Visualizing the Natural Environment

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CIMSS Participation GOES-R Proving Ground
Wayne F. Feltz, Tim Schmit, Kaba Bah, Jordan
Gerth, Scott Bachmeier, Kathy Strabala, Gary
Wade, and Scott Lindstrom CIMSS Aviation
Applications Lead CIMSS AWG PM, CIMSS PG PM,
Co-Chair of Aviation AWG
UW-Madison
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CIMSS Proving Ground Overview

• Demonstration of GOES-R AWG applications at
  Local NWS Offices
• Demonstration of GOES-R AWG applications at
  National Center Testbeds
• AWIPS Weather Event Simulations
• Near real-time NWP simulated ABI radiances

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CIMSS Overview

• Algorithm Working Group
• Proving Ground Exercises
• First Light Decision Support Products

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Algorithm Research to Operations Process
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GOES-R AWG Application Teams

• Soundings (Tim Schmit)
• Winds (Jaime Daniels, Chris Velden)
• Clouds (Andy Heidinger)
• Aviation (Ken Pryor, Wayne Feltz)
• Aerosols / Air Quality / Atmospheric Chemistry
  (Shobha Kondragunta, Steve Ackerman/Chris
  Schmidt/Brad Pierce)
• Land Surface (Dan Tarpley, Chris Schmidt/Elaine
  Prins)
• Cryosphere (Jeff Key)
• Visualization and Imagery (Tim Schmit)
• SST and Ocean Dynamics (Alexander Ignatov)
• Radiation Budget (Istvan Lazslo)
• Lightning (Steve Goodman)
• Space Environment (Steven Hill)
• Hydrology (Robert Kuligowski)
• Proxy Data (Fuzhong Weng, Allen Huang/Tom
  Greenwald)
• Algorithm Integration (Walter Wolf, Ray
  Garcia/Graeme Martin)
• Cal/Val (Changyong Cao, Dave Tobin)

SSEC AWG Involvement in Yellow AWG Chair listed
first Local SSEC/CIMSS POC underlined/italics
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GOES-R AWG Aviation Team
AWG Aviation Team Chairs Ken Pryor, Wayne Feltz

• SO2
• Mike Pavolonis (Lead)
• Andrew Parker (Support)

• Visibility
• Brad Pierce (Lead)
• Wayne Feltz

• Aircraft Icing
• Bill Smith, Jr. (Lead)
• Stephanie Houser (Support)

• Turbulence
• Anthony Wimmers (Lead)
• Wayne Feltz

• Fog/Low Cloud
• Mike Pavolonis (Lead)
• Corey Calvert (Support)

• Volcanic ash
• Mike Pavolonis (Lead)
• Justin Sieglaff (Support)

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GOES-R- Baseline and Option 2 Products (by
inclusion into geocat)
In GEOCAT (from CIMSS)
No known plans for GEOCAT
Near-term plans for GEOCAT (from CIMSS)
GLM Product
No Current plans for GEOCAT (from CIMSS)
Of the 25 Baseline products, 15 are in GEOCAT
Revised 6/30/2009
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Proving Ground Goals

• Provide pre-launch satellite simulated and real
  proxy data and products to stakeholders
• Make data available with end-user decision
  support systems (AWIPS, N-AWIPS, AWIPS-2, Google
  Earth)
• Provide strength and weaknesses documentation
  along with training (in-field) collaborative
  feedback

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Local NWS Offices Demonstration
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CIMSS Satellite Proving Ground NOAAs
Cooperative Institute for Meteorological
Satellite Studies (CIMSS) is engaging in
activities that serve as a Satellite Proving
Ground for new satellite products that are not
yet operationally available in the National
Weather Service AWIPS environment.
AWIPS images of the MODIS visible channel, NDVI,
and LST product showing the Mississippi Alluvial
Valley on 12 May 2008.
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CIMSS Satellite Proving Ground NOAAs
Cooperative Institute for Meteorological
Satellite Studies (CIMSS) is engaging in
activities that serve as a Satellite Proving
Ground for new satellite products that are not
yet operationally available in the National
Weather Service AWIPS environment.
AWIPS images of the MODIS visible channel and
near-IR snow/ice channel, highlighting the
extent of river flooding across the central
Mississippi River and Ohio River valley regions
on 20 March 2008.
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MODIS
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MODIS in AWIPS

• http//www.crh.noaa.gov/news/display_cmsstory.php?
  wfomkxstoryid29173source0
• Lake Michigan Waters Warming Rapidly -- Light
  winds, abundant sunshine and unseasonable warm
  temperatures over the past week across Wisconsin
  and the western Great Lakes have resulted in Lake
  Michigan water temperatures warming 10 to 20
  degrees.

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NWS using MODIS images to show spring green-up

• http//www.crh.noaa.gov/news/display_cmsstory.php?
  wfomkxstoryid29601source0

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Sample Images
TPW SST(Daytime) CTT
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(No Transcript)
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Area Forecast Discussion
MAIN SHORT TERM FORECAST PROBLEM IS EAST FLOW AND
MARINE LAYER INFLUENCE OVER EASTERN
WISCONSIN...AND DENSE FOG POTENTIAL IN THE WEST.
THINK MOST OF THE DENSE FOG WOULD BE IN THE RIVER
VALLEYS...WITH A TENDENCY FOR PATCHY FOG AND SOME
STRATUS AGAIN IN THE EAST WITH MORE OF A
GRADIENT. MODIS 1 KM IMAGERY LAST NIGHT SHOWED
THE DENSE FOG IN LONE ROCK AND BOSCOBEL WAS
CONFINED TO THE IMMEDIATE WISCONSIN RIVER
VALLEY...IMPORTANT INFORMATION. THE LOCAL RIVER
VALLEY DENSE FOG IS NOT SEEN IN THE NORMAL 2 KM
GOES. (HENTZ/MKX)
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(No Transcript)
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AVHRR
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10.7 um
3.7 um
11um -3.7 um
New in AWIPS AVHRR Radiances and Channel
Differences
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AVHRR in AWIPS
Example of other products http//cimss.ssec.wisc
.edu/goes/blog/wp-content/uploads/2009/08/090811_a
vhrr_ir_type_anim.gif
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AVHRR Products in AWIPS (CONUS) Cloud Type,
Cloud Top Height, Cloud Top Temperature, Cloud
Optical Depth, Cloud Particle Effective Radius
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AVHRR Products in AWIPS (Alaska) Cloud Type,
Cloud Top Height, Cloud Top Temperature, Sea
Surface Temperature
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AVHRR Cloud Type Product in AWIPS (10-hour
Period Over CONUS)
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AIRS
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Sample AIRS DPI IN AWIPS- 04- 09-2009
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Involved Weather Forecast Offices
Aberdeen, South Dakota (ABR)Amarillo, Texas
(AMA)Boulder, Colorado (BOU)Dallas/Fort Worth,
Texas (FWD)Davenport, Iowa (DVN)Des Moines,
Iowa (DMX)Duluth, Minnesota (DLH)El Paso, Texas
(EPZ)Glasgow, Montana (GGW)Indianapolis,
Indiana (IND)Kansas City, Missouri (EAX)
Midland, Texas (MAF)Minneapolis, Minnesota
(MPX)Norman, Oklahoma (OUN)Pendleton, Oregon
(PDT)Reno, Nevada (REV)Riverton, Wyoming
(RIW)Springfield, Missouri (SGF)Tulsa, Oklahoma
(TSA)Spaceflight Meteorology Group
Billings, Montana (BYZ)Chicago, Illinois
(LOT)Green Bay, Wisconsin (GRB)La Crosse,
Wisconsin (ARX)Las Vegas, Nevada
(VEF)Marquette, Michigan (MQT)Northern Indiana
(IWX)Spokane, Washington (OTX)Wichita, Kansas
(ICT)
Kansas City, Missouri (CRH)Fort Worth, Texas
(SRH)Salt Lake City, Utah (WRH)
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Milwaukee, Wisconsin (MKX)
TOTAL
SMG
in AWIPS
Last updated on Jan 20, 2009
Distribution Node
25 MODIS AFDs Issued
1 AFD Issued
Receive MODIS Imagery
3
1
9
20
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Involved Weather Forecast Offices
Boulder, Colorado (BOU)Fargo, North Dakota
(FGF)Indianapolis, Indiana (IND)Kansas City,
Missouri (EAX)La Crosse, Wisconsin
(ARX)Nashville, Tennessee (OHX)Rapid City,
South Dakota (UNR)Springfield, Missouri (SGF)
Milwaukee, Wisconsin (MKX)
Aberdeen, South Dakota (ABR)Burlington, Vermont
(BTV)Minneapolis, Minnesota (MPX) Northern
Indiana (IWX)Riverton, Wyoming (RIW)
Bohemia, New York (ERH)Fort Worth, Texas
(SRH)Kansas City, Missouri (CRH)Salt Lake City,
Utah (WRH)
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TOTAL
in AWIPS
Introduction of GRIB2fields in August 2008
Last updated on Jan 20, 2009
Distribution Node
50 CRAS AFDs Issued
1 AFD Issued
Receive CRAS Imagery
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1
6
7
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Instructions Available Online
http//cimss.ssec.wisc.edu/jordang/awips-modis/
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AWIPS Menu Enhancements
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AWIPS D-2D
Panes
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Testbed Integration
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UWCI Algorithm Description

• Day/Night UW Cloud typing product (Pavolonis et
  al, uses 3.9, 6.7, 10.7, and 12.0/13.3 um
  channels)
• Monitor microphysical properties
• Infrared window (10.7 um) box-averaging conducted
  (monitoring mean 10.7 um cooling rate over area)
• This algorithm for convective initiation phase
  only
• Two primary algorithm products are cloud top
  cooling (CTC) rate and CI nowcast
• http//cimss.ssec.wisc.edu/goes_r/proving-ground/G
  OES_CINowcast.html

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UWCI Data Flow Overview
UWCI Algorithm (Fortran 90) Processing time 1-2
minutes
CIMSS McIDAS ADDE Server
NSSL N-AWIPS Image -gt SPC Regridded Overlays
WDSS-II and Google Earth Over 1050 GOES images
processed and delivered from 27 April 8 May
2009
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20090429 Dryline CI CaseSPC HWT Proving Ground
20090429 2015 UTC Instantaneous CI Nowcast
CI Occurring
CI Likely
CI Possible
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29 April 2009
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University of Wisconsin Convective Initiation
(UWCI)

• High-level algorithm overview
• Compute IR-window brightness temperature cloud
  top cooling rates for growing convective clouds
  using a box-average approach
• Combine cloud-top cooling information with
  cloud-top microphysical (phase/cloud type)
  transitions for convective initiation nowcasts

Example from June 17, 2009 over northern KS
First UWCI cooling rate signal precedes NEXRAD 35
dBz signal by 33 minutes
1545 UTC first cloud top cooling signal
1610 UTC - Continued cooling signal
First NEXRAD 35 dBz echo at 1617 UTC
NEXRAD at 1735 UTC
1732UTC - Severe t-storm
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Hastings, NE NEXRAD Radar Reflectivity from
06/17/2009
Radar Reflectivity at 1544 UTC
Radar Reflectivity at 1618 UTC
No echo on radar
Reflectivity echo gt35 dBZ
First signs of convection on radar 33 min after
significant cooling detected
First significant cooling (lt-4K/15min) at 1545 UTC
Radar Reflectivity at 1826 UTC
Resulting strong convection 3.5 hrs after
significant cooling detection
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AWIPS CI/CTC Interaction with Sullivan (MKE) NWS
Office
0502 UTC
0430 UTC
0630 UTC
Forecaster generated screen captures from AWIPS
at MKE
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"The UWCI performed very well in Iowa last night!
 These thunderstorms fired up along an existing
boundary and are coincident with the leading edge
of 700mb moisture transport and weak 850mb warm
air advection. - Marcia Cronce NWS
Forecaster
AWIPS CI/CTC Interaction with Sullivan (MKE) NWS
Office
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Possible UWCI Algorithm Enhancements

• Improve diagnosis of small cumulus, this can be
  improved via UWCI algorithm methodology
• Some of the UWCI thin cirrus detection can
  possibly be improved but new spectral information
  needed for accurate cirrus detection
• Rapid anvil expansion FAR can be mitigated

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GOES-R PG Long-range plans
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FY09

• AWIPS Weather Event Simulations (WES).
• We will explore the development of an
  environmental event simulator for user education.
  This would use historical simulated ABI
  synthetic data sets to build case studies
  demonstrating the utility of the ABI data. This
  activity would leverage the WES (Weather Event
  Simulators) and GOES-R AWG proxy efforts.
  Currently two separate efforts are underway
• CIMSS will continue development of 4-5 June 2005
  convective WES case study (as shown above in
  FY2008 accomplishments) beginning work on
  including level 2 products (cloud properties,
  TPW, and LI).
• b) CIMSS will begin coordination and development
  of WRF-ARW Hurricane Katrina AWIPS WES event.
  NWS Miami has requested an ABI hurricane
  simulation data within AWIPS for training and
  preparing forecasters for future ABI hurricane
  decision support capabilities.
• CIMSS will use proxy WRF-ARW profile and
  satellite radiance cases to simulate top of
  atmosphere radar (satellite perspective) and
  display within AWIPS to provide comprehensive
  forecaster interpretation.
• The CIMSS team will begin investigation of the
  AWIPS-II early access and product demonstration.

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ABI in AWIPS (via netCDF)
Simulated Advanced Baseline Imager (ABI) bands
shown in the legacy AWIPS.
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Wx Event Simulator (all ABI bands)
WES guide underway
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WES beta-version status (ABI radiances)

• Converted to version 9 (from OB8.3).
• Beta release packaged
• This contains the June-04-05-2006 storm outbreak
  (CONUS and mesoscale), Hurricane Katrina, band
  differences, a beta release of WES guide, etc.
• Contact T. Schmit for a copy.

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Collaboration mode
AWIPS-2 (Migration)
Task Order 10
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FY09

• NWP Images.
• CIMSS researchers and scientists will explore the
  creation of simulated (synthetic) GOES-R
  datasets, including forecast images of ABI bands
  using a regional model, such as WRF. CIMSS
  proposes to begin coordinating access to
  simulated ABI channel infrared radiances from WRF
  NWP output (either locally or from local NWS
  office) using AWIPS system.

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One image is simulated, the other observed from
current GOES
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One image is simulated, the other observed from
current GOES Imager. Shown in McIDAS-V.
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Real GOES, Simulated ABI
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Real GOES, Simulated ABI
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Sample forward model images

• Progress on CRAS into AWIPS
• New real-time CRAS website
• http//cimss.ssec.wisc.edu/cras/
• http//cimss.ssec.wisc.edu/cras/cras45_NA/12/p03_m
  .html
• New focus on real-time WRF-ARW at HWT?

Forecast sky cover
Forecast WV
Forecast IR window
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Simulated WV imagery in AWIPS
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Conclusions

• The GOES-R AWG teams are working toward
  algorithms ready to produce decision support
  information at first light
• GOES-R algorithm development has fostered new
  decision support applications with current imager
  technology (expected launch of GOES-R in 2015)
• Convective Initiation
• Overshooting-top
• Turbulence
• Vested interest in providing GOES-R like
  products in hands of end-users such as NWS
  forecasters and FAA decision support (AWG to
  Proving Ground connections)
• NPOESS Proving Ground