAK grid– ADDE

• Access Methods:– Local files– HTTP– ADDE, TDS and OPeNDAP servers– WMS

Supported Data SourcesSupported Data Sources• Data Types:

– Gridded model output– Satellite imagery– Radar data– Point observations– Balloon soundings– NOAA Profiler Network winds– Aircraft Tracks– Fronts– GIS data (WMS, shapefile)– Quick Time movies– Web Cams

• Vertical Coordinates– Pressure– Height/Depth– Other (2D only)

ADDE = Abstract Data Distribution EnvironmentTDS (THREDDS) = Thematic Realtime Environmental Distributed Data Services


Commonly Used DisplaysCommonly Used Displays• Contours• Flow vectors• Vertical Cross Sections• Isosurfaces• Volume Rendering• Charts• Data probes• Non-lat/lon projections• Multiple views (e.g. Plan and cross section)• Subsurface (mantle, ocean)


Analysis CapabilitiesAnalysis Capabilities

• Interactive probes for dataset exploration– Parameter readouts– Vertical profiles– Cross sections– Time/Height displays

• System and user defined diagnostics• Jython for more complicated analysis• Jython Shell for interactive use


IDV Product GenerationIDV Product Generation

IDV supports interactive and script basedgeneration of:

• Images (GIF, JPEG, PNG)• Vector graphics (PDF, PostScript, SVG)• Animation – Quicktime, animated GIF, etc.• Google Earth KML/KMZ


WRF Output into IDVWRF Output into IDV

• Several routes for wrfout data:– Raw netCDF for quick look plots (no derived

quantities)– Recommend using post processing to

destagger and derive standard quantities• WRFpost -> GRIB• wrf2gem -> GEMPAK• ARWpost -> Vis5D• wrf_to_cf -> CF compliant netCDF


Performance TuningPerformance Tuning

• Spatial/Temporal subsetting• Disk Caching• Memory tuning• Multicore support• See User’s Guide page on the subject


IDV, Unidata and WRFIDV, Unidata and WRF

• IDV used in a variety of contexts to viewWRF output in Unidata community– Field Projects (e.g. CUPIDO)– Graduate Research Projects– LEAD– Region of Interest (ROI)


CuPIDOCuPIDO ObsObs with WRF Simulation with WRF Simulation

Data source: Bart Geerts, U. Wyoming

1010thth Annual WRF User Annual WRF User’’s Workshops Workshop

MCS motion: The role of verticalMCS motion: The role of verticalmomentum transportmomentum transport

Kelly Mahoney and Gary LackmannKelly Mahoney and Gary LackmannDepartment of Marine, Earth, and Atmospheric SciencesDepartment of Marine, Earth, and Atmospheric Sciences

North Carolina State UniversityNorth Carolina State University

June 3, 2009June 3, 200923rd Conference on Weather Analysis and Forecasting/23rd Conference on Weather Analysis and Forecasting/

19th Conference on Numerical Weather Prediction19th Conference on Numerical Weather Prediction

Model simulated radar reflectivity Reflectivity, pressure perturbation, 850-mb streamlines


F09 Momentum Budget Terms: Volume- leading

-15 -10 -5 0 5 10 15 20

F09 Momentum Budget Terms: Volume - trailing

-15 -10 -5 0 5 10 15 20

Momentum Budget: ResultsMomentum Budget: Results

• Front, rear driven by differentprocesses:– Front: Vertical advection of u’– Middle-rear: Vertical advection ofū, pressure gradient force

• Note: contributions evolve in time

Positive terms =accelerating westerlies

Divided an eastward-moving chunkof the MCS into two volumes:

Verticaladvection of u’

Verticaladvection of ū

Pressure gradientacceleration

Simulated radar reflectivity, Volumes 1 and 2

12Tendency (ms-1h-1)

Tendency (ms-1h-1)

Verticaladvection of u'

Horizontaladvection

Horizontaladvection

Verticaladvection of ū

Pressure gradientacceleration


Sponsored by the National Science Foundation

Revolutionizing the ability of scientists, students, and operational practitioners toobserve, analyze, predict, understand, and respond to intense local weather by

interacting with it dynamically and adaptively in real time


IDV in LEADIDV in LEAD

• LEAD Visualization Tool:– WRF output from LEAD

workflow simulations– Initial and boundary

conditions for workflow– Compare results to

observations• LEAD-To-LEARN

modules:– Bundles associated with

on-line modules– Support inquiry based

learning


LEAD-to-LEARN:An instructional pathway for meteorology education using a science

gateway

Source: Rich Clark & Sepi Yalda, Millersville University

Undergraduate Meteorology students at Millersville University, working with computer science students atthe National Center for Supercomputing Applications, under the supervision of LEAD project scientists andtechnical support personnel, developed a suite of learning modules for education; primarily for use asclassroom supplements in undergraduate meteorology courses ranging from introductory survey courses tosenior-level mathematically intensive courses. The modules are in the process of a major revision that willintegrate scaffold instructional approaches so that students can follow a tiered, sequential pathway leadingto self-discovery of key features and field variables that are relevant to a particular weather phenomenon.These new instructional approaches are described in the following sequence of slides.


Region of Interest Region of Interest –– GEMPAK/WRF GEMPAK/WRF

• Real-time RegionalModel ROI

• Uses GEMPAK toselect ROI

• WRF-NMM run overROI

• Archive on LEADTestbed at Unidata NMM forecast for objectively

selected ROI


Case StudyCase StudyDenver Blizzard Denver Blizzard –– Dec 20, 2006 Dec 20, 2006

• Hosted on Unidata’s RAMADDA server– Kind of a You-Tube for geoscience data– Allows storing of data and ancillary materials

• http://motherlode.ucar.edu/repository– Case Studies

• December 20, 2006 Colorado Snowstorm

• Accessible remotely in IDV– WRF ARW output, Level II Radar, IR and WV

imagery, surface observations


Download IDVDownload IDV

• Go to:http://www.unidata.ucar.edu/downloads/idv

• Register to download software• Download the version for your system• Run the installer


ExercisesExercises

• Explore the UI• Load in Dataset

– Explore Field Selector• Grid displays

– Topography– Vectors over topography– RH isosurface– Probes

• Time/Height• SkewT

– Volume Rendering


ExercisesExercises

• Precip display– Time step difference

• Formulas/Jython• Saving products• Adding other data

– IR imagery– Surface data


For Further InformationFor Further Information

• Integrated Data Viewer homepage– http://www.unidata.ucar.edu/software/idv

• RAMADDA homepage– http://www.unidata.ucar.edu/software/ramadda/

• VisAD homepage– http://www.ssec.wisc.edu/~billh/visad.html

• All IDV questions/comments– [email protected]

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