ENVISIONING RGBA CAPABILITIES IN AWIPS II AND INITIAL SUCCESSES Jordan Gerth, Research Assistant Cooperative Institute for Meteorological Satellite Studies.

Slides:



Advertisements
Similar presentations
SPoRT Products in Support of the GOES-R Proving Ground and NWS Forecast Operations Andrew Molthan NASA Short-term Prediction Research and Transition (SPoRT)
Advertisements

How AWIPS II will bring GOES-R Capabilities and Science to the Field, both Pre- and Post-Launch Jordan Gerth, Research Assistant Cooperative Institute.
Deirdre Kann National Weather Service WFO Albuquerque Deirdre Kann National Weather Service WFO Albuquerque 7 th GOES User’s Conference October 21, 2011.
24 bit GeoColor Product CIRA GOES and JPSS RGB Product Development Updates for AWIPS II D2D and NCP Debra A. Molenar 1, Scott P. Longmore 2 IntroductionArtifacts.
Transitioning unique NASA data and research technologies to operations GOES-R Proving Ground Activities at the NASA Short-term Prediction Research and.
Application of Multispectral Data to Space Shuttle Landing Operations Doris Hood, Tim Garner, Timothy Oram NWS/ Spaceflight Meteorology Group STS-120 Launch.
1 GOES Users’ Conference October 1, 2002 GOES Users’ Conference October 1, 2002 John (Jack) J. Kelly, Jr. National Weather Service Infusion of Satellite.
Transitioning unique NASA data and research technologies to operations Relevant OCONUS Products Gary Jedlovec NASA / MSFC, Earth Science Office
Hayden Oswald 1 and Andrew Molthan 2 NASA Summer Intern, University of Missouri, Columbia, Missouri 1 NASA SPoRT Center, NASA/MSFC, Huntsville, Alabama.
Green Vegetation Fraction (GVF) derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor onboard the SNPP satellite Zhangyan Jiang 1,2,
First Bytes - LabVIEW. Today’s Session Introduction to LabVIEW Colors and computers Lab to create a color picker Lab to manipulate an image Visual ProgrammingImage.
Transitioning unique data and research technologies to operations Experimental Products Development Team (EPDT) Jason Burks NASA SPoRT.
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.
GOES-R Synthetic Imagery over Alaska Dan Lindsey NOAA/NESDIS, SaTellite Applications and Research (STAR) Regional And Mesoscale Meteorology Branch (RAMMB)
Synthetic Satellite Imagery: A New Tool for GOES-R User Readiness and Cloud Forecast Visualization Dan Lindsey NOAA/NESDIS, SaTellite Applications and.
Computer Systems Nat 4.5 Computing Science Data Representation Lesson 4: Storing Graphics EXTENSION.
1. Outline RAMMB/CIRA Overview RAMMB/CIRA real-time product development & deployment environment GOES-R Proving Ground AWIPS II Overview AWIPS II Configuration.
Charleston, SC Weather Forecast Office Frank Alsheimer Science and Operations Officer NWS Charleston, SC.
AWIPS-II Data Delivery Project Overview December 2013.
GOES Users’ Conference III May 10-13, 2004 Broomfield, CO Prepared by Integrated Work Strategies, LLC GOES USERS’ CONFERENCE III: Discussion Highlights.
Poster 1.66 An Update on CIRA’s GOES-R Proving Ground Activities Ed Szoke 1,2, Renate Brummer 1, Hiro Gosden 1, Steve Miller 1, Mark DeMaria 3, Dan Lindsey.
NOAA Satellite Proving Ground/User Readiness Meeting
1 CIMSS Participation in the Development of a GOES-R Proving Ground Timothy J. Schmit NOAA/NESDIS/Satellite Applications and Research Advanced Satellite.
AWIPS Tracking Point Meteogram Tool Ken Sperow 1,2, Mamoudou Ba 1, and Chris Darden 3 1 NOAA/NWS, Office of Science and Technology, Meteorological Development.
 Jordan Gerth 1 Cooperative Institute for Meteorological Satellite Studies.
Digital Media Exam Review SM1001 Digital Media, Semester A, 2011 School of Creative Media © Week 13, 2011.
GOES-R ABI Synthetic Imagery at 3.9 and 2.25 µm 24Feb2015 Poster 2 Louie Grasso, Yoo-Jeong Noh CIRA/Colorado State University, Fort Collins, CO
The NASA Short-term Prediction Research and Transition (SPoRT) Center GOES-R Proving Ground Update 9 July, 2012 Contributions from: Gary Jedlovec, Kevin.
Weather Forecasting Chapter 9 Dr. Craig Clements SJSU Met 10.
RGB Activities for the GOES-R Proving Ground Gary Jedlovec, NASA / MSFC / SPoRT Mark DeMaria NOAA / NESDIS / STAR Tim Schmit NOAA / NESDIS / CIMSS and.
Briefing Tool Update Herb Grote ESRL/GSD/ISB Boulder, CO June 13, 2006.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Infrared Temperature and.
GEON2 and OpenEarth Framework (OEF) Bradley Wallet School of Geology and Geophysics, University of Oklahoma
Near-Real-Time Simulated ABI Imagery for User Readiness, Retrieval Algorithm Evaluation and Model Verification Tom Greenwald, Brad Pierce*, Jason Otkin,
January 7, 2015 Walter Wolf, Jaime Daniels, and Lihang Zhou NOAA/NESDIS, Center for Satellite Applications and Research (STAR) Shanna Sampson, Tom King,
GOES-R Recommendations from past GOES Users’ Conference: Jim Gurka Tim Schmit Tom Renkevens NOAA/ NESDIS Tony Mostek NOAA/ NWS Dick Reynolds Short and.
High impact weather studies with advanced IR sounder data Jun Li Cooperative Institute for Meteorological Satellite Studies (CIMSS),
CIMSS AWIPS II Activities Jordan Gerth, Research Assistant Cooperative Institute for Meteorological Satellite Studies University of Wisconsin, Madison.
Transitioning research data to the operational weather community Overview of GOES-R Proving Ground Activities at the Short-term Prediction Research and.
Modeling GOES-R µm brightness temperature differences above cold thunderstorm tops Introduction As the time for the launch of GOES-R approaches,
CIRA / SPoRT Update 10/31/12 1 Update: “A Multisensor 4-D Blended Water Vapor Product for Weather Forecasting” Stan Kidder John Forsythe Andy Jones.
Distributed Data Analysis & Dissemination System (D-DADS ) Special Interest Group on Data Integration June 2000.
Hands-on exercise showcasing ABI’s 16 channels with improved spatial resolution and temporal refresh rate (plus Weighting Functions and RGB ABI examples)
Layered Water Vapor Quick Guide by NASA / SPoRT and CIRA Why is the Layered Water Vapor Product important? Water vapor is essential for creating clouds,
Transitioning unique NASA data and research technologies to operations SPoRT AWIPS II Activities Sixth Meeting of the Science Advisory Committee 28 February.
AIRS/AMSU-A/HSB Data Subsetting and Visualization Services at GES DAAC Sunmi Cho, Jason Li, Donglian Sun, Jianchun Qin and Carrie Phelps, Code 902, NASA.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Nearcasting Severe Convection.
McIDAS-X Software Development and Demonstration Dave Santek and Jay Heinzelman 2 June 2009 PDA Animated Weather (PAW) Status by Russ Dengel.
GFE in RFCs Tom LeFebvre ESRL/Global Systems Division.
High impact weather nowcasting and short-range forecasting using advanced IR soundings Jun Li Cooperative Institute for Meteorological.
PRELIMINARY VALIDATION OF IAPP MOISTURE RETRIEVALS USING DOE ARM MEASUREMENTS Wayne Feltz, Thomas Achtor, Jun Li and Harold Woolf Cooperative Institute.
GOES-R ABI AS A WARNING AID Louie Grasso, Renate Brummer, and Robert DeMaria CIRA, Fort Collins, CO Dan Lindsey, Don Hillger, NOAA/NESDIS/RAMMB, Fort Collins,
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Combining GOES Observations with Other Data to Improve Severe Weather Forecasts.
Japan Meteorological Agency, May 2014 Coordination Group for Meteorological Satellites - CGMS Volcanic ash algorithm testbed by JMA for validation and.
NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS LIMB CORRECTION OF POLAR- ORBITING IMAGERY FOR THE IMPROVED INTERPRETATION.
NcBrowse: A Graphical netCDF File Browser Donald Denbo NOAA-PMEL/UW-JISAO
A. FY12-13 GIMPAP Project Proposal Title Page version 26 October 2011 Title: WRF Cloud and Moisture Verification with GOES Status: New GOES Utilization.
Digital Media Exam Review SM1001 Digital Media, Semester A, 2009 School of Creative Media © Week 13, 2010.
Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Spectral response functions (SRF) for the ABI IR bands (blue curves with band numbers.
Satellite Altimetry use in Marine Forecasting at NOAA Joe Sienkiewicz NOAA / National Weather Service weather.gov Ocean Prediction Center
Jordan J. Gerth Assistant Researcher, Liaison to NWS Pacific Region Cooperative Institute for Meteorological Satellite Studies University of Wisconsin.
Hands-on exercise showcasing ABI’s 16 channels with improved spatial resolution and temporal refresh rate (plus RGB ABI examples) Mat Gunshor1, Tim.
GOES-R ABI and Himawari-8 AHI Training using SIFT
GOES-R ABI and Himawari-8 AHI Training using SIFT
USING GOES-R TO HELP MONITOR UPPER LEVEL SO2
Preparation for use of the GOES-R Advanced Baseline Imager (ABI)
ABI Visible/Near-IR Bands
McIDAS-X Software Development and Demonstration
Generation of Simulated GIFTS Datasets
Front page of the realtime GOES-12 site, showing all of the latest Sounder spectral bands (18 infrared and 1 visible) over the central and Eastern US All.
Presentation transcript:

ENVISIONING RGBA CAPABILITIES IN AWIPS II AND INITIAL SUCCESSES Jordan Gerth, Research Assistant Cooperative Institute for Meteorological Satellite Studies University of Wisconsin, Madison 4 May 2012 NOAA Satellite Science Week

RGB/RGBA Image Compositing It is necessary to integrate and support a flexible bit depth data format and user-driven three-way or four-way (with an alpha channel) image blending functionality into the AWIPS II software. Maximizes the use of current and future satellite imagery and products, as well as leverages a red-green-blue-alpha (RGBA) capability in pre-release versions of the migrated software The implementation of a data format and display system allowing for bit depths greater than the current specification has numerous applications useful to operational weather analysis and forecasting beyond current capabilities and techniques. To support data fusion, image differences, individual bands, and other band manipulations can be assigned to a color in the RGB triplet.

Simulated ABI Longwave Bands Bands 8 through 16 are produced from the National Severe Storms Laboratory (NSSL) Weather Research and Forecast (WRF) model output. CompactOPTRAN computes optical depths at each model layer based on temperature and water vapor mixing ratio. 36-hour simulation at 4 km spatial resolution is started once per day at 00 UTC, with imagery available by 12 UTC. Currently limited distribution in AWIPS and N-AWIPS to select NWS forecast offices and National Centers. Output available online at with imagery athttp://

Adding Imagery to AWIPS II netCDF3 plug-in (NWS/CIMSS) Primary development by Tom Kretz Accepts netCDF3 files used with AWIPS I (with modification to global attributes), places them in the data store, and accessible using the Raytheon satellite viz plug-in The ultimate SOA solution Beta release of plug-in available, official release this summer Data array confined to 8 bits McIDAS plug-in (NWS/Raytheon) Stores single band files with a re-projected data array NPP/VIIRS plug-in (Raytheon) Code released recently, NWS plans to disseminate some VIIRS imagery later this year Handles netCDF4 files

Simulated ABI Band 8 (6.19 µm) Weighting function for US Standard profile indicates sensitivity to upper tropospheric moisture

Simulated ABI Band 9 (6.95 µm) Weighting function for US Standard profile indicates sensitivity to upper middle tropospheric moisture

Simulated ABI Band 10 (7.34 µm) Weighting function for US Standard profile indicates sensitivity to lower middle tropospheric moisture

CIMSS Approach to RGBA Use satelliteImageryStyleRules.xml Configure display for individual bands, then layer multiple bands Advantages: Leverages the improved display capabilities of the software and service-oriented architecture RGBA composites can be locally controlled and developed Components are easily visualized and sampled individually Allows control over the minimum and maximum display values Additional bandwidth not required (composite created from bands already delivered on site; transmission of additional product not required) Graphics card facilitates layering, decreasing resources required on remainder of the system (both server and workstation)

Building an RGB: Band 8 – Band 10 Red with alpha gradient (upper–lower tropospheric moisture difference), white clouds with alpha gradient

Weighting function for US Standard profile indicates sensitivity to ozone Simulated ABI Band 12 (9.61 µm)

Building an RGB: Band 12 – Band 13 Green with alpha gradient (brighter high ozone concentration indicative of low potential vorticity surfaces)

Building an RGB: Band 8 Inverted Blue with alpha gradient (brighter blues indicate dryer upper tropospheric air, dry slot)

Building an RGB: Composite Composite shows an amplified weather pattern, synoptic dry slot, and differential tropospheric moisture

Potential AWIPS II Capabilities User interface for the multi-channel RGB color capability Implement with GPU Shader Language for quick display time, a strength of AWIPS II Updated user controls and color scheme selection New color table widget for developing color tables with more than 256 colors (current AWIPS I transmission format and software limitation) Product browser capability (Raytheon concept) Redesign the volume browser? Expanded, refined capability for derived parameters Python scripting easy for end users but not necessarily efficient use of resources for complex calculations User control of image differencing and scaling Permit operations in value space instead of data storage space

GOES-R and NPP Satellite Imagery New satellite true color visualization plug-in Slide credit: Frank Griffith

Summary and Recommendations Multiple ways to input satellite imagery into AWIPS II Software capabilities currently exist for primitive (but functional) defined-on-display AWIPS II RGBA capability Exploited and demonstrated at CIMSS Technical interchange meeting with Raytheon this summer revealed visualization strategy for interactive RGBA composites using graphics card Advantages and disadvantages of interactive user control should be considered What do RGBA composites reveal that are not immediately enhanced in individual bands? Exploit bit depth of satellite imagery in plug-ins Long-term goal should be unification of satellite components and data store to increase and entice manipulation and interrogation by end users Contact me: Jordan Gerth,